This PDF file contains the front matter associated with SPIE Proceedings Volume 12790, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

The vehicle engine is affected by the external excitation force in the actual work, which will make the engine work in a bad condition and easily produce vibration and noise. Therefore, it is necessary to model the engine to control the engine vibration first. In this paper, a type of vehicle engine is taken as the research object, and the six-degree-of-freedom dynamic equation of the engine is established according to the Lagrange Method. The natural frequency of the engine vibration system is calculated by numerical and simulation analysis. The engine vibration is analyzed, and the two results are compared to verify the correctness of the model. This research lays a foundation for the vibration control of the engine.

Aiming at the problems of chemical pollution and the inability to reuse the initiation method adopted by the traditional hood pop-up mechanism, a new hood pop-up mechanism that uses shape memory alloy (SMA) as the trigger power element is proposed to realize the improvement of the hood pop-up mechanism. High-speed triggering and reversible recovery, the mechanism is simple in structure, quick in response, and can be manually recovered after being bounced, which can be adapted to various car models. After the sensor is triggered, the supercapacitor heated the SMA element to drive it at a high speed. The locking mechanism is activated to release the energy stored in the spring, and the engine hood is lifted and limited after reaching a certain height. After the design of the engine hood lifting mechanism and the determination of parameters, the spring stiffness that meets the pedestrian protection requirements is determined to be 11000N/m by the numerical simulation method. Dynamics modeling and simulation were carried out to study the influence of different parameters on the bouncing response. Experimental results show that when the spring stiffness increases from 2000N/m to 5000N/m, the release time decreases from 19ms to 12ms, and the time needed to spring up to 100mm height decreases from 136mm to 84mm. The response speed of the spring mechanism is accelerated, which is consistent with the simulation results.

The overhaul optimization of CPR1000 unit is an effective and important way to reduce operating costs, improve unit availability and core competitiveness, and shorten the overhaul period and reduce overhaul costs are the requirements of nuclear power development planning. In this study, the constraints of flow improvement in the oxidation purification stage of CPR1000 unit during the overhaul period were simulated and analyzed, and the pressure distribution at different positions after the flow increase, the relationship between pressure difference and flow of the equipment, and the margin of pressure valve adjustment were analyzed to achieve the increase of oxidation purification flow and the great shortening of purification time. The calculation and analysis of this study show that the existing equipment of the oxidation purification circuit has the prerequisites for flow improvement, but the reliability of the filter and desalination bed needs to be further verified, and the overhaul period can be saved by 3.84~7.88 h after the flow rate is increased to 40 m³ /h.

Based on intelligent identification technology, a system for transportation structure management of a steel company is designed and developed, which is used to monitor the status and analyzed the behavior of vehicles used by the steel company. According to the statistics of vehicles used by the steel company for one year, the results show that the vehicle structure of the steel enterprise is stable, and the frequency of use of vehicles accounting for less than a quarter exceeds 95%; The frequency of vehicles use in different seasons shows a regular distribution. Combined with the vehicle status data, the vehicle frequency can be reduced to improve the ambient air quality based on ensuring the production activities of the company

The emergence of rotary steering drilling systems(RSS) is well adapted to the needs of high-difficult drilling operations in directional wells. Buckling analysis of bottom hole assembly can guide drilling operation and has guiding significance for field application of rotary steering drilling system. Based on the structure of a push-the-bit RSBHA, this paper uses Abaqus finite element software to solve the buckling mode of RSBHA and further solve the critical buckling load of RSBHA.

To solve the problems of the new energy vehicles’ electric drive system test work, in contrast with traditional test sands based on real motors, a new electric machine emulator system is established. To improve the performance, the LCL-type topology is chosen for the interface, a key component of the system. With the problems of multiple parameters and strong coupling, the design of the LCL-type interface parameter is transformed into a multi-objective, multi-disciplinary optimization problem, and a multi-disciplinary collaborative optimization architecture is established with an improved particle swarm optimization algorithm based on dual time scales to obtain the optimal parameters that consider simulation accuracy and system stability, total volume and cost. The simulation and physical platform test results show that the new electric machine emulator system can achieve accurate simulation of real motors, which can complete the test of the electric drive system for vehicles. When the optimization parameters obtained by this paper method are used, the phase current error is significantly reduced while the total inductor is also reduced, resulting in a significant increase in the simulation accuracy and a reduction in the volume and cost. This verifies the superiority of the multi-disciplinary collaborative optimization architecture and improved optimization algorithm for interface parameter design.

Outfitting plays a vital role in the construction of large ocean passenger ships. The management of outfitting, especially iron outfitting, plays an important role in improving construction efficiency, saving logistics costs and storage costs, and improving the digital progressiveness level of the shipbuilding industry. This paper establishes a modular pallet stowage model to optimize the stowage mode of outfitting materials for large ocean-going passenger ships, which can help improve the utilization rate of storage space, pallet utilization rate and the timely response ability of required materials.

At present, although the exclusive delivery navigation for delivery personnel implemented by major food delivery platforms has basic navigation functions, it is still insufficient in terms of optimizing navigation details and ensuring the safety of delivery personnel. Aiming at the problem that the food delivery route planned by the food delivery platform does not meet the actual traffic demand and the average delivery time allocated by the platform is too short, this system is based on the traditional ant colony algorithm and fully considers the traffic lights and road impassability that the food delivery personnel may encounter on the way and the platform route planning does not consider the actual traffic demand and other common problems. By adding the corresponding constraints of the ant colony algorithm, the delivery staff's takeaway navigation path can be carried out in a way that is more in line with actual safety and traffic rules. The system is equipped with real-time road condition monitoring and voice broadcast navigation functions to find the optimal route for takeaway delivery under the premise of ensuring the delivery safety of takeaway workers.

With the rapid development of the social economy, take-out food service has gradually developed and popularized. While take-out service provides dining convenience for the dining group, the over speed delivery behavior of take-out deliverers also brings traffic safety risks to society. In order to avoid the delivery in the process of over speed driving electric motorcycle crash or other traffic safety accidents, This paper designs a set of early warning and obstacle avoidance system for distribution vehicles from two aspects of automatic early warning and automatic obstacle avoidance. At the same time, the feasibility of early warning and obstacle avoidance is verified by the joint simulation of simulink software and carsim in matlab. When there is a dangerous situation in the delivery process, the system will give an early warning to extend the reaction time of the delivery workers, and realize the automatic obstacle avoidance function of the delivery vehicles through the automatic obstacle avoidance system to ensure the traffic safety in the delivery process.

As user needs increase and cars with more complex features, production cycle time and cost will increase if OEMs continue to use the traditional vehicle development process. To shorten the design development cycle and reduce the production cost, this paper proposes a tool chain for Electrical/Electronic Architecture design based on the PREEvision platform and the MBSE methodology. The model was developed using PREEvision in combination with MATLAB/Simulink, CANoe, and other engineering software. The interface between the software was analyzed, and the preliminary development and design work was tested and verified by the model, providing a complete theoretical and methodological basis for real vehicle production.

Due to the complex overall structure of the "vehicle-ground-vehicle" communication method system currently adopted, it relies heavily on trackside equipment and has high cost. Therefore, On the basis of the original train control system, a train control system based on vehicle communication was produced. The system can simplify the system structure, save costs, and realize direct communication between two vehicles in the next door. During normal train operation, the two cars communicate directly through vehicle-to-car communication^[1]. If the train communication fails, the communication method between trains will switch to backup mode. In this paper, the new train control system of high-speed railway is modeled by the method of time automata, and the backup mode of the new train control system is verified.

The mismatch between passenger flow demand and train capacity during peak hours can easily cause passengers to stay at the platform for a long time. Collaborative passenger flow control is an effective method to manage inbound passenger flow, reduce platform congestion and reduce operational risk. In this paper, a new metro passenger flow collaborative control model is proposed, which explicitly considers the dynamic characteristics of inbound passenger flow and the impact of platform constraints on inbound passenger flow. To describe the dynamic change of inbound passenger flow, nonlinear constraints are introduced into the model. Therefore, a linearization operator is proposed in this study to overcome the difficulty of solving the nonlinear model. Finally, a case study based on the Batong line of the Beijing Subway is conducted, and the results validate the effectiveness of the model and linearization operator proposed.

In the era of intelligent and connected vehicles, AUTOSAR software architecture-based automotive basic software platforms are increasingly used to meet the growing demand for safety and intelligent driving in automotive software. This paper presents an in-depth research and analysis of the AUTOSAR software architecture technology for intelligent and connected vehicles, focusing on the components of the AUTOSAR software architecture, the current state of technology development, the toolchain configuration process, the challenges faced and the future development outlook, intending to present the development and application of the AUTOSAR software architecture technology for intelligent and connected vehicles.

The launching of autonomous driving vehicle relies on enormous tests and a reasonable test evaluation system. Compared with the real vehicle test characterized by long test cycle, high cost, high risk and low coverage, virtual simulation tests are found with the advantages of infinite expansion of scenarios, arbitrary setting of traffic flow, dynamics-based parameterized vehicle simulation model and customized configuration of driver model. This paper based on international standards of L1-L2 automatic driving functions related to real world testing, delivered a methodology for test cases design. through function-based evaluation indicators and scenario-based evaluation indicators, a systematic and logical simulation test evaluation method and framework based on driving scenario is proposed.

Wheel load data is a crucial signal for active vehicle safety and driving assistance systems, especially for future electric and smart vehicles. There have been many technical routes to determine wheel load, however, these studies suffer from high cost and complexity and have not been realized commercially. In the Formula Student Competition, the car needs to pass through many sharp corners at high speed, which puts high demands on the car’s steering characteristics. This paper focuses on the estimation method based on suspension analysis to optimize steering characteristics, which has considerable advantages such as: a) it can be performed on a non-rotating part, b) the suspension system usually serves the entire life cycle of the car, c) not only can wheel loads be measured but also suspension rod forces can be calculated. This paper proposes a novel analysis method based on suspension deformation and forces, which decouples the calculation from the known vehicle mass. The proposed method is verified by Adams Car software simulation and sensitivity analysis. The experiment results on a Formula Student race car demonstrate that the system can measure the wheel load with sufficient accuracy. In addition, wheel load data is used for the active control of the race car's anti-roll bar to give the car better performance and higher safety on the circuit.

In order to study the performance of the combined driving assistance system in the pedestrian crossing scenario, this paper selects two scenarios of pedestrian crossing with shelter and pedestrian crossing without shelter, selects three representative vehicles for testing, analyzes the difference of these vehicles, include braking time, braking effect and other data, and puts forward improvement suggestions.

When the truck brakes frequently, rutting phenomenon will be severe near the stopping line at the intersection of urban roads. With the development of autonomous technology, autonomous truck platoon have been put into use in some ports and surrounding collection and distribution corridors. The rutting problem caused by this new traffic object is different from the rutting phenomenon caused by traditional single human vehicle. The mechanism of its generation is an important topic for future intersection pavement damage management. Therefore, in this research, the specific autonomous driving lanes at urban road intersections is chosen to figure out the influence of the deceleration and the platoon space between trucks in the platoon on the pavement rutting. In this study, finite element simulation of intersection pavement is performed using ABAQUS software. The platoon space within the platoon is used as an explicit input to quantify the effect of deceleration and platoon space near the intersection stopping line. The results show that the autonomous truck has a high degree of robustness. Both of the deceleration speed and platoon spacing are negatively correlated with rutting depth,. The purpose of delaying rutting and prolonging pavement life can be achieved by increasing deceleration speed and platoon space inside the platoon. Further analysis of the correlation coefficient index shows that increasing the deceleration rate is the key factor to slowdown the rutting of intersections. By quantifying the influence of the platoon dynamics parameters on rutting, this study clarifies the influence mechanism of the new traffic object on the existing intersection asphalt pavement. It provides a theoretical basis for improving the adaptability of the existing infrastructure and optimizing the platoon combination of the truck platoon.

The rational scheduling of AGVs is conducive to the safe and efficient operation of automated container terminals. A dynamic scheduling method is proposed for the scheduling problem of AGVs in automated container terminals, considering the abnormal conditions that may occur during AGV operations. To minimize the total energy consumption of AGV operation, an optimization model is established based on the pre-optimization concept followed by dynamic adjustment. In the pre-optimization stage, the initial scheduling scheme is obtained by designing an adaptive genetic algorithm that considers both import/export container operation and the influence of the QCs and the YCs on the AGV operation. In the dynamic adjustment stage, the rescheduling strategy and related constraints are determined to readjust the scheduling scheme of the AGV, according to the different impacts generated by dynamic events. The effectiveness of the proposed model and algorithm is verified by comparing and analyzing various scales of arithmetic cases. The example analysis demonstrates that the proposed dynamic scheduling method can respond promptly to the occurrence of dynamic events, such as abnormal AGV behavior, and better meet the actual operational requirements of the terminal.

Aiming at the problem of the integration of cab safety and sense of safety, the research on the integration of cab shape structure safety is carried out. Firstly, the relationship among shape, function, and structure design is analyzed, and the safety fusion model of shape structure is proposed. Secondly, according to the safety standard of the cab, the finite element modeling and analysis of the cab are carried out. Finally, the influence of structure size on the cab is analyzed. The results show that: since the safety of the cab is not sensitive to the length, width, and height of the structural dimensions, once the structural design of the cab meets the safety requirements, the length, width, and height of the structural dimensions of the cab can be appropriately adjusted to improve the safety and comfort of drivers and passengers.

As a key rotating component for power transfer in an aeroengine, the reliability of the turbine disc plays a decisive role in operational safety. Since monitoring, detection, prediction and decision making are not yet available for its life design and evaluation technology, digital twin technology is applied to its life management. Firstly, according to the functional requirements, the framework of the digital twin system for life management is clarified; secondly, in the model layer and application layer, the design of the system is completed to realize the virtual mapping of physical entities; finally, through application examples, it is shown that this system can realize the functions of online monitoring, signal control and life prediction to optimize the operation and maintenance.

With the continuous progress of automatic driving technology, a large number of L3 and higher level automatic driving vehicles have entered the testing and demonstration application stage. Efficient testing is the most core technical problem to be solved. However, the test method based on a single scenario obviously cannot meet the needs of high-level automatic driving test, and the actual road test is difficult to ensure the test efficiency. Simulation testing based on continuous scenarios can solve these problems well. This paper designs a continuous scenario automated generation method for highlevel automatic driving testing. Through scientific analysis of the coupling relationship between terrain, environment, and action elements, it can quickly find all reasonable scenario combinations that may occur on the road section. Using these combinations, it can efficiently and automatically generate scenario cases that can be directly used for high-level automatic driving simulation testing. The experimental results show that this method can generate a large number of reasonable continuous test scenarios as simulation test input, greatly improving test efficiency, and providing strong support for the iteration of L3 and higher level automatic driving technology.

In recent years, with the continuous development of new energy vehicles and automotive electronics, some parts of the GB 21670-2008 standard are no longer applicable to new brake systems. Therefore, there is an urgent need to revise the relevant content of the standard. This article provides a brief introduction to standard dynamics and trends, and proposes specific testing plans for the electromagnetic immunity of passenger car anti lock braking systems, including two testing methods for braking conditions: 1. The vehicle is in active mode and drives the drum to run; 2. The vehicle is in passive mode and is driven by rolls. Verification experiments were conducted on vehicles under two different braking conditions, and the advantages and disadvantages of the two testing methods were analyzed in detail.

This paper is focused on mean sensitization of controlled systems. The sensitivity of the controlled system is equivalent to mean sensitivity of it for the finite-dimensional Banach space. A mean sensitization condition for the space of p-summable sequences is established.

In order to solve the problem of fast, safe and efficient transmission of various medical items in the hospital, this paper developed a rail type logistics transmission scheduling system. The detailed design scheme of the track vehicle system (TVS) is focused on, including the structure analysis and modeling, construction of electronic map, control system structure, path planning algorithm and dynamical scheduling strategy. Finally, the system testing and verification work are given. The proposed TVS system adopts partition scheduling strategy and electronic tag identification technology, which provides an effective solution to the multi-vehicle and multi-task logistics scheduling problem in the scene of hospital logistics transportation.

In order to solve the problem of capacity calculation and verification in high-speed railway operation, this paper designs a real capacity calculation-simulation verification framework of high-speed railway based on the average minimum train interval method. In the capacity calculation stage, the average minimum train interval method is used to design the structural index of train operation diagram from the two perspectives of travel time and running line stability, and the average buffer time and the section occupation time of different train groups are calculated as the initial input parameters of simulation verification. In the stage of simulation verification, OpenTrack railway simulation software is used to iteratively adjust the buffer time of the train diagram, output the actual passing capacity of the train diagram, and analyze the correlation between the passing capacity and the structure of the train diagram. Finally, taking Xu-Beng section of Beijing-Shanghai high-speed railway as an example, this paper designs a series of train operation diagrams, calculates the actual passing capacity, explores the nonlinear relationship between the capacity and the structure of the train operation diagram, and points out that when the homogeneity coefficient is between [-0.07, 0.11] and the speed variance is between [183, 192], the actual passing capacity can reach [184, 187]. The structural analysis of train diagram in this paper can provide auxiliary decision support for train diagram scheduling.

The LNG unloading arm is one of the important equipment of LNG storage and transportation, whose performance directly affects the efficiency and safety of LNG handling. In this paper, the 16-inch unloading arm is taken as an example to carry out weight reduction optimization for the supporting structure of the unloading arm, such as the column and the inner and outer walls, and the finite element simulation analysis is carried out on the weight reduction unloading arm under working condition. Through the numerical simulation method, the thermal solid coupling check analysis, vibration analysis, and buckling analysis of the column are carried out to fully check the weight reduction unloading arm. The results show that the strength of the weight reduction unloading arm meets the requirements and has good vibration characteristics and stability. At the same time, the total weight of the device is reduced, and the processing and manufacturing costs are saved, which has guiding significance for the production and manufacturing of LNG unloading arm in practical engineering.

Aero-engine performance simulation is an indispensable and important means for the whole life cycle of aero-engine. It can greatly improve the efficiency and quality of aero-engine research and development, reduce the repetition of physical tests, shorten the development cycle and reduce the development cost. Its technology is developing rapidly, and various simulation software has developed maturely. However, how to obtain the accurate simulation results of the steady state and transition state of the whole machine still has a lot of research space. This paper introduces the nonlinear dynamic performance model of mixed-flow turbofan engine in steady state based on characteristic correction diagram. In this model, the engine component model is established by using MATLAB Simulink simulation, and the interpolation calculation of component characteristic diagram is carried out to realize the calculation of working parameters and component performance parameters in the engine transition state, so as to further improve the accuracy of the model and use this model to analyze the engine performance and monitor the state.

The extensive application of automatic driving technology must be based on sufficient test verification, so the test technology of auto drive system also develops rapidly and iteratively. In this paper, a Vehicle-in-the-Loop (VIL) platform for auto drive system test verification is studied. It has real dynamic response, rich Scenarios, high test efficiency and low test cost. After studying the platform architecture, key sensor simulation technology, and data injection technology, a vehicle in the loop simulation system was constructed, and VIL simulation and real vehicle testing comparisons were conducted. The results indicate that the test results of VIL simulation technology are reliable and can be used for testing and verifying autonomous vehicles.

With the gradual realization of high-level automatic driving vehicles, the previous testing and evaluation methods for Advanced Driver Assistance Systems(ADAS) functions are gradually unable to meet the requirements for testing and evaluation of high-level ADS. In order to effectively test and evaluate the auto drive system, a system framework is proposed, which consists of a hardware system for data acquisition and pre-processing and a software system for data slicing, identification and evaluation. The system is a modular framework, which can be used to build system adaptability for different test requirements of hardware-in-loop, vehicle-in-loop and open road test. The core of the system is firstly to extract Region of Interesting(ROI) data segment from real-time test data stream based on Responsibility-Sensitive Safety(RSS) model, secondly perform scenario recognition and classification processing on this data segment，thirdly index the corresponding evaluation criteria from the scene knowledge base to evaluate each operating parameter in this data segment, Finally, a comprehensive evaluation is conducted by weighting the three levels of "operating parameters", "scenario" and "performance" separately. This study proposes a novel and feasible technical framework for the efficient automated evaluation of high-level autonomous driving systems, which can serve as a reference for related subsequent research.

To ensure the safety of shipping enterprises, the traditional work breakdown structure-risk breakdown structure (WBSRBS) method has been improved. While retaining its comprehensive and accurate risk identification characteristics, the method's limitations in identifying risks have been optimized. Furthermore, the method's risk assessment ability has been increased, and the introduction of the intuitive fuzzy theory has addressed the subjectivity in expert scoring that was present in traditional risk assessment. This study establishes a model for identifying and assessing production risks in shipping enterprises using an improved WBS-RBS method and intuitionistic fuzzy theory. The model is applied to a case analysis of shipping company A, and the results demonstrate that this combination of methods can enhance the comprehensiveness of risk identification and the accuracy of risk assessment.

The current evaluation system of vehicle performance has some imperfections. Engineers should do the design according to customer demands, and carry out simulation analysis and test. This paper takes the EV dynamic and economic performances as the design objectives. The parameters of EV drive motor and battery are calculated in detail, and the vehicle simulation model is established. The simulation analysis is carried out in combination with customer demands in AVL Cruise software. Based on the simulation results, the matching of the driving motor and battery of the power system are completed, providing the corresponding theoretical basis and scheme reference for the research and development of task-based pure electric vehicles.

A deep learning based scheduling command classification method is proposed for railway scheduling command text data. Firstly, text preprocessing is performed on the scheduling command, and Word2VEC is used to train the word vector of the scheduling command; To address the issue of imbalanced scheduling command data samples, the SMOTE method is used to automatically generate subcategory samples; Then, the word vector is embedded into the CNN input layer, and the features of the text are extracted using the convolutional and pooling layers of the CNN. The scheduling command is automatically classified using a SoftMax classifier. Through experimental verification of partial railway dispatch command data and comparison with other classification models, the experimental results show that the text classification method proposed in this paper can significantly improve various evaluation indicators

To address the problem of efficient and safe passage in bottleneck sections inside motorway tunnels, this paper designs a projected lane change coordinated passage srategy (PCPS) with the help of an cyber-physical system (CPS) concept in a mixed traffic flow pattern consisting of connected and autonomous vehicles (CAVs) and connected human-drive vehicles (CHVs). Taking into account the characteristics of traffic flow inside motorway tunnels, vehicle following rules and lane changing rules are optimised and corresponding evaluation indicators are selected. The model is simulated with SUMO software, and the comparison of traffic flow, emergency braking ratio and average speed is carried out in two states: no passage strategy (NPS) and PCPS strategy. The results demonstrate that the PCPS strategy can effectively improve the efficiency and safety of traffic flow in bottleneck sections inside motorway tunnels.

As a crucial component of railway transportation, the safety protection measures for local railway shunting are inadequate. The design of a shunting protection system that fulfills the requirements of the local railways is essential in guaranteeing safety during shunting operations and also enhancing efficiency in shunting operations. The vehicle-ground radio communication serves as a key link in shunting safety protection, which is closely related to the safety and efficiency of train operation. In this paper, the Systems Modeling Language (SysML) is used to analyze the process of vehicle-ground radio communication. We propose the activity diagram probabilistic model description method based on discrete-time Markov chains to convert the SysML activity diagram into the probabilistic model, which can provide a reference for the formal verification and analysis of the SysML model and reduces the difficulty of directly using formal methods. We analyze the reliability of vehicle-ground wireless communication under random conditions. And the system's control capability is further enhanced through the optimization of vehicle-ground wireless communication transmission strategy. The results hold significant reference significance to the improvement of shunting efficiency and the design of shunting protection system.

This paper details the timing characteristics of the DSP chip TMS320F28335 and dual-channel SDC. It analyzes the matching problem of interface timing, discusses the software and hardware design of the TMS320F28335 extended digitizer, and provides an oscilloscope observation waveform diagram.

To solve the trajectory tracking control problem of deep-sea polymetallic sulfide mining vehicle, this paper proposes an adaptive backstepping trajectory tracking control algorithm based on the kinematics model of deep-sea polymetallic sulfide mining vehicle, aiming for accurate tracking and taking into consideration the effect of error and interference. The closed-loop control system’s stability and convergence is proved by Lyapunov stability theory, and its effectiveness is further verified by simulations. Results from the simulation have demonstrated that the proposed algorithm has good robustness in realizing trajectory tracking control.

In view of the current situation of super-high concrete bridge tower construction, facing the huge demand of high efficiency and high quality construction and labor intensive production, combined with the cable tower construction of Lingdingyang bridge on Shenzhong-Zhongshan link and modern factory manufacturing, the concept of "vertical factory" for bridge tower construction is put forward. The finite element static strength analysis of the tower building machine structure is carried out, and the mechanical performance of the climbing system and the bearing capacity of the corresponding anchorage system are verified through the test, so as to provide data support for the use of the tower building machine.

In this paper, linear switched reluctance motor (LSRM) is applied to automatic sliding door control system, and a threeclosed position control strategy based on fuzzy PI control and current chopper control is proposed and designed. The simulation model of automatic sliding door control system is established, and the simulation is carried out to verify the effectiveness of the control strategy designed in this paper.

In this paper, we use a model construction, model solution and empirical study to investigate the container space allocation problem in container yards within automated container terminals. We consider both inbound and outbound container yard flows, with the objective of minimising the number of crushed containers and the total stacking height resulting from the space allocation process. We propose a multi-objective optimisation model and design a greedy algorithm to solve the model. By comparing our container space allocation strategy with the actual container space allocation strategy of Tianjin Port before optimisation, we find that our research can effectively reduce the number of new pressurised containers and the number of new layer heights generated during the container stacking process, which can fully guarantee the operational efficiency and safety of the yard in the automated container terminal. This ensures the operational efficiency and safety of the yard in the automated container terminal, and thus provides effective decision support for the construction and operation of the automated container terminal.

In view of the problems of the existing servo tracking and stability, designed a kind of fast and stable tracking servo system mechanical structure, using modular independent function and expansion capability design technology, the servo system undervoltage, overcurrent, runaway, overtemperature design protection function, to ensure the safety of the system and load; using the anti-interference key design of isolation and shielding, and the motor and power amplifier are designed according to the requirements of each shaft speed and acceleration of the system. According to the simulation results, product measurement and field development, the air target can be quickly tracked quickly.

By adding disturbance, or Dither signal, to ADC, the periodicity of quantization error can be broken, thus improving SFDR and SNR of the system. To solve the problem that the frequency of the Dither signal generated by the traditional large narrow-band Dither structure is limited by the designed analog filter, a new narrow-band Dither structure is proposed in this paper, which can directly generate Dither noise in a certain bandwidth range. In this paper, the determination of the frequency position of Dither signal and the requirements of the frequency range are analyzed and verified by the theoretical analysis and simulation. Secondly, the frequency adjustable narrowband Dither generation structure is analyzed and realized by the simulation after the addition of VCO, which proves the realizability of this structure. Finally, the Matlab simulink module is used to build the simulation platform, and the large narrowband Dither algorithm based on this structure is simulated. The simulation results show that this structure can improve the SFDR and SNR of ADC while changing the band range of Dither signal.

A measured fatigue load model, tailored for the Beijing-Tianjin-Hebei region, was developed using dynamic weighing system(WIM). In addition, fatigue experiment were performed on orthotropic steel bridge decks. The findings of this study reveals that fatigue crack tend to initiate at the weld toes between deck and U-rib, developing along the thickness direction of deck. the stress near the fatigue crack significantly decreases after redistribution, resulting in a reduced bearing capacity of the structure. Furthermore, the position of the fatigue crack suggests that welding residual stress has a crucial role in the structural fatigue failure process.

Currently, the commonly used proportional valve scheme in variable load hydraulic cylinder systems has problems such as high cost, large internal leakage, high failure rate, large installation volume, and heavy component weight, especially for multi-channel static load systems. In order to solve these problems, this paper adopts an optimized design and replaces the proportional valve with an electrically controlled one-way valve with a conical valve core. By combining effective software logic control, proportional pressure control of the hydraulic cylinder is achieved. At the same time, the new scheme has the advantages of low manufacturing cost, low internal leakage, low failure rate, and a compact and lightweight system.

The construction of transportation powerhouse has put forward higher requirements for waterborne transport safety. Carrying out refined prediction of waterborne traffic accidents in the Yangtze River is an important part of promoting the improvement of the level of waterborne transport safety development. Through the use of gray correlation analysis method, the influencing factors of waterborne transport safety production situation in the Yangtze River are systematically analyzed, and a monthly-scale Yangtze River waterborne transport safety production situation prediction model is constructed. The results show that there are many factors that affect the safe production situation of waterborne transport in the Yangtze River. Among them, the throughput of dangerous goods, the average daily traffic flow of the cross-section and the passenger traffic are the most prominent, and the correlation coefficient of different months exceeds 0.5. The simulation results of the gray system prediction model constructed are basically the same as the trend of the actual values, especially the consistency of the peaks is high, and the overall simulation results are relatively impressive.

The cooling system is one of the essential systems for the normal operation of vehicle engine. This article takes a 1.5L naturally aspirated vehicle model as the prototype, a simplified simulation model is established by using Amesim software. And the performance of engine cooling system is simulated under extremely cold and normal temperature conditions. In addition, the effects of multiple influencing factors such as water pump transmission ratio, radiator row number, and radiator windward area are further analyzed on cooling performance under normal temperature conditions. The simulation results show that the radiator row number has a significant impact on the performance for the cooling system, the water pump transmission ratio and radiator windward area also play an important role. The research in this article is beneficial for early development of the cooling system components influencing factors in projects. It can enable the product development team to quickly develop and select optimal solution schemes. That is to say the design cycle of the cooling system can be greatly shorten, and the research in this article has certain engineering application value.

As concerns regarding sustainable development, high efficiency, environmental protection, and a low-carbon economy increase, the energy efficiency and economic benefits of heat pump technology for heating issues have captured the public's attention. After analyzing validation sample data with linear regression coefficients, the PSO-BP neural network was found to be the best prediction model for the ideal exhaust pressure of the R744 transcritical heat pump system. The structure of the optimal model was validated by the analysis and discussion of the PSO-BP network's indicated layers and particle swarm iterations. Comparisons are made between the prediction model and ideal exhaust pressure correlations, and the properties and error sources of each algorithm are examined to demonstrate its efficacy. The PSOBP neural network is superior at predicting optimal pressure on units of comparable design, thereby expanding the application scenario for the cross-critical R744 heat pump. Simulated and experimental results demonstrate that the composite system can reliably generate hot water at varying feedwater and ambient temperatures.

Addressing issues such as information symmetry, transparency, traceability, and data security in traditional supply chains, this study adopts Hyperledger Fabric as the blockchain technology platform, proposes a blockchain-based information traceability scheme, and designs and implements a blockchain-based supply chain information system. This system has undergone functional and performance tests. Tests indicate that this system not only achieves the storage of relevant data information in the blockchain, ensuring the security and traceability of system data, but also realizes functions such as account management for users on the supply chain, upload of organization peer information, and consumer information queries

Short-term load forecasting is a crucial for improving the level of power grid dispatching and operation. In recent years, extreme weather occurs frequently, and deep learning is a method that depends on data volume, which leads to low accuracy of load forecasting in extreme scenarios. In this paper, the regularization technique is used to avoid the overfitting of deep learning in extreme scenes, by adding the regularization term to the objective function of the neural network, and improving the back propagation algorithm. Finally, this paper proves that regularization can effectively improve the load forecasting accuracy in extremely small sample scenarios through the comparison of actual examples.

For parking path generation, Reeds-Shepp curve is commonly adopted in algorithms such as Hybrid A*. However, path planning for underground parking with pillars and lanes occupancy cases is difficult due to the narrow space constraints. In narrow environment, RS curve might cause frequent turning and generate large radian arc that are not suitable for parking. In addition, the last segment of RS curve is an arc that occupies large area when parking into slots and is easy to collide with obstacles like pillars. Therefore, we proposed AP-RS curve to promote performance of path searching and obstacle avoidance by taking driver’s parking habits into consideration. For oblique parking lots, CCS curve is designed to ensure the last segment of curve parallel to the slot, which have less occupancy and straighten the car up in movement to reduce tire wear. The proposed method is tested under different oblique slot with 30, 60, 90, 120, 150 degrees and its performance is compared with RS curve and KKL-RS curve. The results show that AP-RS curve for oblique slot have fewer search iterations, higher adaptability to different kinds of slots, higher success rate of path planning in multipleobstacles environment.

Aiming at a two-speed AMT (Automatic Mechanical Transmission) pure electric MPV, according to the economic and dynamic indicators of the vehicle, the drive motor, power battery, transmission and other components of the vehicle are matched, and the AVL Cruise software is used to establish a pure electric MPV vehicle model. On this basis that the power and economy meets the demand, a combined simulation between Cruise and Isight is designed to further improve the economy. The MIGA (Multi Island Genetic Algorithm) is utilized to optimize the gear shifting speed and load state, and the performance simulation of pure electric MPV is carried out on the optimization results. The results show that under NEDC (New European Driving Cycle) condition, the power consumption per 100 kilometers after the optimization is reduced by 0.46kWh compared with that before the optimization, and the economy is increased by 3.03%.

The prediction of the remaining useful life (RUL) of the equipment is one of the important parts of the equipment health management and safety. We focus on trajectory similarity-based prognostic method in the data-driven scheme adopting migratory linear regression model, similarity-metric technique and Beta-KDE method based on nuclear density estimation (KDE) to predict some devices’ RUL. The training set generate the training HI library. The migratory linear regression model trained by above library transforms the test embedding into the test health indicator (HI), which are used to describe health degradation of some device. One test HI curve is compared with all the training HI curves to get the inaccurate RUL estimation. The Beta-KDE method based on KDE sifts the inaccurate value to get a valid RUL estimation, which is used to calculate the final result. This scheme was applied for turbofan engine dataset #1 and the result proved an advantage in other approaches.

In this paper, a vehicle in the loop simulation test approach of performance evaluation for driving assistance system is proposed, which contains testing model validation method and testing execution procedure. The vehicle dynamics model of the vehicle on the dynamometer is proposed to control the road load simulation that applied by shaft-coupled dynamometer. The method of integrating radar simulator, camera simulator, dynamometer system, and real time machine and scenario software to the vehicle in the closed loop simulation test platform is proposed. The performance of the vehicle with ACC function is evaluated on the simulation test platform, as well as the tests on closed-road. The results demonstrate that the performance of the vehicle tested on the simulation test bench is highly consistent with the results of closed-road. The proposed vehicle in the loop test approach is useful for evaluating the performance in longitudinal scenarios.

CBTC vehicle equipment is one of the key equipment of CBTC system, in the CBTC system test, the test scenario of vehicle equipment and the interface with other equipment such as trackside equipment and ATS equipment are more complicated. In this paper, the urban rail CBTC system is used as the carrier and the vehicle-mounted equipment is the research object. Build a simulation test environment for urban rail CBTC system, and study the test scenarios of on-board equipment and test cases, test sequences and test methods of on-board equipment. In the scenario study of vehicle equipment, the formal method based on UML activity diagram model is used to model complex scenes, and test sequences are written based on real field data for simulation test verification.

In the acquisition and evaluation stage of overseas oil and gas projects, the uncertain risk factors of surface engineering investment estimation are very different from those in the project design and construction stage. There are political, economic, social, security, and other macro risks, the project’s construction conditions, and other uncertain risk factors. The risk factors are complex and changeable, difficult to quantify, and the estimation of contingency is more difficult. At present, the contingency mainly adopts the rate method, which is based on the experience of previous similar projects. It is simple and practical, but it fails to quantify various risks and cannot fully reflect the impact of various risk factors on the final investment result of the project. Based on the historical evaluation projects, this paper analyzes and determines the risk factors affecting investment in the acquisition and evaluation stage of overseas oil and gas projects, determines the degree of influence of risk factors on the investment, determines the probability distribution function of the corresponding cost of each risk factor, and gives the contingency estimation results through Monte Carlo algorithm simulation. This paper discusses a method to solve the traditional method of determining the contingency rate mainly by subjective judgment, and quantifies the value of contingency by probability method, to improve the accuracy of the project tender offer and reduce the investment risk after the project acquisition.

With the expanding scale of urban rail transit network, the difficulty of operation organization is increasing. Unbalanced distribution of time and space in passenger flow demand make it difficult for operation managers to accurately grasp the changing trend of passenger flow and analyze the unbalanced area of network load to take timely adjustment measures. Based on the difficulties in the operation of urban subway, the evaluation method of coupling between transport capacity and passenger flow was proposed in this paper. Firstly, the passenger flow characteristics of urban rail transit network are analyzed. Secondly, according to passenger flow characteristics and train capacity variation rules, a coupling evaluation method combined with the line OD passenger flow ratio calculation is proposed. The method consists of four stages: cutting the passenger waiting time fragment based on the arrival and departure time of each train in the train diagram, calculating the total passenger demand based on the short-term forecast passenger flow, calculating the station passenger retention based on train capacity constraints, calculating the train capacity index and passenger flow index. Finally, the method was verified by taking Line 2 of a city in central and western China as an example.

Different from the general calculation of the section passing capacity, evaluating the capacity of the block post where multiple lines meet in the hub area is a com-plex task, because the influence of the speed limit of lateral turnout, tracking interval of rail lines in all directions and actual train timetable of each rail line on the capacity of the block post should be taken into account. On the basis of summarizing the existing research on capacity calculation and its influencing factors, we propose a capacity evaluation method of the block post in the hub area, taking Liwan block post as an example. This method mainly supplements and improves the assessment of the passing capacity of the block post from three aspects, that is evaluating the time horizon of each rail line, determining the tracking interval of each rail line and analyzing the influence of passing through the lateral turnout on the tracking interval. The case study shows that the method proposed in this paper can comprehensively consider many problems involved in the calculation of the passing capacity of the block post.

Railway point machine is the key equipment to control the train path and change the operation direction. Considering the anti-interference characteristics of vibration signals, this paper innovatively proposes a fault diagnosis method for point machine based on vibration signal, which provides a new fault diagnosis method for point machine. Firstly, the vibration data of the point machine are preprocessed by using variational mode decomposition (VMD). Secondly, a hybrid feature extraction method is developed by combining various methods such as wavelet transform and frequency-domain feature extraction method, which can characterize the fault features more comprehensively. Finally, support vector machine (SVM) algorithm is used to judge fault conditions. The diagnosis accuracies of localization and inverse switching processes reach 100% and 98.9%, respectively. Comparative experiments indicate the superiority of the proposed method.

The rapid development of rail transit has put forward higher requirements for the reliability testing of all components of rail lines. There are some drawbacks in relying on manual handheld device detection, so it is urgent to develop an intelligent and convenient rail fastener detection system. This paper introduces a rail fastener detection method based on YOLOV5, which can identify fasteners by training existing classified pictures, and continuously improve the accuracy of rail fasteners by modifying training documents and capturing frameworks. In this experiment, through training and training of the classified and labeled pictures, take 500 or 600 pictures as a group and 200 rounds as an experiment to improve the recognition accuracy of the experiment, so as to identify the position of the rail fastener with a suitable frame, and classify the identified fastener into its category. Through the analysis of the pr value of the experimental results, the experimental parameters are continuously modified to achieve the above effect. Finally, the pr value obtained from the experiment is about 0.6.

In order to accurately analyze the acceleration load acting on the general FPSO pipeline system, based on the potential flow theory, the hydrodynamic calculation software is used to analyze the long-term forecast value of the acceleration of the general FPSO under different overrun probabilities, and the calculated value of the fatigue load coefficient for fatigue evaluation is obtained, and the regression analysis is carried out. At the same time, the design wave method is used to convert the acceleration envelope value at any position of the general-purpose FPSO into a fatigue evaluation load, and a simplified formula for acceleration calculation is fitted. The results show that the applicability of the simplified formula is ideal. Provides a simple algorithm for calculating acceleration loads for general-purpose FPSOs.

With the vigorous development of railway industry, railway passenger transport and freight has become the most important link in today's transport industry. The operation of receiving and sending trains at the station is related to the transportation safety of the whole railway, so the action standard of the railway assistant on duty is more strict. In this paper, an improved action recognition algorithm for assistant duty officers based on dual flow convolutional neural network embedded attention mechanism is proposed. First, the TV-L1 method was used for optical flow processing of the video, and the mediapipe was used to obtain the coordinate data of human bone points. The two kinds of data were used as network input for training. Then, the trained network model is fused, and the two flow convolutional neural networks embed attention mechanisms. VGG16 network is selected for both spatial network and time network. Finally, the two models were weighted and fused by softmax function as the output result to complete the command action recognition of the assistant on duty. Experiments were carried out on the dataset UCF101, and the accuracy of the model on this dataset was 86.7%. Experimental results show that the improved network model has better recognition effect.

Motor heating can easily lead to the reduction of its working performance, and it is necessary to introduce highperformance fluid-cooling radiators. A non-pseudo-density thermal-fluid coupling optimization method based on component position parameters is proposed. By proposing the component disjoint constraint function, the sensitivity solution of the single constraint function to component parameter is obtained analytically. After the optimization progress based on component position parameters is completed, the average temperature of the design domain is greatly reduced, which illustrates the effectiveness of component positional parameter optimization method in the fluid-cooling radiator optimization problem.

The logistics industry is crucial to the global economy due to economic globalization and e-commerce. Matching vehicles and goods is a bottleneck problem in logistics, and improving the accuracy and efficiency of truck-cargo matching is a research hotspot. This study proposes a vehicle-cargo matching method based on deep learning using a deep reinforcement learning algorithm to train an agent. The Q-learning algorithm is used to train the agent, taking vehicle and source data as input, and outputting the matching scheme. The results show that this method has high timeliness, shortening matching time, reducing matching cost, and improving logistics efficiency and service quality.

The Multi-Trip Vehicle Routing Problem with Time Window (MTVRPTW) is a variant of the Vehicle Routing Problem with Time Window (VRPTW) that allows for the scheduling of multiple trips per vehicle within the driver's maximum working time limit. This article provides a review of existing research on MTVRPTW and proposes a two-stage heuristic algorithm that incorporates a novel initial solution generation method for solving general MTVRPTW test cases. Unlike existing methods, this approach utilizes greedy and ILS algorithms to generate multiple high-quality initial solutions in the first stage and employs the VNS algorithm to optimize the total distance objective in the second stage. The paper concludes by highlighting the significance of heuristic algorithms in solving MTVRPTW and offering suggestions for future research directions.

In order to improve the efficiency of outfitting production order selection in shipyard, the outfitting operation in the assembly center was studied from two aspects of order batch strategy and selection path. Aiming to minimize the weighted time of order picking time and order delay time, an order batch picking model based on improved envelope batch algorithm was constructed to complete the batch work of production orders. Then, a selection path optimization model based on improved genetic algorithm was constructed to complete the selection path planning of production orders. Finally, comparative analysis is carried out by an example. The experimental results show that the optimized production order reduces the order selection time and order delay time, improves the sorting efficiency of the assembly center, and also proves the effectiveness and practicability of the algorithm.

As rail vehicles cover more mileage and run at higher speeds, the problem of abnormal wear between the wheel and rail becomes increasingly prominent. Identifying wheel polygons is a crucial aspect of tackling this issue. In this study, acceleration signals are collected using the wheel rotation angle as the reference instead of time, and signal processing is carried out using the spatial spectrum Fourier transform. The results demonstrate that the Fourier transform based on the spatial spectrum can accurately identify the abnormal frequency of polygon distribution. This method solves the problem of polygon order recognition under changing train speeds and maintains good recognition accuracy. Simulation results show that the recognition accuracy under different speed segments is higher than 95%, and polygon order recognition can be conducted under different working conditions with robustness.

In order to shorten the tracking interval of urban rail trains and improve the transportation capacity of the line, under the framework of the train control system of vehicle-to-vehicle communication, it is proposed to predict the running trajectory of the preceding train by constructing a time-domain convolutional network model TCN, which provides a basis for the generation of the driving permission of the rear train, forms a tracking mode based on relative position, and finally verifies the logical correctness of the driving permission function design based on the prediction of the preceding vehicle trajectory through the modeling and simulation of the nonferrous Petri network (CPN).

Compared with 4G, 5G has greatly improved spectral efficiency, speed, security, etc., and 5G network is suitable for large-scale and ultra-high-speed application scenarios that are highly consistent with rail transit communication modes, and can meet the communication needs of vehicle-vehicle communication. Introducing vehicle-vehicle communication into the traditional train control system, vehicle-vehicle communication will occupy the physical resource block of vehicle-ground communication, resulting in serious interference phenomenon. Aiming at the interference problem caused by the reuse of vehicle-to-vehicle communication resources, a wireless resource allocation algorithm is proposed under the premise of ensuring its reliability. The improved HM algorithm is used to allocate the channel, and finally the spectrum utilization is improved through power optimization.

Aiming at the problem of facility location in traffic line construction, combined with the spatial and temporal characteristics of line construction, a multi-period multi-facility dynamic location model is constructed. Objective function is minimizing the total logistics costs. Subject to the characteristics of the model, the curved demand is represented by line integral, and the location and allocation of multiple facilities are decided. It uses the iterative dynamic programming method to solve the location of facilities in reverse order, and uses the nearest center allocation method to solve the demand. An example analysis shows that compared with static facility location, dynamic location of facilities can reduce the total cost.

Uninsulated track circuits are a key part of the train operation control system, and in uninsulated track circuits, compensation capacitor faults lead to reduced transmission distances due to increased transmission decay[1].In this paper, the sample nonparametric test method is used to analyze the difference of the compensating capacitor fault samples according to the different carrier frequencies, and the influence of different carrier frequencies on the compensating capacitor faults is excluded. On this basis, the spatiotemporal distribution of the fault capacitor is analyzed, and the main factors affecting the fault of the compensated capacitor are identified.

This paper mainly studies the application of DBSCAN and kernel density analysis methods in identifying accident-prone areas in the scene division of the diversion area of a highway, and compares the two methods. Firstly, 150 traffic accident data in a four-lane highway diversion area were collected, and the spatial correlation analysis was used to prove the clustering of accidents. Secondly, DBSCAN and kernel density methods were used for clustering analysis of the 150 traffic accident data, and their respective accident-prone areas were identified. Finally, an evaluation index Z value considering the total equivalent accidents and the average distance between accident points was used to compare and evaluate the accident-proneness in each area, and the advantages and disadvantages of the two methods were discussed. The research results of this article indicate that DBSCAN performs better in identifying multiple accident-prone areas in microscenes, while kernel density analysis can only identify a small number of accident-prone areas. This article provides theoretical basis and methods for the traffic safety management of highway diversion areas and even other short-distance areas.

This paper aims to address the current lack of accurate hourly traffic flow measurement by proposing a speed-flow measurement method based on the two integrated learning methods of LightGBM and XGBoost. The road network information, traffic speed and flow data from intelligent monitoring and recording system were integrated to build the traffic speed-flow model. The tree parzen estimator (TPE), a Bayesian optimization algorithm, was performed for the hyperparameter search of LightGBM and XGBoost, which combined with cross-validation to finally determine the optimal parameters. In addition, we compared the simulated results of LightGBM and XGBoost with BP neural network, random forest, and Van Aerde model. These results indicated that the TPE-LightGBM and TPE-XGBoost based on Bayesian optimization had more accurate and better prediction results than the other models. The MAPE of TPE-XGBoost and TPE-LightGBM decreased 12.19% and 12.26% than Van Aerde model on average, respectively. Compared with the traditional deep learning algorithm, such as BP neural network, the MAPE of TPE-XGBoost and TPE-LightGBM decreased by 4.45% and 4.52%, respectively. Our results further showed that the TPE-XGBoost had higher accuracy for estimating the flow of expressway, while the TPE-LightGBM was more suitable for analysis in the main roads and secondary roads.

The activation of transit signal priority (TSP) will bring some delay savings to the vehicles running in the same direction, but also increase the delay of vehicles running in the conflicting direction. In order to quantify the impact of transit signal priority activation on the delay change of vehicles in the same direction and other directions, and limit its adverse impact on the overall delay of the road, this paper takes the mixed-traffic road without bus lane as the research object, and simulates the vehicle operation and signal timing scheme on the road with multiple intersections. With the goal of minimizing the total delay of social traffic flow and minimizing the negative impact of transit signal priority on the delay of road travelers, the coordinated timing control of signals at multiple intersections and selective activation of transit signal priority is realized, simulated annealing algorithm and implicit enumeration method are used to implement the model respectively. Finally, the delay of three types of road travelers under various signal schemes is compared. The results show that the optimization scheme can maximize the operation efficiency in the artery and reduce the adverse impact on the cross-street vehicles, so as to improve the operation condition of the vehicles on the road with multiple intersections and reduce the overall delay of the travelers.

The design of modern civil aircraft systems pays great attention to its economy. Auxiliary power unit systems (APS) is used continuously while waiting for passengers on the ground, and the market demands for its performance and fuel consumption gradually improve. The APS performance of APS is greatly affected by aerodynamic performance. Referring to the calculation method of aerodynamic theory, a set of methods suitable for the numerical calculation of the aerodynamic performance of APS based on the practice of system design is researched and summarized in this paper. A design example is selected and the method is used to calculate the total pressure loss and ram recovery of aerodynamic performance indicators. The results indicate the ground total pressure loss and air ram recovery under the five working conditions meet the design requirements and close to the simulation results. This provides a reference for the aerodynamic design of APS.

This research investigates the bus stop loss time under different rainfall intensities, discusses its influencing factors and introduces indicators such as the number of passengers getting on and off, the loss time and the total time of getting on and off. The change in the bus loss time is analyzed with daily rainfall intensity and the number of berths as independent variables. It explores whether the loss time differs at different bus stops. Based on Pearson correlation analysis, the regression prediction model of loss time is established by SPSS. The results show that the number of passengers getting on and off differs under different rainfall intensities. Generally, the number of passengers on light and moderate rainy days is more than that on heavy rainy days, and this change is more prominent during the weekend. For the same number of passengers, the bus stop loss time of heavy rain tended to be more than that of light and moderate rain. The bus transit system is affected by the drainage capacity of the bus stop, especially in heavy rain. With the same number of passengers, the total time of getting on and off in heavy rain is usually more than in light and moderate rain

Mobile edge computing (MEC) is a promising paradigm for offloading compute-intensive services on vehicles to alleviate the problem of limited resources in the vehicles themselves. However, since the vehicle network involves multiple edge servers, MEC is facing the dilemma of how to fully utilize the edge resources to achieve the maximum benefit. In this paper, we aim to analyze MEC task offloading strategies from a multi-objective optimization perspective by considering independent partitionable computational tasks, and an MEC communication and computation offloading framework is constructed. A partial computational resource optimization (PCRO) algorithm is proposed, which jointly considers computational resource allocation and unit price adjustment to achieve minimum cost for vehicle users and maximum profit for edge servers. Extensive experimental results demonstrate the effectiveness of our proposed PCRO algorithm.

In order to improve the problem of lack of finger dexterity due to the use of rigid palms in traditional manipulators, this paper designs a new type of dexterous hand with a variable cell structure based on the palm of a planar five-bar variable cell mechanism, combined with a three-finger structure that imitates the joint-coupled drive of a human finger. The introduction of the variable cell structure increases the working range and dexterity of the mechanism and also improves the adaptability of the dexterous hand to grasp objects of different sizes. This paper presents the mechanical structure, kinematic model, and simulation results of the working space of the variable cell mechanism dexterous hand.

In this paper, based on the study of the mean, standard deviation and other eigenvalues of travel time, the expression of path travel time reliability was derived step by step from the road-section travel time reliability, which avoided the limitation of direct assumption of the expression of path travel time reliability, and had a certain degree of persuasion. At the same time, combined with the edge capacity reliability model, a standby application bi-level programming model of the road network under random conditions was established, and the chaos optimization idea was used to solve the problem. The effectiveness of the model was further verified by case analysis.

The reduced thrust takeoff is a practical method for cutting off airplane maintenance costs. To satisfy the various takeoff targets, different types of civil aircrafts have different reduced thrust takeoff functions. Correctly designed thrust reduction function is crucial for the competitiveness of a newly developed aircraft. However, the design of the reduced thrust takeoff function including the coupling of several disciplines, which results in challenges. To solve the problem, the benefits of reduced thrust takeoff under various takeoff conditions are computed. The calculation results are used to discuss the design method of the reduced thrust takeoff function of civil aircrafts.

Build a driver side restraint system model of an SUV according to MPDB (50% overlapping progressive deformation barrier impact test on the front) working conditions. Evaluation of the system using the Thor 50M dummy revealed poor performance in terms of chest compression and neck tension Fz, both of which exceeded the requirements set by C-NCAP regulations. To address this issue, we utilized a high-dimensional multi-objective optimization technique to optimize the airbag design parameters. To optimize the dummy injury values, we conducted an analysis of each airbag parameter using the univariate test method. We studied the effect of each parameter on the injury values of the dummy's head, neck, and chest, and selected parameters that exhibited high sensitivity. Specifically, we selected the dummy chest compression, head HIC15, acumulative 3ms acceleration value of the head, and neck tension Fz as our optimization objectives. To perform the sampling simulation, we used uniform Latin hypercube sampling for the parameters. We constructed an agent model for the four optimization objectives using the response surface modeling method, followed by a high-dimensional multiobjective optimization. We substituted the local optimal solutions of the optimized airbag parameters into the simulation model to verify their effectiveness in improving the dummy injury values. The simulation results demonstrate that the optimized airbag parameters reduced the dummy's chest compression by 13.53%, head HIC15 by 31.28%, neck tension Fz by 30.41%, and acumulative 3ms acceleration value of the head by 19.76%. These improvements enhance the occupant protection provided by the restraint system. Our study shows that optimizing the airbag design parameters can provide new ideas and techniques to enhance vehicle safety.

Traffic congestion and delays are common problems in most urban areas, especially downtown, industrial and commercial distinct. The traffic condition affects economic development and people's quality of life in the distinct. Therefore, it is imminent to solve the road congestion problem. A significant factor in this problem is inefficient traffic signal timings for intersection, which is the hub of road traffic and plays a vital role in relieving the pressure of traffic. In this research, we propose a district-oriented traffic signal timing optimization algorithm that considers the characteristics of different districts and their traffic patterns. It improves traffic parameters of traffic control and improve road congestion problem by improving the traffic conditions of intersection. Our algorithm leverages real-world data from intersections and the type of transportation vehicles. We compare the performance of our algorithm with Webster classic algorithm using real-world data from smart town transportation system. The results show that our algorithm outperforms the other methods in terms that, the average green letter ratio increased by 7.77%, the saturation decreased by 67.6%, the delay time decreased by 59.08%, the traffic capacity increased by 6.1%, and the transportation capacity increased 68.51%.

The number of highway renovation and expansion projects continues to increase, and the construction of this project is bound to increase its adverse impact on road survey buildings. To reduce environmental impact, a fully enclosed sound barrier is planned to be constructed in some sections of the Shen-Shan West Expressway. The fully enclosed sound barrier forms an operating environment similar to a highway tunnel. Due to its strong sealing and low visibility characteristics, once a fire occurs, the consequences will be extremely serious. PyroSim and Pathfinder software are used to simulate the diffusion speed of fire smoke in enclosed environments and the evacuation efficiency of drivers and passengers, and to evaluate whether the design scheme of fully enclosed sound barrier road sections meets the needs of personnel evacuation under fire conditions. The experimental results found that under fire conditions, drivers and passengers on the research section can safely escape through the road entrance and emergency escape doors.

In recent years, with the continuous improvement of automobile manufacturing technology, road traffic pressure has gradually increased. According to relevant traffic accident statistics, there are approximately 500000 traffic accidents in China each year, of which about 30% are caused by road blind area, resulting in serious losses. Due to factors such as car structural design and human physiological structure, there is currently no suitable response methods for cars when facing blind area on the road. So developing a reliable blind area monitoring system for vehicles has become a research focus in the field of active vehicle safety. From the first perspective of automobiles, this article proposes a detection and warning device for blind area on the road in the driving map of automobiles. The main body of the device is installed inside the driver's cab and outside the vehicle. Through image acquisition and convolutional processing, data is analyzed. If dangerous situations are detected in the blind area ahead, the system will promptly provide graded warnings to the driver. This research in this article greatly expands the research on blind area on roads and traffic signal processing, which is of great significance for promoting road traffic safety and social order stability.

Aiming at the actual traffic driving environment, this paper proposes an acoustic perception method of intelligent vehicle based on microphone array, and combines the visual perception method of monocular camera to study the acoustic visual fusion perception method. The main research contents are as follows: Firstly, an acoustic simulation environment for intelligent vehicles is designed. Secondly, a sound source localization algorithm based on time delay estimation is proposed. Based on the geometry of the microphone array, the sound source localization problem is abstracted as a time delay estimation problem, and the sound source localization is realized. The received signal of the microphone is added by weighted delay to form a beam with a certain direction, which is visualized as a spatial SRP power map. The passive sound reception is transformed into an active search for space, which improves the positioning accuracy in low SNR and reverberation environment. Thirdly, a sound source perception localization algorithm combining deep learning network and delay algorithm is developed. Based on SELDnet neural network, the SRP power map is used as input, and the cyclic convolution layer is replaced by the temporal convolution layer. The simulation results show that the positioning accuracy of the fusion positioning network is 65.04 % higher than that of the SELDnet network in the ideal environment and 76.19 % higher in the low SNR environment. The feasibility verification experiment and simulation experiment of the algorithm are carried out, and the sensor data in the real vehicle environment is collected for the real vehicle data verification experiment. The results show that the average positioning error of the acoustic vision fusion algorithm is 0.1 m at the 60 m scale. At the same time, the algorithm also has strong adaptability to visual blind spots, which proves the deployment potential of the algorithm in the actual environment.

To address the imbalance in the duration of crew pairings from different crew bases in current research, we propose a crew scheduling optimization model for high-speed railways. The objective is to minimize the connection time between crew trips for multiple crew bases, while also ensuring duration balance of crew pairings, based on the multiple Travelling Salesman Problem (mTSP) modelling. Then, this study designs a heuristic Ant Colony Optimization (ACO) algorithm to solve the model. The numerical experiments demonstrate the effectiveness of the proposed model in reducing the connection time between crew trips and maintaining balance in the duration of crew pairings.

In order to achieve the collection and real-time transmission of LVDS video signals, a design scheme for airborne LVDS video signal conversion and branching is proposed. In response to the high speed and strong real-time characteristics of LVDS video signals, signal equalization compensation, signal conversion, signal branching, and balanced encoding design have been completed. The serial LVDS video signals extracted from the aircraft are adjusted and processed to convert into parallel LVDS video signals, which are amplified and processed to output two parallel LVDS signals. One is used for measurement system data recording and telemetry transmission, and the other is converted into serial LVDS signals, Return to the original system on the aircraft. The experimental results show that the LVDS video signal conversion device has good stability, high reliability, and strong real-time performance, solving the problem of real-time transmission and monitoring of LVDS video signals, and meeting the requirements of aircraft flight tests.

The basic charging needs of electric vehicles have been met. However, due to the diversity of charging modes and types of charging stations, it is still of great significance to study the electric vehicle routing problem with time windows and different types of charging stations. Considering the impact of different charging modes on the total distribution cost and operational efficiency, this paper establishes a model of electric vehicle routing problem with time windows and multiple types of charging stations (EVRPTWMTCS), designs a solution algorithm based on the adaptive large neighborhood search (ALNS) algorithm theory, and analyzes and verifies it with the EVRPTW international standard data set.

The variation of surface meteorological conditions caused by different precipitation phases has multiple effects on the safe operation of expressways. In this study, based on the dual-polarimetric Doppler radar data and other meteorological data the rain and snow process in Jiang Province of China in January, 2018 is taken as an example. The data of dual polarization Doppler radar and various meteorological data are applied to the diagnostic analysis of physical quantities. Then, the phase distribution characteristics of polarization parameters and non-polarization parameters of radar echo under different phases of precipitation are studied. Based on the variation relationship between radar echo and pavement meteorological conditions, the application research of road weather forecast has been carried out. The results show that in the whole rain and snow process the stratus exists in low levels, which can wet-warm the atmosphere and provide favorable conditions for the continuous snowfall. The radar echo can accurately reflect the fine vertical structure of the rain-producing cloud body at each stage, which contributes to the precise forecast of precipitation phase. In order to respond to the variation of surface meteorological conditions, the pavement slipperiness index is constructed, and the management schemes of variable speed limit under different traffic flowrates are designed.

This paper takes a unsignalized intersection as the background, takes the Connected Autonomous Vehicles (CAVs) as the research object, and focuses on the path optimization problem of the CAV in a traffic environment with both CAVs and Human-Driven Vehicles (HDVs) with the goal of ensuring traffic safety and improving traffic efficiency. In view of the above problems, this paper proposes a path optimization method for driving CAV at unsignalized intersections with the assistance of Road Side Unit (RSU). Simulation results show that the path optimization algorithm proposed in this paper can guide the CAV to pass through the unsignalized intersection safely and efficiently.

By carrying out line tests to obtain the original data on the vibration acceleration of the stabilizing device, rail and sleeper during the operation of dynamic track stabilizer. And analysis of the measured data, from the time domain, frequency domain and energy and other aspects, research track power stabilization of different parameters under the operation of transverse vibration transmission characteristics, the results show that: transverse vibration from the stabilization device to the rail and then to the rail sleeper this process is gradually decreasing, different stabilization operation frequency vibration transmission is different, to acceleration signal root mean square value as an evaluation index, from the stabilization device to the rail sleeper transmission efficiency in the lowest at 44.2% up to 52.7%; Stabilization frequency change on vibration transmission efficiency, 25Hz-33Hz with the increase of stabilization frequency transmission efficiency also increased, 33Hz transmission efficiency reached the maximum, 33Hz-38Hz as the frequency continues to increase transmission efficiency has decreased; stabilization device at the fundamental wave corresponding to energy 33Hz>gt;38Hz>gt;30Hz>gt;25Hz; rail at the fundamental wave corresponding to energy 33Hz>gt;38Hz>gt;30Hz>gt;25Hz; rail at the fundamental wave corresponding to energy 38Hz>gt;25Hz>gt;33Hz>gt;30Hz; 33Hz>gt;38Hz>gt;30Hz>gt;25Hz for the fundamental wave at the rail sleeper, the frequency band of the energy carried by the vibration signal from 25Hz to 38Hz increases with the increase of frequency.

By analyzing the impact of right-turn accidents of tractor and semi-trailer on traffic safety, foreign commonly used test methods for vehicle combination turning performance were studied. Based on the above, a semi-trailer train right-angle turn test method suitable for China was proposed and the effectiveness of the method was verified through full vehicle road tests. The study adopts a combination of theoretical analysis and field tests, and through comprehensive analysis of factors such as the turning ability and operating environment of tractor and semi-trailer, a suitable tractor and semi-trailer right-angle turn test method for China is established, and the effectiveness of the method is verified. The results of the study show that the proposed test method can accurately evaluate the passing performance of tractor and semi-trailer, effectively avoiding the impact of right-turn accidents on traffic safety, and has practical value and promotion significance.

Urban rail transit (URT) is popular in many big cities because of its advantage of traffic performance. Affected by the whole life cycle, URT lines often involve renovation projects. In view of the increasing needs for the renovation of URT signal systems, this paper studies the signal system and its interface, analyzes the general process of the renovation, and then discusses the careful planning, safety supervision and related ancillary works for the installation and debugging supervision in the renovation. Installation and debugging are the key link of a renovation. The content of this paper has guiding significance for the concrete implementation of renovation projects of URT signal systems.

Based on the Botanical Garden station of Xi'an Metro Line 8, the finite element analysis model of Pile-Beam-Arch excavation method(PBA) is established. Combined with the actual construction and geological conditions, the finite element simulation analysis was carried out according to different excavation sequences, and the settlement, deformation and stress behaviors under different working conditions were screened, and the displacement and stress characteristics of the guide tunnel excavated by the hole pile method under the multi-factor change effect were analyzed. The variation characteristics of the displacement and internal force of the whole system with different excavation processes are revealed, which provides an important reference for the design and construction of the PBA guide tunnel.

When encountering dangerous scenarios that is difficult to deal with, intelligent vehicles should prompt the driver to take over the driving right of the vehicle. The effect of the take-over warning signal is related to the driving safety. The human-machine takeover experiment of intelligent vehicle is carried out through the driving simulator, the reaction time of the driver is analyzed, and the effects of different warning modes are studied. The results show that: warning signal can obviously shorten the driver's reaction time and improve driving safety; the combination of visual and auditory signal is better than a single warning signal; there is an interaction effect between auditory and visual signals; the effect of auditory signal is better than that of visual signal when there is a single warning signal.

In order to analyse the changing quality evaluation indexes in the compaction process of cement-stabilised gravel subgrade, and to analyse its change mechanism from the perspective of its calculation principle, the secondary development of Abaqus finite element analysis software was further carried out by writing USDFLD subroutine; at the same time, the experimental data of large-thickness water-stabilised layer compaction were brought into the finite element software analysis to realise the The data from the large-thickness water-stabilized layer compaction experiments were brought into the FEA software to analyze the dynamic changes in material parameters and strain changes during the cement-stabilized subgrade compaction process, effectively improving the accuracy of the numerical simulation results. This will provide a comprehensive understanding of the changes in the compaction of the subgrade during the vertical vibratory rolling process, which is of practical significance for the analysis of the subgrade rolling process and the reduction of damage caused by compaction testing.

As a new type of vessel, unmanned surface vessels (USV) have been widely applied in ocean transportation. In order to improve the accuracy of USV dynamic information prediction, a Bayesian Optimization Long Short-Term Memory (BOLSTM) neural network model is proposed. The model utilizes the Automatic Identification System (AIS) to extract and process the time-series data of USV dynamic information for training and prediction. The results of BO-LSTM are compared with those of traditional LSTM networks and BP neural networks, which demonstrate that BO-LSTM has higher accuracy, timeliness, and applicability. Furthermore, it can provide important reference for USV route planning, abnormal point detection of navigation track and other related issues

As the functions of ADAS system are gradually general and play an increasingly important role in driving tasks, it has high requirements on the reliability and safety of ADAS system. It is necessary to validate ADAS system in various complex traffic conditions to test whether it can correctly identify and deal with various dangerous situations. ADAS system simulation test method includes software in the loop (SIL), hardware in the loop (HIL), vehicle in the loop (VIL) and represented by closed field and open road represented by the real vehicle test method, real vehicle test is difficult to cover dangerous or extreme scenarios, simulation test in the test coverage and test efficiency has irreplaceable advantages. Although most simulation platforms have the ability of sensor modeling simulation, vehicle dynamics modeling simulation and traffic scene construction simulation, most of the simulation models are built under ideal conditions, and the confidence level of the results obtained by simulation has not been evaluated by specific quantifiable indicators. In this paper, based on the hardware simulation test of ADAS function, compare the actual road test results in real physical environment, and analyze the error of the simulation test to provide reference for the simulation confidence study.

The tracking time of high-speed maglev trains is the basis for improving maglev transportation capacity. As the key of train stepping, the relationship between the position of auxiliary stopping area and tracking interval time is worth exploring. In this paper, we analyze the vehicle tracking process, calculate the tracking interval time, observe the change of tracking interval time by the change of auxiliary stopping area position, get the dynamic influence relationship between tracking interval time and auxiliary stopping area position, and provide the theoretical basis for the cooperative optimization design of tracking interval time and auxiliary stopping area.

As biomechanics research evolves, the significance of motion capture technology in domains like film and television, gaming, and motion training is progressively gaining prominence, with an expanding repertoire of applications. Optical motion capture, employing optical dynamic capture equipment founded on a 3D imaging analysis system within a specified setting, stands as the most mature technique. However, its high cost and constraints pertaining to venue and environmental factors limit its usage. Conversely, inertial motion capture devices, functional under non-optical conditions, can cater to the needs of the broader public. To further enhance affordability, portability, and simplification of the device, this study proposes an embedded system design grounded on a nine-axis inertial sensor. It captures the posture of each joint in the human upper limb and wirelessly transmits the data to the Unreal Engine 3Darmmodel for action replication and motion trajectory delineation. Thus, it generates feedback results facilitating remote motion control.

Due to the advantages of high punctuality and speed, urban rail transit systems are attracting more and more commuters. In consequence, overcrowding during peak periods has become the norm in megacities, which poses a great challenge to operations. To address this challenge, this paper investigates the integrated optimization of passenger flow control and bus-bridging on oversaturated urban rail transit lines. Based on the time-dependent passenger demand, we propose an integer nonlinear programming model that aims to minimize the overall system cost. Then, to cope with the solving difficulty due to nonlinearity, the proposed formulation is further transformed into an equivalent mixed-integer linear programming model. Finally, real-world case studies based on the operating data of Beijing metro Batong line are applied to verify the effectiveness of our proposed approach. The computational results illustrate that our proposed method can significantly reduce the average passenger waiting time and improve operational safety.

In the process of walking, pedestrians usually have a certain destination. However, the current velocity of the pedestrian is not constantly consistent with the destination. Thus the pedestrian needs to adjust the current velocity by changing lanes. In this study, based on different velocities of reaching the destination, the deviation coefficient is introduced to represent the deviation of the pedestrian's current velocity from the destination; It is also proposed that the pedestrian has inertia for adjustments of the current velocity and would tolerate a certain degree of deviation out of walking comfort. Thus the pedestrian's lane-changing action is transformed into a dynamic balance between maintaining the current velocity and adjusting the velocity for the destination. In the end, a velocity-based pedestrian lane-changing simulation model is proposed, and a single pedestrian walking scene is simulated to obtain the smooth walking trajectory, in which the phenomenon of hysteresis for lane-changing can be clearly observed.

In order to explore the location and sizing problem of electric vehicle charging stations, this paper comprehensively considers the impact of different land types on user travel and charging station construction costs, and establishes an electric vehicle charging station location and sizing model based on charging demand forecasting. This paper first analyzes the travel behavior characteristics of electric vehicles, including travel time, travel destination, parking time, and travel times, and builds an electric vehicle travel chain based on this. Second, we use the Monte Carlo method to calculate the electric vehicle's position and state of charge. At the same time, considering the user's power anxiety coefficient, we judge the charging behavior of electric vehicles and obtain the spatial and temporal distribution of electric vehicle charging demand. Then we consider the impact of land type on the construction cost of electric vehicle charging stations and use the queuing theory to analyze the queuing system of charging stations. We establish an electric vehicle charging station location and capacity model with the goal of minimizing social costs, using the genetic algorithm to solve. Finally, we verify the effectiveness of the proposed planning method through case analysis. The results show that construction and operation costs will continue to rise with the increase in the number of charging stations. In contrast, the time cost of electric vehicle users will continue to decline. The charging station location and capacity determination method proposed in this paper can effectively balance the interests of both charging station construction operators and electric vehicle users. In the planning process of charging stations, it is worth considering the impact of land types on user travel and construction costs. Building charging stations in residential and industrial areas close to commercial or leisure areas is valid to reduce total costs.

With the rapid development of rail transit, passenger comfort and other indicators began to receive more and more attention, the stability and comfort of subway vehicles have higher requirements. The stability test of subway train is usually used for the performance evaluation of new cars, which is one of the important parts of the type test of new cars. In this paper, the dynamic performance test of PW80E-I(G) type metro bogie is firstly carried out. According to《GB/T5599-2019 Specification for Evaluation and Test of Locomotive and Rolling Stock Dynamic Performance》and《GB/T14894-2005 Inspection and Test Rules after Assembly of Urban Rail Transit Vehicles》and other standards, The stability and safety of the bogies were evaluated under no-load and heavy load conditions as well as air spring failure and normal operation. Through the calculation and analysis of the data, the operation quality of the starting vehicle and trailer under aw0 and aw3 working conditions is obtained, and the comprehensive dynamic evaluation of PW80E - Ⅰ (G) Metro is carried out. The test results show that the vehicle running safety index meets the requirements, the running stability index is excellent, and the bogie frame does not appear lateral instability phenomenon.

Under the requirement of ' double carbon ' target, the proportion of PV generation and electric vehicle connected to power grid is higher and higher, and its uncertainty brings challenges to the stable operation of power system, especially distribution network. This design uses Gaussian mixture model to depict the uncertainty of photovoltaic power output and depict the daily time series characteristic curve of photovoltaic power output. Then, a multi-objective planning model of electric vehicle charging pile is proposed, which aims at the minimum investment cost, the minimum active network loss and the minimum node voltage deviation. The entropy weight method is used to transform the multi-objective into a single objective as an index to measure the planning scheme. On this basis, the information gap decision theory is introduced, and the influence of the uncertainty of the electric vehicle charging pile load is considered. The installed capacity of the charging pile is planned, and the feasible range of the installed capacity is given. In the verification of the comparison example, the correctness and effectiveness of the planning scheme under this kind of index are verified.

By optimizing the traction force of each load node bending moment matching blade loading process, a full-size set of frequency control of motor speed electro-hydraulic drive static test system has been researched. Deviation at each node load force as the input, the frequency for each load point of the output control, the BP (back propagation) neural network PID (proportion-proportion-differentiation) control algorithm was designed. Value output deviation value into PID controller operation frequency, deviation value and frequency value on-line adjustment of BP network, at the same time get the PID parameter setting, reduced the number of each node traction coupling, realized the node coordinate loading full size. Experimental results show that the control algorithm to solve more coupling and loading in the process of loading point traction can maintain smooth, coordinate change, have stronger anti-jamming adaptability, meet the requirement of the static loading test for blades of wind power.

Artificial fish swarm algorithm is a typical intelligent algorithm, which is suitable for solving nonlinear optimization problems, such as unit commitment optimization. However, the algorithm has some defectiveness including premature convergence and easily trapped into local extremes. To make up these disadvantages, this paper proposes a modified artificial fish swarm algorithm, which adopts a variable vision, makes adjustment to the movement strategy and combines the mutation operation of genetic algorithm. A mathematical model of unit commitment with phased optimization is established to solve the problem of long computing time results from large scale units. According to the results of simulations for up to 1000 units, the modified algorithm performs better in convergence and global search, and has certain advantages in solving unit commitment problems, and the phased optimization significantly shortens the calculation time of large-scale unit commitment optimization.

In order to explore the influence of the combined action of fragments and shock wave on the surface deformation of the contour shape of metro vehicles, the combined effect of shock wave and fragments on the wheels of metro vehicles is simulated by using any Lagrange-Euler method. The unobstructed area of the wheel, the contact area between the wheel and the frame and the contact area between the wheel and the track are simulated according to the actual structure of the wheel. Firstly, through the simulation results of fragments and shock wave in the air domain, the speed change of fragments and the pressure change of shock wave are obtained, and then the simulation model is established near the three areas of the wheel, lastly, the deformation degree and deformation area of the wheel, frame and track in different areas are obtained. The results show that in the air domain without wheels, the maximum shock wave of fragments can reach 1390 MPa, and the maximum fragments speed can reach 1541 m/s. When the fragments and shock waves act on the wheel, the shock wave and fragments in the unobstructed area of the wheel have obvious effects on the deformation of the wheel flange surface, while the deformation effect of the wheel in the area where the wheel and the frame are connected is concentrated on the side of the wheel, and the wheel deformation is concentrated on the side of the wheel and the tread in the contact area between the wheel and the track.

The role of the rail is to directly bear the weight of the train and its load transmitted by the wheels, and to guide the direction of the train. Prolonged train travel can cause unavoidable defect to the rails; however, China's railways are developing at a high speed, and rail damage will also increase. In order to ensure the safety of railway operation, the detection of rail damage must be fast and efficient. So, a method is needed to quickly and accurately detect the type of rail defect. Due to the superiority of machine vision detection, a rail surface anomaly detection method based on deep learning is proposed. Firstly, the image data features are extracted through the image annotation tool labeling. After that, the YOLO v5 deep learning network is trained by the training set. Finally, the accuracy of the trained network is checked, and the relevant parameters are modified to adjust the accuracy to the best. The overall rail defect detection accuracy reaches 97%, indicating the feasibility and effectiveness of the proposed method.

The reliability of solenoid directional valve has great influence on the working performance of hydraulic system. Based on the fault analysis of the solenoid directional valve, the typical fault of the valve core not acting is studied. Through the modeling and simulation of the dynamic characteristics of the solenoid directional valve, the current and displacement signals that can be used as the real-time fault monitoring parameters of the solenoid directional valve are extracted, and the current and displacement signals of the energizing and closing section of the solenoid directional valve under different states are simulated, which verifies the rationality of the selected two fault monitoring parameters, and provides the basis for the construction of the real-time fault monitoring system of the solenoid directional valve.

In recent years, the rapid development of the new retail economy, which is centered on consumers and deeply integrates online services with offline experience and modern logistics, has put forward higher requirements for the timeliness of distribution, and the problem of insufficient transportation capacity in the distribution link has become increasingly apparent. This paper uses logistics information technology to solve the problem of transport capacity, and uses Anylogic computer simulation software to establish a distribution simulation model, combined with cases, to optimize the distribution plan. Experiments have proved that the optimized scheme can reasonably solve the capacity problem.

The armored vehicle, a main weapon of the army, has been exposed to harsh conditions for a long time, and its smoothness affects combat effectiveness. Optimizing the suspension system can improve the vehicle's stability and ride comfort, thus enhancing performance. This paper uses a 8×8 wheeled armored vehicle as an example, modeling and simulating its ride comfort on asphalt, sand, and pulse roads with ADAMS/Car software, optimizing suspension parameters, and analyzing the optimized results. Optimizing damping and stiffness parameters of the suspension improves ride comfort, verifying the feasibility of using approximate D-optimal method to optimize suspension parameters.

In order to solve the problem that minimum control strategy of equivalent fuel consumption for plug-in hybrid electric vehicles (PHEVs) is not effective, an ECMS energy management strategy based on improved annealing algorithm was designed. Firstly, based on the traditional control model, the optimized PID equivalent factor control model is constructed. In order to solve the problem of overfitting when optimizing the traditional annealing algorithm (SA), tempering link and memory search function were added to the algorithm, and the improved algorithm was used to optimize the PID equivalent factor, and the vehicle dynamics simulation was carried out in MATLAB/SIMULINK environment. The results show that: Under the Worldwide Light-duty Test Cycle (WLTC) conditions, compared with the rule-based logical threshold control strategy and the pre-optimized ECMS strategy, the optimized ECMS strategy increased the fuel saving rate by 18.49% and 3.28%, respectively. Under the New European Driving Cycle (NEDC) conditions, compared with the rule-based logical threshold control strategy and the pre-optimized ECMS strategy, the fuel saving rate is increased by 20.20% and 2.61%, respectively. The proposed model effectively reduces fuel consumption and has good robustness.

In the process of developing an electric vehicle test bench, control accuracy is often low due to interference and other factors. To address this problem, this paper proposes a dynamic load emulation algorithm based on dynamic matrix control. Firstly, we create a detailed model of the distributed electric drive system. Then, we analyze the process of dynamic load emulation and propose an algorithm based on dynamic matrix control. Comparative simulations and bench tests are conducted to verify the algorithm. The results demonstrate that the proposed algorithm can achieve hardware-in-loop (HIL) test and improve test accuracy, as intended.

In order to solve the problem of controlling the pressure fluctuation in the oxygen supply train in the extreme tunnel conditions with high altitude, extra-long and large gradient in the western mountainous railway, this paper analyses the gas exchange path of the train, establishes a semi-empirical model of the internal pressure in the oxygen supply train, and verifies the accuracy of the model by using the simulation results of one-dimensional numerical simulation. For the passive pressure control method of controlling the stop valve of the air exchange system, an internal pressure iterative learning control algorithm with oxygen partial pressure as a constraint is proposed to meet the pressure comfort requirements and oxygen supply needs of passengers. The results are compared with those under the uncontrolled and traditional control methods. The comparison results show that the iterative learning control algorithm for internal pressure with oxygen partial pressure as a constraint is effective in reducing pressure fluctuations, and that the oxygen partial pressure level also meets the oxygen supply standard. the iterative learning control reduces the peak pressure in the vehicle without control from 9212.77 Pa to 8062.90 Pa, an improvement of 12.48%.

The controller design of an automatic train operation system under multiple operating constraints is studied in this paper. Based on the nonlinear multi-particle model of metro trains, a predictive control algorithm of the automatic train operation model has been established to meet the requirements of train punctuality, energy saving, and passenger comfort. On this basis, the input blocking technology was introduced to adjust and reorganize the distribution of the control time domain in the prediction time domain of the (Model Predictive Control) (MPC)algorithm. At the same time, the simulation model was used to verify the effectiveness of this algorithm. The simulation results show that when the operational constraints are met, the calculation time of this algorithm is less than that of the standard model predictive control algorithm, when accuracy is ensured.

In order to alleviate the congestion of roundabout and adjacent intersections, the intersection group composed of roundabout and adjacent intersections as the research object, the delay of vehicles at each intersection of the trunk is analyzed, the minimum delay model of the trunk is established, and the method of trunk coordinated control is adopted to optimize the signal timing of each intersection in the control area. The parking and delay of the example are analyzed by VISSIM simulation software. The results show that the average number of vehicle stops after optimization is reduced by 13.86%, and the average delay time of vehicles after optimization is reduced by 19.37%. The optimization effect is obvious. The coordinated control method of circular intersection and adjacent intersections proposed in this paper is feasible and practical.

The reliability and accuracy are low when the traditional method is used for fault diagnosis of shearer bearing. It was proposed that bearing fault diagnosis of shearer based on artificial jellyfish search (JS) optimized probabilistic neural network (PNN). The vibration signals of different states of bearings are identified and classified. The artificial jellyfish search algorithm is used to optimize the smoothing factor of the probabilistic neural network model. Finally, the optimized model is used for fault diagnosis. The experimental results show that the diagnostic accuracy of the probabilistic neural network model optimized by the artificial jellyfish search algorithm is higher than that of the traditional probabilistic neural network model and particle swarm optimization probabilistic neural network model, with an accuracy of 95.4%.

The vehicle can achieve stable control, which is very important for the handling stability and safety of the vehicle. The vehicle ESP algorithm needs to be fully tested during the development process to ensure that the algorithm has good functionality and robustness. The commonly used algorithm testing methods usually include software-in-the-loop testing, hardware-in-the-loop testing, real vehicle testing and other means. This paper studies how to test the vehicle ESP algorithm through the driver-in-loop test. This test method can take into account the subjective feelings of drivers while ensuring safety.

Speed limit sign is an important measure to control driver’s driving speed and improve road traffic safety. It will have a series of impacts on the driver’s behavior, but the mechanism of its impact on the driver’s speed choice behavior is still unclear. In this study, three road scenes under different speed limit sign environments were constructed through UCwin/Road software, 20 drivers were recruited publicly, and a driving simulation test was carried out. Using mathematical statistics to summarize and analyze the data, taking the driving speed and acceleration of the drivers as the analysis indicators, the speed behaviors of the drivers when passing the speed limit sign were analyzed, and the influence rule of the speed limit sign on the driver’s speed selection was obtained. The results show that drivers tend to drive at high speed; the 100km/h and 80km/h speed limit signs have an impact on the speed choice of some drivers, but this impact is extremely limited, and drivers will still drive over the speed limit.

The four-link constant support hanger often causes the pipeline to bear additional stress due to the excessive load invariance, which poses a safety hazard. Starting from the force analysis of the four-link constant support hanger, the control conditions of the load invariance are theoretically deduced, and the finite element model is established. Using two working conditions, the relationship between the control parameters of the load invariance is compared and studied. The theoretical control conditions of the load invariance are verified, and the applicability and influencing factors of the load invariance control conditions are studied. The results show that: in the example model whose geometric structure is determined, the load invariance is not affected by the spring stiffness, it is only related to the spring precompression, and when the spring precompression is not less than 172mm, the load invariance can be satisfied not more than 6%. The standard requirements, the conclusion is consistent with the theoretical derivation; while the geometric size has an impact on the load invariance, choosing the appropriate size parameters can make the load invariance as low as 1.2% and 0.2%. This study can provide a reference for the design and selection of the four-link constant support hanger.

In order to study the dynamic performance of the higher-speed inner axle box bogie, the rolling vibration mechanics test of the higher-speed inner axle box bogie is carried out on the test rig. Through the simulation calculation of the dynamic simulation software SIMPACK, the stability of the hunting stability, the running stability and the difference of the suspension natural frequency of the car body and the bogie frame are analyzed. The results show that the linear critical speed of the built-in axle box bogie is greater than 600km/h; there is little difference between the simulation and test results of the lateral acceleration, lateral stability, comfort index and natural frequency of the frame end, which fully shows the superiority of the dynamic performance of the built-in axle box bogie and the accuracy of the model. It can provide theoretical support and reference for the dynamic simulation research of the built-in axle box of high-speed train.

According to the vibration and noise requirements of the electromechanical system, the paper analyzed the vibration causes of the pump unit and the complex pipeline in detail, and carried out targeted analysis and corresponding treatment measures for the source of vibration, and selected the proper vibration isolator and flexible connection mode. Finally through the test and verify, the vibration of the motor pump unit meets the requirements of the system vibration index.

The planetary reducer is a key component of the main drive system of the shield tunneling machine. During operation, the frictional heat on the tooth surface causes the gear temperature to be too high, resulting in thermal stress and deformation that directly affect the time-varying meshing stiffness of the gear teeth. Gear stiffness, as an important internal excitation of the gear system, is the basis for analyzing the dynamic characteristics of the system. In this paper, the finite element method is used to study the temperature field of the shield machine reducer planetary gear system, and on this basis, the time-varying meshing stiffness of the gear considering temperature effects is calculated. The results show that, considering temperature, the single tooth meshing stiffness of the gear pair increases significantly in the single tooth meshing zone, and the time-varying meshing stiffness increases overall. The research results of this article provide a theoretical basis for accurately predicting the dynamic characteristics of shield machine reducers

As a new type of green transportation, electric vehicle is widely used in a variety of logistics distribution scenarios. And some scholars have begun to use electric vehicles as mobile charging facilities to provide mobile charging services for electric vehicles that need to be charged. However, home charging and fixed charging are still the mainstream modes of electric vehicle charging, and the number of electric vehicles requiring mobile charging services is relatively small, which can not meet the conditions of special supporting mobile charging facilities. Therefore, this paper combines the traditional logistics distribution with the mobile charging service, introduces the electric vehicle which can provide both the goods distribution service and the mobile charging service, proposes the electric vehicle route optimization problem considering the electricity and goods distribution, establishes the integer programming model of the problem, and designs the genetic algorithm to solve it. Finally, the model and algorithm are tested and numerically analyzed based on a Solomon example to verify their effectiveness.

To study the vibration characteristics of loader gearbox, based on the theory of elasticity, the time-varying meshing stiffness of each level of gear pair is calculated using analytical method. Establish a finite element model for the dynamic contact of gear pairs at all levels, and simulate and analyze the dynamic meshing force of the gear pair during the meshing process. Establish a multi body dynamic finite element model of the gearbox gear transmission system, obtain the vibration modes and corresponding frequencies of the gearbox and the box through modal analysis, and compare them with the excitation frequency to determine that the system will not resonate; Taking the dynamic meshing force of each level of gear pair as the load condition, the modal superposition method is used to calculate the vibration response of the system. The peak value of the frequency domain response mainly occurs at the meshing frequency and its doubling frequency of the gear pair.

The main control methods for helicopter turboshaft engines are cascade feedforward control and model predictive control. The former is difficult to solve the delay of power turbine response caused by the large inertia of the rotor system, while the latter often requires a great amount of computation due to the iteration of the optimal algorithm. To improve the real-time rapidity of power turbine control for turboshaft engines, a control system framework based on thermo-gas-dynamic performance model is proposed in this paper. The calculation of this model is lightweight based on component characteristics, and a double closed-loop feedback control system of the two rotational speeds of gas generator (GG) and power turbine (PT) based on small-step fuel flow (Wf) is further designed. The simulation results show that the power turbine speed is stable, the engine power response is fast, and the control process can be fast and reliable when this control framework is utilized for the acceleration and deceleration processes of the engine.

The paper focuses on truck platooning control and its stability on highways, which has gained significant attention due to its potential to improve traffic efficiency and reduce energy consumption. A coupled longitudinal and lateral dynamics model for a single truck in a platoon is proposed to analyze truck’s kinematics and dynamics relationship under platooning. A control strategy based on distributed model predictive control (DMPC) is developed to compensate for communication delay. A bounded communication delay is synthesized to the proposed method, which employs a constant-spacing control policy to design a cost function for the control objective, by combining with state information to solve a nonlinear optimization problem for local optimal control. Based on one-way communication, the collaborative adaptive cruise control (CACC) platoon system is suitable for intelligent truck platooning on straight highways

Based on a hybrid vehicle, this paper studies the method of vehicle energy evaluation. Through testing and analyzing the energy flow and system component characteristics of the entire vehicle, a sensor layout plan for the energy flow testing of the entire vehicle was developed. At the same time, through vehicle energy flow testing, the distribution characteristics of vehicle energy flow are calculated using the basic theory of vehicle energy flow calculation and analysis. Finally, the energy flow relationship of the entire vehicle is calculated and analyzed.

When a high-speed train repeatedly passes through a tunnel, tunnel pressure waves induce pressure fluctuation inside the carriage. The traditional passive control strategy of closing the air ducts for a fixed period may fail to meet the requirements of pressure comfort and air quality. The similar properties of morphologically-similar tunnel pressure waves provide a new perspective for performing quasi-periodic repetitive tasks by iterative learning control (ILC) algorithm. In order to break the limitation of strict repeatability of tracking targets in traditional ILC algorithm, this paper proposes a novel ILC based on condition and performance matching algorithm. By matching the current working condition and expected performance with the condition and performance of the historical database, and processing the matched control input with a variable time scale, the optimal control input can be obtained. The control input and the historical database can be updated based on the error and performance after control. The simulation results show that, compared with the uncontrolled, traditional control and traditional open-loop ILC, the proposed algorithm can effectively suppress the internal pressure fluctuation under morphologically-similar tunnel pressure waves, and has higher control accuracy and faster convergence speed.

This article conducts simulation research on the control model of the intelligent warning system for blind spots of large vehicles. Firstly, select appropriate vehicle wheelbase and turning radius parameters, and use PC Crash simulation software to simulate and analyze the impact of wheel difference on turning driving; Then, through PreScan simulation experiments, the turning blind spots of vehicles with different turning angles and corresponding onboard radar detection angles are determined, and a turning angle inner wheel difference radar detection angle model equation is established for the design of intelligent warning schemes for turning blind spots of large vehicles. This study is of great significance for the design of intelligent warning systems for blind spots in large vehicle turns.

Due to the need for transformation and upgrading, it has been proposed to change the front suspension of a large mining vehicle from a candle type to a double-wishbone type. The manufacturer and user units are concerned about the impact of this change on tire wear and handling stability. To address this concern, a simulation study has been conducted. The first step was to establish the entire vehicle model of the mining dump truck using Solidworks and Adams/Car. Next, a DOE analysis was conducted on the hard point parameters of the front suspension. The TOPSIS method of grey correlation analysis was used to select the six hard point parameters with the highest comprehensive contribution as optimization variables. Finally, the NCGA algorithm in Isight was used for multi-objective optimization. This not only improved the optimization efficiency but also helped obtain the structural characteristics with excellent performance. The improved structure can enhance the handling stability and smoothness of the entire vehicle while also minimizing tire wear. Overall, this study demonstrates the benefits of using simulation techniques and multi-objective optimization methods for improving the performance of mining vehicles.

Crawler excavators often work on uneven road surface, and need to cross obstacles when driving, thus being subject to the impact load from obstacles, which leads to the fatigue damage of excavator structural parts. Therefore, it is very necessary to study the dynamics of excavator obstacles for the reliable design of excavator structural parts. Based on Recurdyn dynamics software, the dynamic characteristics of unilateral and bilateral excavator obstacle crossing are studied. The results show that in the vertical displacement of the whole machine, the bilateral barrier is 2.09 times of the unilateral obstacle; in the horizontal impact load, 3.18 times of the bilateral obstacle; in the vertical impact load, 1.08 times of the unilateral obstacle.

In order to improve the dynamic positioning control performance of the trailing suction dredger. In this paper, an improved particle swarm optimization PID control method is proposed for the dredging process of offshore operations. And the upper computer monitoring technology has been introduced to visually display the status of the suction dredger during offshore dredging. This paper designs the dynamic positioning controller based on the improved particle swarm optimization PID algorithm, and uses Labview to design the monitoring interface of the upper computer, which intuitively shows the reliability of Dynamic positioning.

This paper discusses the optimization and simulation of passenger flow organization in the Lanzhou West Hub, which is crucial for enhancing transportation capacity within and outside of Lanzhou. The author use AnyLogic simulation software to model the environment and transfer logic in the Lanzhou West Hub, and then simulate the two directions in which Metro stations and high-speed rail stations transfer to each other to identify bottleneck locations in the transfer process under normal and peak traffic conditions. After proposing corresponding optimization suggestions for passenger flow organization, the paper conduct another round of simulation analysis and conclude that the proposed optimization strategies effectively reduce congestion and queuing time. This paper provides practical guidance for optimizing passenger transfer flow in the Lanzhou West Hub, which plays an important role in the transportation system of Lanzhou.

Establishing an equivalent circuit model for leakage current circuits is an important approach to studying coupling leakage current, and the equivalent capacitance of coupling is a key parameter in the circuit model. This thesis analyzes the equivalent capacitance structure of coupling based on meshing state of the tooth pairs during operation. By analyzing the elastic deformation of coupling under stress, formulas for calculating the oil film area and thickness between the inner and outer teeth were derived, and the equivalent capacitance model of coupling was established. Taking a certain type of EMU coupling as the research object, the equivalent capacitance was calculated through the equivalent capacitance model of coupling and finite element simulation. The error rate between results of the model calculation and the results of finite element simulation calculation was 5.83%, which verified accuracy of model. The research results can provide reference for the study of the equivalent circuit model of the leakage current circuit of EMU.

Extreme environment such as high temperature seriously threatens the normal operation of special vehicles, and the key components of vehicles are sensitive to environmental changes. In order to study the thermal environment evolution of key parts of special vehicles under fuel tank Fire, Fire Dynamics Simulator (FDS) is adopted to build a vehicle model, and the fuel is set as -10 diesel. The flame characteristics, combustion propagation and temperature changes of the key parts of the vehicle in different stages and different fuel tank positions of the simplified vehicle model were calculated, and the application requirements of special vehicles in special scenarios were verified.

High track quality is the basis of ensuring the safe and comfortable operation of trains, and it is of great significance to accurately grasp the degradation law of track geometry to ensure track quality. Long Short-Term Memory (LSTM) network in machine learning has the function of remembering historical information, which can better predict the development trend of nonlinear time series, a prediction model of orbital geometric degradation based on LSTM is constructed by using historical data of track quality index (TQI). In order to verify the validity of the model, the test data of Lanzhou-Urumqi High-speed Railway Track Inspection Vehicle are selected. The results show that the prediction model of track geometric degradation based on LSTM established in this paper is effective and has high prediction accuracy.

In order to solve the problem that the traditional muffler in the field of low-frequency pulsation noise control of submarine hydraulic system is easily interfered by external factors and does not have adaptive ability. Scholars from all over the world have carried out research on the active control of pulsation noise of liquid pipelines. This paper first explains the principle of active control of hydraulic line pulsation and active noise. Sound control technology, from the aspects of software and hardware to sort out and review the noise reduction principle and research progress of the control system, analyze the advantages and disadvantages one by one. And the future research direction and application prospect are prospected.

This article investigates the stress distribution characteristics of piles and tunnel lining structures in a tunnel-landslide system under the working conditions of anti-slip pile treatment with three different pile spacing distances. The study compares and analyzes the regular changes in the displacement of the pile top, tunnel, bending moment of the pile body, and tunnel under landslide loads with different pile spacing distances. The numerical simulation results show that when the pile spacing distance increases from the initial 5cm to 10cm and 15cm, i.e., from 2.08d to 4.16d and 6.24d, respectively, the horizontal displacement of the pile top, tunnel, and the bending moment of the pile body and tunnel gradually increase under the same load. However, the increase in displacement and bending moment is much greater when the pile spacing distance increases from 4.16d to 6.24d than when it increases from 2.04d to 4.16d. The results indicate that, for practical engineering and economic considerations, if the landslide thrust is relatively small, the pile spacing distance can be increased to 6.24d, or even larger depending on the actual situation, with some limitations. However, if a large landslide thrust is encountered, the pile spacing distance should be reduced to 2.08d or even smaller. This is beneficial for protecting the tunnel lining structure under landslide loads. Nevertheless, regardless of whether the landslide thrust is large or small, a pile spacing distance of 4.16d is a relatively cost-effective choice for protecting the tunnel when implementing anti-slip pile treatment.

This paper addresses the limitations of conventional model predictive current control (MPCC) of permanent magnet synchronous motors (PMSM) in selecting only one optimal voltage vector per sampling cycle and its poor steady-state performance. A dual-vector model predictive control strategy is proposed to distribute the action time and synthesize a new voltage vector to act on the permanent magnet synchronous motor to improve performance. In this paper, we propose to reduce the computational effort of MPCC traversal search optimization by reducing the selection range of two voltage vectors while ensuring the accuracy of the obtained voltage vectors. Simulation experiments are conducted to compare and analyze the dynamic and steady-state aspects of both the single-vector MPCC and the proposed improved dual-vector MPCC. The results indicate that the improved dual-vector MPCC performs better in dynamic and steady-state performance.

The anti-slip performance of the road surface is closely related to the technical condition of the road surface. Long-term operation of the highway road surface will cause different damage situations, resulting in varying degrees of reduction in the anti-slip performance of the road surface, which has a serious impact on operational safety. In response to the impact of variable thickness paving on the protective capacity of guardrails in emergency lanes, numerical simulation analysis was used to calculate the process of a vehicle collision with guardrails. The deformation of guardrails and related indicators of vehicle inclination during vehicle collision was obtained. The results show that: (1) Under both overlay and non-overlay conditions, the driving trajectory of the vehicle after colliding with the guardrail is within the range of the guided exit frame. The vehicle has not broken through the guardrail, and the guardrail provides effective protection for the vehicle. The guidance and blocking functions of the guardrail meet the requirements. (2) When a vehicle collides with a guardrail structure under two conditions, the maximum lateral dynamic deformation value D and the maximum lateral dynamic extension value W of the guardrail structure themselves are relatively close, with a difference of no more than 5cm. The deformation of the guardrail is not significantly different. (3) For the vehicle camber index, under the conditions of overlay and no overlay, the camber value when the vehicle collides with the guardrail is relatively close, with a difference of about 0.9 cm between the two. The camber situation when the vehicle collides with the guardrail under the two conditions is relatively similar, and the difference in guardrail protection ability is not significant. (4) Based on the comprehensive analysis of the deformation index of the guardrail structure and the vehicle inclination index, when the height difference of the road surface is 4 cm within the 3 m range of the emergency lane, the deformation index of the guardrail and the vehicle inclination index are relatively close to those under the condition of no overlay. The variable thickness overlay does not have a significant adverse effect on the actual protective ability of the guardrail, and the safety performance of the guardrail structure meets the requirements.

Ecological driving can significantly cut down on fuel use and exhaust emissions, which benefits both the environment and the economy. The development of an individual ecological driving behavior evaluation model is therefore crucial for ecological driving research and promotion. In order to assess environmentally friendly driving practices, this research suggests a model based on the distribution of Vehicle Specific Power (VSP). Based on the continuous second-by-second operating data of 7000+ light vehicles over the course of 60 days, the baseline VSP distribution and individual drivers' VSP distribution at various speeds were obtained for this study. The ecological driving behavior was qualitatively divided into three categories: radical, ordinary, and ecological. The Fuel Consumption Index (FCI) is then created to assess the ecological level of ecological driving behaviors from level 0 to 10, followed by the proposal of an ecological driving evaluation model based on Fuel Consumption per unit time. The findings demonstrate that the model put out in this research can segment ecology in great depth and that individual drivers' driving patterns can remain consistent in a variety of traffic situations.

In response to the conflict and restrictions between targets during the multi-target optimization of the ship manufacturing process, it is difficult to reasonably arrange the scheduling plan, and propose a multi-target empire competition algorithm MOICA (Multi-Objective Imperialist Competition Algorithm). The algorithm takes the latest completion time, the total load of the machine and the maximum load of the machine as the optimization goal. Considering the heterogeneity of information between the colonies between the empires, different assimilation and revolutionary strategies for different levels of colonies are designed to adapt to it to adapt to it Search characteristics and improve their search efficiency and effect. By comparative experiments, the MOICA algorithm can effectively solve the problem of multi-target flexible operating workshop scheduling problems, while ensuring the convergence and diversity of populations

In practical engineering, the fault of rolling bearing is very common, so the research on fault diagnosis of rolling bearing is of great significance to the safe and stable operation of equipment. Because the vibration signals collected by different bearing faults are different and not easy to obtain, it is not easy to mark them. In order to solve this problem, a fault diagnosis classification and recognition method based on one-dimensional convolutional neural network and transfer learning is proposed. First of all, the vibration signal of the source domain is directly used as the input of the onedimensional convolutional neural network, and the model is trained; then transfer learning is introduced, some of the trained model parameters are frozen, and some target domain data are fine-tuned to reduce the training time; finally, the model is used to diagnose the fault of the target domain. The experimental results show that after using the source domain model transfer learning, the average accuracy of bearing fault classification is 95.82%, which has good adaptability.

With the continuous development of technology, the utilization of underground space is getting higher and higher, and the development of close stacked tunnels is becoming more and more complex and diversified. In this paper, we simulate a close stacked tunnel for an engineering example, and analyze the vibration response of typical measurement points respectively, and derive the vertical vibration acceleration response values of 0.37m/s² and 0.59m/s² for ordinary rail structures under single-line operation and double-line operation respectively, and the vibration acceleration under double-line operation is greater than that under single-line operation under different working conditions. The vibration acceleration under double-line operation is greater than that under single-line operation. At the same time, the ground vibration level of the common rail structure was evaluated without and with the total vibration level, and it was concluded that it did not meet the code requirements, and it was not recommended to use the common rail structure in the overlapping tunnel, and the response vibration reduction measures should be taken if the common rail structure is used.

Side frames of a typical single side bulk carrier is a critical structure to carry the pressure of both the outboard seawater and the cargo in the hold and to play the role of connecting the top side tank and the lower side tank. The effective connection between the upper and lower ends of the side frame and other structures is particularly important. The IACS (International Association of Classification Societies) CSR (Common Structure Rule) [1] has emphasized requirements for the structure type here. In this paper, we study the stresses at the end connection of the side frames through the derivation of mechanical equations and finite element modeling calculations, analyze the requirements of the IACS CSR specification. It is proved that when using the IACS CSR to calculate the area of support bracket and end bracket size, we can also use required minimum parameters rather than the actual parameters. This paper also gives the prerequisites.