Mr. You Zhou Profile

You Zhou

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Proceedings Article | 14 February 2024 Open Access

Study on prediction of skid resistance of asphalt pavement based on genetic neural network

Quanlei Wang, Zhoucong Xu, Haonan Zhou, Jie Wu, You Zhou, Tianlong Chen

Proceedings Volume 13018, 130182V (2024) https://doi.org/10.1117/12.3024354

KEYWORDS: Neural networks, Genetic algorithms, Asphalt pavements, Statistical modeling, Data modeling, Evolutionary algorithms, Mathematical optimization

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The prediction of skid resistance of asphalt pavement plays a pivotal role in formulating maintenance plans and determining maintenance schemes. At present, the typical intelligent algorithms such as the neural network and the genetic algorithm have seen extensive applications in the evaluation and prediction of pavement performance. The combination forecasting model can leverage the complementary advantages of the two, thereby enhancing the reliability of prediction. As a case study, this paper focuses on the prediction of pavement skid resistance for an expressway in Chongqing. The research establishes a pavement skid resistance forecasting model using a genetic neural network and compares it with the single neural network, genetic algorithm, and regression models. Through this comparative analysis, the study validates the applicability and reliability of the genetic neural network approach for predicting asphalt pavement skid resistance. The results demonstrate that the regression model exhibits a limited fitting degree for highly nonlinear problems, leading to noticeably lower prediction accuracy than the genetic algorithm or neural network algorithm. In contrast, the combination forecasting model significantly enhances prediction accuracy in comparison to a single neural network model or genetic algorithm. Notwithstanding, it is worth noting that the operational efficiency of the combination forecasting model is inferior to that of a single neural network model. Consequently, the genetic neural network combination forecasting model proves more suitable for pavement skid resistance prediction, and nevertheless, there is room for further improvement in the operational efficiency of the model.

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Proceedings Article | 22 December 2022 Paper

Research on the pavement performance of high-ash composite modified rock asphalt mixture

Quanlei Wang, Zhoucong Xu, Jie Wu, Fei Chen, You Zhou, Haifeng Zhang

Proceedings Volume 12460, 124601Y (2022) https://doi.org/10.1117/12.2658690

KEYWORDS: Resistance, Composites, Minerals, Safety, Roads, Particles, Abrasives, Surface finishing, Shape memory alloys, Protactinium

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With the ever-increasing highway transport volume and the transportation development towards the heavy-duty direction, pavement rutting, which has become one of the main highway pavement diseases, is increasingly serious and generates a strong impact the traffic safety. The main method currently used to handle pavement rutting is pavement overlay by means of pavement milling and repaving. When this method is used, however, the road needs to be closed to traffic, accompanied by complex construction technologies and a high engineering cost. How to enhance the rutting resistance of asphalt concrete and reduce the later-stage curing cost is a great difficulty faced by asphalt pavement engineering technicians at present. In this study, a high-ash composite modified rock asphalt mixture was prepared and evaluated, followed by the rutting test, immersion Marshall test, freeze-thaw splitting test, and low-temperature bending test. The results showed that the composite modification of common asphalt using natural Buton Rock Asphalt (BRA) could effectively improve the high-temperature performance, low-temperature performance, and resistance to water damage of pavements, especially showing evident advantages in rutting resistance.

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