This paper develops a smart hybrid rotary damper using a re-centering smart shape memory alloy (SMA) material as well as conventional energy-dissipating metallic plates that are easy to be replaced. The ends of the SMA and steel plates are inserted in the hinge. When the damper rotates, all the plates bend, providing energy dissipating and recentering characteristics. Such smart hybrid rotary dampers can be installed in structures to mitigate structural responses and to re-center automatically. The damaged energy-dissipating plates can be easily replaced promptly after an external excitation, reducing repair time and costs. An OpenSEES model of a smart hybrid rotary was established and calibrated to reproduce the realistic behavior measured from a full-scale experimental test. Furthermore, the seismic performance of a 3-story moment resisting model building with smart hybrid rotary dampers designed for downtown Los Angeles was also evaluated in the OpenSEES structural analysis software. Such a smart moment resisting frame exhibits perfect residual roof displacement, 0.006”, extremely smaller than 18.04” for the conventional moment resisting frame subjected to a 2500 year return period ground motion for the downtown LA area (an amplified factor of 1.15 on Kobe earthquake). The smart hybrid rotary dampers are also applied into an eccentric braced steel frame, which combines a moment frame system and a bracing system. The results illustrate that adding smart hybrid rotaries in this braced system not only completely restores the building after an external excitation, but also significantly reduces peak interstory drifts.
Current procedures in post-earthquake safety and structural assessment are performed by a skilled triage team of
structural engineers/certified inspectors. These procedures, in particular the physical measurement of the damage
properties, are time-consuming and qualitative in nature. Spalling has been accepted as an important indicator of
significant damage to structural elements during an earthquake, and thus provides a sound springboard for a model in
machine vision automated assessment procedures as is proposed in this research. Thus, a novel method that
automatically detects regions of spalling on reinforced concrete columns and measures their properties in image data is
the specific focus of this work. According to this method, the region of spalling is first isolated by way of a local
entropy-based thresholding algorithm. Following this, the properties of the spalled region are depicted by way of
classification of the extent of spalling on the column. The region of spalling is sorted into one of three categories by way
of a novel global entropy-based adaptive thresholding algorithm in conjunction with well-established image processing
methods in template matching and morphological operations. These three categories are specified as the following: (1)
No spalling; (2) Spalling of cover concrete; and (3) Spalling of the core concrete (exposing reinforcement). In addition,
the extent of the spalling along the length of the column is quantified. The method was tested on a database of damaged
RC column images collected after the 2010 Haiti Earthquake, and comparison of the results with manual measurements
indicate the validity of the method.
A macroscopic phenomenological framework is used for developing a closed-form solution for analyzing the pure
bending of shape memory alloy (SMA) beams. In order to study the effect of tension-compression asymmetry
on the bending response, two different transformation functions are considered; a J2-based solution with symmetric
tension-compression response, and a J2 - I1-based solution capable of modeling the tension-compression
asymmetry. The constitutive equations are reduced to an appropriate form for studying the pseudoelastic bending
response of SMAs, and closed-form expressions are obtained for the stress and martensitic volume fraction
distributions in the cross section. These expressions are used for calculating the bending moment-curvature
analytically. Both circular and rectangular cross sections are considered and several case studies are presented
for analyzing the accuracy of the presented method and also the effect of considering the tension-compression
asymmetry on the bending response of SMAs.
Shape memory alloys (SMAs) are a class of metallic alloys that exhibit unique characteristics such as shape memory effect and superelasticity effect. SMAs are found in two main phases: the high temperature phase, which is known as austenite (superelastic), and the low temperature phase, which is known as martensite. Although there are few civil engineering applications using SMAs, there have been considerably large numbers of research studies focusing on exploiting SMAs in seismic resistant design and retrofit of buildings and bridges. Most of these studies focus on utilizing the superelasticity phenomenon exhibited by SMAs at high temperatures. The effect of ambient temperature variation on the efficacy of superelastic SMA devices that are used in seismic applications is a major concern. This paper presents an analytical investigation on the effect of ambient temperature variation on the performance of superelastic SMA bridge restrainers during earthquakes. A thermomechanical constitutive model is developed to describe the constitutive behavior of the SMA restrainers at various temperatures. The SMA model is implemented in a 2-DOF bridge model and tested using 20 historical ground motion records. The ambient temperature is varied from a temperature below Af to a relatively high temperature. The results of the study showed that SMAs are more effective when used in its austenitic phase and thus when the temperature decreases below Af SMA devices lose a major part of their efficiency. On the other hand, the study also showed that at high temperatures the ductility demand of the bridge frames increases.
The objective of this study is to evaluate the effect that mechanical training has on the properties of NiTi based shape memory alloys. The unique mechanical behavior of shape memory alloys, which allows the material to undergo large deformations while returning to their original undeformed shape through either the shape memory effect or superelastic effect, has shown potential for use in seismic design and retrofit applications for civil engineering structures. However, cyclic loading has been shown to degrade the energy dissipation capacity and decrease the recentering capability of the material due to fatigue effects. It has been recommended that mechanical training of superelastic shape memory alloys prior to use in applications can limit these fatigue effects. A factorial experimental design is employed to explore the optimal number of mechanical training cycles, strain level of training, and the effect of the loading rate after training in order to minimize the degradation in the loading plateau stress, residual strain, and equivalent viscous damping properties. The results presented can serve as a guide to optimizing the properties of NiTi shape memory alloys for seismic applications. The ability to obtain stable properties of shape memory alloys under a specified training schedule further supports the eventual implementation of the material into actual building and bridge systems as seismic design and retrofit devices.
The cyclic behavior of shape memory alloys (SMAs) in their austenitic form is studied to determine the most appropriate method of modeling in terms of both accuracy and ease of implementation. Four different models for SMA behavior are evaluated: (a) a simple nonlinear elastic model, (b) a trigger-line model, (c) a one-dimensional thermomechanical model, and (d) a one-dimensional thermomechanical model which accounts for the behavior of SMAs under cyclic loading. Using a two degree-of-freedom bridge model with SMA restrainers and a single degree-of-freedom building model with SMA cross-braces, the effect of using the different models on the seismic response of the bridge and building is evaluated. Using a suite of nine earthquake ground motions, the displacement response histories with the four different models are compared. The results illustrate that although the models show quite different behaviors for the SMAs, the resulting responses of the bridge and building are insensitive to the type of model used. For most of the ground motion records used, the difference in the maximum displacement for the four models was less than 15%. This study lends support to the use of more simplified models when evaluating the effectiveness of the SMAs for seismic response modification.
This study evaluates the properties of superelastic shape memory alloys under cyclical loading to asses their potential for applications in seismic resistant design and retrofit of civil engineering structures. Shape memory alloy bars are tested to evaluate the effect of bar size (diameter) and loading history on the strength, equivalent viscous damping, and recentering properties of the shape memory alloys in superelastic form. The bars are tested under both quasi-static and dynamic loading. The results show nearly ideal superelastic properties can be obtained in large diameter shape memory alloy bars. However, comparing these results to previous studies, the more common wire form of the shape memory alloys show higher strength and damping properties compared with the large bars. The recentering capabilities (based on residual strains) are not affected by the section size of the bar. Overall, the damping potential of superelastic shape memory alloys is low for large diameter bars, typically less than 7% equivalent viscous damping. Degradation of the superelastic properties of the shape memory alloys occurs for cyclical strain greater than 6%, leading to increased residual strains and reduction in energy dissipated. Finally, strain rate effects are evaluated by subjecting the shape memory alloys to loading rates representative of typical seismic loadings. The results show that increased loading rates lead to slight decreases in the equivalent damping, but have negligible effect on the recentering of the shape memory alloys.
The application of Nitinol shape memory alloys (SMA) in steel connections is evaluated using connections incorporating SMA tendons. Shape memory alloys are a class of alloys that exhibit thermo-mechanical characteristics that are ideally suited for seismic applications. They have the ability to dissipate significant energy with little permanent deformation, and possess highly reliable energy dissipation based on a repeatable solid state phase transformation. To assess the validity of using SMA in real structures, two full-scale connections are tested. The tests are conducted on exterior joint specimens and tested according to the SAC testing protocol. The beams are W24 x 94 and the columns W14 x 159, all of A572 Grade 50 steel. Companion regular steel connections are tested for comparison. The connections are of a T-stub type, with four 11/2 inch diameter SMA rods providing the tensile resistance to the column. The specimens are re-tested several times to determine the ability of the SMA rods to regain their original configuration. The tests will lead to the development of an innovative beam-column connection that can be used for both retrofit and new construction that exhibits performance which is superior to existing designs.
Recent earthquakes in the US and Japan have highlighted the vulnerability of bridges to collapse due to excessive movement at the hinges as a result of bearing and restrainer failure. Conventional hinge restrainers used in the US and Japan do not provide adequate protection from unseating, which can lead to collapse of bridges. This paper investigates the efficacy of using 'smart restrainers' to reduce the seismic vulnerability of bridges. The use of shape memory alloy devices as replacements for conventional restrainers are investigated as a method of improving the seismic response of bridges. Analytical studies show that these deices, used as passive dampers, are effective in both limiting the relative displacement between frames, and reducing the negative effects of pounding of bridge decks. In addition, by concentrating damage and energy dissipation in controlled locations, these devices can be used to reduce the demand on individual frames in multiple-frame bridges. Comparisons with conventional restrainers show that the 'smart restrainers' are more effective for a wide range of ground motions and bridge types than current restrainers.
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