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    Stress-Softening Behavior of High-Damping Rubber Bearings at Low Temperatures 

    Source: Journal of Structural Engineering:;2024:;Volume ( 150 ):;issue: 006:;page 04024050-1
    Author(s): Yuqing Tan; Yanhui Liu; Ji Dang; Akira Igarashi; Takehiko Himeno; Yuki Hamada
    Publisher: ASCE
    Abstract: High-damping rubber (HDR) bearings exhibit obvious initial stress hardening at lower ambient temperatures and stress softening under cyclic loading. The phenomenon of stress softening is usually referred to as the Mullins ...
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    Multiple-Spring Model for Square-Section Steel Bridge Columns under Bidirectional Seismic Load 

    Source: Journal of Structural Engineering:;2017:;Volume ( 143 ):;issue: 005
    Author(s): Ji Dang; Huihui Yuan; Akira Igarashi; Tetsuhiko Aoki
    Publisher: American Society of Civil Engineers
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    Curve-Approximated Hysteresis Model for Steel Bridge Columns 

    Source: Journal of Structural Engineering:;2014:;Volume ( 140 ):;issue: 009
    Author(s): Ji Dang; Huihui Yuan; Akira Igarashi; Tetsuhiko Aoki
    Publisher: American Society of Civil Engineers
    Abstract: A curve-approximated hysteresis model of the lateral load-displacement behavior of steel bridge columns is proposed for nonlinear seismic response assessment of single-column-type bridges using single-degree-of-freedom ...
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    Smartphone-Based Bridge Seismic Monitoring System and Long-Term Field Application Tests 

    Source: Journal of Structural Engineering:;2020:;Volume ( 146 ):;issue: 002
    Author(s): Ashish Shrestha; Ji Dang; Xin Wang; Shogo Matsunaga
    Publisher: ASCE
    Abstract: In this study, a bridge seismic monitoring system was developed based on smartphones connected together in the same project as a sensor network using a cloud server for easy upload and access to data. Thus, a decentralized ...
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    Geometric Attention Regularization Enhancing Convolutional Neural Networks for Bridge Rubber Bearing Damage Assessment 

    Source: Journal of Performance of Constructed Facilities:;2021:;Volume ( 035 ):;issue: 005:;page 04021061-1
    Author(s): Mida Cui; Gang Wu; ZhiQiang Chen; Ji Dang; Minghua Zhou; Dongming Feng
    Publisher: ASCE
    Abstract: Rubber bearing condition evaluation is crucial for bridge inspection, and the current practice heavily relies on human-vision inspection. Convolutional neural networks (CNNs) have shown great potential for structured damage ...
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