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Full-Text Articles in Engineering
Energy Dissipation Using Negative Stiffness Shells, Mohamed Elgawady, Yasser Darwish
Energy Dissipation Using Negative Stiffness Shells, Mohamed Elgawady, Yasser Darwish
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
A negative stiffness shell has a convex first position, but can transition or snap to a concave second position under a force applied to the exterior surface of the shell in the convex first position. During the transition, the shell exhibits negative stiffness that permits a large amount of energy to be absorbed. The negative stiffness shell can withstand a high initial force threshold prior to transitioning. In the second, concave position the shell can still resist force. Moreover, it is possible for the shell to revert back to the first, convex position with minimal plastic deformation for subsequent use. …
Fiber Optic-Based Thermal Integrity Profiling Of Drilled Shaft: Inverse Modeling For Spiral Fiber Deployment Strategy, Wen Deng, Ruoyu Zhong, Haiying Ma
Fiber Optic-Based Thermal Integrity Profiling Of Drilled Shaft: Inverse Modeling For Spiral Fiber Deployment Strategy, Wen Deng, Ruoyu Zhong, Haiying Ma
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The current state of practice to interpret the thermal integrity profiling (TIP) data of drilled shaft is the so-called effective radius method. It uses the concrete pouring log and average temperature to construct a relationship between temperature distribution and effective radius that can be used to reconstruct a drilled shaft model. While this effective radius method is computationally inexpensive and has good operationality, it is not good at predicting the dimensions and shape of shaft defects. Upgrading the sensor used in conventional TIP from thermocouples/thermal wires to fiber optic sensors, the spatial resolution of the measured temperature will be enhanced. …
Enhancing Mixed Traffic Flow Safety Via Connected And Autonomous Vehicle Trajectory Planning With A Reinforcement Learning Approach, Yanqiu Cheng, Chenxi Chen, Xianbiao Hu, Kuanmin Chen, Qing Tang, Yang Song
Enhancing Mixed Traffic Flow Safety Via Connected And Autonomous Vehicle Trajectory Planning With A Reinforcement Learning Approach, Yanqiu Cheng, Chenxi Chen, Xianbiao Hu, Kuanmin Chen, Qing Tang, Yang Song
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The longitudinal trajectory planning of connected and autonomous vehicle (CAV) has been widely studied in the literature to reduce travel time or fuel consumptions. The safety impact of CAV trajectory planning to the mixed traffic flow with both CAV and human-driven vehicle (HDV), however, is not well understood yet. This study presents a reinforcement learning modeling approach, named Monte Carlo tree search-based autonomous vehicle safety algorithm, or MCTS-AVS, to optimize the safety of mixed traffic flow, on a one-lane roadway with signalized intersection control. Crash potential index (CPI) is defined to quantitively measure the safety performance of the mixed traffic …