Abstract: Prompt identification of structural damage is essential for effective postdisaster responses. To this end, this paper proposes a deep neural network (DNN)–based framework to identify seismic damage based on structural ...

Abstract: In the reliability assessment of a bridge in operation with regards to its ultimate limit state, it should be noted that the strengths of members and effects of traffic load vary continuously over its lifespan due to the ...

Abstract: It is of great significance to incorporate various uncertainties into the design optimization of structures and other engineering systems. Many reliability-based design optimization (RBDO) methods have been developed, but ...

Abstract: Accurate prediction of the dynamic response of a structure is crucial for its system identification, reliability analysis, and health monitoring. However, uncertainties in physics-based models and parameters may cause a ...

Abstract: Current design codes for long-span bridges rely on the conservative live load models developed based on the assumed severe traffic congestion scenarios. To properly consider the site-specific traffic environment in designs ...

Abstract: Uncertain changes in spatial distribution of structural parameters, caused by deterioration or damage, may weaken the structure and result in unexpected losses of properties or casualties. In recent decades, to identify ...

Abstract: Many structural systems are subjected to the risk of fatigue-induced failures caused by repeated loading during their service. For effective management of such risk, it is essential to estimate the reliability of a structure ...

Abstract: Bounds on system probability in terms of marginal or joint component probabilities are of interest when exact solutions cannot be obtained. Currently, bounding formulas employing unicomponent probabilities are available ...