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RL-Controller: a reinforcement learning framework for active structural control
To maintain structural integrity and functionality during the designed life cycle of a structure, engineers are expected to accommodate for natural hazards as well as operational load levels.
Transfer Learning for Input Estimation of Vehicle Systems
This study proposes a learning-based method with domain adaptability for input estimation of vehicle suspension systems.
Crowdsourcing Bridge Vital Signs with Smartphone Vehicle Trips
The primary study collects smartphone data from controlled field experiments and "uncontrolled" UBER rides on a long-span suspension bridge in the USA and develops an analytical method to accurately recover modal properties.
Computers and Society Applied Physics
Bridge Structural Health Monitoring using Asynchronous Mobile Sensing Data
In this study, the continuous wavelet transform is applied to each trip, and the results are combined to estimate the structural modal response of the bridge.
DynNet: Physics-based neural architecture design for linear and nonlinear structural response modeling and prediction
Data-driven models for predicting dynamic responses of linear and nonlinear systems are of great importance due to their wide application from probabilistic analysis to inverse problems such as system identification and damage diagnosis.
Finite Difference Neural Networks: Fast Prediction of Partial Differential Equations
Discovering the underlying behavior of complex systems is an important topic in many science and engineering disciplines.
