A new method, MIDA, uses physics-based ground motion simulations tied to earthquake magnitude to better assess seismic performance of near-fault structures. This approach reduces subjectivity and nonphysical distortion, providing a more stable and realistic prediction of structural response.
Research finds that building gypsum powder reduces soil strength when exposed to water, but augments it at low concentrations of sodium sulfate. The study also reveals the impact of dry-wet cycles on soil pores, structure, and resistance.
Researchers use machine learning to characterize recovery processes, predict outcomes, and optimize strategies for restoring critical infrastructure systems. The review highlights the potential of reinforcement learning to identify effective repair sequences.