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We have designed a video-comprehension model to analyze the moving trajectory and potential failure modes of nonstructural components during earthquakes, directly from video footage. We are hoping to leverage such a model to minimize the post-earthquake on-site inspections on nonstructural damages

A bidirectional long short-term memory network model with an attention mechanism is developed to predict floor response spectrum.

This paper presents a computationally efficient collapse fragility assessment approach that leverages the collaborative filtering (CF) …

As the smart city concept becomes increasingly popular and important in both industries and academia, a broad range of data collected …

When machine learning (ML) is used to solve practical problems in structural engineering (SE), the associated data may not reflect the …

Recently, a number of machine-learning models have been proposed for the prediction of 28-day compressive strength of concrete using …

The fire resistance behavior of T-stub joint components at elevated temperatures was experimentally and numerically investigated..

The existing and newly developed models for estimating building seismic drift demands are comparatively assessed in this study.

An end-to-end computational platform is presented, which automates seismic design, nonlinear structural model construction, and response simulation (static and dynamic) of steel moment resisting frames.

This article introduces the development of a comprehensive database, which includes 621 special steel moment-resisting frames designed in accordance with modern codes and standards and their corresponding nonlinear structural models and seismic responses (i.e. peak story drifts, peak floor accelerations, and residual story drifts).