This paper proposes a damage assessment framework based on the visual features of a
damaged reinforced concrete shear wall, such as crack pattern distribution, crushing areal …

Abstract Machine learning (ML) has been recognized by researchers in the architecture,
engineering, and construction (AEC) industry but undermined in practice by (i) complex …

The purpose of this paper is to estimate the stiffness and strength of damaged rectangular
reinforced concrete shear walls after an earthquake using surface crack patterns. Assessing …

During the last two decades, thin concrete walls have been frequently used to brace mid-to
high-rise buildings in some Latin American countries. This structural system differs …

This paper introduces a probabilistic framework to quantify the spatial distribution of cracking
and crushing in rectangular reinforced concrete shear walls at different drift ratios. In this …

In this paper, a probabilistic methodology based on image analysis for identifying the
postearthquake performance level of reinforced concrete shear walls is proposed. A …

The purpose of this paper is to quantify the extent of damage of rectangular reinforced
concrete shear walls after an earthquake using surface crack patterns. One of the most …

This paper proposes a new data‐driven method to generate three‐dimensional fragility
surfaces for post‐earthquake damage assessment of reinforced concrete (RC) shear walls …

In this paper, an image-based methodology using machine learning algorithms is developed
for earthquake-induced damage state prediction in rectangular reinforced concrete shear …

Reinforced concrete (RC) shear walls are primarily designed to resist lateral actions in
buildings, in addition to carrying the vertical loads from above. Recent changes in the …