After a seismic event, damage quantification is necessary for safety evaluation, collapse
proximity judgment, and measurement of the residual seismic capacity of the joints. Machine …

In this paper, a probabilistic post-earthquake loss estimation methodology based on image
processing is proposed for non-seismically designed reinforced concrete moment frames …

Concrete surface cracks are one of the primary indicators of structural deterioration; thus,
crack analysis is crucial to maintain the intact serviceability of the structural components …

Robust post-earthquake loss measurement is essential in community level for policy makers
and an area of interest for insurance companies at the building level. The seismic loss …

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

In this paper, a probabilistic methodology based on image analysis is proposed for
earthquake‐induced loss estimation in rectangular reinforced concrete shear walls …

Manual visual inspection is the conventional method for post-earthquake damage
assessment, which is unsafe, subjective, and prone to human error. This paper presents an …

This study presents a nonmodel-based machine learning framework for estimating
engineering demand parameters (EDPs) of eccentrically braced frames with soil-structure …

The blurred concrete crack images are typically the result of unexpected camera motion in
engineering. Consequently, deblurring and segmentation of them represents a challenging …

This paper presents a model for predicting water sorption isotherms of cement-based
materials. In this model, hysteresis contributions of interlayer pores and gel/capillary pores …