Machine learning for enhanced regional seismic risk assessments
The ability to conduct accurate regional seismic risk assessments is key to informing a risk-
reduction policy and fostering community resilience. This paper presents a machine learning …
reduction policy and fostering community resilience. This paper presents a machine learning …
Incorporation of machine learning into multiple stripe seismic fragility analysis of reinforced concrete wall structures
This study proposes a novel procedure that incorporates machine learning (ML) into the
multiple stripe analysis (MSA) approach to efficiently produce seismic fragility curves for …
multiple stripe analysis (MSA) approach to efficiently produce seismic fragility curves for …
Toward multivariate fragility functions for seismic damage and loss estimation of high‐rise buildings
Data‐driven models for seismic damage and loss assessment of buildings have become
more common in recent years due to the availability of large repositories of recorded and …
more common in recent years due to the availability of large repositories of recorded and …
Community perspectives on simulation and data needs for the study of natural hazard impacts and recovery
With the aim of fostering the development of robust tools to simulate the impact of natural
hazards on structures, lifelines, and communities, the Natural Hazards Engineering …
hazards on structures, lifelines, and communities, the Natural Hazards Engineering …
Estimating economic losses of midrise reinforced concrete shear wall buildings in sedimentary basins by combining empirical and simulated seismic hazard …
Studies of recorded ground motions and simulations have shown that deep sedimentary
basins can greatly increase the intensity of earthquake ground motions within a period …
basins can greatly increase the intensity of earthquake ground motions within a period …
[HTML][HTML] Seismic collapse performance of high-rise RC dual system buildings in subduction zones
The satisfactory 'collapse prevention'performance level of reinforced concrete (RC) buildings
has been widely recognized during recent earthquakes in Chile. However, there is limited …
has been widely recognized during recent earthquakes in Chile. However, there is limited …
Development of data-driven models to predict seismic drift response of RC wall structures: An application of deep neural networks
This research aimed to develop data-driven models using deep neural networks (DNNs) that
can rapidly predict the seismic drift responses of reinforced concrete (RC) wall structures in …
can rapidly predict the seismic drift responses of reinforced concrete (RC) wall structures in …
Design strategies to achieve target collapse risks for reinforced concrete wall buildings in sedimentary basins
Studies of recorded ground motions and simulations have shown that deep sedimentary
basins can greatly increase the damage expected during earthquakes. Unlike past …
basins can greatly increase the damage expected during earthquakes. Unlike past …
Quantifying the effects of long‐duration earthquake ground motions on the financial losses of steel moment resisting frame buildings of varying design risk category
This paper investigates the effect of ground motion duration on risks to life safety and costs
associated with low‐to‐medium‐rise reference steel moment resisting frame buildings …
associated with low‐to‐medium‐rise reference steel moment resisting frame buildings …
Improved computational methods for probabilistic liquefaction hazard analysis
AJ Makdisi, SL Kramer - Soil Dynamics and Earthquake Engineering, 2024 - Elsevier
Current procedures for analysis of and design against liquefaction hazards focus primarily
on the use of probabilistic ground motions at a single ground-shaking hazard level, with the …
on the use of probabilistic ground motions at a single ground-shaking hazard level, with the …