Results 241 to 250 of about 91,370 (354)
Differences in Individual Perceptions of Volcanic and Seismic Hazards
Justin Elwonger
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The impact of 1D seismostratigraphical amplification effects on probabilistic seismic hazard maps at regional scale: the case of Tuscany (Central Italy) [PDF]
Dario Albarello +2 more
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Tectonic styles of expected earthquakes in Italy as an input for seismic hazard modeling
Silvia Pondrelli +5 more
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Carbonate sedimentology: An evolved discipline
Abstract Although admired and examined since antiquity, carbonate sediment and rock research really began with Charles Darwin who, during a discovery phase, studied, documented and interpreted their nature in the mid‐19th century. The modern discipline, however, really began after World War II and evolved in two distinct phases.
Noel P. James, Peir K. Pufahl
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Cluster‐based chemostratigraphy using XRF‐CS enables high‐resolution correlation of event deposits across contrasting depositional settings in the Japan Trench. This approach reveals previously unrecognised events and compositional heterogeneity, offering new insights into sediment provenance and earthquake‐triggered deposition, with implications for ...
Jyh‐Jaan Steven Huang +4 more
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Unified Hysteresis Modeling via Physics‐Based Deep Learning and Data Augmentation
ABSTRACT Deep learning‐based models have recently emerged as alternatives to traditional form‐constrained hysteresis models, including Bouc‐Wen class models, offering significant potential for unified hysteresis modeling to capture complex nonlinearities and diverse response patterns exhibited under stochastic excitations such as ground motions.
Jaehwan Jeon, Oh‐Sung Kwon, Junho Song
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ABSTRACT This study develops a high‐resolution regional seismic loss assessment framework for reinforced concrete (RC) bridges, focusing on direct losses due to bridge repair and replacement. Indirect losses tied to traffic downtime, business disruption, delayed recovery, etc., can also be attributed to bridge damage but are considered outside the ...
Shanshan Chen +4 more
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ABSTRACT Earthquakes pose a major threat to urban areas, causing fatalities, injuries, and significant economic losses. This study proposes a Gaussian process parametrized by deep neural networks (DNN–GP) as an efficient surrogate for assessing seismic losses of building structures at a regional scale.
Byeongseong Choi +2 more
wiley +1 more source

