Results 341 to 350 of about 4,511,405 (380)
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Machine learning in ground motion prediction
Computational Geosciences, 2021F. Khosravikia, P. Clayton
semanticscholar +1 more source
Evaluation of ground motion selection and modification procedures using synthetic ground motions
Earthquake Engineering & Structural Dynamics, 2015SummaryThis study presents a novel approach for evaluating ground motion selection and modification (GMSM) procedures in the context of probabilistic seismic demand analysis. In essence, synthetic ground motions are employed to derive the benchmark seismic demand hazard curve (SDHC), for any structure and response quantity of interest, and to establish
N. Simon Kwong +2 more
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A Nonergodic Ground‐Motion Model for California with Spatially Varying Coefficients
, 2016Traditional probabilistic seismic‐hazard analysis as well as the estimation of ground‐motion models (GMMs) is based on the ergodic assumption, which means that the distribution of ground motions over time at a given site is the same as their spatial ...
Niels Landwehr +3 more
semanticscholar +1 more source
2016
To determine the location of an earthquake occurrence, two geometric notations, namely hypocenter and epicenter, will be introduced first. Because the majority of earthquakes are caused by the rupture of the rock along a fault or multiple faults, and thousands of square kilometers of fault plane surface may be involved in this rupture, while it is ...
openaire +2 more sources
To determine the location of an earthquake occurrence, two geometric notations, namely hypocenter and epicenter, will be introduced first. Because the majority of earthquakes are caused by the rupture of the rock along a fault or multiple faults, and thousands of square kilometers of fault plane surface may be involved in this rupture, while it is ...
openaire +2 more sources
, 2015
The evaluation of seismic hazard from induced seismicity requires the development of ground‐motion prediction equations (GMPEs) that are tuned to the key magnitude–distance range for such applications. I use events of M 3–6 at hypocentral distances less
G. Atkinson
semanticscholar +1 more source
The evaluation of seismic hazard from induced seismicity requires the development of ground‐motion prediction equations (GMPEs) that are tuned to the key magnitude–distance range for such applications. I use events of M 3–6 at hypocentral distances less
G. Atkinson
semanticscholar +1 more source
Amplification of Earthquake Ground Motions by Surface Ground
2019This chapter introduces the amplification of seismic ground motion by surface ground. A calculation method for the amplification magnification of the acceleration due to surface grounds \( G_{s} \) is presented and a concrete calculation example is shown.
Akiko Kishida +3 more
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, 2015
We develop a generic ground‐motion prediction equation (GMPE) that can be adjusted for use in any region by modifying a few key model parameters. The basis of the GMPE is an equivalent point‐source simulation model whose parameters have been calibrated ...
E. Yenier, G. Atkinson
semanticscholar +1 more source
We develop a generic ground‐motion prediction equation (GMPE) that can be adjusted for use in any region by modifying a few key model parameters. The basis of the GMPE is an equivalent point‐source simulation model whose parameters have been calibrated ...
E. Yenier, G. Atkinson
semanticscholar +1 more source
, 2015
We present a ground‐motion prediction equation (GMPE) for Turkey and Iran to investigate the possible regional effects on ground‐motion amplitudes in shallow active crustal earthquakes.
Ö. Kale +3 more
semanticscholar +1 more source
We present a ground‐motion prediction equation (GMPE) for Turkey and Iran to investigate the possible regional effects on ground‐motion amplitudes in shallow active crustal earthquakes.
Ö. Kale +3 more
semanticscholar +1 more source
, 2021