Benchmark tests for strong ground motion prediction methods: Case for stochastic green's function method (part 1)

Kenichi Kato; Yoshiaki Hisada; Hidenori Kawabe; Susumu Ohno; Atsushi Nozu; Arihide Nobata; Atsushi Morikawa; Yu Yamamoto

doi:10.3130/aijt.17.49

Benchmark tests for strong ground motion prediction methods: Case for stochastic green's function method (part 1)

Kenichi Kato, Yoshiaki Hisada, Hidenori Kawabe, Susumu Ohno, Atsushi Nozu, Arihide Nobata, Atsushi Morikawa, Yu Yamamoto

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

We performed a benchmark test for the strong motion simulation methods using stochastic Green's function method. All the results calculated by six teams from different institutions generally show good agreement to each other. Since random numbers are used in generating time histories and so on, synthesized amplitude shows variation in particular frequencies. When applying the stochastic Green's function method, this variation should be in mind.

Original language	English
Pages (from-to)	49-54
Number of pages	6
Journal	AIJ Journal of Technology and Design
Volume	17
Issue number	35
DOIs	https://doi.org/10.3130/aijt.17.49
Publication status	Published - 2011

Keywords

Benchmark tests
Fault model
Point source
Random numbers
Stochastic Green's function method
Strong motion prediction methods

ASJC Scopus subject areas

Architecture
Building and Construction

Access to Document

10.3130/aijt.17.49

Cite this

@article{01f72750a4ee4243ad0c821ea004638a,

title = "Benchmark tests for strong ground motion prediction methods: Case for stochastic green's function method (part 1)",

abstract = "We performed a benchmark test for the strong motion simulation methods using stochastic Green's function method. All the results calculated by six teams from different institutions generally show good agreement to each other. Since random numbers are used in generating time histories and so on, synthesized amplitude shows variation in particular frequencies. When applying the stochastic Green's function method, this variation should be in mind.",

keywords = "Benchmark tests, Fault model, Point source, Random numbers, Stochastic Green's function method, Strong motion prediction methods",

author = "Kenichi Kato and Yoshiaki Hisada and Hidenori Kawabe and Susumu Ohno and Atsushi Nozu and Arihide Nobata and Atsushi Morikawa and Yu Yamamoto",

note = "Funding Information: This work was supported by the Deutsche Forschungsgemeinschaft (DFG). We are grateful to Dr. B. Bachmann for supplying strains and Dr. W. Klipp for many helpful discussions.",

year = "2011",

doi = "10.3130/aijt.17.49",

language = "English",

volume = "17",

pages = "49--54",

journal = "AIJ Journal of Technology and Design",

issn = "1341-9463",

publisher = "Architectural Institute of Japan",

number = "35",

}

TY - JOUR

T1 - Benchmark tests for strong ground motion prediction methods

T2 - Case for stochastic green's function method (part 1)

AU - Kato, Kenichi

AU - Hisada, Yoshiaki

AU - Kawabe, Hidenori

AU - Ohno, Susumu

AU - Nozu, Atsushi

AU - Nobata, Arihide

AU - Morikawa, Atsushi

AU - Yamamoto, Yu

N1 - Funding Information: This work was supported by the Deutsche Forschungsgemeinschaft (DFG). We are grateful to Dr. B. Bachmann for supplying strains and Dr. W. Klipp for many helpful discussions.

PY - 2011

Y1 - 2011

N2 - We performed a benchmark test for the strong motion simulation methods using stochastic Green's function method. All the results calculated by six teams from different institutions generally show good agreement to each other. Since random numbers are used in generating time histories and so on, synthesized amplitude shows variation in particular frequencies. When applying the stochastic Green's function method, this variation should be in mind.

AB - We performed a benchmark test for the strong motion simulation methods using stochastic Green's function method. All the results calculated by six teams from different institutions generally show good agreement to each other. Since random numbers are used in generating time histories and so on, synthesized amplitude shows variation in particular frequencies. When applying the stochastic Green's function method, this variation should be in mind.

KW - Benchmark tests

KW - Fault model

KW - Point source

KW - Random numbers

KW - Stochastic Green's function method

KW - Strong motion prediction methods

UR - http://www.scopus.com/inward/record.url?scp=84856948799&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856948799&partnerID=8YFLogxK

U2 - 10.3130/aijt.17.49

DO - 10.3130/aijt.17.49

M3 - Article

AN - SCOPUS:84856948799

SN - 1341-9463

VL - 17

SP - 49

EP - 54

JO - AIJ Journal of Technology and Design

JF - AIJ Journal of Technology and Design

IS - 35

ER -

Benchmark tests for strong ground motion prediction methods: Case for stochastic green's function method (part 1)

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this