Structural seismic damage and loss assessments using a multi-conditioning ground motion selection approach based on an efficient sampling technique

The application of Latin Hypercube and Monte Carlo ( MC ) sampling techniques for ground motion selection purposes is investigated. Latin Hypercube Sampling ( LHS ) works by first stratifying a probability distribution domain into multiple equally spaced and non-overlapping stripes and then by permu...

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Vydané v:	Bulletin of earthquake engineering Ročník 19; číslo 3; s. 1271 - 1287
Hlavní autori:	Ghotbi, Abdoul R., Taciroglu, Ertugrul
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Dordrecht Springer Netherlands 01.02.2021 Springer Nature B.V
Predmet:	Civil Engineering Concrete Concrete construction Conditioning Damage assessment Earth and Environmental Science Earth Sciences Earthquake damage Earthquakes Environmental Engineering/Biotechnology Epistemology Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Ground motion Hydrogeology Hypercubes Latin hypercube sampling Methods Multivariate analysis Original Article Probability distribution Probability theory Reinforced concrete Sampling Sampling methods Sampling techniques Statistical methods Structural damage Structural Geology Loss assessments Conditioning criteria Damage analyses
ISSN:	1570-761X, 1573-1456
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Abstract	The application of Latin Hypercube and Monte Carlo ( MC ) sampling techniques for ground motion selection purposes is investigated. Latin Hypercube Sampling ( LHS ) works by first stratifying a probability distribution domain into multiple equally spaced and non-overlapping stripes and then by permutationally drawing samples from those stripes. To examine the efficiency of these two distinct sampling methods, a set of conditional multivariate distributions was fit to an intensity measure vector based on a single, two, or average of more-than-two (average) conditioning intensity measure. LHS was then utilized for sampling purposes from the conditional multivariate distributions, which in turn demonstrated superiority over MC given the same number of realization samples. Accordingly, it was utilized as an underlying peace of a broader ground motion selection framework to facilitite the selection of a number of ground motion suites based on different methods of conditioning. Using the selected suites, response history and subsequent damage/loss analyses were conducted on a generic 4-story non-ductile reinforced concrete building. The outcomes of these latter studies demonstrated that the ground motion suite selected based on an average-intensity-measure conditioning criterion performed better than those selected through single- and two-intensity-measure conditioning criteria.
AbstractList	The application of Latin Hypercube and Monte Carlo (MC) sampling techniques for ground motion selection purposes is investigated. Latin Hypercube Sampling (LHS) works by first stratifying a probability distribution domain into multiple equally spaced and non-overlapping stripes and then by permutationally drawing samples from those stripes. To examine the efficiency of these two distinct sampling methods, a set of conditional multivariate distributions was fit to an intensity measure vector based on a single, two, or average of more-than-two (average) conditioning intensity measure. LHS was then utilized for sampling purposes from the conditional multivariate distributions, which in turn demonstrated superiority over MC given the same number of realization samples. Accordingly, it was utilized as an underlying peace of a broader ground motion selection framework to facilitite the selection of a number of ground motion suites based on different methods of conditioning. Using the selected suites, response history and subsequent damage/loss analyses were conducted on a generic 4-story non-ductile reinforced concrete building. The outcomes of these latter studies demonstrated that the ground motion suite selected based on an average-intensity-measure conditioning criterion performed better than those selected through single- and two-intensity-measure conditioning criteria. The application of Latin Hypercube and Monte Carlo ( MC ) sampling techniques for ground motion selection purposes is investigated. Latin Hypercube Sampling ( LHS ) works by first stratifying a probability distribution domain into multiple equally spaced and non-overlapping stripes and then by permutationally drawing samples from those stripes. To examine the efficiency of these two distinct sampling methods, a set of conditional multivariate distributions was fit to an intensity measure vector based on a single, two, or average of more-than-two (average) conditioning intensity measure. LHS was then utilized for sampling purposes from the conditional multivariate distributions, which in turn demonstrated superiority over MC given the same number of realization samples. Accordingly, it was utilized as an underlying peace of a broader ground motion selection framework to facilitite the selection of a number of ground motion suites based on different methods of conditioning. Using the selected suites, response history and subsequent damage/loss analyses were conducted on a generic 4-story non-ductile reinforced concrete building. The outcomes of these latter studies demonstrated that the ground motion suite selected based on an average-intensity-measure conditioning criterion performed better than those selected through single- and two-intensity-measure conditioning criteria.
Author	Ghotbi, Abdoul R. Taciroglu, Ertugrul
Author_xml	– sequence: 1 givenname: Abdoul R. orcidid: 0000-0001-9344-3502 surname: Ghotbi fullname: Ghotbi, Abdoul R. email: civil_ghotbi40@yahoo.com organization: University of California – sequence: 2 givenname: Ertugrul surname: Taciroglu fullname: Taciroglu, Ertugrul organization: University of California
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Cites_doi	10.1193/1.3457158 10.1061/(ASCE)ST.1943-541X.0000456 10.1016/j.probengmech.2009.01.004 10.1785/0120080298 10.1002/eqe.2876 10.1193/1.4000094 10.1002/eqe.2546 10.1002/eqe.2213 10.1002/eqe.495 10.1029/2002WR001822 10.1061/(ASCE)ST.1943-541X.0001030 10.1093/imanum/22.3.329 10.1016/j.probengmech.2010.04.001 10.1061/(ASCE)0733-9445(2009)135:10(1146) 10.1016/j.soildyn.2012.04.007 10.1139/l04-040 10.1002/eqe.3009 10.1193/072113EQS209M 10.1016/j.engstruct.2013.02.036 10.1109/MCSE.2011.66 10.1016/j.soildyn.2011.04.007 10.1016/j.strusafe.2009.06.009 10.1002/eqe.869 10.1061/(ASCE)ST.1943-541X.0002419 10.1193/061317EQS114M 10.1061/(ASCE)1084-0702(2007)12:6(689) 10.1193/1.2830434 10.1193/1.4000067 10.1193/021113EQS025M 10.1007/s11803-014-0273-6 10.1002/eqe.2282 10.1002/eqe.2721 10.1002/eqe.3380 10.1002/eqe.3383 10.1002/eqe.2407 10.1002/eqe.995 10.1002/eqe.935
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SubjectTerms	Civil Engineering Concrete Concrete construction Conditioning Damage assessment Earth and Environmental Science Earth Sciences Earthquake damage Earthquakes Environmental Engineering/Biotechnology Epistemology Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Ground motion Hydrogeology Hypercubes Latin hypercube sampling Methods Multivariate analysis Original Article Probability distribution Probability theory Reinforced concrete Sampling Sampling methods Sampling techniques Statistical methods Structural damage Structural Geology
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Title	Structural seismic damage and loss assessments using a multi-conditioning ground motion selection approach based on an efficient sampling technique
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