Surrogate statistical model of a school building in Nepal using ASCE 41-17

S. Bose; A. Stavridis; P. C. Anastasopoulos; K. Sett

Surrogate statistical model of a school building in Nepal using ASCE 41-17

Department of Civil, Structural & Environmental Engineering

University at Buffalo

SUNY Buffalo

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

This study focuses on the development of a statistical model for buildings with infilled reinforced concrete frames. The cornerstone of this study is the nonlinear numerical model of a school building in Nepal. The model is developed based on the ASCE 14-17 guidelines, and it is extensively validated with field data. Then, it is used in a series of parametric studies conducted to identify the influential material parameters, and in incremental dynamic analyses conducted to provide data for the calibration of the statistical model. The three-staged least square statistical modeling approach is employed to relate the influential material parameters and ground motion intensity measures with important response quantities related to the peak and residual first story drift ratios.

Original language	English
Journal	Proceedings of the International Conference on Natural Hazards and Infrastructure
State	Published - 2019
Event	2nd International Conference on Natural Hazards and Infrastructure, ICONHIC 2019 - Chania, Greece Duration: Jun 23 2019 → Jun 26 2019

Keywords

Masonry infilled RC frame
Statistical modeling
Surrogate model
Three-staged least square approach

Cite this

@article{5be59cead7ae4f5ab0e2de38bd5cf8fc,

title = "Surrogate statistical model of a school building in Nepal using ASCE 41-17",

abstract = "This study focuses on the development of a statistical model for buildings with infilled reinforced concrete frames. The cornerstone of this study is the nonlinear numerical model of a school building in Nepal. The model is developed based on the ASCE 14-17 guidelines, and it is extensively validated with field data. Then, it is used in a series of parametric studies conducted to identify the influential material parameters, and in incremental dynamic analyses conducted to provide data for the calibration of the statistical model. The three-staged least square statistical modeling approach is employed to relate the influential material parameters and ground motion intensity measures with important response quantities related to the peak and residual first story drift ratios.",

keywords = "Masonry infilled RC frame, Statistical modeling, Surrogate model, Three-staged least square approach",

author = "S. Bose and A. Stavridis and Anastasopoulos, \{P. C.\} and K. Sett",

note = "Publisher Copyright: {\textcopyright} 2019, National Technical University of Athens. All rights reserved.; 2nd International Conference on Natural Hazards and Infrastructure, ICONHIC 2019 ; Conference date: 23-06-2019 Through 26-06-2019",

year = "2019",

language = "English",

journal = "Proceedings of the International Conference on Natural Hazards and Infrastructure",

issn = "2623-4513",

publisher = "National Technical University of Athens",

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T1 - Surrogate statistical model of a school building in Nepal using ASCE 41-17

AU - Bose, S.

AU - Stavridis, A.

AU - Anastasopoulos, P. C.

AU - Sett, K.

PY - 2019

Y1 - 2019

N2 - This study focuses on the development of a statistical model for buildings with infilled reinforced concrete frames. The cornerstone of this study is the nonlinear numerical model of a school building in Nepal. The model is developed based on the ASCE 14-17 guidelines, and it is extensively validated with field data. Then, it is used in a series of parametric studies conducted to identify the influential material parameters, and in incremental dynamic analyses conducted to provide data for the calibration of the statistical model. The three-staged least square statistical modeling approach is employed to relate the influential material parameters and ground motion intensity measures with important response quantities related to the peak and residual first story drift ratios.

AB - This study focuses on the development of a statistical model for buildings with infilled reinforced concrete frames. The cornerstone of this study is the nonlinear numerical model of a school building in Nepal. The model is developed based on the ASCE 14-17 guidelines, and it is extensively validated with field data. Then, it is used in a series of parametric studies conducted to identify the influential material parameters, and in incremental dynamic analyses conducted to provide data for the calibration of the statistical model. The three-staged least square statistical modeling approach is employed to relate the influential material parameters and ground motion intensity measures with important response quantities related to the peak and residual first story drift ratios.

KW - Masonry infilled RC frame

KW - Statistical modeling

KW - Surrogate model

KW - Three-staged least square approach

UR - https://www.scopus.com/pages/publications/85104448775

M3 - Conference article

SN - 2623-4513

JO - Proceedings of the International Conference on Natural Hazards and Infrastructure

JF - Proceedings of the International Conference on Natural Hazards and Infrastructure

T2 - 2nd International Conference on Natural Hazards and Infrastructure, ICONHIC 2019

Y2 - 23 June 2019 through 26 June 2019

ER -

Surrogate statistical model of a school building in Nepal using ASCE 41-17

Abstract

Keywords

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