Machine learning-based surrogate model for calibrating fire source properties in FDS models of façade fire tests-Reference-Cited by-同舟云学术

Machine learning-based surrogate model for calibrating fire source properties in FDS models of façade fire tests

Published:2022-06 Issue: Volume:130 Page:103591
ISSN:0379-7112
Container-title:Fire Safety Journal
language:en
Short-container-title:Fire Safety Journal

Author:

Nguyen Hoang T.^ORCID,Abu-Zidan Yousef^ORCID,Zhang Guomin,Nguyen Kate T.Q.

Funder

Australian Research Council

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Safety, Risk, Reliability and Quality,General Materials Science,General Chemistry,Building and Construction

Reference52 articles.

1. Performance of modern building façades in fire: a comprehensive review;Nguyen;Electron. J. Struct. Eng.,2016

2. British Standard, BS 8414-2: 2015 Fire Performance of External Cladding Systems. Test Method for Non-loadbearing External Cladding Systems Fixed to and Supported by a Structural Steel Frame,2015

3. JIS A 1310:2015 Test Method for Fire Propagation over Building Facades;Japanese Standards Association,2015

4. Experimental and numerical investigations on the thermal response of multilayer glass fibre/unsaturated polyester/organoclay composite;Nguyen;Fire Mater.,2016

5. Modeling of fire exposure in facade fire testing;Anderson;Fire Mater.,2018

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