Collapse comparison of offshore platforms before and after fire using plastic analysis and genetic algorithm

Author:

Pouria Mohammad Mehdi,Akbarpour Abbas,Ahmadi Hassan,Tavassoli Mohammad Reza,Saedi Daryan Amir

Abstract

PurposeOffshore structures are among the structures exposed to fire more often. Most of these structures are likely to be associated with flammable materials. In this research, some of the structures constructed on top of marine decks have been studied.Design/methodology/approachFor this purpose, the upper-bound theory of plastic analysis has been used to investigate its collapse behavior. In this way, genetic algorithm has been used for application of the combination of elementary mechanisms in the classic plastic analysis problem.FindingsThe studied structures are optimized by plastic analysis theory before and after the fire and their failure modes are compared with each other. The comparison of the results indicates significant changes in the load factor value, as well as the critical collapse mode of the structure before and after the fire.Originality/valueResults indicate that the combination of plastic analysis and a genetic algorithm can predict the collapse mode of the structure before and after the fire accurately.

Publisher

Emerald

Subject

Mechanical Engineering,Mechanics of Materials,Safety, Risk, Reliability and Quality

Reference29 articles.

1. Predicting the behaviour of semi-rigid joints in fire using an artificial neural network;Steel Structures,2007

2. Fire performance of composite materials in ships and offshore structures;Marine Structures,1991

3. Estimating shear strength of short rectangular reinforced concrete columns using nonlinear regression and gene expression programming;Structures,2017

4. A new plastic analysis procedure for collapse prediction of braced frames by means of Genetic algorithm;Journal of Structural Engineering,2019

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3