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  • 标题:Evolutionary optimization of reinforced concrete beams, taking into account design reliability, safety and risks during the emergency loss of supports
  • 本地全文:下载
  • 作者:Ashot Tamrazyan ; Anatoliy Alekseytsev
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2019
  • 卷号:97
  • 页码:1-8
  • DOI:10.1051/e3sconf/20199704005
  • 出版社:EDP Sciences
  • 摘要:An algorithm has been developed to optimize the reinforced concrete beams in removing the supports based on an adapted genetic algorithm and RBDO approach. Multiple cross-sectional dimensions of elements, concrete class, class and diameter of the reinforcements vary. Avoiding significant changes in the geometry of the structure after emergency actions is considered as the main active constraints. It is believed that this constraints provides the required structural resistibility in an emergency situation. The value terms of material losses risk in case of a possible structure failure as a component of the objective function is considered. The proposed genetic algorithm includes an adapted mutation operator and the elitism strategy for selecting the best solutions. The algorithm presented allows obtaining design solutions of high operational reliability for rectangular reinforced concrete beams, taking into account the optimal ratio of a structure costs and the risks of its failure in an accident.
  • 其他摘要:An algorithm has been developed to optimize the reinforced concrete beams in removing the supports based on an adapted genetic algorithm and RBDO approach. Multiple cross-sectional dimensions of elements, concrete class, class and diameter of the reinforcements vary. Avoiding significant changes in the geometry of the structure after emergency actions is considered as the main active constraints. It is believed that this constraints provides the required structural resistibility in an emergency situation. The value terms of material losses risk in case of a possible structure failure as a component of the objective function is considered. The proposed genetic algorithm includes an adapted mutation operator and the elitism strategy for selecting the best solutions. The algorithm presented allows obtaining design solutions of high operational reliability for rectangular reinforced concrete beams, taking into account the optimal ratio of a structure costs and the risks of its failure in an accident.
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