The GBESO Method Based on FEA with Discrete Models and Application for Aided Design to Members in RC D-Region

DOI Web Site 参考文献29件
  • Zhang Hu-zhi
    School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, China.
  • Kang Yi-jun
    School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, China.
  • Li Li-kun
    CCCC-SHEC First Highway Engineering Co. Ltd., Wuhan, Hubei 430014, China.
  • Wang Jian-qun
    School of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, China.

抄録

<p>To better utilize topology optimization theory to assist in designing reinforced concrete (RC) D-region members, a novel application mode, the Genetic Bi-directional Evolutionary Structural Optimization (GBESO) method based on Finite Element Analysis (FEA) with discrete models is proposed. Correspondingly a design method for reinforcement layout of RC D-region members is also derived. Non-linear FEA verification is conducted on numerical examples involving deep beams with openings. The results demonstrate that the GBESO algorithm exhibits better global optimization capacities compared to Evolutionary Structural Optimization-type (ESO-type) algorithms. It also provides rebar topologies that are more in line with the optimization objective, bringing lower steel consumption and higher rebar utilization rates. Moreover, by introducing inclined rebar to the members, their shear strength is enhanced to a level comparable to the flexural one, significantly improving ultimate load-bearing capacity, elastoplastic deformation capacity, and better ductility compared to empirical method. </p>

収録刊行物

参考文献 (29)*注記

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ