Research on multi-objective function optimization of self insulation hollow block structure based on genetic algorithm

2018 International Conference on Civil and Hydraulic Engineering

土木建筑工程;水利工程

Yang, Zhaotong^1 ; Liu, Yong^2 ; Shi, Minghui^1 ; Yin, Guansheng^1

School of Science, Chang'An University, Xi'an, Shaanxi

710064, China^1

School of Architecture, Chang'An University, Xi'an, Shaanxi

710064, China^2

关键词: Abaqus finite element software;    Bearing structure;    Economic performance;    Insulation performance;    Mechanical performance;    Multi-objective functions;    Optimization problems;    Thermal Performance;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/189/2/022077/pdf
DOI  :  10.1088/1755-1315/189/2/022077

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

Considering the multi-objective characteristics of the self insulation hollow block optimization problem, the thermal performance objective function, the mechanical performance objective function and the economic performance objective function are established for the self insulation block. The multi-objective function optimization method based on genetic algorithm is used to optimize the thermal performance, mechanical performance and economy of the hollow block. The opening rate, heat transfer coefficient and compressive strength of the three row interlaced hollow block, four row of staggered hollow block and five row of staggered hollow block were analyzed by using the ABAQUS finite element software. The results show that the opening rate of the five row staggered holes is 38.9% and the heat transfer coefficient is 0.592 W / (m 2 ⋅ K). The insulation performance of the three and four row hollow blocks is better and the compressive strength is 10.23 Mpa, which meets the strength requirement of the bearing structure.