Layout Optimization of Spatial Rigid Frame by Second-Order Effect Analysis

LI Yinqi; CHENG Wenming; LIU Huasen

doi:10.3969/j.issn.0258-2724.20170863

Volume 54 Issue 5

Oct. 2019

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Journal of Southwest Jiaotong University > 2019 > 54(5): 971-979.

LI Yinqi, CHENG Wenming, LIU Huasen. Layout Optimization of Spatial Rigid Frame by Second-Order Effect Analysis[J]. Journal of Southwest Jiaotong University, 2019, 54(5): 971-979. doi: 10.3969/j.issn.0258-2724.20170863

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LI Yinqi, CHENG Wenming, LIU Huasen. Layout Optimization of Spatial Rigid Frame by Second-Order Effect Analysis[J]. Journal of Southwest Jiaotong University, 2019, 54(5): 971-979. doi: 10.3969/j.issn.0258-2724.20170863

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Layout Optimization of Spatial Rigid Frame by Second-Order Effect Analysis

doi: 10.3969/j.issn.0258-2724.20170863

Received Date: 07 Dec 2017
Rev Recd Date: 06 Sep 2018

Available Online: 14 Sep 2018

Publish Date: 01 Oct 2019

Abstract

Abstract

In order to handle three-dimensional spatial frame layout optimization, nonlinear rigidity matrix of the beam-column element with seven degrees of freedom was deduced by second-order elastic theory, while the geometric nonlinearity and restrained torsional warping were considered. An overall second-order analysis for rigid-frame structure was conducted by integrating the nonlinear rigidity matrices of all beam-column elements. A numerical layout optimization model of spatial rigid frame was built, which was able to satisfy the requirements for structural strength, stiffness and stability. In order to solve the numerical model, a two-way control method of reliable topology and guided genetic algorithm (KLGA) was proposed based on the improvement of the genetic algorithm (GA). In one respect, this method enables the separation of the topological variables from the layout design variables, and then integrates them after evaluating the reliable topological variable combinations based on component importance. In addition, the guidance information of structure was added in the algorithm to guide the path of global optimal solution for GA. Finally, two typical examples of rigid frame structure are presented to validate the feasibility and effectiveness of the second-order effect model and optimization method KLGA. For example, in the second-order effect model of example 2, the optimal structural mass acquired by KLGA is 24.5% less than that of GA, and its range of fluctuation promotes from 9.61% to 1.39%, indicating the stability of KLGA.
- spatial rigid frame,
- second-order effect,
- layout optimization,
- reliable topology,
- guided genetic algorithm

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Layout Optimization of Spatial Rigid Frame by Second-Order Effect Analysis

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