• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 30 Issue 3
Jun.  2017
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Article Contents
YOU Fang, CHEN Jianjun, LIN Feng, CAO Hongjun. Topology Optimization of Heat Conduction Structures Based on Probabilistic and Non-probabilistic Hybrid Reliability[J]. Journal of Southwest Jiaotong University, 2017, 30(3): 578-583,599. doi: 10.3969/j.issn.0258-2724.2017.03.019
Citation: YOU Fang, CHEN Jianjun, LIN Feng, CAO Hongjun. Topology Optimization of Heat Conduction Structures Based on Probabilistic and Non-probabilistic Hybrid Reliability[J]. Journal of Southwest Jiaotong University, 2017, 30(3): 578-583,599. doi: 10.3969/j.issn.0258-2724.2017.03.019

Topology Optimization of Heat Conduction Structures Based on Probabilistic and Non-probabilistic Hybrid Reliability

doi: 10.3969/j.issn.0258-2724.2017.03.019
  • Received Date: 14 Jan 2015
  • Publish Date: 25 Jun 2017
  • Topology optimization design of heat conduction structures with interval variables and random variables was studied. Firstly, structural physical parameters and applied loads were regarded as interval variables and random variables. The probabilistic reliability and the non-probabilistic reliability were utilized as the measurement of hybrid structural reliability. Secondly, the optimization mathematical model was constructed, in which the relative thermal conductivity of elements was taken as design variables, minimum volume of heat conductive material was taken as objective function and the hybrid reliability index for dissipation of heat transport potential capacity was taken as the constraint. Lastly, the evolutionary structural optimization method was used in the optimization. In the two numerical examples, the probabilities of hybrid reliability of optimal topology structures are 0.94476 and 0.944476, which are larger than the given probability of 0.928650 and 0.933129, respectively, validating the feasibility and effectiveness of the optimal model and solving strategy.

     

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