A Bionic Hierarchy Generative Design for Conductive Heat Transfer

Author:

Lin Qiyin1,Liu Lian1,Wang Jihong1,Yan Ke1,Guo Junkang1,Su Wenjun2

Affiliation:

1. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, Xi'an Jiaotong University, Xi'an 710049, China; Institute of Design Science and Basic Components, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China

2. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, Xi'an Jiaotong University, Xi'an 710049, China; Institute of Design Science and Basic Components, School of Mechanical Engineering, Design Science and Basic Components, Xi'an Jiaotong University, Xi'an 710049, China

Abstract

Abstract A bionic hierarchy generative design algorithm inspired by the leaf vein growth process is presented for the layout design of heat conduction channels. The design domain is discretized based on the element-free Galerkin (EFG) method. The generations of main channels and lateral channels are separated. The effectiveness of the developed bionic hierarchy generative design approach is investigated based on the general “volume-to-point” heat conduction problem.

Publisher

ASME International

Subject

Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science

Reference22 articles.

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4. Investigation Into the Topology Optimization for Conductive Heat Transfer Based on Deep Learning Approach;Int. Commun. Heat Mass Transfer,2018

5. Method for Directly and Instantaneously Predicting Conductive Heat Transfer Topologies by Using Supervised Deep Learning;Int. Commun. Heat Mass Transfer,2019

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