Back to Search
Start Over
Investigation into the topology optimization for conductive heat transfer based on deep learning approach.
- Source :
-
International Communications in Heat & Mass Transfer . Oct2018, Vol. 97, p103-109. 7p. - Publication Year :
- 2018
-
Abstract
- Abstract A deep learning approach combining with the traditional solid isotropic material with penalization (SIMP) method is presented in this paper to accelerate the topology optimization of the conductive heat transfer. This deep learning predictor is structured based on the deep fully convolutional neural network. The validity and accuracy of this deep learning approach is investigated based on the typical ‘Volume-Point’ heat conduction problems. The time consumption of the optimization process will be reduced significantly by introducing the deep learning approach. [ABSTRACT FROM AUTHOR]
- Subjects :
- *HEAT transfer
*DEEP learning
*NEURAL circuitry
*TOPOLOGY
*HEAT conduction
Subjects
Details
- Language :
- English
- ISSN :
- 07351933
- Volume :
- 97
- Database :
- Academic Search Index
- Journal :
- International Communications in Heat & Mass Transfer
- Publication Type :
- Academic Journal
- Accession number :
- 131525719
- Full Text :
- https://doi.org/10.1016/j.icheatmasstransfer.2018.07.001