A Deep Learning Surrogate Model for Topology Optimization-Reference-Cited by-同舟云学术

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A Deep Learning Surrogate Model for Topology Optimization

Published:2021-06 Issue:6 Volume:57 Page:1-4
ISSN:0018-9464
Container-title:IEEE Transactions on Magnetics
language:
Short-container-title:IEEE Trans. Magn.

Author:

Barmada Sami^ORCID,Fontana Nunzia^ORCID,Formisano Alessandro^ORCID,Thomopulos Dimitri^ORCID,Tucci Mauro^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials

Link

http://xplorestaging.ieee.org/ielx7/20/9432870/09367238.pdf?arnumber=9367238

Cited by 23 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Scalar Field Prediction on Meshes Using Interpolated Multiresolution Convolutional Neural Networks;Journal of Applied Mechanics;2024-07-12

2. Comprehensive examination of topologically optimized thermo-fluid heat sinks;Energy;2024-07

3. A double-layer progressive architecture-based surrogate model for efficiency analysis of spiral shaft in shield machine;Automation in Construction;2024-04

4. Machine Learning for the Design and the Simulation of Radiofrequency Magnetic Resonance Coils: Literature Review, Challenges, and Perspectives;Sensors;2024-03-19

5. Super-Resolution Based Topology Optimization for Rapid Generation of Low Mass Structural Designs;2024 IEEE Aerospace Conference;2024-03-02

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