Thermal analysis benchmarks

Papers

[1] Chen, X., Zhao, X. Gong, Z., Zhang，J., Chen, X., Yao, W., (2021) A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout, Science China-Physics, Mechanics & Astronomy.

[2] Chen, X., Chen, X., Zhou, W., Zhang, J., Yao, W.,(2021). The heat source layout optimization using deep learning surrogate modeling. Structural and Multidisciplinary Optimization.

[3] Zhao., X, Gong, Z., Zhang, J., Yao, W., Chen, X., (2021). A surrogate model with data augmentation and deep transfer learning for temperature field prediction of heat source layout. Structural and Multidisciplinary Optimization.(to appear)

The Intelligent Design and Robust Learning laboratory of Defense Innovation Institute of Academy of Military Sciences focuses on the basic frontier and cross-research of artificial intelligence and aircraft design. The team has developed a series of data and model driven deep learning methods for efficient multi-disciplinary analysis and optimization of aircraft, and tries to construct a intelligent auxiliary aircraft design optimization cloud platform, namely IDaaS （Intelligent Design as a Service）. The team has already publicly released two thermal analysis benchmarks, namely the HSLD （Heat-source layout dataset） and TFRD （Temperature field reconstruction dataset）. Besides, they developed a physical informed neural network framework IDRLNet. In the past three years, they have published more than 30 related papers, and more than 30 patent applications.

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