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学术成果

飞桨团队致力于与国内外高校、科研院所、企业等机构开展深度合作，共同推动飞桨生态在科学计算领域的应用和发展。

  1. Wang, T., & Wang, C. (2024). Latent Neural Operator for Solving Forward and Inverse PDE Problems. Neural Information Processing Systems.
  2. Deng, J., Li, X., Xiong, H., Hu, X., & Ma, J. (2024).Geometry-Guided Conditional Adaption for Surrogate Models of Large-Scale 3D PDEs on Arbitrary Geometries. International Joint Conference on Artificial Intelligence.
  3. Xu, P., Gao, T., Wang, Y., Yin, J., Zhang, J., Zheng, X., ... & Chen, X. (2024). YingLong: Skillful High Resolution Regional Short Term Forecasting with Boundary Smoothing. arXiv preprint arXiv:2401.16254.
  4. Chu, X., Guo, W., Wu, T., Zhou, Y., Zhang, Y., Cai, S., & Yang, G. (2024). Flow reconstruction over a SUBOFF model based on LBM-generated data and physics-informed neural networks. Ocean Engineering, 308, 118250.
  5. Huang, B., Hua, H., Han, H., He, S., Zhou, Y., Liu, S., & Zuo, Z. (2024). Physics-informed neural networks for advection–diffusion–Langmuir adsorption processes. Physics of Fluids, 36(8).
  6. Lu, Z., Zhou, Y., Zhang, Y., Hu, X., Zhao, Q., & Hu, X. (2024). A fast general thermal simulation model based on Multi-Branch Physics-Informed deep operator neural network. Physics of Fluids, 36(3).
  7. Xu, B., Zhou, Y., & Bian, X. (2024). Self-supervised learning based on transformer for flow reconstruction and prediction. Physics of Fluids, 36(2).
  8. Chen, K., Dai, M., Xu, L., Xu, S., Xie, X., Hu, X., ... & Zhang, H. (2024). Inverse parameter identifications and forward strip temperature simulations of the continuous annealing line with physics-informed neural network and operation big data. Engineering Applications of Artificial Intelligence, 127, 107307.
  9. Pang, H. Q., Shao, X., Zhang, Z. T., Xie, X., Dai, M. Y., Guo, J. F., ... & Gao, Y. F. (2023). Physics-informed learning for thermophysical field reconstruction and parameter measurement in a nano-porous insulator's heat transfer problem. International Communications in Heat and Mass Transfer, 148, 107045.
  10. Zhu, Y., Yan, Y., Zhang, Y., Zhou, Y., Zhao, Q., Liu, T., ... & Liang, Y. (2023, June). Application of Physics-Informed Neural Network (PINN) in the Experimental Study of Vortex-Induced Vibration with Tunable Stiffness. In ISOPE International Ocean and Polar Engineering Conference (pp. ISOPE-I). ISOPE.
  11. Chen, K., Huang, F., & Zhang, H. (2023, August). Fan Rotation Speed Real-Time Optimizations of Continuous Annealing Line with Mechanism-Guided Multitask Classification and Regression Model. In Journal of Physics: Conference Series (Vol. 2575, No. 1, p. 012010). IOP Publishing.
  12. Xiang, H., Zhang, Y., Zhou, Y., Liu, T., Xie, X., Li, Y., & Zhao, Q. (2022). Simulation of Unsteady Incompressible 2D Cylinder Flow with Physics-Informed Neural Network. 한국전산유체공학회 학술대회논문집, 121-121.
  13. Chen, K., Xie, X., Chu, Y., Leng, M., Zhang, J., Xu, Z., ... & Zhang, H. (2022, July). Heat transfer coefficient predictions of the air-cooled condenser with machine learning based on the operation big data of the power plant. In Heat Transfer Summer Conference (Vol. 85796, p. V001T08A002). American Society of Mechanical Engineers.