[29] Zhiqing Sun, Yiming Yang, and Shinjae Yoo. A neural pde solver with temporal stencil modeling. arXiv preprint arXiv:2302.08105, 2023.
[30] Jacqueline H Chen, Alok Choudhary, Bronis De Supinski, Matthew DeVries, Evatt R Hawkes, Scott Klasky, Wei-Keng Liao, Kwan-Liu Ma, John Mellor-Crummey, Norbert Podhorszki, et al. Terascale direct numerical simulations of turbulent combustion using S3D. Computational Science & Discovery, 2(1):015001, 2009.
[31] Akash Dhruv, Elias Balaras, Amir Riaz, and Jungho Kim. A formulation for high-fidelity simulations of pool boiling in low gravity. International Journal of Multiphase Flow, 120:103099, 2019.
[32] Akash Dhruv, Elias Balaras, Amir Riaz, and Jungho Kim. An investigation of the gravity effects on pool boiling heat transfer via high-fidelity simulations. International Journal of Heat and Mass Transfer, 180:121826, 2021.
[33] S. S. Beauchemin and J. L. Barron. The computation of optical flow. ACM Comput. Surv., 27(3):433-466, sep 1995.
[34] Simon Baker, Stefan Roth, Daniel Scharstein, Michael J. Black, J.P. Lewis, and Richard Szeliski. A database and evaluation methodology for optical flow. In 2007 IEEE 11th International Conference on Computer Vision, pages 1-8, 2007.
[35] Moritz Menze, Christian Heipke, and Andreas Geiger. Joint 3d estimation of vehicles and scene flow. ISPRS annals of the photogrammetry, remote sensing and spatial information sciences, 2:427, 2015.
[36] Daniel J. Butler, Jonas Wulff, Garrett B. Stanley, and Michael J. Black. A naturalistic open source movie for optical flow evaluation. In Andrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, and Cordelia Schmid, editors, Computer Vision – ECCV 2012, pages 611–625, Berlin, Heidelberg, 2012. Springer Berlin Heidelberg.
[37] Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox. Flownet: Learning optical flow with convolutional networks. In Proceedings of the IEEE international conference on computer vision, pages 2758-2766, 2015.
[38] Nikolaus Mayer, Eddy Ilg, Philip Hausser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, and Thomas Brox. A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4040-4048, 2016.
[39] Hoang-An Le, Tushar Nimbhorkar, Thomas Mensink, Sezer Karaoglu, Anil S. Baslamisli, and Theo Gevers. Unsupervised generation of optical flow datasets for videos in the wild, 2018.
[40] Ivar Stakgold. Boundary Value Problems of Mathematical Physics: Volume 1. SIAM, 2000.
[41] Joseph Oliger and Arne Sundström. Theoretical and practical aspects of some initial boundary value problems in fluid dynamics. SIAM Journal on Applied Mathematics, 35(3):419-446, 1978.
[42] B. L. J. Gysen, K. J. Meessen, J. J. H. Paulides, and E. A. Lomonova. General formulation of the electromagnetic field distribution in machines and devices using fourier analysis. IEEE Transactions on Magnetics, 46(1):39-52, 2010.
[43] MA Ebadian and CX Lin. A review of high-heat-flux heat removal technologies. Journal of heat transfer, 133(11), 2011.
[44] Gangtao Liang and Issam Mudawar. Pool boiling critical heat flux (chf)—part 1: Review of mechanisms, models, and correlations. International Journal of Heat and Mass Transfer, 117:1352–1367, 2018.
[45] Seyed Moein Rassoulinejad-Mousavi, Firas Al-Hindawi, Tejaswi Soori, Arif Rokoni, Hyunsoo Yoon, Han Hu, Teresa Wu, and Ying Sun. Deep learning strategies for critical heat flux detection in pool boiling. Applied Thermal Engineering, 190:116849, 2021.