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tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow [article]

You Xie, Erik Franz, Mengyu Chu, Nils Thuerey
2018 arXiv   pre-print
We propose a temporally coherent generative model addressing the super-resolution problem for fluid flows.  ...  Based on a conditional generative adversarial network that is designed for the inference of three-dimensional volumetric data, our model generates consistent and detailed results by using a novel temporal  ...  We would like to thank Wei He for helping with making the videos, and all members of the graphics labs of TUM, IST Austria and ETH Zurich for the thorough discussions.  ... 
arXiv:1801.09710v2 fatcat:eihainku2vh4zdsfghmz4gbbxm

Application of Video-to-Video Translation Networks to Computational Fluid Dynamics

Hiromitsu Kigure
2021 Frontiers in Artificial Intelligence  
In particular, the time evolution of density distributions in the cases of a high-resolution grid is reproduced from that in the cases of a low-resolution grid through GANs, and the density inhomogeneity  ...  Qualitative and quantitative comparisons of the results of the proposed method with those of several super-resolution algorithms are also presented.  ...  Xie et al. (2018) proposed a method for super-resolution fluid flow by a temporally coherent generative model (tempoGAN).  ... 
doi:10.3389/frai.2021.670208 pmid:34568812 pmcid:PMC8461073 fatcat:3thstqntizdzhiwzju243nmuk4

Super-Resolution of Near-Surface Temperature Utilizing Physical Quantities for Real-Time Prediction of Urban Micrometeorology [article]

Yuki Yasuda and Ryo Onishi and Yuichi Hirokawa and Dmitry Kolomenskiy and Daisuke Sugiyama
2021 arXiv   pre-print
The present paper proposes a super-resolution (SR) model based on a convolutional neural network and applies it to the near-surface temperature in urban areas.  ...  We train the SR model with sets of low-resolution (LR) and high-resolution (HR) images from building-resolving large-eddy simulations (LESs) in a city, where the horizontal resolutions of LR and HR are  ...  Thuerey, Tempogan: A temporally coher- ent, volumetric gan for super-resolution fluid flow, ACM Trans. Graph. 37 (7 2018). doi:10.1145/3197517.3201304.  ... 
arXiv:2108.00806v2 fatcat:mkfsrpyiwfhpzd3sq4sunkpj3u

Deep Hierarchical Super-Resolution for Scientific Data Reduction and Visualization [article]

Skylar W. Wurster, Han-Wei Shen, Hanqi Guo, Thomas Peterka, Mukund Raj, Jiayi Xu
2021 arXiv   pre-print
We present an approach for hierarchical super resolution (SR) using neural networks on an octree data representation.  ...  We utilize these networks in a hierarchical super resolution algorithm that upscales multiresolution data to a uniform high resolution without introducing seam artifacts on octree node boundaries.  ...  Xie et al. create tempoGAN [70] , which upscales fluid flows for temporally consistent high resolution output. Fukami et al. compare two ML-based SSR methods for 2D fluid flow [14] .  ... 
arXiv:2107.00462v1 fatcat:37qe5d6v4bgrzb3cy5fnzf2qjm

Subspace Graph Physics: Real-Time Rigid Body-Driven Granular Flow Simulation [article]

Amin Haeri, Krzysztof Skonieczny
2021 arXiv   pre-print
Granular flows and their interactions with rigid bodies still pose several open questions. A promising direction for accurate, yet efficient, modeling is using continuum methods.  ...  Also, a new direction for real-time physics modeling is the use of deep learning.  ...  Tempogan: A temporally coherent, volumetric gan for super-resolution fluid flow. ACM Trans. Graph. 37. URL: https://doi.org/10.1145/3197517.3201304, doi:10.1145/3197517.3201304.  ... 
arXiv:2111.10206v1 fatcat:vntwi2zoevfsrfmvohvydhqqte

Physics-based Deep Learning [article]

Nils Thuerey and Philipp Holl and Maximilian Mueller and Patrick Schnell and Felix Trost and Kiwon Um
2021 arXiv   pre-print
We live in exciting times: these methods have a huge potential to fundamentally change what computer simulations can achieve.  ...  This digital book contains a practical and comprehensive introduction of everything related to deep learning in the context of physical simulations.  ...  [XFCT18] You Xie, Erik Franz, Mengyu Chu, and Nils Thuerey. tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow. ACM Trans. Graph., 2018.  ... 
arXiv:2109.05237v2 fatcat:dm2wyckg6fcxzhsxi4hmo76sny