CFD: Algorithms I
ORAL · A15 · ID: 1765999
Presentations
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Solution multiplicity and effects of data and eddy viscosity on Navier-Stokes solutions inferred by physics-informed neural networks
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Presenters
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George E Karniadakis
Brown University
Authors
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George E Karniadakis
Brown University
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Zhicheng Wang
Dalian University of Technology
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Xuhui Meng
huazhong university of science and technology
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Parallel evolutional deep neural networks for compressible Navier-Stokes
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Presenters
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Hadden Kim
Johns Hopkins University
Authors
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Hadden Kim
Johns Hopkins University
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Tamer A Zaki
Johns Hopkins University
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A Simple Inteface-Capturing Scheme for Simulating Compressible Two-Phase Flows
ORAL
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Publication: In preparation:<br>A Simple Interface-Capturing Scheme for Simulating Compressible Two-Phase Flows
Presenters
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Yijun Wang
ETH Zurich
Authors
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Yijun Wang
ETH Zurich
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Hossein Gorji
EMPA, Switzerland
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Patrick Jenny
ETH Zurich
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Computation of 2D Stokes flows via lightning and AAA rational approximation
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Publication: Preprint: Xue, Y., Waters, S. L. and Trefethen, L. N. 2023. Computation of 2D Stokes flows via lightning and AAA rational approximation. arXiv. https://arxiv.org/abs/2306.13545
Presenters
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Yidan Xue
University of Oxford
Authors
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Yidan Xue
University of Oxford
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Sarah L Waters
University of Oxford
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Lloyd N Trefethen
University of Oxford
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Applicability of a semi-implicit pressure-based algorithm without spurious pressure oscillations to real fluid flows
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Presenters
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Sho Wada
Kyoto university, Kyoto University
Authors
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Sho Wada
Kyoto university, Kyoto University
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Reo Kai
Kyushu University
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Abhishek Lakshman L Pillai
Kyoto University
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Ryoichi Kurose
Kyoto University, Kyoto Univ
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On the analysis of conservation- and pressure-equilibrium-preserving schemes for compressible real-fluid simulations
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Presenters
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Hiroshi Terashima
Hokkaido University, Stanford University
Authors
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Hiroshi Terashima
Hokkaido University, Stanford University
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Nguyen Ly
Stanford University
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Matthias Ihme
Stanford University
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Abstract Withdrawn
ORAL Withdrawn
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Efficient computation of unsteady turbulent flows using an implicit solver and an adaptive time-stepping algorithm
ORAL
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Publication: 1. Nived, M. R., Kalkote, N., & Eswaran, V. (2023). Convergence acceleration of turbulent flow simulations using an implicit adaptive time-stepping (ATS) algorithm. In AIAA SCITECH 2023 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2023-2147<br>2. Nived, M. R., Athkuri, S. S. C., & Eswaran, V. (2022). On the application of higher-order Backward Difference (BDF) methods for computing turbulent flows. Computers and Mathematics with Applications, 117, 299–311. https://doi.org/10.1016/j.camwa.2022.05.007
Presenters
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M. R Nived
Indian Institute of Technology, Hyderabad
Authors
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M. R Nived
Indian Institute of Technology, Hyderabad
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Vinayak Eswaran
Indian Institute of Technology Hyderabad
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The Theory of Fast Projection Methods for High-Fidelity Fast Solution of the Navier-Stokes Equations
ORAL
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Publication: Karam, M., & Saad, T. (2022a). High-order pressure estimates for Navier-Stokes Runge-Kutta solvers using stage pseudo-pressures. Journal of Computational Physics, 111602. https://doi.org/10.1016/j.jcp.2022.111602<br>Karam, M., & Saad, T. (2022b). High-order pressure estimates for projection-based Navier-Stokes solvers. Journal of Computational Physics, 452, 110925. https://doi.org/10.1016/j.jcp.2021.110925<br>Karam, M., & Saad, T. (2022c). Improvements to a Fast Projection Method for the Navier-Stokes Equations. AIAA Journal, In Press. https://doi.org/10.2514/1.J061546<br>Karam, M., Sutherland, J. C., & Saad, T. (2021). Low-cost Runge-Kutta integrators for incompressible flow simulations. Journal of Computational Physics, 110518. https://doi.org/10.1016/j.jcp.2021.110518
Presenters
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Tony Saad
University of Utah
Authors
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Tony Saad
University of Utah
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Mokbel Karam
University of Utah
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