CFD: Algorithms I

Presentations

• A coupled space-time framework aided by physics-informed neural networks to accelerate fluid flow simulations

  ORAL

  Nov. 25, 2024, 3:50 PM – Nov. 25, 2024, 4:03 PM

  Publication: None

  Presenters

  • ABHISHEK BARMAN

    Iowa State

  Authors

  • ABHISHEK BARMAN

    Iowa State

  • Biswajit Khara

    Iowa State University

  • Baskar Ganapathysubramanian

    Iowa State University

  • Anupam Sharma

    Iowa State University

  View abstract →

• Accelerated Neural Network Solvers of Navier Stokes Equations for Turbulent Flows

  ORAL

  Nov. 25, 2024, 4:03 PM – Nov. 25, 2024, 4:16 PM

  Publication: K.Bhaganagar and D.Chambers, Accelerated Elliptical PDE Solver for Computational Fluid Dynamics based on Configurable U-Net Architecture : Analogy to V-Cycle Multigrid, Machine Intelligence Research (Accepted, 2024)

  Presenters

  • Kiran Bhaganagar

    University of Texas at San Antonio

  Authors

  • Kiran Bhaganagar

    University of Texas at San Antonio

  • David Chambers

    Southwest Research Institute

  View abstract →

• Sharp, stable, and collocated numerical simulation of incompressible, multi-phase fluid flows

  ORAL

  Nov. 25, 2024, 4:16 PM – Nov. 25, 2024, 4:29 PM

  Presenters

  • Adam L Binswanger

    University of California, Merced

  Authors

  • Adam L Binswanger

    University of California, Merced

  • Matthew Blomquist

    University of California, Merced

  • Scott West

    University of California, Merced

  • Shilpa Khatri

    University of California, Merced

  • maxime theillard

    University of California Merced

  View abstract →

• Numerical stability and convergence of iterative low-Mach variable density time-integration schemes

  ORAL

  Nov. 25, 2024, 4:29 PM – Nov. 25, 2024, 4:42 PM

  Presenters

  • Guillaume Blanquart

    Caltech

  Authors

  • Aaron Nelson

    Caltech

  • Guillaume Blanquart

    Caltech

  View abstract →

• A Novel Add-On Tool for Calculating Hydrodynamic Force on Immersed Object Independent of Local Wall Orientation

  ORAL

  Nov. 25, 2024, 4:42 PM – Nov. 25, 2024, 4:55 PM

  Presenters

  • Matthew Blubaugh

    IUPUI

  Authors

  • Huidan (Whitney) Yu

    Purdue University

  • Matthew Blubaugh

    IUPUI

  • Duan Zhong Zhang

    Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)

  • Min Wang

    Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)

  View abstract →

• Robust Gradient-Based Solver for Invariant Solutions to the Navier-Stokes Equations using Resolvent Analysis

  ORAL

  Nov. 25, 2024, 4:55 PM – Nov. 25, 2024, 5:08 PM

  Publication: Two planned papers derived from this work:
  1. "Robust Gradient-Based Solver for Invariant Solutions to the Navier-Stokes Equations, using Resolvent Analysis"
  2. "Resolvent-Based Optimisation for Approximating the Statistics of Chaotic Dynamics"

  Presenters

  • Thomas Burton

    University of Southampton

  Authors

  • Thomas Burton

    University of Southampton

  • Davide Lasagna

    University of Southampton

  • Sean P Symon

    University of Southampton

  View abstract →

• Fast Projection Methods for Variable Density and low-Mach Reacting Flows.

  ORAL

  Nov. 25, 2024, 5:08 PM – Nov. 25, 2024, 5:21 PM

  Presenters

  • Maher Eid

    University of Utah

  Authors

  • Maher Eid

    University of Utah

  • Tony Saad

    University of Utah

  View abstract →

• Semi-Lagrangian Pressure Solver for Accurate, Consistent, and Conservative Volume-of-Fluid Simulations

  ORAL

  Nov. 25, 2024, 5:21 PM – Nov. 25, 2024, 5:34 PM

  Presenters

  • Julian Lewis Fox

    Montana State University

  Authors

  • Julian Lewis Fox

    Montana State University

  • Mark F Owkes

    Montana State University

  View abstract →

• Towards an adaptive mesh refinement approach for stability and resolvent Analysis of external flows around complex geometries

  ORAL

  Nov. 25, 2024, 5:34 PM – Nov. 25, 2024, 5:47 PM

  Presenters

  • Wei Hou

    Caltech

  Authors

  • Wei Hou

    Caltech

  • Tim Colonius

    Caltech

  View abstract →