Can Partial Multigrid Solutions Enhance Efficiency in CFD Simulations?

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SUMMARY

This discussion focuses on enhancing the efficiency of Computational Fluid Dynamics (CFD) simulations by exploring partial multigrid solutions for solving the Navier-Stokes equations. The traditional approach involves solving a sparse linear system using either Preconditioned Conjugate Gradient (PCG) or Multigrid methods, but this can be resource-intensive. The proposal suggests selectively solving the Poisson equation in areas of high velocity or vorticity, potentially reusing previous results to optimize computation. This method aims to balance the need for speed with accuracy, allowing for more frequent updates of pressure gradients without fully solving the system at each time step.

PREREQUISITES
  • Understanding of Navier-Stokes equations in fluid dynamics
  • Familiarity with Preconditioned Conjugate Gradient (PCG) and Multigrid methods
  • Knowledge of Courant-Friedrichs-Lewy (CFL) condition in numerical simulations
  • Basic concepts of sparse linear systems and pressure gradient calculations
NEXT STEPS
  • Research advanced techniques in Multigrid methods for CFD applications
  • Explore optimization strategies in frameless rendering for computational efficiency
  • Study the implementation of selective pressure solving in CFD simulations
  • Investigate the impact of time step adjustments on simulation accuracy and performance
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CFD engineers, simulation developers, and researchers looking to improve computational efficiency in fluid dynamics simulations.

curiousOne
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Hey everyone,
When solving Navier Stokes equations for simulation, one usually has to make the velocity field divergence free and solve a sparse linear system of equations. The Poisson equation that results is usually solved using either a Pre conditioned CG method or a Multigrid method.
Because the resulting pressure gradient is essential to the quality of the next simulation step (which is itself limited by Courant Friedriech Levy) is there any way that the system could be solved only partially ?
Normally, the problem is solved by taking a full step forward ( < CFL) and solving the pressure then repeating the iteration, using the pressure to advect the velocity.
The need for speed is at odds against limited computing resources, so the time step is chosen closer to the CFL and the Poisson system is solved once for each step. This way the error is limited and the simulation remains accurate.
The result however is a sparse set of pressure gradients at each step. Could someone solve for the pressure only in some areas of high velocity, or vorticity, re-using previous results to complete the system before solving ?
Could the system be solved inaccurately (say half the multigrid steps) at the half step mark, providing twices as many frames of semi-accurate pressure gradients ?
I'm borrowing these ideas from the emerging world of frameless rendering, where optimizations have been made to identify areas that need re-calculation and those than can be re-used.
J.D.
 
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Is anyone familiar with Multigrid or Conjugate Gradient methods ?
 

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