A Computational Study of Explicit CFD Solvers (eBook, ePUB)
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In "Computational Study of Explicit CFD Solvers: With Applications to Inviscid Flow", Rahul Basu-a graduate of the California Institute of Technology-presents a rigorous exploration of explicit numerical methods for computational fluid dynamics. This insightful work demystifies efficient solver algorithms, their stability, and implementation challenges, with focused applications to inviscid flow simulations in aerospace and engineering. Ideal for researchers and practitioners seeking advanced tools for high-speed flow modeling, it bridges theory and computation with clarity and precision. Comp...
In "Computational Study of Explicit CFD Solvers: With Applications to Inviscid Flow", Rahul Basu-a graduate of the California Institute of Technology-presents a rigorous exploration of explicit numerical methods for computational fluid dynamics. This insightful work demystifies efficient solver algorithms, their stability, and implementation challenges, with focused applications to inviscid flow simulations in aerospace and engineering. Ideal for researchers and practitioners seeking advanced tools for high-speed flow modeling, it bridges theory and computation with clarity and precision. Complete python programs and sample outputs are included
CFD solvers approximate fluid dynamics equations (e.g., Navier-Stokes or Euler for inviscid flows) via spatial discretization and temporal integration.
Spatial Discretization:
Explicit methods (as in the book) excel in parallel efficiency for aerospace but need stability tweaks.
CFD solvers approximate fluid dynamics equations (e.g., Navier-Stokes or Euler for inviscid flows) via spatial discretization and temporal integration.
Spatial Discretization:
- Finite Difference (FDM): Taylor-based derivatives on structured grids; simple, efficient for regular shapes but struggles with irregularities.
- Finite Volume (FVM): Conserves fluxes over control volumes; versatile for unstructured grids and shocks, common in industry.
- Finite Element (FEM): Variational basis functions; strong for adaptive meshes and multiphysics.
Explicit methods (as in the book) excel in parallel efficiency for aerospace but need stability tweaks.
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