An image-incorporated immersed boundary method for diffusion equations
Andrew C. Chiang (1), Po-Nan Li (2, 3), Soichi Wakatsuki (1, 3), ((1) Department of Structural Biology, Stanford University, Stanford, USA,, (2) Department of Electrical Engineering, Stanford University, Stanford, USA,, (3) SLAC National Accelerator Laboratory, Menlo Park, USA)

TL;DR
This paper introduces a new immersed boundary method called ECMLS for diffusion equations, optimizing parameters against an analytical model, and demonstrating improved accuracy and stability over existing methods.
Contribution
The paper presents the ECMLS algorithm, a novel ghost-cell based immersed boundary method with optimized parameters for diffusion problems, outperforming previous approaches.
Findings
ECMLS yields lower boundary errors and better stability.
Optimal internal node radius scales with boundary curvature logarithm.
Quartic basis functions outperform simpler basis functions.
Abstract
A novel sharp interface ghost-cell based immersed boundary method has been proposed and its parameters have been optimized against an analytical model in diffusion applications. The proposed embedded constrained moving least-squares (ECMLS) algorithm minimizes the error of the interpolated concentration at the image point of the ghost point by applying a moving least-squares method on all internal nodes, near the ghost image point, and the associated mirrored image points of these internal nodes through the corresponding boundary conditions. Using an analytical model as a reference, the ECMLS algorithm is compared to the constrained moving least-squares (CMLS) algorithm and the staircase model using various grid sizes, interpolation basis functions, weight functions, and the penalty parameter of the constraint. It is found that using ECMLS algorithm in the investigated diffusion…
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Taxonomy
TopicsLattice Boltzmann Simulation Studies · Aerosol Filtration and Electrostatic Precipitation · Heat and Mass Transfer in Porous Media
