An Induce-on-Boundary Magnetostatic Solver for Grid-Based Ferrofluids

Author:

Ni Xingyu1ORCID,Wang Ruicheng2ORCID,Wang Bin3ORCID,Chen Baoquan4ORCID

Affiliation:

1. School of CS & State Key Lab of General AI, Peking University, Beijing, China

2. Peking University, Beijing, China

3. Beijing Institute for General Artificial Intelligence, Beijing, China

4. School of IST & State Key Lab of General AI, Peking University, Beijing, China

Abstract

This paper introduces a novel Induce-on-Boundary (IoB) solver designed to address the magnetostatic governing equations of ferrofluids. The IoB solver is based on a single-layer potential and utilizes only the surface point cloud of the object, offering a lightweight, fast, and accurate solution for calculating magnetic fields. Compared to existing methods, it eliminates the need for complex linear system solvers and maintains minimal computational complexities. Moreover, it can be seamlessly integrated into conventional fluid simulators without compromising boundary conditions. Through extensive theoretical analysis and experiments, we validate both the convergence and scalability of the IoB solver, achieving state-of-the-art performance. Additionally, a straightforward coupling approach is proposed and executed to showcase the solver's effectiveness when integrated into a grid-based fluid simulation pipeline, allowing for realistic simulations of representative ferrofluid instabilities.

Publisher

Association for Computing Machinery (ACM)

Reference96 articles.

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4. Liquid surface tracking with error compensation

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