{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/intracranial-hemodynamics-simulations-an","title":"Intracranial hemodynamics simulations: An efficient and accurate immersed boundary scheme","arxiv_id":"2007.13411","date":"2020-07-27","proceeding":null,"authors":["D. S. Lampropoulos","G. C. Bourantas","B. F. Zwick","G. C. Kagadis","A. Wittek","K. Miller","V. C. Loukopoulos"],"abstract":"Computational fluid dynamics (CFD) studies have been increasingly used for blood flow simulations in intracranial aneurysms (ICAs). However, despite the continuous progress of body-fitted CFD solvers, generating a high quality mesh is still the bottleneck of the CFD simulation, and strongly affects the accuracy of the numerical solution. To overcome this challenge, which will allow preforming CFD simulations efficiently for a large number of aneurysm cases we use an Immersed Boundary (IB) method. The proposed scheme relies on Cartesian grids to solve the incompressible Navier-Stokes (N-S) equations, using a finite element solver, and Lagrangian points to discretize the immersed object. All grid generations are conducted through automated algorithms which require no user input. Consequently, we verify the proposed method by comparing our numerical findings (velocity values) with published experimental results. Finally, we test the ability of the scheme to efficiently handle hemodynamic simulations on complex geometries on a sample of four patient-specific intracranial aneurysms.","url_abs":"https://arxiv.org/abs/2007.13411v1","url_pdf":"https://arxiv.org/pdf/2007.13411v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"intracranial-hemodynamics-simulations-an","repo_url":"https://github.com/DmLabrop/Oasis_IMB","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}