libMobility: A Python library for hydrodynamics at the Smoluchowski level.
Saved in:
| Title: | libMobility: A Python library for hydrodynamics at the Smoluchowski level. |
|---|---|
| Authors: | Fish, Ryker, Carter, Adam, Diez-Silva, Pablo, Delgado-Buscalioni, Rafael, Pelaez, Raul P., Sprinkle, Brennan |
| Source: | Journal of Chemical Physics; 1/28/2026, Vol. 164 Issue 4, p1-17, 17p |
| Subject Terms: | HYDRODYNAMICS, BIOPHYSICS, BOUNDARY value problems, PYTHON programming language, COMPUTATIONAL fluid dynamics |
| Abstract: | Effective hydrodynamic modeling is crucial for accurately predicting fluid–particle interactions in diverse fields such as biophysics and materials science. Developing and implementing hydrodynamic algorithms is challenging due to the complexity of fluid dynamics, necessitating efficient management of large-scale computations and sophisticated boundary conditions. Furthermore, adapting these algorithms for use on massively parallel architectures such as GPUs adds an additional layer of complexity. This paper presents the libMobility software library, which offers a suite of CUDA-enabled solvers for simulating hydrodynamic interactions in particulate systems at the Rotne–Prager–Yamakawa level. The library facilitates precise simulations of particle displacements influenced by external forces and torques, including both the deterministic and stochastic components. Notable features of libMobility include its ability to handle linear and angular displacements, thermal fluctuations, and various domain geometries effectively. With an interface in Python, libMobility provides comprehensive tools for researchers in computational fluid dynamics and related fields to simulate particle mobility efficiently. This article details the technical architecture, functionality, and wide-ranging applications of libMobility. libMobility is available at https://github.com/stochasticHydroTools/libMobility. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Chemical Physics is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
Nájsť tento článok vo Web of Science Be the first to leave a comment!