Best Multiphysics Simulation Software for Linux of 2025

FEATool Multiphysics – "Physics Simulator Made Easy" – a fully integrated physics simulation, FEA and CFD toolbox. FEATool Multiphysics provides a fully integrated simulation platform that includes a unified user interface for several multi-physics solvers such as OpenFOAM and Computational fluid dynamics (CFD), including SU2 Code and FEniCS. This allows users to model coupled physics phenomena, such as those found in fluid flow and heat transfer, structural, electromagnetics acoustics and chemical engineering applications. FEATool multiphysics is a trusted tool for engineers and researchers in the energy, automotive and semi-conductor industries.

Utilize COMSOL's multiphysics software to replicate real-world designs, devices, and processes effectively. This versatile simulation tool is grounded in sophisticated numerical techniques. It boasts comprehensive capabilities for both fully coupled multiphysics and single-physics modeling. Users can navigate a complete modeling workflow, starting from geometry creation all the way to postprocessing. The software provides intuitive tools for the development and deployment of simulation applications. COMSOL Multiphysics® ensures a consistent user interface and experience across various engineering applications and physical phenomena. Additionally, specialized functionality is available through add-on modules that cater to fields such as electromagnetics, structural mechanics, acoustics, fluid dynamics, thermal transfer, and chemical engineering. Users can select from a range of LiveLink™ products to seamlessly connect with CAD systems and other third-party software. Furthermore, applications can be deployed using COMSOL Compiler™ and COMSOL Server™, enabling the creation of physics-driven models and simulation applications within this robust software ecosystem. With such extensive capabilities, it empowers engineers to innovate and enhance their projects effectively.

Energy2D is an interactive multiphysics simulation program grounded in computational physics, designed to model the three primary modes of heat transfer: conduction, convection, and radiation, while also integrating particle dynamics. This software operates efficiently on a wide range of computers, simplifying the process by removing the need for switches between preprocessors, solvers, and postprocessors that are usually necessary for computational fluid dynamics simulations. Users can create "computational experiments" to explore scientific hypotheses or address engineering challenges without the need for intricate mathematical formulations. Additionally, development is ongoing to introduce various energy transformation types and to enhance support for different fluid types. While Energy2D excels in accurately modeling conduction, its representations of convection and radiation are not entirely precise, which means results involving these elements should be regarded as qualitative. Over 40 scientific papers have utilized Energy2D as a valuable research instrument, showcasing its adoption in the academic community. As the program evolves, its capabilities are expected to expand further, potentially offering more comprehensive insights into complex physical interactions.

NVIDIA Modulus is an advanced neural network framework that integrates the principles of physics, represented through governing partial differential equations (PDEs), with data to create accurate, parameterized surrogate models that operate with near-instantaneous latency. This framework is ideal for those venturing into AI-enhanced physics challenges or for those crafting digital twin models to navigate intricate non-linear, multi-physics systems, offering robust support throughout the process. It provides essential components for constructing physics-based machine learning surrogate models that effectively merge physics principles with data insights. Its versatility ensures applicability across various fields, including engineering simulations and life sciences, while accommodating both forward simulations and inverse/data assimilation tasks. Furthermore, NVIDIA Modulus enables parameterized representations of systems that can tackle multiple scenarios in real time, allowing users to train offline once and subsequently perform real-time inference repeatedly. As such, it empowers researchers and engineers to explore innovative solutions across a spectrum of complex problems with unprecedented efficiency.