MatForge — Open Knowledge Hub for Scientific Simulation and Modeling

Reading Time: 7 minutesKey Takeaways FEM, or the Finite Element Method, is strong for complex shapes and structural problems where geometric flexibility matters. FVM, or the Finite Volume Method, is a natural choice for fluid dynamics and transport problems because it supports local conservation of mass, energy, and momentum. FDM, or the Finite Difference Method, is the simplest […]

Reading Time: 9 minutesTL;DR Before running any scientific simulation, verify that the mesh passes geometric quality checks and then prove that the results do not change significantly with further refinement. A mesh convergence study using at least three grid levels can quantify discretization error through Richardson extrapolation and the Grid Convergence Index. This guide explains the key metrics, […]

Reading Time: 8 minutesKey Takeaways Python code can run on a laptop and a large HPC system with the same core logic when the workflow uses mpi4py or Dask correctly. Environment reproducibility is often the hardest part of HPC work. Conda environments, lockfiles, and job scripts help solve it. The workflow has three stages: prototype locally, parallelize with […]

Reading Time: 7 minutesLearn how to document research software with practical templates, the Diátaxis framework, and proven strategies from the Software Sustainability Institute and PLOS guidelines.

Reading Time: 8 minutesChoosing between Python PDE solvers can feel like choosing between three different languages. The same problem, solving partial differential equations numerically, is handled in very different ways depending on the library you choose. This guide compares FiPy, py-pde, and FEniCS across the criteria that matter for research: numerical method, geometry support, learning curve, ecosystem, performance, […]

Reading Time: 8 minutesMonte Carlo methods use random sampling to estimate outcomes for problems that are too complex for analytical solutions. By running thousands or millions of simulated trials with randomized inputs, you can map the range of possible behavior in a scientific model. These methods are useful for uncertainty bounds, sensitivity analysis, materials modeling, probabilistic simulation, and […]

Reading Time: 5 minutesKey Takeaways Explicit methods calculate the next state directly from the current state. They are cheap per step but require small time steps for stability. Implicit methods solve a coupled system that includes both current and future states. They are more expensive per step but can be stable for much larger time steps. Stiff equations […]

Reading Time: 8 minutesYou need to know two different things about a simulation: whether the code solves the equations correctly, and whether the model is accurate enough for the real-world problem. The first question is verification. The second question is validation. But that is not enough. You also need to understand how much you can trust the numbers […]

Reading Time: 8 minutesWhen you work with multi-physics simulations, you often need to couple two or more specialized solvers so they exchange data during computation. preCICE is a mature open-source coupling library for partitioned multi-physics simulations, especially when connecting independent solvers such as FiPy, OpenFOAM, or CalculiX. But preCICE is not always an option. You may work in […]

Reading Time: 8 minutesKey Takeaways Periodic boundaries in FiPy are most cleanly implemented with PeriodicGrid objects or Gmsh periodic mesh commands rather than manual face coupling. Symmetric boundaries are zero-flux Neumann conditions applied to symmetry planes. They are not a separate FiPy category, but a physical use of standard boundary condition patterns. Robin boundaries combine value and flux […]