Category Simulation & Modeling Projects
Python CFD for Aerospace: Supersonic Flow and Shock Capturing
Reading Time: 10 minutesCovers compressible Navier-Stokes, shock-capturing methods (Roe, WENO), Python solvers (pyBaram, OpenSBLI, JANC), and benchmark cases like Sod shock tube.
GPU-Accelerated Uncertainty Quantification: Scaling Monte Carlo and PCE Methods on GPU
Reading Time: 9 minutesKey Takeaways GPU acceleration delivers 10–1000× speedup for batch Monte Carlo sampling compared to CPU-only approaches. pygpc is currently the only Python UQ library with native GPU (CUDA) support for PCE computation. Numba @cuda.jit outperforms CuPy for compute-heavy MC tasks when data transfer is minimal; CuPy is faster for bulk array math. JAX-based Bayesian UQ […]
Structured Learning Path for Computational Mechanics Students
Reading Time: 9 minutesA step-by-step guide from first Python script to your own FEM solver. Learn the progressive skills, tools, and benchmarks top programs use.
Geophysics Applications with Python: Groundwater Flow and Seismic Modeling
Reading Time: 9 minutesGeophysical phenomena — from groundwater flow to seismic wave propagation — are governed by partial differential equations that describe how physical quantities change across space and time. Post 242 introduced the broader PDE framework for earth systems modeling, covering finite volume methods and the tools available for tackling these equations at scale. This article drills […]
Python Data Versioning and Provenance: dvc, DVC, and Scientific Workflows
Reading Time: 16 minutesPython Data Versioning and Provenance: dvc, DVC, and Scientific Workflows Data versioning in scientific simulation isn’t about tracking code changes — Git already handles that perfectly well. It’s about tracking which specific combination of data file, code commit, and parameter file produced a particular result. That distinction is what separates a fragile experimental workflow from […]
Debugging Numerical Simulations: Diagnosing Divergence and Instability
Reading Time: 11 minutesLearn how to diagnose why your simulation diverges or becomes unstable. Systematic workflow for identifying root causes: CFL violations, mesh pathology, boundary conditions, and solver settings.
In-Situ Visualization vs Post-Processing — A Decision Framework
Reading Time: 11 minutesChoose between in-situ visualization and post-processing with a practical decision framework covering energy savings, debugging use cases, and hybrid workflows.
Modern Scientific Python Tooling in 2026: uv, Ruff, and ty
Reading Time: 11 minutesLearn the modern scientific Python toolchain — uv for package management, Ruff for linting, and ty for type checking. Updated for 2026 with benchmarks and migration guides.
Multi-Fidelity Surrogate Models: Combining Physics and Machine Learning
Reading Time: 14 minutesLearn how multi-fidelity surrogate models combine cheap simulations with ML corrections for high accuracy at lower cost. Covers co-kriging, neural operators, and Python implementation.
Benchmarking Scientific Python Libraries: Performance & Accuracy
Reading Time: 11 minutesComprehensive performance and accuracy benchmarks comparing NumPy, SciPy, JAX, Polars, Pandas, and more across array operations, data processing, linear algebra, and GPU acceleration.