Why Geometry Is Challenging in CAE: A Practical Guide
A practical overview of why geometric complexity creates bottlenecks in CAE workflows, and how mesh‑driven strategies can mitigate them.
A structured collection of articles and guides covering refinement, metric tensors, geometry processing, and the foundations of TheMeshProject ecosystem.
Designed for engineers, researchers, and developers who care about mesh quality, numerical robustness, and clear architecture.
A practical overview of why geometric complexity creates bottlenecks in CAE workflows, and how mesh‑driven strategies can mitigate them.
An intuitive introduction to curvature and its role in mesh quality, refinement, segmentation, and feature detection.
A survey of essential mesh quality metrics, their mathematical foundations, and how they influence solver stability and accuracy.
A conceptual guide to ridge/valley extraction and feature line detection, with applications in segmentation and visualization.
A structured overview of segmentation strategies for complex surfaces, focusing on geometric cues and mesh‑driven partitioning.
A theory‑first introduction to curvature on smooth surfaces and how these concepts translate to discrete triangle meshes.
A practical follow‑up to the theoretical article, covering discrete curvature operators, estimation techniques, and implementation considerations.
A comprehensive analysis of refinement approaches, trade‑offs, and engineering‑grade strategies for producing high‑quality meshes.
A deep dive into metric tensor construction, anisotropic refinement, and how metric‑driven adaptation improves mesh quality.
Setting up the platform layer and OpenGL context using btm‑framework.
Designing adjacency, connectivity, and attribute storage for efficient processing.
Implementing principal curvature estimation and visualization.
Geometric Quantities, Discrete Operators, and Their Role in Simulation Workflows.
Ridge/valley detection and feature line extraction for visualization and segmentation.
Using curvature fields, principal directions, and feature intensity to drive robust surface segmentation.
Quadric error metrics and topology‑aware simplification.