TauTORT3D: A Geometry-Based Particle Tracing Framework for Tortuosity in 3D Porous Geometries

Tortuosity is a key parameter governing transport behavior in complex porous media and plays a critical role in engineering, biological, and environmental applications. In this study, we present TauTORT3D, a geometry-based particle tracing framework implemented in MATLAB for estimating geometric tortuosity and mass transport in three-dimensional porous geometries imported from STL surface meshes. The method is user-friendly, computationally efficient, and capable of identifying connected transport paths through complex pore networks. TauTORT3D employs a voxel-based particle tracking approach in which finite-size spherical particles are propagated through interconnected pore spaces along prescribed directions. Particle motion is governed by continuous geometric fields derived from signed distance functions, enabling robust collision handling and geometrically consistent trajectories without reliance on pore-network abstraction, skeletonization, or continuum flow solvers. Particle trajectories are recorded until exit is reached, from which tortuosity distributions, exit time statistics, and time-dependent mass flux are computed. Parametric studies show that increasing particle number improves statistical sampling without altering the underlying transport behavior, indicating that tortuosity distributions are intrinsic, architecture-driven features. A benchmark study is performed using literature-inspired porous geometries to assess the consistency of the proposed framework, and the results are compared with diffusion-based pore-network simulations implemented in Dragonfly, showing consistent median trends within approximately 3–8%, reflecting differences between geometric and diffusion-based definitions of tortuosity. The framework is applicable to a broad class of porous media and micro-architected structures, including triply periodic minimal surface lattices and cellular foams.