Enclosed spaces with little to no ventilation present significant chemical exposure risks in many occupational environments. This study develops and verifies an open-source computational fluid dynamics (CFD)-based diffusion model to predict vapor-phase transient concentrations as a function of time and geometry-specific context. Our contribution is to make foundational diffusion-based exposure models accurate, reliable, and broadly accessible to nonspecialists. A combined mesh and time-step refinement study was performed to evaluate the convergence of observables (i.e., concentrations and time) for diffusion-based simulations. Simulations tracked vapor front progression of benzene, a carcinogen, and our selected model compound using its OSHA Short-Term Exposure Limit (STEL) of 5 ppm in the headspace of a truck tank. We compare our model with results from the analytical semi-infinite medium solution. The diffusion model aligned closely with the analytical solution at early times but diverged later due to transverse diffusion resulting from the space-specific geometry. Additionally, we report analyses that quantified deviations as well as posture-dependent exposure timelines. Sensitivity analyses of varying temperatures and liquid pool heights were also performed. These findings underscore the importance of transient, geometry-conscious modeling for risk assessment, complementing and informing physical sampling needs, and ventilation strategies. By relying on open-source software like OpenFOAM and shareable code, this work expands the CFD-based exposure modeling beyond specialized commercial environments, moving toward a more practical use in public and noncontrolled situations.
Godavarti et al. (Wed,) studied this question.