0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Sign in to save

Flow analysis and thermochemical insight during supercritical water gasification of polypropylene particles

Nature Water 2025
Abouelmagd Abdelsamie, Dominique Thévenin

Summary

Researchers used particle-resolved direct numerical simulations to model polypropylene gasification in supercritical water, finding that 3D simulations more accurately capture boundary layer dynamics and multi-particle wake interactions than 2D models, and that higher particle Reynolds numbers accelerate convective transport but reduce heat release and surface reaction rates relevant to plastic waste conversion.

Polymers

This study presents a comprehensive numerical investigation of polypropylene particle gasification in supercritical water using particle-resolved direct numerical simulations in both two-dimensional (2D) and three-dimensional (3D) configurations involving a single particle or three particles in interaction. The results are analyzed systematically to assess the effects of dimensionality, particle position, and particle Reynolds number (Rep = 50–125) on flow dynamics, interfacial heat and mass transfer, and species distribution. 3D simulations reveal higher drag coefficients, Nusselt numbers, and Sherwood numbers than 2D simulations, primarily due to thinner boundary layers and weaker Stefan flow. While 2D simulations capture general trends, 3D modeling is essential to resolve boundary layer development and wake interactions accurately. In multi-particle arrangements, downstream particles experience significant shielding in 2D, whereas 3D wake structures mitigate these effects. Species H2 shows complex, nonlinear behavior due to high diffusivity and strong coupling with local flow, unlike the approximately linear temperature trends of CO2, CO, and CH4. Higher particle Reynolds numbers enhance convective transport but reduce residence time, heat release, and surface reactions, slowing particle shrinking rates. These findings provide key insight into supercritical water gasification and support the development of predictive models and scalable reactor designs for plastic waste conversion.

Share this paper