The transition toward fossil-free steel production in Sweden, exemplified by the hydrogen-based HYBRIT initiative, introduces new opportunities and challenges in process metallurgy. One promising concept is replacing coal with hydrogen as a fuel in the induration process, which could lead to an excess of oxygen in the system. This surplus oxygen has the potential to improve energy efficiency and productivity during pellet oxidation. To quantify and predict these effects, advanced modeling and simulation are essential. This project focuses on simulating oxidation behavior in a porous packed bed of magnetite pellets under varying oxygen concentrations. The approach combines Computational Fluid Dynamics (CFD) for gas-phase transport with a Lagrangian Particle Tracking (LPT) method, where each particle executes a single-pellet oxidation model. The key research question is: To what extent can oxidation behavior be predicted based on oxygen content and other critical parameters using a particle-resolved approach? Due to the complexity of coupled heat, mass, and chemical reactions in large-scale packed beds, high-performance computing resources are required. The simulations involve millions of particles and transient flow fields, demanding substantial CPU/GPU capacity and memory. Access to NAISS SUPR will enable accurate, scalable modeling, supporting Sweden’s green steel transition and contributing to industrial decarbonization strategies.