The traditional Eulerian view of biomass in bioprocess modelling results in issues when modelling large-scale bioreactors in which heterogeneous conditions are common. As the field increasingly moves from “scale-up” to “scale-down” philosophy, in which such heterogeneities are included from the start of process design, accurate modelling of the biomass response to these varying conditions is essential. Euler-Lagrange (EL) simulations provide a means of modelling the microbial lifelines of cells traversing heterogenous conditions of a bioreactor. Lapin et al. were the pioneers of EL simulation in their 2004 paper where a metabolic model of glycolysis is coupled to a Lagrangian biomass phase. This BSc thesis focusses on reproducing their model using modern computational fluid dynamics (CFD) techniques. Specifically, by using a dynamic Lattice Boltzmann Method using Large Eddy Simulation model for CFD as opposed to a frozen-flow Finite Volume Reynolds Averaged Navier- Stokes model. The resulting differences in the overall behaviour of the cell metabolism through the lens of glycolytic oscillations are discussed. In addition, possible pitfalls in model validity such as grid dependence, the effects of heterogeneous particle distributions and the effects of particle numbers were explored. The synchronisation and desynchronisation of glycolytic oscillations as observed in Lapin et al. 2004 were able to be reproduced.