Modelling aerosol evolution under quiescent and turbulent conditions using a coupled fluid–particle dynamics solver incorporating fractal morphology

Accurate prediction of aerosol evolution in enclosed environments is essential for estimating source terms and assessing containment performance in nuclear and industrial facilities. Conventional well-mixed models neglect spatial gradients arising from stratification and turbulence. This study develops and applies an enhanced Coupled Fluid–Particle Dynamics solver, which incorporates turbulence-induced coagulation and morphology-dependent drag corrections for fractal aggregates within an Eulerian–Eulerian framework. The solver, implemented in OpenFOAM, was validated against experiments from the 10 m³ Nuclear Aerosol Test Facility at BARC under quiescent and turbulent conditions.Under quiescent conditions, simulations reproduced the experimentally observed crossover between upper and lower ports at ~1200 s and the subsequent plateau in aerosol mass concentration (~0.20 g m⁻³) up to 10,000 s. Inclusion of fractal morphology (fractal dimension d_f = 1.8) improved agreement with experiments, yielding CMD growth from 0.45 to 1.3 µm and decay times consistent within 10%. Sensitivity studies showed negligible dependence on monomer density (2–4 g cm⁻³), whereas increasing d_f from 1.8 to 2.25 reduced coagulation rates by ~20%. Under turbulent conditions (Re ≈ 2×105, turbulence intensity 5–10%), solver predicted uniform concentrations of 0.06–0.08 g m⁻³ at both ports, matching experiments within 15%.The validated solver accurately captures spatial heterogeneity, morphology effects, and turbulence-enhanced coagulation across laminar and turbulent regimes, offering a robust predictive framework for aerosol behavior in small modular reactor (SMR) containments and similar confined systems.