Nico Jurtz

Direct Numerical Simulations (DNS) are widely employed to simulate thermo-fluid dynamics in packed bed reactors, offering high-fidelity insights into complex flow and heat transfer phenomena. However, recent studies have revealed notable differences in isothermal turbulent flow results across different DNS frameworks, leaving open the question of how conjugate heat transfer is affected. This study presents a comparison between DNS based on a finite volume method (FVM) and a lattice Boltzmann method (LBM) for predicting turbulent heat transfer in a low porosity face-centered cubic (FCC) packed unit. First, the methods are compared with respect to the required resolution and computational cost. Subsequently, global parameters for drag, heat transfer, and spatial as well as temporal variances are evaluated. The flow topology is further analyzed by examining the mean and fluctuating components of hydrodynamic and thermal fields. While good agreement between the methods is shown regarding time-averaged velocity and temperature profiles, more pronounced differences are observed when comparing the respective temporal variances between the two methods. Additionally, the FVM, which relies on a surface-fitted mesh, requires more degrees of freedom to obtain a grid-converged solution but delivers results of higher certainty than the LBM. These findings highlight important methodological considerations when selecting DNS approaches for resolving turbulent heat transfer in complex porous geometries.

The mixing performance and power consumption for four dual‐impeller configurations in a stirred tank are studied using the mean age theory (MAT) approach, the fully transient techniques (FTT), and experiments. A novel method is developed based on the scaled mean age probability distribution curve, allowing the MAT method to be applied to multi‐impeller systems for the first time. The MAT approach provides three‐dimensional tracer distribution within the vessel, which is confirmed by FTT and experiments. Compared to the experimental data, the predicted mixing time from the MAT approach shows a deviation within 20%. This is a good degree of accuracy compared to FTT and correlations. For steady‐state predicted power numbers, a 20% deviation from the experimental data is observed, while the transient approach exhibits a lower deviation at 10%. However, the computational time can be reduced significantly using the steady‐state MAT approach.

The description of the mixing characteristics is of fundamental interest for modeling mass transport in fixed‐bed reactors. A method based on Lagrangian parcel tracking is presented to determine the axial dispersion coefficient in the mechanical dispersion regime from particle‐resolved computational fluid dynamics (CFD) results. The impact of fluid dynamic entry effects and the necessary averaging length on the axial dispersion coefficient is studied, showing that the often reported dependency on the entry length is almost not existent, but a result of insufficient averaging, caused by to short bed heights. The axial dispersion coefficients are determined for different particle shapes and a novel reactor wall concept. A strong correlation is found between the relative variance of the axial velocity and the axial dispersion coefficient.

Process intensification of catalytic fixed-bed reactors is of vital interest and can be conducted on different length scales, ranging from the molecular scale to the pellet scale to the plant scale. Particle-resolved computational fluid dynamics (CFD) is used to characterize different reactor designs regarding optimized heat transport characteristics on the pellet scale. Packings of cylinders, Raschig rings, four-hole cylinders, and spheres were investigated regarding their impact on bed morphology, fluid dynamics, and heat transport, whereby for the latter particle shape, the influence of macroscopic wall structures on the radial heat transport was also studied. Key performance indicators such as the global heat transfer coefficient and the specific pressure drop were evaluated to compare the thermal performance of the different designs. For plant-scale intensification, effective transport parameters that are needed for simplified pseudo-homogeneous two-dimensional plug flow models were determined from the CFD results, and the accuracy of the simplified modeling approach was judged.

Fixed bed reactors are widely used in the chemical, nuclear and process industry. Due to the solid particle arrangement and its resulting non-homogeneous radial void fraction distribution, the heat transfer of this reactor type is inhibited, especially for fixed bed reactors with a small tube to particle diameter ratio. This work shows that, based on three-dimensional particle-resolved discrete element method (DEM) computational fluid dynamics (CFD) simulations, it is possible to reduce the maldistribution of mono-dispersed spherical particles near the reactor wall by the use of macroscopic wall structures. As a result, the lateral convection is significantly increased leading to a better radial heat transfer. This is investigated for different macroscopic wall structures, different air flow rates (Reynolds number Re = 16 ...16,000) and a variation of tube to particle diameter ratios (2.8, 4.8, 6.8, 8.8). An increase of the radial velocity of up to 40%, a reduction of the thermal entry length of 66% and an overall heat transfer increase of up to 120% are found.

The accuracy of coarse‐grained discrete element method (CGDEM) relies on appropriate scaling rules for contact and fluid‐particle interaction forces. For fluidized bed applications, different scaling rules are used and compared with DEM results. The results indicated that in terms of averaged values as mean particle position and voidage profile, the coupling of computational fluid dynamics and CGDEM leads to accurate results for low scaling factors. Regarding the particle dynamics, the approach leads to an underestimation of RMS values of particle position indicating a loss of particle dynamics in the system due to coarse graining. The impact of cell cluster size on drag force calculation is studied. The use of energy minimization multiscale drag correction is investigated, and a reduced mesh dependency and good accuracy are observed.