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In this paper, an efficient ghost-cell based immersed boundary method (IBM) is used to perform direct numerical simulation (DNS) of reactive fluid-particle systems. With an exothermic first order reaction proceeding at the exterior particle surface, the solid temperature rises and consequently increases the reaction rate via an Arrhenius temperature dependence. In other words, the heat and mass transport is dependently coupled through the particle thermal energy equation and the Arrhenius equation, and they offer dynamic boundary conditions for the fluid phase thermal energy equation and species equation respectively. The fluid-solid coupling is enforced at the exact position of the particle surface by implicit incorporation of the boundary conditions into the discretized momentum, species and thermal energy conservation equations of the fluid phase. Different fluid-particle systems are studied with increasing complexity: a single sphere, three spheres and a dense array consisting of hundreds of randomly generated particles. In these systems the mutual impacts between heat and mass transport processes are investigated.

In this paper two immersed boundary methods (IBM), specifically a continuous forcing method (CFM) and a discrete forcing method (DFM), are applied to perform direct numerical simulations (DNSs) of heat transfer problems in tubular fluid-particle systems. Both IBM models are built on the well-developed models utilized in momentum transfer studies, and have the capability to handle mixed boundary conditions at the particle surface as encountered in industrial applications with both active and passive particles. Following a thorough verification of both models for the classical Graetz-Nusselt problem, we subsequently apply them to study a much more advanced Graetz-Nusselt problem of more practical importance with a dense stationary array consisting of hundreds of particles randomly positioned inside a tube with adiabatic wall. The influence of particle sizes and fractional amount of passive particles is analyzed at varying Reynolds numbers, and the simulation results are compared between the two IBM models, finding good agreement. Our results thus qualify the two employed IBM modules for more complex applications.

In this study, an efficient ghost cell‐based immersed boundary method is used to perform direct numerical simulations of mass‐transfer processes in bidisperse arrays. Stationary spherical particles, with a size ratio of 1.5, are homogeneously distributed in a periodic domain in the spanwise directions. Simulations are performed over a range of solids volume fractions, volume fraction ratios of small‐to‐large particles, and Reynolds numbers. Through our studies, we find that large particles have a negative influence on the overall mass‐transfer performance; however, the performance of individual particle species is independent on the relative volume fraction ratios. We propose two correlations: (a) a refitted Gunn correlation for a better description of the interfacial transfer performance based on individual particle species; (b) a fractional calculation for a simple estimation of the overall performance in bidisperse systems using characteristics of individual particle species. We also investigate how well the overall mass‐transfer coefficient can be predicted by defining an appropriate equivalent diameter.

In this paper, an efficient ghost-cell based immersed boundary method is applied to perform direct numerical simulation (DNS) of mass transfer problems in particle clusters. To be specific, a nine-sphere cuboid cluster and a random-generated spherical cluster consisting of 100 spheres are studied. In both cases, the cluster is composed of active catalysts and inert particles, and the mutual influence of particles on their mass transfer performance is studied. To simulate active catalysts the Dirichlet boundary condition is imposed at the external surface of spheres, while the zero-flux Neumann boundary condition is applied for inert particles. Through our studies, clustering is found to have negative influence on the mass transfer performance, which can be then improved by dilution with inert particles and higher Reynolds numbers. The distribution of active/inert particles may lead to large variations of the cluster mass transfer performance, and individual particle deep inside the cluster may possess a high Sherwood number.

In this paper, an efficient ghost-cell based immersed boundary method is introduced to perform direct numerical simulation (DNS) of mass transfer problems in particulate flows. The fluid-solid coupling is achieved by implicit incorporation of the boundary conditions into the discretized momentum and species conservation equations of the fluid phase. Taking the advantage of a second order quadratic interpolation scheme utilized in the reconstruction procedures, the unique feature of this ghost-cell based immersed boundary method is its capability to handle mixed boundary conditions at the exact position of the particle surface as encountered in systems with interplay between surface reactions and diffusion. A fixed Eulerian grid is used to solve the conservation equations for the entire computational domain. Following a detailed verification of the method in the limiting case of unsteady molecular diffusion without convection, we apply our method to study fluid-particle mass transfer for flow around a single sphere and a dense stationary array consisting of hundreds of spheres over a range of Damkohler numbers.

In this paper, direct numerical simulation (DNS) is performed to study coupled heat and mass-transfer problems in fluid-particle systems. On the particles, an exothermic surface reaction takes place. The heat and mass transport is coupled through the particle temperature, which offers a dynamic boundary condition for the thermal energy equation of the fluid phase. Following the case of the unsteady mass and heat diffusion in a large pool of static fluid, we consider a stationary spherical particle under forced convection. In both cases, the particle temperatures obtained from DNS show excellent agreement with established solutions. After that, we investigate the three-bead reactor, and finally a dense particle array composed of hundreds of particles distributed in a random fashion is studied. The concentration and temperature profiles are compared with a one-dimensional heterogeneous reactor model, and the heterogeneity inside the array is discussed.