Development of an Openfoam Solver for Numerical Simulation of Carbonization of Biomasses in Rotary Kilns

Carbonization is a key process to increase the energy density of high moisture-containing biomasses and biogenic wastes and to provide multipurpose raw chemicals for further applications. Steam-assisted carbonization is a kind of slow pyrolysis, in which wet biomass is treated continuously in superheated steam at elevated temperature and atmospheric pressure. Rotary kiln reactors due to their flexibility and easy control of operating conditions are well suited for this process. In this work, a numerical simulation tool based on an Eulerian-Langrangian approach has been developed to simulate the carbonization of biomasses in rotary kiln reactors resolved in time and space by combining existing OpenFOAM features and developing new physical models. This study demonstrates the features of this extended and validated Eulerian-Lagrangian approach for simulating dense particulate multiphase flows in large-scale rotary kiln reactors. The focus is to use the new tool to aid the design of large-scale rotary kiln reactors by performing parameter studies. The simulations of this kind of large-scale reactors require large computational resources on supercomputers. Therefore, a further focus lies in different approaches to reduce the computational effort while keeping the accuracy at an acceptable level. By using the MP-PIC model, computing time increases linearly with the number of biomass particles instead of exponentially with the DPM model. The optimal cell size has been found to be about twice the largest particle diameter. By choosing the optimal domain decomposition method, simulation time can be reduced by a factor of 1/10. Introducing a solver frequency parameter to the DOM radiation model can help to reduce simulation times further by a factor of 1/8 while decreasing the accuracy by only 2%. Parallel scaling tests show good performance with over 1000 CPU cores. These results show that simulations with a total of 40,000 CPU-hours per studied case become feasible proving the developed solver to be an efficient tool for the design of rotary kiln reactors

Validation study for Large-Eddy Simulation of Forest Flow

The publication presents Large-Eddy Simulation (LES) of flow over a reduced-scale wind tunnel model of a forest canopy. The final aim of the study is to determine factors responsible for damage in forests by strong winds. The wind tunnel forest was represented by an open-porous foam material for the crown layer and wooden dowels for the trunk layer. The forest model was installed in the open test section of a Goettingen-type wind tunnel and Particle Image Velocimetry (PIV) measurements were made for the acquisition of the flow field data. The numerical simulations were performed with OpenFOAM®. The forest was modelled by an additional sink term in the momentum transport equations based on the leaf area density and a characteristic drag coefficient for the underlying tree specimen. Large-eddy simulations with different subgrid-scale (SGS) turbulence models were carried out and compared to wind tunnel data. The Smagorinsky SGS model outperformed the dynamic Lagrangian SGS model in the windward edge region (within a distance of approximately 2 tree heights from the leading edge) whereas the dynamic Lagrangian SGS model showed a better performance for regions farther downstream

Detailed Transport and Performance Optimization for Massively Parallel Simulations of Turbulent Combustion with OpenFOAM

This work describes the implementation of two key features for enabling high performance computing (HPC) of highly resolved turbulent combustion simulations: detailed molecular transport for chemical species and efficient computation of chemical reaction rates. The transport model is based on an implementation of the thermo-chemical library Cantera [1] and is necessary to resolve the inner structure of flames. The chemical reaction rates are computed from automatically generated chemistry-model classes [2], which contain highly optimized code for a specific reaction mechanism. In combination with Sundials’ [3] ODE solver, this leads to drastic reductions in computing time. The new features are validated and applied to a turbulent flame with inhomogeneous mixing conditions on a grid with 150 million cells. The simulation is performed on Germany’s fastest supercomputer “Hazel Hen” [4] on 28,800 CPU cores, showing very good scalability. The good agreement with experimental data shows that the proposed implementations combined with the capabilities of OpenFOAM are able to accurately and efficiently simulate even challenging flame setups

Parameters influencing the droplet formation in a focusing microfluidic channel

In the present work a detailed numerical study of the parameters influencing the droplet formation in a flow-focusing microfluidic device are made. First, an extensive verification of the simulations with data from the literature is carried out. Influence of parameters like viscosity and inflow velocity are compared with the results from literature showing a good agreement. Some differences are attributed to the different numerical techniques used: in the present work a pure volume-of-fluid method is used, while in the reference study this method is combined with the level-set method. As a second step of the verification of the present model, a comparison with experimental data from the literature was carried out which shows a very good agreement. After the verification was completed, eight new simulations are carried out covering a wide range of velocities of the continuous phase uc. In these simulations the velocity of the discrete phase ud remains unchanged. The variation of the continuous phase velocity reveals that with increasing the value of uc, respectively the value of the capillary number Ca, the droplet length reaches a point of saturation, i.e. a point where the droplet length does not decrease any more. For the present setup this saturation occurs for Ca > 0,03. On the other hand, when the velocity of the continuous phase goes towards very low values (Ca < 0,01 for the present setup), the droplet size increases significantly. Further, it was found that for increasing capillary numbers Ca above a value around 0,015 for water/oil and above 0,025 for water + 40% glycerol / oil systems, a transmission from the dripping towards the jetting regimes of droplet formation occurs. It was shown that when the viscosity of the continuous phase increases, higher total pressure jumps in the droplet occur, also leading to the formation of smaller droplets

Modeling of radiation heat transfer in dense-bed flows of solids in indirectly heated rotary kilns

This work presents further development and validation of the Discrete Ordinates Model for thermal radiation implemented in OpenFOAM® for application to packed beds of particles. The radiation model is an important part of a more comprehensive model for simulating the thermochemical conversion of the discrete phase (here for instance wet biomass particles). The comprehensive Eulerian-Lagrangian model is part of a three-dimensional, time-resolved simulation of the essential chemical and physical processes occurring within and in-between particles in a moving bed. For the thermal treatment of solid particles, convective and radiative heat transfer couple the energy exchange between the reactor wall, gas- and disperse phase. The original implementation of the finite volume Discrete Ordinate Model (fvDOM) present in OpenFOAM® is valid for a dilute particulate phase and neglects the effect of local opacity due to the existence of individual particles. In the present application, a dense-packed bed of the particulate phase exists in the reactor and, therefore, this direction-based radiation model is adjusted for a computational cell with arbitrary particle volume fractions. To validate the results with the present thermal radiation model, a simple test case is first presented, where a bed of particles is heated from the top of the computational domain. A second test case relates to an experimentally investigated laboratory-scale reactor. The results of the improved fvDOM are compared to the original implementation in OpenFOAM® and the more simple and computationally cheap P-1 radiation model. In the presence of a packed bed, the P-1 model largely overpredicts the radiative heat transfer while the original fvDOM underpredicts the heat flux by about 15 % for the first test case. The new improved model delivers results within 1% deviation at the expense of maximum of 10 % increase in the computational time. Large-scale parallel simulations of real setups are crucial tools to predict the efficiency of a process and improve the operational parameters. To achieve the pre-defined product quality at minimum cost, an example of the implemented radiation model in thermochemical conversion of wet biomass in a rotary drum is been given and the importance of the radiation heat transport to the bulk is highlighted

Validation study for Large-Eddy Simulation of Forest Flow

The publication presents Large-Eddy Simulation (LES) of flow over a reduced-scale wind tunnel model of a forest canopy. The final aim of the study is to determine factors responsible for damage in forests by strong winds. The wind tunnel forest was represented by an open-porous foam material for the crown layer and wooden dowels for the trunk layer. The forest model was installed in the open test section of a Goettingen-type wind tunnel and Particle Image Velocimetry (PIV) measurements were made for the acquisition of the flow field data. The numerical simulations were performed with OpenFOAM®. The forest was modelled by an additional sink term in the momentum transport equations based on the leaf area density and a characteristic drag coefficient for the underlying tree specimen. Large-eddy simulations with different subgrid-scale (SGS) turbulence models were carried out and compared to wind tunnel data. The Smagorinsky SGS model outperformed the dynamic Lagrangian SGS model in the windward edge region (within a distance of approximately 2 tree heights from the leading edge) whereas the dynamic Lagrangian SGS model showed a better performance for regions farther downstream