Three-dimensional CFD-DEM simulation of raceway transport phenomena in a blast furnace

in Fuel (2023), 334(2),

Improving energy efficiency in a blast furnace (BF) has a significant effect on energy consumption and pollutant emission in a steel plant. In the BF, the blast injection creates a cavity, the so-called ... [more ▼]

Improving energy efficiency in a blast furnace (BF) has a significant effect on energy consumption and pollutant emission in a steel plant. In the BF, the blast injection creates a cavity, the so-called raceway, near the inlet. On the periphery of the raceway, a ring-type zone is formed which is associated with the highest coke combustion rate and temperatures in the raceway. Therefore, predicting the raceway size or in other words, the periphery of the ring-type zone with accuracy is important for estimating the BF’s energy and coke consumption. In the present study, Computational Fluid Dynamics (CFD) is coupled to Discrete Element Method (DEM) to develop a three-dimensional (3D) model featuring a gas–solid reacting flow, to study the transport phenomena inside the raceway. The model is compared to a previously developed two-dimensional (2D) model and it is shown that the assumptions associated with a 2D model, result in an overestimation of the size of the raceway. The 3D model is then used to investigate the coke particles’ combustion and heat generation and distribution in the raceway. It is shown that a higher blast flow rate is associated with a higher reaction rate and a larger raceway. A 10% increase in the inlet velocity (from 200 m/s to 220 m/s) caused the raceway volume to grow by almost 40%. The DEM model considers a radial discretization over the particle, therefore the heat and mass distributions over the particle are analyzed as well. [less ▲]

Local Verlet buffer approach for broad-phase interaction detection in Discrete Element Method

E-print/Working paper (2022)

The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as Discrete Element Method (DEM) by additional properties ... [more ▼]

The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as Discrete Element Method (DEM) by additional properties such as the thermodynamic state, stress/strain for each particle. Such DEM simulations used by industries to set up their experimental processes are complexes and heavy in computation time. At each time step, those simulations generate a list of interacting particles and this phase is one of the most computationally expensive parts of a DEM simulation. The Verlet buffer method, initially introduced in Molecular Dynamic (MD) (and also used in DEM), allows keeping the interaction list for many time steps by extending each particle neighbourhood by a certain extension range, and thus broadening the interaction list. The method relies on the temporal coherency of DEM, which guarantees that no particles move erratically from one time step to the next. In the classical approach, all the particles have their neighbourhood extended by the same value which leads to suboptimal performances in simulations where different flow regimes coexist. Additionally, and unlike in MD, there is no comprehensive study analysing the different parameters that affect the performance of the Verlet buffer method in DEM. In this work, we propose a new method for the dynamic update of the neighbour list that depends on the particles individual displacement and define a particle-specific extension range based on the local flow regime. The interaction list is analysed throughout the simulation based on the particle's displacement allowing a flexible update according to the flow regime conditions. We evaluate the influence of the Verlet extension range on the execution time through different test cases and analyse empirically the extension range value giving the best performance. [less ▲]

Analysis of Coke Particle Gasification in the Raceway of a Blast Furnace

in IFAC-PapersOnLine (2022), 55(20), 277-282

Parallel Multi-Physics Simulation of Biomass Furnace and Cloud-based Workflow for SMEs

in Practice and Experience in Advanced Research Computing (PEARC '22) (2022, July)

Biomass combustion is a well-established process to produce energy that offers a credible alternative to reduce the consumption of fossil fuel. To optimize the process of biomass combustion, numerical ... [more ▼]

Biomass combustion is a well-established process to produce energy that offers a credible alternative to reduce the consumption of fossil fuel. To optimize the process of biomass combustion, numerical simulation is a less expensive and time-effective approach than the experimental method. However, biomass combustion involves intricate physical phenomena that must be modeled (and validated) carefully, in the fuel bed and in the surrounding gas. With this level of complexity, these simulations require the use of High-Performance Computing (HPC) platforms and expertise, which are usually not affordable for manufacturing SMEs. In this work, we developed a parallel simulation tool for the simulation of biomass furnaces that relies on a parallel coupling between Computation Fluid Dynamics (CFD) and Discrete Element Method (DEM). This approach is computation-intensive but provides accurate and detailed results for biomass combustion with a moving fuel bed. Our implementation combines FOAM-extend (for the gas phase) parallelized with MPI, and XDEM (for the solid particles) parallelized with OpenMP, to take advantage of HPC hardware. We also carry out a thorough performance evaluation of our implementation using an industrial biomass furnace setup. Additionally, we present a fully automated workflow that handles all steps from the user input to the analysis of the results. Hundreds of parameters can be modified, including the furnace geometry and fuel settings. The workflow prepares the simulation input, delegates the computing-intensive simulation to an HPC platform, and collects the results. Our solution is integrated into the Digital Marketplace of the CloudiFacturing EU project and is directly available to SMEs via a Cloud portal. As a result, we provide a cutting-edge simulation of a biomass furnace running on HPC. With this tool, we demonstrate how HPC can benefit engineering and manufacturing SMEs, and empower them to compute and solve problems that cannot be tackled without. [less ▲]

HEAT AND MASS TRANSFER BETWEEN XDEM & OPENFOAM USING PRECICE COUPLING LIBRARY

Scientific Conference (2022, June 09)

This work demonstrates the rapid development of a simulation environment to achieve Heat and Mass Transfer (HMT) between Discrete Element Methods (DEM) and Computa- tional Fluid Dynamics (CFD). The HMT ... [more ▼]

This work demonstrates the rapid development of a simulation environment to achieve Heat and Mass Transfer (HMT) between Discrete Element Methods (DEM) and Computa- tional Fluid Dynamics (CFD). The HMT coupling can be employed to simulate processes such as drying, pyrolysis, combustion, melting, solid-fluid reactions etc and have indus- trial applications such as biomass furnaces, boilers, heat exchangers, and flow through packed beds. This shows that diverse CFD features and solvers need to be coupled with DEM in order to achieve various applications mentioned above. The proposed DEM-CFD Eulerian-Lagrangian coupling for heat and mass transfer is achieved by employing the preCICE coupling library[1] on volumetric meshes. In our prototype, we use the eXtended Discrete Element Method (XDEM)[2] for handling DEM calculations and OpenFOAM for the CFD. The XDEM solver receives various CFD data fields such as fluid properties, and flow conditions exchanged through preCICE, which are used to set boundary conditions for particles. Various heat transfer and mass transfer laws have been implemented in XDEM to steer HMT source term computations. The heat and mass source terms computed by XDEM are transferred to CFD solver and added as source. These source terms represent particles in CFD. The generic coupling interface of preCICE, XDEM and its adapter allows to tackle a di- verse range of applications. We demonstrate the heat, mass & momentum coupling capa- bilities through various test cases and then compared with our legacy XDEM-OpenFOAM coupling and experimental results. [less ▲]

RESIF 3.0: Toward a Flexible & Automated Management of User Software Environment on HPC facility

in ACM Practice and Experience in Advanced Research Computing (PEARC'21) (2021, July)

High Performance Computing (HPC) is increasingly identified as a strategic asset and enabler to accelerate the research and the business performed in all areas requiring intensive computing and large ... [more ▼]

High Performance Computing (HPC) is increasingly identified as a strategic asset and enabler to accelerate the research and the business performed in all areas requiring intensive computing and large-scale Big Data analytic capabilities. The efficient exploitation of heterogeneous computing resources featuring different processor architectures and generations, coupled with the eventual presence of GPU accelerators, remains a challenge. The University of Luxembourg operates since 2007 a large academic HPC facility which remains one of the reference implementation within the country and offers a cutting-edge research infrastructure to Luxembourg public research. The HPC support team invests a significant amount of time (i.e., several months of effort per year) in providing a software environment optimised for hundreds of users, but the complexity of HPC software was quickly outpacing the capabilities of classical software management tools. Since 2014, our scientific software stack is generated and deployed in an automated and consistent way through the RESIF framework, a wrapper on top of Easybuild and Lmod [5] meant to efficiently handle user software generation. A large code refactoring was performed in 2017 to better handle different software sets and roles across multiple clusters, all piloted through a dedicated control repository. With the advent in 2020 of a new supercomputer featuring a different CPU architecture, and to mitigate the identified limitations of the existing framework, we report in this state-of-practice article RESIF 3.0, the latest iteration of our scientific software management suit now relying on streamline Easybuild. It permitted to reduce by around 90% the number of custom configurations previously enforced by specific Slurm and MPI settings, while sustaining optimised builds coexisting for different dimensions of CPU and GPU architectures. The workflow for contributing back to the Easybuild community was also automated and a current work in progress aims at drastically decrease the building time of a complete software set generation. Overall, most design choices for our wrapper have been motivated by several years of experience in addressing in a flexible and convenient way the heterogeneous needs inherent to an academic environment aiming for research excellence. As the code base is available publicly, and as we wish to transparently report also the pitfalls and difficulties met, this tool may thus help other HPC centres to consolidate their own software management stack. [less ▲]

OpenMP optimisation of the eXtended Discrete Element Method (XDEM)

Report (2021)

The eXtended Discrete Element Method (XDEM) is an extension of the regular Discrete Element Method (DEM) which is a software for simulating the dynamics of granular material. XDEM extends the regular DEM ... [more ▼]

The eXtended Discrete Element Method (XDEM) is an extension of the regular Discrete Element Method (DEM) which is a software for simulating the dynamics of granular material. XDEM extends the regular DEM method by adding features where both micro and macroscopic observables can be computed simultaneously by coupling different time and length scales. In this sense XDEM belongs the category of multi-scale/multi-physics applications which can be used in realistic simulations. In this whitepaper, we detail the different optimisations done during the preparatory PRACE project to overcome known bottlenecks in the OpenMP implementation of XDEM. We analysed the Conversion, Dynamic, and the combined Dynamics-Conversion modules with Extrae/Paraver and Intel VTune profiling tools in order to find the most expensive functions. The proposed code modifications improved the performance of XDEM by ~17% for the computational expensive Dynamics-Conversion combined modules (with 48 cores, full node). Our analysis was performed in the Marenostrum 4 (MN4) PRACE infrastructure at Barcelona Supercomputing Center (BSC). [less ▲]

Eulerian-Lagrangian momentum coupling between XDEM and OpenFOAM using preCICE

in 14th WCCM & ECCOMAS Congress 2020 (2021, January)

Eulerian-Lagrangian couplings consider problems with a discrete phase as a particulate material that is in contact with a fluid phase. These applications are as diverse as engineering, additive ... [more ▼]

Eulerian-Lagrangian couplings consider problems with a discrete phase as a particulate material that is in contact with a fluid phase. These applications are as diverse as engineering, additive manufacturing, biomass conversion, thermal processing or pharmaceutical industry, among many others. A typical approach for this type of simulations is the coupling between Computation Fluid Dynamics (CFD) and Discrete Element Method (DEM), which is challenging in many ways. Such CFD--DEM couplings are usually implemented using an ad-hoc coupling layer, specific to the both DEM and CFD software, which considerably reduces the flexibility and applicability of the proposed implementation. In this work, we present the coupling of eXtended Discrete Element Method (XDEM), with the CFD library OpenFOAM, using the preCICE coupling library~\cite{preCICE} on volumetric meshes. Such momentum coupling requires the CFD side to account for the change of porosity due to the particulate phase and the particle momentum, while the particles of the DEM will be affected by the buoyancy and drag force of the fluid. While preCICE significantly simplifies the coupling between standalone libraries, each solver and, its respective adapter, have to be made aware of the new data involved in the physic model. For that, a new adapter has been implemented for XDEM and the existing adapter for OpenFOAM has been extended to include the additional data field exchange required for the momentum coupling, e.g porosity, particle momentum, fluid velocity and density. Our solution is tested and validated using simple benchmarks and advanced testcases such as a dam break, and shows consistent results. [less ▲]

Process analysis in thermal process engineering with high-performance computing using the example of grate firing

in Scherer, Viktor; Fricker, Neil; Reis, Albino (Eds.) Proceedings of the 12th European Conference on Industrial Furnaces and Boilers (2020, November)

Biomass as a renewable energy source continues to grow in popularity to reduce fossil fuel consumption for environmental and economic benefits. In the present contribution, the combustion chamber of a 16 ... [more ▼]

Biomass as a renewable energy source continues to grow in popularity to reduce fossil fuel consumption for environmental and economic benefits. In the present contribution, the combustion chamber of a 16 MW geothermal steam super-heater, which is part of the Enel Green Power "Cornia 2" power plant, is being investigated with high-performance computing methods. For this purpose, the extended discrete element method (XDEM) developed at the University of Luxembourg is used in a high-performance computing environment, which includes both the moving wooden bed and the combustion chamber above it. The XDEM simulation platform is based on a hybrid four-way coupling between the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD). In this approach, particles are treated as discrete elements that are coupled by heat, mass, and momentum transfer to the surrounding gas as a continuous phase. For individual wood particles, besides the equations of motion, the differential conservation equations for mass, heat, and momentum are solved, which describe the thermodynamic state during thermal conversion. The consistency of the numerical results with the actual system performance is discussed in this paper to determine the potentials and limitations of the approach. [less ▲]

Numerical Analysis of Interaction between a Reacting Fluid and a Moving Bed with Spatially and Temporally Fluctuating Porosity

Scientific Conference (2020, August 31)

The purpose of this study is to propose a numerical approach that combines low computational costs through the use of high computing efficiency, allowing the realistic use of the design with a sufficient ... [more ▼]

The purpose of this study is to propose a numerical approach that combines low computational costs through the use of high computing efficiency, allowing the realistic use of the design with a sufficient result's accuracy for industrial applications to investigate biomass combustion in a large-scale reciprocating grate. In the present contribution, a Biomass combustion chamber of a 16 MW geothermal steam super-heater, which is part of the Enel Green Power "Cornia 2" power plant,is being investigated with high-performance computing methods. For this purpose, the extended discrete element method (XDEM) developed at the University of Luxembourg is used in an HPC environment, which includes both the moving wooden bed and the combustion chamber above it. The XDEM simulation platform is based on a hybrid four-way coupling between the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD). In this approach, particles are treated as discrete elements that are coupled by heat, mass, and momentum transfer to the surrounding gas as a continuous phase. For individual wood particles, besides the equations of motion, the differential conservation equations for mass, heat, and momentum are solved, which describe the thermodynamic state during thermal conversion. The grate system has three different moving sections to ensure good mixing of the biomass parts and appropriate residence time. The primary air enters from below the grate and is split into four different zones. Furthermore, a secondary air is injected at high velocity straight over the fuel bed through nozzles. A Flue Gas Recirculation is present and partly injected through two jets along the vertical channel and partly from below the grate. The numerical 3D model presented is based on a multi-phase approach. The biomass particles are taken into consideration via the XDEM Method, while the gaseous phase is described by CFD with OpenFOAM. Thus, the combustion of the particles on the moving beds in the furnace is processed by XDEM through conduction, radiation and conversion along with the interaction with the surrounding gas phase accounted for by CFD. The coupling of CFD-XDEM as an Euler-Lagrange model is used. The fluid phase is a continuous phase handled with an Eulerian approach and each particle is tracked with a Lagrangian approach. Energy, mass and momentum conservation is applied for every single particle and the interaction of particles with each other in the bed and with the surrounding gas phase are taken into account. An individual particle can have a solid, liquid, gas or inert material phases (immobile species) at the same time. The different phases can undergo a series of conversion through various reactions that can be homogeneous, heterogeneous or intrinsic (drying, pyrolysis, gasification and oxidation). Our first results are consistent with actual data obtained from the sampling of the residual solid in the industrial plant. Our model is also able to predict gas flux behaviour inside the furnace, particularly the flue gas recirculation on the combustion process injection. [less ▲]