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SediFoam: A general-purpose, open-source CFD-DEM solver for particle-laden flow with emphasis on sediment transport
Rui Sun, Heng Xiao
TL;DR
Sediment transport lacks a robust CFD–DEM solver that addresses its specialized physical and computational requirements. This paper develops and evaluates the open-source, three-dimensional, massively parallel solver SediFoam using OpenFOAM and LAMMPS. Validation demonstrates capability across sediment-transport regimes, while scalability is reported as satisfactory for simulations using up to O(10^7) particles.
Problem
A robust CFD–DEM solver for sediment transport remains desirable because existing approaches do not fully address sediment-specific requirements and some research codes have limited accessibility.
Method
SediFoam combines the open-source CFD solver OpenFOAM with the massively parallel DEM solver LAMMPS in a three-dimensional parallel CFD–DEM framework.
Results
SediFoam simulations demonstrate capability across various sediment-transport regimes, with satisfactory scalability compared with existing CFD–DEM approaches.
Takeaways & Limitations
SediFoam provides an open-source CFD–DEM solver for sediment-transport applications with demonstrated validation and parallel performance.
Takeaways & Limitations
The lift and added mass force models are applicable only to particle-laden flows at small Reynolds number and low volume fraction.
Abstract
from arXiv · showhide
With the growth of available computational resource, CFD-DEM (computational fluid dynamics-discrete element method) becomes an increasingly promising and feasible approach for the study of sediment transport. Several existing CFD-DEM solvers are applied in chemical engineering and mining industry. However, a robust CFD-DEM solver for the simulation of sediment transport is still desirable. In this work, the development of a three-dimensional, massively parallel, and open-source CFD-DEM solver SediFoam is detailed. This solver is built based on open-source solvers OpenFOAM and LAMMPS. OpenFOAM is a CFD toolbox that can perform three-dimensional fluid flow simulations on unstructured meshes; LAMMPS is a massively parallel DEM solver for molecular dynamics. Several validation tests of SediFoam are performed using cases of a wide range of complexities. The results obtained in the present simulations are consistent with those in the literature, which demonstrates the capability of SediFoam for sediment transport applications. In addition to the validation test, the parallel efficiency of SediFoam is studied to test the performance of the code for large-scale and complex simulations. The parallel efficiency tests show that the scalability of SediFoam is satisfactory in the simulations using up to O(10^7) particles.
1. Introduction
SediFoam addresses the need for a robust, accessible CFD–DEM solver tailored to sediment transport, whose distinctive forces, particle–mesh mapping, and scale require specialized treatment. It combines open-source CFD and DEM components with parallel algorithms and is designed for three-dimensional sediment-transport simulations.
- Motivation: Existing CFD–DEM efforts emphasize gas-solid flows, while sediment transport requires additional attention to lubrication and added mass forces.These forces are larger than in gas-solid flows and should be included in simulations.
- Motivation: Sediment transport occurs near boundary layers, where CFD meshes can be smaller than particles, requiring robust particle-to-Eulerian-mesh averaging.The averaging algorithm must convert discrete-particle properties into continuum CFD fields.
- Motivation: Sediment-transport simulations can involve O(10^6) particles, making parallel efficiency important for laboratory-scale problems.The particle count creates a direct computational requirement for scalable algorithms.
- Contribution: SediFoam is a three-dimensional, massively parallel, open-source CFD–DEM solver developed with emphasis on sediment transport.It is built using the open-source solvers OpenFOAM and LAMMPS.
- Contribution: Its originality includes lubrication and added mass forces, Lagrangian-to-Eulerian averaging, and parallel performance testing.The solver also supports polydispersed particle mixtures and flexible turbulence-model application through OpenFOAM.
2. Methodology
SediFoam couples Lagrangian particle dynamics with locally averaged Eulerian fluid equations, exchanging fluid–particle forces between LAMMPS and OpenFOAM. The methodology combines soft-sphere contact mechanics, sediment-transport force models, particle-to-cell averaging, and finite-volume fluid solution procedures.
- Particle dynamics: Particle translation and rotation are calculated from Newton’s second law using contact, lubrication, fluid–particle, and body forces, with corresponding torques for rotational motion.Particles use a soft-sphere contact model with an elastic spring and viscous dashpot.
- Fluid phase: The fluid phase is modeled with locally averaged incompressible Navier–Stokes equations using solid and fluid volume fractions, fluid velocity, stress, gravity, and fluid–particle interaction terms.Large eddy simulation represents the stress tensor with viscous and Reynolds stresses, while particle-boundary flow fluctuations remain unresolved.
- Solver coupling: At each time step, OpenFOAM computes fluid forces for individual particles, LAMMPS integrates particle motion and contacts, and particle forces are averaged back into the fluid equations.The fluid equations are solved in OpenFOAM with a finite-volume method on a collocated grid and PISO velocity–pressure decoupling.
- Interaction forces: Fluid–particle coupling includes buoyancy, drag, lift, and added-mass forces, with added mass included because carrier-fluid and particle densities can be comparable.The lift and added-mass models are stated to apply only to small-Reynolds-number, low-volume-fraction flows, although their accuracy is considered acceptable for sediment transport.
- Averaging procedure: Particle data are converted into Eulerian fields by computing cellwise particle volumes and solving a transient diffusion equation for the solid volume fraction.The averaging procedure is described as conservative, mesh-independent, and theoretically equivalent to Gaussian-kernel averaging.
3. Implementations
SediFoam couples parallel CFD and DEM modules while exchanging non-local particle information between processor subdomains. Its workflow updates particle and fluid data, averages particle properties, and advances both solvers.
- Coupled solver workflow: SediFoam solves fluid and particle equations separately through CFD and DEM modules at each time step.Particle information is updated before CFD averaging and fluid–particle interaction forces are applied before DEM advances particle motion.
- Parallel coupling: Non-local particle data are identified, transferred between processors, and localized to the CFD module before the next CFD step.The coupling procedure exchanges information when CFD and DEM subdomains are inconsistent across processors.
- Parallel coupling: The parallel coupling procedure transfers updated information in both directions between CFD and DEM modules.After DEM data update, CFD-derived non-local information can also be transferred back to particles in the DEM module.
4. Results
SediFoam is evaluated across single-particle, fixed-bed, and larger sediment-transport cases. The simulations reproduce experimental or numerical benchmarks while exposing force-model and averaging effects.
- Validation cases: Three sediment-transport tests assess lubrication and added mass, fluid and particle properties, and simulations with O(10^5) particles.The cases cover single-particle sedimentation, 500 particles on a fixed bed, and relatively large particle populations.
- Single-particle sedimentation: Considering lubrication and added mass produces particle–wall collision predictions consistent with experiments, whereas omitting these forces causes substantial discrepancies.Added mass increases rebound height, while lubrication is especially influential at St = 27 and less influential at St = 742.
- Numerical effects and limitations: Lubrication calculations increase computational cost, while diffusion-based averaging can produce a negative near-bed velocity and larger Ryy discrepancy than DNS.The Ryy discrepancy is attributed to unresolved flow fluctuations at particle surfaces in CFD–DEM.
- Sediment-transport benchmarks: SediFoam reproduces benchmark velocity, Reynolds-stress, solid-volume-fraction, and sediment-transport results with favorable or satisfactory agreement.The predicted streamwise particle velocity is 0.28 versus a benchmark value of 0.35, corresponding to a reported 20% error.
- Sediment-transport benchmarks: The solver predicts sediment transport rates favorably against experiments, with better suspended-load q* predictions than results reported in the literature.The reported comparison attributes this improvement to the drag-force model in the presence of movable particles.
5. Scalability
SediFoam is tested for strong and weak scalability in fluidized-bed and sediment-transport simulations. Efficiency remains useful at large processor counts and particle populations, although communication and CFD costs become important.
- Scalability tests: Strong and weak scalability tests evaluate SediFoam for constant-size problems and increasing problem sizes across fluidized-bed and sediment-transport cases.The study separately examines fluidized-bed and sediment-transport setups because their flow regimes and particle behavior differ.
- Fluidized-bed scalability: 85% strong-scaling efficiency is retained at 128 processors, while efficiency falls to 52% at 256 processors in the fluidized-bed test.At 256 processors, each processor handles approximately 20,000 sediment particles.
- Fluidized-bed scalability: 61% weak-scaling efficiency and a scale-up of 156 are achieved at 256 processors for fluidized-bed simulations.The weak-scaling particle count increases from 0.3 million to 21 million across the tested processor range.
6. Conclusion
SediFoam is a parallelized, open-source CFD–DEM solver developed for sediment transport, combining CFD and DEM modules through parallel communication. Validation tests support its capability across sediment-transport regimes, while scalability tests support large-scale simulations.
- SediFoam is a parallelized, open-source CFD–DEM solver developed with emphasis on sediment transport.
- Its CFD and DEM modules are based on OpenFOAM and LAMMPS, respectively, with parallel communication enabling large-scale simulations.
- The single-particle sedimentation test demonstrates the importance of added mass and lubrication in CFD–DEM simulations.
- 500-particle simulations produce fluid and particle properties consistent with an interface-resolved method, indicating desirable accuracy.
- O(10^5) particles demonstrate SediFoam's capability to simulate various sediment-transport regimes.
- Parallel efficiency tests show satisfactory scalability compared with other existing CFD–DEM solvers, supporting large-scale and complex sediment-transport simulations.