Lethe: An open-source parallel high-order adaptative CFD solver for incompressible flows

Blais, Bruno; Barbeau, Lucka; Bibeau, Valérie; Gauvin, Simon; Geitani, Toni El; Golshan, Shahab; Kamble, Rajeshwari; Mirakhori, Ghazaleh; Chaouki, Jamal

doi:10.1016/j.softx.2020.100579

Cited by 27 publications

(34 citation statements)

References 22 publications

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“…The equations were solved by the finite element method using stabilization techniques which allows to circumvent the limitations of the classical Galerkin approach and satisfies the Ladyzhenskaya-Babuska-Brezzi (LBB) inf-sup condition. For a more detailed explanation, we refer the reader to the Lethe paper 15,19 .…”

Section: Governing Equations and Numerical Implementationmentioning

confidence: 99%

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A High Order Stabilized Solver for the Volume Averaged Navier-Stokes Equations

Geitani¹,

Golshan²,

Blais³

2022

Preprint

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The Volume-Averaged Navier-Stokes equations are used to study fluid flow in the presence of fixed or moving solids such as packed or fluidized beds. We develop a high-order finite element solver using both forms A and B of these equations.We introduce tailored stabilization techniques to prevent oscillations in regions of sharp gradients, to relax the Ladyzhenskaya-Babuska-Brezzi inf-sup condition, and to enhance the local mass conservation and the robustness of the formulation. We calculate the void fraction using the Particle Centroid Method. Using different drag models, we calculate the drag force exerted by the solids on the fluid. We implement the method of manufactured solution to verify our solver. We demonstrate that the model preserves the order of convergence of the underlying finite element discretization. Finally, we simulate gas flow through a randomly packed bed and study the pressure drop and mass conservation properties to validate our model.

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Section: Governing Equations and Numerical Implementationmentioning

confidence: 99%

“…In this paper, we build a high-order FEM stabilized VANS solver as a first step in realizing a coupled CFD-DEM solver within the open-source software Lethe 15 . We present a fully implicit finite element VANS solver.…”

Section: Introductionmentioning

confidence: 99%

A High Order Stabilized Solver for the Volume Averaged Navier-Stokes Equations

Geitani¹,

Golshan²,

Blais³

2022

Preprint

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“…At the beginning, the simulation domain is defined using a triangulation (grid), which defines the system outer and inner boundaries. Similar to Lethe [23], unstructured meshes (using the GMSH [33] file format) and native meshes produced by the deal.II library (ranging from a simple ball and cube to more complex ones like airfoils) are supported. Lethe-DEM supports writing and reading checkpoint files, which enables the user to quickly restart an unfinished simulation.…”

Section: Overview Of Lethe-demmentioning

confidence: 99%

“…Lethe-DEM is directly integrated within Lethe [23]. It is built as separate executable and is configured using CMake [34].…”

Section: Version Control Continuous Integration and Testingmentioning

confidence: 99%

“…In this work, we introduce a new open-source, parallel and load-balanced software for the simulation of granular systems: Lethe-DEM. Lethe-DEM is a DEM solver in the framework of Lethe [23], a high-order CFD solver to simulate incompressible flows and targeting practice-oriented chemical engineering applications. Lethe is built upon deal.II [24], a well-established open-source finite element modelling library.…”

Section: Introductionmentioning

confidence: 99%

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Lethe-DEM : An open-source parallel discrete element solver with load balancing

Golshan¹,

Münch²,

Gassmöller³

et al. 2021

Preprint

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Approximately 75% of the raw material and 50% of the products in the chemical industry are granular materials. The Discrete Element Method (DEM) provides detailed insights of phenomena at particle scale and it is therefore often used for modeling granular materials. However, because DEM tracks the motion and contact of individual particles separately, its computational cost increases nonlinearly O(n p log(n p )) -O(n 2 p ) depending on the algorithm) with the number of particles (n p ). In this article, we introduce a new open-source parallel DEM software with load balancing: Lethe-DEM. Lethe-DEM, a module of Lethe, consists of solvers for two-dimensional and three-dimensional DEM simulations. Loadbalancing allows Lethe-DEM to significantly increase the parallel efficiency by ≈ 25 − 70% depending on the granular simulation. We explain the fundamental modules of Lethe-DEM, its software architecture, and the governing equations. Furthermore, we verify Lethe-DEM with several tests including analytical solutions and comparison with other software. Comparisons with experiments in a flat-bottomed silo, wedge-shaped silo, and rotating drum validate Lethe-DEM. We investigate the strong and weak scaling of Lethe-DEM with 1 ≤ n c ≤ 192 and 32 ≤ n c ≤ 320 processes, respectively, with and without load-balancing. The strong-scaling analysis is performed on the wedge-shaped silo and rotating drum simulations, while for the weak-scaling analysis, we use a dam break simulation. The best scalability of Lethe-DEM is obtained in the range of 5000 ≤ n p /n c ≤ 15 000. Finally, we demonstrate that large scale simulations can be carried out with Lethe-DEM using the simulation of a three-dimensional

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Artificial neural network to predict the power number of agitated tanks fed by CFD simulations

et al. 2023

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The power consumption of the agitator is a critical variable to consider in the design of a mixing system. It is generally evaluated through a dimensionless number known as the power number . Multiple empirical equations exist to calculate the power number based on the Reynolds number and dimensionless geometrical variables that characterize the tank, the impeller, and the height of the fluid. However, correlations perform poorly outside of the conditions in which they were established. We create a rich database of 100 k computational fluid dynamics (CFD) simulations. We simulate paddle and pitched blade turbines in unbaffled tanks from 1 to 100 and use an artificial neural network (ANN) to create a robust and accurate predictor of the power number. We perform a mesh sensitivity analysis to verify the precision of the values given by the CFD simulations. To sample the 100 k mixers by their geometrical and physical properties, we use the Latin hypercube sampling (LHS) method. We then normalize the data with a MinMax transformation to put all features in the same scale and thus avoid bias during the ANN's training. Using a grid search cross‐validation, we find the best architecture of the ANN that prevents overfitting and underfitting. Finally, we quantify the performance of the ANN by extracting 30% of the database, predicting the using the ANN, and evaluating the mean absolute percentage error. The mean absolute error in the ANN prediction is 0.5%, and its accuracy surpasses correlations even for untrained geometries.

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Lethe: An open-source parallel high-order adaptative CFD solver for incompressible flows

Cited by 27 publications

References 22 publications

A High Order Stabilized Solver for the Volume Averaged Navier-Stokes Equations

A High Order Stabilized Solver for the Volume Averaged Navier-Stokes Equations

Lethe-DEM : An open-source parallel discrete element solver with load balancing

Artificial neural network to predict the power number of agitated tanks fed by CFD simulations

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