Ecfd:ecfd 8th edition - Revision history

Dauptain at 12:25, 1 April 2025

2025-04-01T12:25:41Z

Lkorzeczek: /* U3 - Yales2 Trame Editor, toward a fully featured graphical user interface for YALES2 */

2025-02-27T09:18:31Z

‎U3 - Yales2 Trame Editor, toward a fully featured graphical user interface for YALES2

Lkorzeczek: /* U3 - Yales2 Trame Editor, toward a fully featured graphical user interface for YALES2 */

2025-02-24T15:25:37Z

‎U3 - Yales2 Trame Editor, toward a fully featured graphical user interface for YALES2

Dillon: /* C11 - Exploring efficient tabulation strategies for detailed chemistry */

2025-02-24T15:01:32Z

‎C11 - Exploring efficient tabulation strategies for detailed chemistry

Dillon: /* C12 - Dynamic sub-grid-scale modelling of multi-regime flame wrinkling */

2025-02-24T15:01:01Z

‎C12 - Dynamic sub-grid-scale modelling of multi-regime flame wrinkling

Lkorzeczek at 11:59, 24 February 2025

2025-02-24T11:59:33Z

Robin.barbera: /* Mesh adaptation - A. Grenouilloux, ONERA & G. Balarac, LEGI */

2025-02-19T15:23:54Z

‎Mesh adaptation - A. Grenouilloux, ONERA & G. Balarac, LEGI

Bricteux: /* M6 - Dynamic mesh adaptation of turbulent flows (G. Balarac, L. Bricteux, P. Bénard, S. Mendez) */

2025-02-19T12:51:20Z

‎M6 - Dynamic mesh adaptation of turbulent flows (G. Balarac, L. Bricteux, P. Bénard, S. Mendez)

Bricteux: /* M6 - Dynamic mesh adaptation of turbulent flows (G. Balarac, L. Bricteux, P. Bénard, S. Mendez) */

2025-02-19T12:48:31Z

‎M6 - Dynamic mesh adaptation of turbulent flows (G. Balarac, L. Bricteux, P. Bénard, S. Mendez)

Bricteux: /* Mesh adaptation - A. Grenouilloux, ONERA & G. Balarac, LEGI */

2025-02-19T12:45:40Z

‎Mesh adaptation - A. Grenouilloux, ONERA & G. Balarac, LEGI

← Older revision		Revision as of 12:25, 1 April 2025
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		+	==== U4 - Deep Refactoring of an excessive OOP structure in the SCHEMA-based Opentea3 GUI generator ====
		+
		+	Participants: Antoine Dauptain (CERFACS), Thibault Marzlin (CERFACS)
		+
		+	Opentea3 is an interface generator using the SCHEMA standard to create UIs with forms, visual cues, and 2D/3D feedback. Used at Safran for three years, it suffers from a visual cue changing unexpectedly due to an overly object-oriented design, making status management complex and fixes risky. A key code smell is the use of = for recursive updates. Refactoring focused on code metrics to clarify abstractions, reducing code size by 21% while maintaining lexical scope. Structural complexity was halved, improving readability, but cyclomatic complexity doubled, exposing business logic. This trade-off enhances maintainability with a more direct logic management.
	<!-- Masqué		<!-- Masqué

@@ Line 324: / Line 324: @@
 Participants: Laurent Korzeczek, Serge Meynet (GDTECH), Julien Leparoux, Melody Cailler (SAFRAN)
-Currently, YALES2 mainly depends on basic tools like text editors and command-line interfaces for tasks such as data setup, initiating calculations, monitoring progress, and extracting relevant data. Additionally, tools like ParaView are used for visualizing results.
+Currently, the YALES2 user experience relies mainly on scripted tools such as text editors and command-line interfaces for tasks ranging from setting up input files to monitoring calculations. Additionally, tools like ParaView are used for visualizing results.
 The goal of this project was to design and develop a graphical user interface (GUI) for YALES2, making it easier for a wider range of users to perform complex multiphysics calculations through an intuitive and well-structured interface. The initial version of this interface has been created using the Trame framework, an open-source platform developed by Kitware. This framework offers several benefits, such as access to various graphic libraries, ease of development with Python, and straightforward deployment. The interface can now locally set up, run, and monitor simple incompressible flow calculations. Throughout the development, a test-driven development (TDD) methodology was followed, ensuring the creation of high-quality, robust, and maintainable code.

← Older revision		Revision as of 15:25, 24 February 2025
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	Participants: Laurent Korzeczek, Serge Meynet (GDTECH), Julien Leparoux, Melody Cailler (SAFRAN)		Participants: Laurent Korzeczek, Serge Meynet (GDTECH), Julien Leparoux, Melody Cailler (SAFRAN)

		+	Currently, YALES2 mainly depends on basic tools like text editors and command-line interfaces for tasks such as data setup, initiating calculations, monitoring progress, and extracting relevant data. Additionally, tools like ParaView are used for visualizing results.
		+	The goal of this project was to design and develop a graphical user interface (GUI) for YALES2, making it easier for a wider range of users to perform complex multiphysics calculations through an intuitive and well-structured interface. The initial version of this interface has been created using the Trame framework, an open-source platform developed by Kitware. This framework offers several benefits, such as access to various graphic libraries, ease of development with Python, and straightforward deployment. The interface can now locally set up, run, and monitor simple incompressible flow calculations. Throughout the development, a test-driven development (TDD) methodology was followed, ensuring the creation of high-quality, robust, and maintainable code.

← Older revision		Revision as of 15:01, 24 February 2025
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	==== C10 - TECERACT : Tabulated chemistry generator for aeronautical combustion ====		==== C10 - TECERACT : Tabulated chemistry generator for aeronautical combustion ====
−
−	~~==== C11 - Exploring efficient tabulation strategies for detailed chemistry ====~~

	==== C12 - Dynamic sub-grid-scale modelling of multi-regime flame wrinkling ====		==== C12 - Dynamic sub-grid-scale modelling of multi-regime flame wrinkling ====

← Older revision		Revision as of 15:01, 24 February 2025
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	==== C12 - Dynamic sub-grid-scale modelling of multi-regime flame wrinkling ====		==== C12 - Dynamic sub-grid-scale modelling of multi-regime flame wrinkling ====
		+	Large-eddy-simulation (LES) of reactive flows is widely used in both academic and industrial applications. Combustion phenomena occur at a scale often smaller than the LES mesh size, therefore, turbulent combustion models are required to account for unresolved turbulent flame interactions. The modeling of sub-grid-scale (SGS) flame turbulence interactions can be described with a flame surface wrinkling factor which measures the ratio of the total flame surface area to the resolved flame surface area. Flame surface wrinkling models are often expressed by assuming equilibrium between turbulent motions and flame surface wrinkling, however, in realistic burners non-equilibrium is present and dynamic models are needed to adapt model parameters. Current dynamic models identify flame surface areas from scalars such as the progress variable <math>\widetilde{c}</math> or the mixture fraction <math>\widetilde{z}</math>, however, in multi-regime flames where filtered gradients <math>\overline{\|\nabla c\|}</math> and <math>\overline{\|\nabla z\|}</math> coexist, such approaches tend to fail. In this project we introduced a multi-regime dynamic formalism for determining flame wrinkling factors based on a mixed approach between premixed and diffusion flame surfaces. Model validation was performed using a DNS database of the HYLON configuration, a dual-swirl coaxial H2/air injector. The operating condition of interest was the lifted flame, HYLON L, which was studied in the framework of the turbulent flame workshop TNF. This flame has characteristic behavior of both non-premixed and partially-premixed flames, which allowed the model to be tested under conditions where iso-surfaces of <math>\widetilde{c}</math> and <math>\widetilde{z}</math> coexist.

	==== C13 - LES of a semi-industrial burner using a non-adiabatic virtual chemical scheme ====		==== C13 - LES of a semi-industrial burner using a non-adiabatic virtual chemical scheme ====

@@ Line 307: / Line 307: @@
-==== U1 - Low-fidelity (RANS) rotor/stator simulations, application to Kaplan Turbine - Y. Lakrifi, G. Balarac (LEGI),  R. Mercier (SAFRAN), V. Moureau (CORIA) ====
+==== U1 - Low-fidelity (RANS) rotor/stator simulations, application to Kaplan Turbine -  ====
 RANS rotor/stator coupling simulation has recently been developed within YALES2. This approach involves coupling the rotor, in the rotational frame, with the stator using a patch located at the domain interface. This patch allows interaction between the two regions and enables azimuthal averaging to account for azimuthal periodicity.
@@ Line 313: / Line 315: @@
 This year, the main objective was to improve the automatic mesh convergence (AMC) procedure for coupled RANS simulations by managing the AMC of coupled runs, integrating coupling runs into the workflow, which was not previously supported and, finally, implementing parallel remeshing of periodic boundaries.
-==== U2 - Coupling PyTorch/YALES2, combustion cartesian look-up tables - J. Leparoux, N. Treleaven, S. Dillon (SAFRAN), K. Bioche, G. Lartigue (CORIA) ====
+==== U2 - Coupling PyTorch/YALES2, combustion cartesian look-up tables ====
 Participants: Julien Leparoux (Safran Tech), Kévin Bioche (CORIA), Ghislain Lartigue (CORIA), Nicholas Treleaven (Safran Tech)
@@ Line 319: / Line 321: @@
 Neural Networks offer a promising alternative to Cartesian look-up tables for combustion simulations, reducing memory footprint. In this project, we investigated how to integrate an NN model for real-time inference in the YALES2 platform, exploring two approaches: a Python interface and a Fortran Torch binding (using FTorch[https://github.com/Cambridge-ICCS/FTorch]). We validated that the model remains accurate when embedded online and identified improvements for robustness. Inference costs were evaluated on a Mac M3 and the Austral cluster, revealing a strong dependency on data volume. To optimize efficiency, we propose grouping cells at the processor level.
-==== U3 - Yales2 Trame Editor, toward a fully featured graphical user interface for YALES2 - L. Korzeczek, S. Meynet (GDTECH), J. Leparoux, M. Cailler (SAFRAN) ====
+==== U3 - Yales2 Trame Editor, toward a fully featured graphical user interface for YALES2 ====

@@ Line 85: / Line 85: @@
 ==== M3 - Development and definition of a new Automatic Mesh Convergence (AMC) driver for automating static mesh convergence in YALES2 (C. Papagiannis (LEGI/INRIA), G. Balarac (LEGI), O. LeMaître (INRIA), P.M. Congedo (INRIA)) ====
 Static mesh adaptation requires re-adapting an existing (usually coarse) mesh, to conform to some quality metric that satisfies some optimality criterion. This involves statistics (Mean and RMS fields) that need to be adequately converged. We proposed and developed a novel AMC strategy that can converge an initial coarse mesh to an adequately refined one by taking into account the quality of the calculated statistics before each adaptation. Specifically, so far, the moment (in terms of integrating the LES equations) at which to launch the adaptation was unknown and had to be set apriori as a parameter of the AMC, dependent on the flow physics and therefore on the case at hand. Our method is automatically performing adaptations when the quality of the volume averaged mean field estimate (characterized by its RMSE) reaches the levels of the bias error that this field has, due to the mesh being far from the desired one (dictated by the quality criterion). This was achieved through drawing inspiration from a theoretical model that treats the AMC as a "conditionally" contractive mapping with a fixed point.
 ==== M6 - Dynamic mesh adaptation of turbulent flows (G. Balarac, L. Bricteux, P. Bénard, S. Mendez) ====

@@ Line 87: / Line 87: @@
 ==== M6 - Dynamic mesh adaptation of turbulent flows (G. Balarac, L. Bricteux, P. Bénard, S. Mendez) ====
-This work focuses on developing dynamic mesh adaptation strategies for turbulent flows, particularly in cases where static (statistical-based) adaptation is not suitable. The objective is to create a dynamic mesh metric that can compute the required physical metric directly, eliminating the need for an explicitly prescribed mesh size. Here, we assessed th method based on QC6 developed at LEGI with encouraging results.
+This work focuses on developing dynamic mesh adaptation strategies for turbulent flows, particularly in cases where static (statistical-based) adaptation is inadequate. The objective is to design a dynamic mesh metric capable of computing the required physical metric directly, without the need for an explicitly prescribed mesh size.
-The approach has been validated with excellent results on hemisphere flow at Re=55k (a regime for which LDV experimental measurements are available).
+The method, based on QC6 and developed at LEGI, has been assessed with encouraging results. Validation was performed on hemisphere flow at  Re=55k —a regime for which LDV experimental measurements are available—yielding promising results in terms of Drag coefficient. Additionally, the approach was tested on vortex ring collisions, a canonical case where static adaptation is ineffective. The results demonstrated that the adaptation strategy performs well in capturing vortical flow regions. Furthermore, the strategy was applied to an elliptic jet flow (aspect ratio 3) generating vortex rings at Re=30k.
-The vortex ring collision test case which is a typical test case for which static adaptation is not relevant has also been ran with promising results showing that the adaptation performs well in vortical flow regions.
+The dynamically generated meshes successfully tracked the regions of interest, confirming the method’s robustness and effectiveness in complex flow configurations.
-The adaptation strategy has already been used in the case of an elliptic jet flow Elliptic (aspect ratio 3) generating vortex rings at Re = 30,000. It was shown that the dynamically generated meshes follows properly the region of interests.
 === Numerics - M. Bernard, LEGI & G. Lartigue, CORIA ===