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Analysis of institutional authors

Kheir-Eddine, OtmaniAuthorMateo-Gabin, AndresAuthorRubio, GonzaloAuthorFerrer, EstebanAuthor

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September 29, 2024
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Accelerating high order discontinuous Galerkin solvers through a clustering-based viscous/turbulent-inviscid domain decomposition

Publicated to: ENGINEERING WITH COMPUTERS. 41 (2): 949-964 - 2025-04-01 41(2), DOI: 10.1007/s00366-024-02062-3

Authors:

Otmani, KE; Mateo-Gabín, A; Rubio, G; Ferrer, E
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Affiliations

Univ Politecn Madrid, Ctr Computat Simulat, Campus Montegancedo, Madrid 28660, Spain - Author
Univ Politecn Madrid, Sch Aeronaut, ETSIAE, UPM, Plaza Cardenal Cisneros 3, Madrid 28040, Spain - Author

Abstract

We explore the unsupervised clustering technique introduced in Otmani et al. (Phys Fluids 35:027112, 2023) to identify viscous/turbulent from inviscid regions in incompressible flows. The separation of regions allows solving the Navier-Stokes equations including Large Eddy Simulation closure models only in the viscous/turbulent ones, while solving the Euler equations in the remaining of the computational domain. By solving different sets of equations, the computational cost is significantly reduced. This coupling strategy is implemented within a discontinuous Galerkin numerical framework, which allows discontinuous solutions (i.e., different sets of equations) in neighboring elements that interact through numerical fluxes. The proposed strategy maintains the same accuracy at lower cost, when compared to solving the full Navier-Stokes equations throughout the entire domain. Validation of this approach is conducted across diverse flow regimes, spanning from unsteady laminar flows to unsteady turbulent flows, including an airfoil section at Reynolds numbers Re=10(3) and 10(4) and large angles of attack, and the flow past a wind turbine, modelled using actuator lines. The computational cost is reduced by 25% and 29% for the unsteady turbulent flow around an airfoil section and the flow past the wind turbine, respectively. In addition, to further accelerate the simulations, we combine the proposed decoupling with local P-adaptation, as proposed in Tlales et al. (Eng Comput, 2024). When doing so, we reduce the computational cost by 41% and 45% for the flow around the airfoil section and the flow past the wind turbine, respectively.
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Keywords

Adaptation strategiesAirfoiAirfoil sectionComputational costsComputational fluid dynamicsComputational fluid mechanicsDiscontinuous galerkinElastohydrodynamicsEuler equationsGalerkin methodsIncompressible flowLaminar flowLarge eddy simulationLarge eddy simulationsLarge-eddy simulationsMachine learningMachine-learningNaca0012Navier stokes equationsNavier-stokes equationP-adaptationReynolds equationReynolds numberTurbulenceTurbulent flowUnsteady flowUnsupervised clusteringWind turbinWind turbineWind turbines

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal ENGINEERING WITH COMPUTERS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 30/182, thus managing to position itself as a Q1 (Primer Cuartil), in the category Engineering, Mechanical.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-26:

  • WoS: 1
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-26:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 2.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 2 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 2.
  • The number of mentions on the social network X (formerly Twitter): 2 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/86486/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 110
  • Downloads: 46
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (KHEIR-EDDINE, OTMANI) and Last Author (FERRER VACCAREZZA, ESTEBAN).

the author responsible for correspondence tasks has been Otmani, Kheir-eddine.

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Awards linked to the item

Kheir-Eddine Otmani aknowledges the Grant 072 Bis/PG/Espagne/2020-2021 of Ministere de l'Enseignement Superieur et de la Recherche Scientifique, Republique Algerienne Democratique et Populaire. Gonzalo Rubio and Esteban Ferrer acknowledge the funding received by the Grant DeepCFD (Project No. PID2022-137899OB-I00) funded by MICIU/AEI/10.13039/501100011033 and by ERDF, EU. Esteban Ferrer would like to thank the support of Agencia Estatal de Investigacion (for the grant "Europa Excelencia 2022" Proyecto EUR2022-134041/AEI/10.13039/501100011033) y del Mecanismo de Recuperacion y Resiliencia de la Union Europea. This research has been cofunded by the European Union (ERC, Off-coustics, project number 101086075). Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. Finally, all authors gratefully acknowledge the Universidad Politecnica de Madrid (www.upm.es) for providing computing resources on Magerit Supercomputer.
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