Aurélien Larcher

669 total citations · 1 hit paper
24 papers, 482 citations indexed

About

Aurélien Larcher is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Numerical Analysis. According to data from OpenAlex, Aurélien Larcher has authored 24 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computational Mechanics, 7 papers in Statistical and Nonlinear Physics and 3 papers in Numerical Analysis. Recurrent topics in Aurélien Larcher's work include Lattice Boltzmann Simulation Studies (10 papers), Advanced Numerical Methods in Computational Mathematics (9 papers) and Model Reduction and Neural Networks (7 papers). Aurélien Larcher is often cited by papers focused on Lattice Boltzmann Simulation Studies (10 papers), Advanced Numerical Methods in Computational Mathematics (9 papers) and Model Reduction and Neural Networks (7 papers). Aurélien Larcher collaborates with scholars based in France, Germany and United Kingdom. Aurélien Larcher's co-authors include Elie Hachem, Jonathan Viquerat, Philippe Méliga, Jean Rabault, Alexander Kuhnle, Murtazo Nazarov, Anselmo Soeiro Pereira, Thierry Coupez, Rudy Valette and J.‐C. Latché and has published in prestigious journals such as Scientific Reports, Journal of Computational Physics and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

Aurélien Larcher

24 papers receiving 472 citations

Hit Papers

A review on deep reinforcement learning for fluid mechanics 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A review on deep reinforcement learning for fluid mechanics
    2021 186 citations Jonathan Viquerat, Jean Rabault et al. Computers & Fluids profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aurélien Larcher France 11 296 190 90 69 36 24 482
Qiming Zhu United States 8 312 1.1× 124 0.7× 57 0.6× 213 3.1× 27 0.8× 24 640
Nicola Demo Italy 11 118 0.4× 207 1.1× 71 0.8× 35 0.5× 37 1.0× 22 336
Tingwei Ji China 11 313 1.1× 224 1.2× 216 2.4× 52 0.8× 41 1.1× 32 569
Xinshuai Zhang China 10 187 0.6× 128 0.7× 156 1.7× 72 1.0× 36 1.0× 24 499
Francesco Ballarin Italy 17 524 1.8× 618 3.3× 73 0.8× 110 1.6× 30 0.8× 54 909
Tianyuan Liu China 14 196 0.7× 144 0.8× 206 2.3× 177 2.6× 32 0.9× 26 527
Feng Ren China 11 472 1.6× 161 0.8× 162 1.8× 47 0.7× 37 1.0× 50 644
Domenico Borzacchiello France 12 114 0.4× 204 1.1× 32 0.4× 76 1.1× 20 0.6× 29 460
Yue Hua China 14 143 0.5× 132 0.7× 78 0.9× 100 1.4× 17 0.5× 35 416
Burigede Liu United States 11 77 0.3× 148 0.8× 35 0.4× 97 1.4× 79 2.2× 18 477

Countries citing papers authored by Aurélien Larcher

Since Specialization
Citations

This map shows the geographic impact of Aurélien Larcher's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aurélien Larcher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aurélien Larcher more than expected).

Fields of papers citing papers by Aurélien Larcher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aurélien Larcher. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aurélien Larcher. The network helps show where Aurélien Larcher may publish in the future.

Co-authorship network of co-authors of Aurélien Larcher

This figure shows the co-authorship network connecting the top 25 collaborators of Aurélien Larcher. A scholar is included among the top collaborators of Aurélien Larcher based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aurélien Larcher. Aurélien Larcher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chau, Yves, et al.. (2024). Analysis of Intracranial Aneurysm Haemodynamics Altered by Wall Movement. Bioengineering. 11(3). 269–269. 7 indexed citations
2.
Méliga, Philippe, et al.. (2023). Evaluating the Impact of Domain Boundaries on Hemodynamics in Intracranial Aneurysms within the Circle of Willis. Fluids. 9(1). 1–1. 4 indexed citations
3.
Larcher, Aurélien, et al.. (2023). Large-scale parallel topology optimization of three-dimensional incompressible fluid flows in a level set, anisotropic mesh adaptation framework. Computer Methods in Applied Mechanics and Engineering. 416. 116335–116335. 4 indexed citations
4.
Hachem, Elie, Philippe Méliga, Jonathan Viquerat, et al.. (2023). Reinforcement learning for patient-specific optimal stenting of intracranial aneurysms. Scientific Reports. 13(1). 7147–7147. 8 indexed citations
5.
Viquerat, Jonathan, et al.. (2023). Deep learning model for two-fluid flows. Physics of Fluids. 35(2). 1 indexed citations
6.
Larcher, Aurélien, et al.. (2022). Anisotropic adaptive body-fitted meshes for CFD. Computer Methods in Applied Mechanics and Engineering. 400. 115562–115562. 4 indexed citations
7.
Viquerat, Jonathan, et al.. (2022). Single-step deep reinforcement learning for two- and three-dimensional optimal shape design. AIP Advances. 12(8). 12 indexed citations
8.
Viquerat, Jonathan, Philippe Méliga, Aurélien Larcher, & Elie Hachem. (2022). A review on deep reinforcement learning for fluid mechanics: An update. Physics of Fluids. 34(11). 71 indexed citations
9.
Viquerat, Jonathan, et al.. (2021). Single-step deep reinforcement learning for open-loop control of laminar and turbulent flows. Physical Review Fluids. 6(5). 1 indexed citations
10.
Hachem, Elie, et al.. (2021). Deep reinforcement learning for the control of conjugate heat transfer. Journal of Computational Physics. 436. 110317–110317. 37 indexed citations
11.
Larcher, Aurélien, et al.. (2021). Stabilized finite element method for incompressible solid dynamics using an updated Lagrangian formulation. Computer Methods in Applied Mechanics and Engineering. 384. 113923–113923. 12 indexed citations
12.
Viquerat, Jonathan, et al.. (2021). Robust deep learning for emulating turbulent viscosities. Physics of Fluids. 33(10). 13 indexed citations
13.
Viquerat, Jonathan, et al.. (2020). Direct shape optimization through deep reinforcement learning. Journal of Computational Physics. 428. 110080–110080. 6 indexed citations
14.
Pereira, Anselmo Soeiro, et al.. (2020). Viscoplastic dam-breaks. Journal of Non-Newtonian Fluid Mechanics. 287. 104447–104447. 21 indexed citations
15.
Pereira, Anselmo Soeiro, Aurélien Larcher, Elie Hachem, & Rudy Valette. (2019). Capillary, viscous, and geometrical effects on the buckling of power-law fluid filaments under compression stresses. Computers & Fluids. 190. 514–519. 12 indexed citations
16.
Larcher, Aurélien, et al.. (2019). Conservative and adaptive level-set method for the simulation of two-fluid flows. Computers & Fluids. 191. 104223–104223. 20 indexed citations
17.
Larcher, Aurélien, et al.. (2019). Anisotropic boundary layer mesh generation for reliable 3D unsteady RANS simulations. Finite Elements in Analysis and Design. 170. 103345–103345. 18 indexed citations
18.
Nazarov, Murtazo & Aurélien Larcher. (2016). Numerical investigation of a viscous regularization of the Euler equations by entropy viscosity. Computer Methods in Applied Mechanics and Engineering. 317. 128–152. 24 indexed citations
19.
Herbin, Raphaèle, et al.. (2014). Analysis of a fractional-step scheme for the P $$_1$$ 1 radiative diffusion model. Computational and Applied Mathematics. 35(1). 135–151. 3 indexed citations
20.
Larcher, Aurélien, et al.. (2011). Convergence of a finite volume scheme for the convection-diffusion equation with $\mathrm{L}^{1}$ data. Mathematics of Computation. 81(279). 1429–1454. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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