Thomas Jaravel

622 total citations
32 papers, 441 citations indexed

About

Thomas Jaravel is a scholar working on Computational Mechanics, Fluid Flow and Transfer Processes and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Thomas Jaravel has authored 32 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computational Mechanics, 16 papers in Fluid Flow and Transfer Processes and 10 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Thomas Jaravel's work include Combustion and flame dynamics (20 papers), Advanced Combustion Engine Technologies (16 papers) and Fire dynamics and safety research (10 papers). Thomas Jaravel is often cited by papers focused on Combustion and flame dynamics (20 papers), Advanced Combustion Engine Technologies (16 papers) and Fire dynamics and safety research (10 papers). Thomas Jaravel collaborates with scholars based in France, United States and United Kingdom. Thomas Jaravel's co-authors include Matthias Ihme, Bénédicte Cuenot, Éléonore Riber, Hao Wu, Peter Ma, Thierry Poinsot, Ghenadie Bulat, Olivier Vermorel, Oliver Schulz and Nicolas Noiray and has published in prestigious journals such as International Journal of Hydrogen Energy, Combustion and Flame and Building and Environment.

In The Last Decade

Thomas Jaravel

31 papers receiving 433 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Jaravel France 12 357 256 137 116 47 32 441
Reetesh Ranjan United States 12 459 1.3× 222 0.9× 202 1.5× 66 0.6× 64 1.4× 45 526
Laurent Benoit France 6 492 1.4× 289 1.1× 178 1.3× 105 0.9× 130 2.8× 10 555
Luı́s Fernando Figueira da Silva Brazil 15 484 1.4× 222 0.9× 260 1.9× 127 1.1× 49 1.0× 66 638
A. Mäck Germany 12 366 1.0× 103 0.4× 254 1.9× 50 0.4× 44 0.9× 41 466
M. González France 12 412 1.2× 116 0.5× 275 2.0× 194 1.7× 94 2.0× 36 539
Dennis P. Stocker United States 13 381 1.1× 227 0.9× 180 1.3× 121 1.0× 24 0.5× 47 451
Ekaterina Fedina Sweden 8 524 1.5× 196 0.8× 255 1.9× 79 0.7× 21 0.4× 17 562
T. M. Muruganandam India 13 560 1.6× 249 1.0× 284 2.1× 98 0.8× 44 0.9× 57 640
Heeseok Koo United States 13 509 1.4× 157 0.6× 236 1.7× 51 0.4× 33 0.7× 30 581
Jonathan F. MacArt United States 11 288 0.8× 111 0.4× 74 0.5× 55 0.5× 57 1.2× 29 339

Countries citing papers authored by Thomas Jaravel

Since Specialization
Citations

This map shows the geographic impact of Thomas Jaravel'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 Thomas Jaravel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Jaravel more than expected).

Fields of papers citing papers by Thomas Jaravel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas Jaravel. 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 Thomas Jaravel. The network helps show where Thomas Jaravel may publish in the future.

Co-authorship network of co-authors of Thomas Jaravel

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Jaravel. A scholar is included among the top collaborators of Thomas Jaravel 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 Thomas Jaravel. Thomas Jaravel 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.
Rochoux, Mélanie C., et al.. (2025). Surrogate-based ensemble data assimilation for reducing uncertainty in large-eddy simulation of microscale pollutant dispersion. Building and Environment. 287. 113863–113863.
2.
3.
Jaravel, Thomas, et al.. (2024). A modeling strategy for the Thickened Flame simulation of propagating lean hydrogen–air flames. International Journal of Hydrogen Energy. 78. 1133–1141. 4 indexed citations
4.
Jaravel, Thomas, et al.. (2024). Numerical study of the flame acceleration mechanisms of a lean hydrogen/air deflagration in an obstructed channel. International Journal of Hydrogen Energy. 89. 224–232. 9 indexed citations
5.
Rochoux, Mélanie C., et al.. (2024). Uncertainty-aware surrogate modeling for urban air pollutant dispersion prediction. Building and Environment. 267. 112287–112287. 3 indexed citations
6.
Sánchez-Gómez, Emilia, et al.. (2024). Past and Future Trends in Clear‐Air Turbulence Over the Northern Hemisphere. Journal of Geophysical Research Atmospheres. 129(13). 4 indexed citations
7.
Jaravel, Thomas, et al.. (2024). LES of the combustion efficiency of wake stabilized methane jet flames in crossflow. Combustion and Flame. 273. 113916–113916. 3 indexed citations
8.
Vermorel, Olivier, et al.. (2024). Flame-turbulence interactions in lean hydrogen flames: Implications for turbulent flame speed and fractal modelling. Combustion and Flame. 273. 113926–113926. 5 indexed citations
9.
Staffelbach, Gabriel, et al.. (2024). A Systematic Adaptive Mesh Refinement Method for Large Eddy Simulation of Turbulent Flame Propagation. Flow Turbulence and Combustion. 112(4). 1127–1160. 4 indexed citations
10.
Jaravel, Thomas, et al.. (2022). On the controlling parameters of the thermal decomposition of inhibiting particles: A theoretical and numerical study. Combustion and Flame. 240. 111991–111991. 10 indexed citations
11.
Watson, Leighton M., et al.. (2021). Infrasound Radiation From Impulsive Volcanic Eruptions: Nonlinear Aeroacoustic 2D Simulations. Journal of Geophysical Research Solid Earth. 126(9). 11 indexed citations
12.
Lapeyre, Corentin, et al.. (2021). Generalization Capability of Convolutional Neural Networks for Progress Variable Variance and Reaction Rate Subgrid-Scale Modeling. Energies. 14(16). 5096–5096. 9 indexed citations
13.
Jaravel, Thomas, et al.. (2020). Deflagration to detonation transition in fast flames and tracking with chemical explosive mode analysis. Proceedings of the Combustion Institute. 38(3). 3529–3536. 15 indexed citations
14.
Yu, Hans, Thomas Jaravel, Matthias Ihme, Matthew P. Juniper, & Luca Magri. (2019). Data Assimilation and Optimal Calibration in Nonlinear Models of Flame Dynamics. Journal of Engineering for Gas Turbines and Power. 141(12). 12 indexed citations
15.
Ma, Peter, Hao Wu, Thomas Jaravel, Luis Bravo, & Matthias Ihme. (2018). Large-eddy simulations of transcritical injection and auto-ignition using diffuse-interface method and finite-rate chemistry. Proceedings of the Combustion Institute. 37(3). 3303–3310. 44 indexed citations
16.
Wu, Hao, Peter Ma, Thomas Jaravel, & Matthias Ihme. (2018). Pareto-efficient combustion modeling for improved CO-emission prediction in LES of a piloted turbulent dimethyl ether jet flame. Proceedings of the Combustion Institute. 37(2). 2267–2276. 18 indexed citations
17.
Jaravel, Thomas, Jeffrey W. Labahn, Brandon Sforzo, Jerry Seitzman, & Matthias Ihme. (2018). Numerical study of the ignition behavior of a post-discharge kernel in a turbulent stratified crossflow. Proceedings of the Combustion Institute. 37(4). 5065–5072. 16 indexed citations
18.
Jaravel, Thomas, et al.. (2018). Coupling of turbulence on the ignition of multicomponent sprays. Proceedings of the Combustion Institute. 37(3). 3295–3302. 14 indexed citations
19.
Bauerheim, Michaël, Thomas Jaravel, Lucas Esclapez, et al.. (2015). Multiphase Flow LES Study of the Fuel Split Effects on Combustion Instabilities in an Ultra Low-NOx Annular Combustor. 7 indexed citations
20.
Bellis, Cédric, et al.. (2012). A non-iterative sampling approach using noise subspace projection for EIT. Inverse Problems. 28(7). 75015–75015. 3 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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2026