Philip Avery

1.9k total citations · 1 hit paper
50 papers, 1.3k citations indexed

About

Philip Avery is a scholar working on Computational Mechanics, Civil and Structural Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Philip Avery has authored 50 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Mechanics, 16 papers in Civil and Structural Engineering and 12 papers in Statistical and Nonlinear Physics. Recurrent topics in Philip Avery's work include Model Reduction and Neural Networks (12 papers), Aerospace Engineering and Energy Systems (10 papers) and Gas Dynamics and Kinetic Theory (10 papers). Philip Avery is often cited by papers focused on Model Reduction and Neural Networks (12 papers), Aerospace Engineering and Energy Systems (10 papers) and Gas Dynamics and Kinetic Theory (10 papers). Philip Avery collaborates with scholars based in United States, Australia and France. Philip Avery's co-authors include Charbel Farhat, Todd Chapman, Julien Cortial, Radek Tezaur, Jason Rabinovitch, Jing Li, John H. Lau, Mahen Mahendran, Matthew J. Zahr and Jing Li and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and AIAA Journal.

In The Last Decade

Philip Avery

49 papers receiving 1.2k citations

Hit Papers

A mechanics‐informed artificial neural network approach i... 2022 2026 2023 2024 2022 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philip Avery United States 21 579 420 364 314 272 50 1.3k
Ludovic Chamoin France 22 405 0.7× 447 1.1× 278 0.8× 447 1.4× 272 1.0× 90 1.1k
David Ryckelynck France 17 681 1.2× 396 0.9× 414 1.1× 477 1.5× 165 0.6× 80 1.4k
Boris Krämer United States 21 496 0.9× 246 0.6× 331 0.9× 261 0.8× 144 0.5× 77 1.6k
Francisco Chinesta France 15 681 1.2× 490 1.2× 392 1.1× 560 1.8× 173 0.6× 41 1.5k
Pedro Dı́ez Spain 21 475 0.8× 761 1.8× 268 0.7× 591 1.9× 228 0.8× 111 1.5k
Julien Cortial France 8 820 1.4× 499 1.2× 401 1.1× 115 0.4× 188 0.7× 16 1.1k
Adrien Leygue France 26 894 1.5× 503 1.2× 453 1.2× 787 2.5× 386 1.4× 82 2.3k
Bryan Glaz United States 16 238 0.4× 333 0.8× 201 0.6× 146 0.5× 106 0.4× 45 957
Jean‐Charles Passieux France 20 200 0.3× 348 0.8× 137 0.4× 466 1.5× 244 0.9× 58 1.2k
José Vicente Aguado France 16 404 0.7× 149 0.4× 223 0.6× 259 0.8× 232 0.9× 31 979

Countries citing papers authored by Philip Avery

Since Specialization
Citations

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

Fields of papers citing papers by Philip Avery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Avery

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Avery. A scholar is included among the top collaborators of Philip Avery 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 Philip Avery. Philip Avery 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
2.
Rabinovitch, Jason, et al.. (2024). Permeability Modeling of Mars Parachute Broadcloth Materials. 1 indexed citations
3.
Avery, Philip, et al.. (2024). Sensitivity Analysis and Validation of a Computational Framework for Supersonic Parachute Inflation Dynamics. AIAA Journal. 63(5). 1743–1763. 1 indexed citations
4.
Avery, Philip, et al.. (2022). Validation of a High-Fidelity Supersonic Parachute Inflation Dynamics Model and Best Practice. AIAA SCITECH 2022 Forum. 10 indexed citations
5.
Rabinovitch, Jason, et al.. (2022). Update: Modeling Supersonic Parachute Inflations for Mars Spacecraft. 7 indexed citations
6.
Ghnatios, Chady, et al.. (2022). Acceleration of a Physics-Based Machine Learning Approach for Modeling and Quantifying Model-Form Uncertainties and Performing Model Updating. Journal of Computing and Information Science in Engineering. 23(1). 10 indexed citations
7.
Avery, Philip, et al.. (2022). Dimensionality Reduction of Embedded Boundary Models for Problems with Large Shape Changes. AIAA SCITECH 2022 Forum. 1 indexed citations
8.
Avery, Philip, et al.. (2020). In situ adaptive reduction of nonlinear multiscale structural dynamics models. International Journal for Numerical Methods in Engineering. 121(22). 4971–4988. 20 indexed citations
9.
Rabinovitch, Jason, et al.. (2019). Towards a Validated FSI Computational Framework for Supersonic Parachute Deployments. AIAA Aviation 2019 Forum. 5 indexed citations
10.
Avery, Philip, et al.. (2019). Studies into Computational Modeling of Fabric in Inflatable Structures. AIAA Scitech 2019 Forum. 1 indexed citations
11.
Huang, Daniel Zhengyu, et al.. (2019). Mesh adaptation framework for embedded boundary methods for computational fluid dynamics and fluid‐structure interaction. International Journal for Numerical Methods in Fluids. 90(8). 389–424. 33 indexed citations
12.
Peterson, Lee D., et al.. (2018). Model Verification and Validation Assessment for a Simulation of Supersonic Parachute Inflation during Martian Entry. 2018 AIAA Aerospace Sciences Meeting. 5 indexed citations
13.
Toivanen, Jari, Philip Avery, & Charbel Farhat. (2018). A multilevel FETI‐DP method and its performance for problems with billions of degrees of freedom. International Journal for Numerical Methods in Engineering. 116(10-11). 661–682. 21 indexed citations
14.
Grimberg, Sebastian, et al.. (2018). An Adaptive Mesh Refinement Concept for Viscous Fluid-Structure Computations Using Eulerian Vertex-Based Finite Volume Methods. 2018 AIAA Aerospace Sciences Meeting. 9 indexed citations
15.
Zahr, Matthew J., Philip Avery, & Charbel Farhat. (2017). A multilevel projection‐based model order reduction framework for nonlinear dynamic multiscale problems in structural and solid mechanics. International Journal for Numerical Methods in Engineering. 112(8). 855–881. 39 indexed citations
16.
Watson, Robert J., et al.. (2015). Phase noise analysis in FMCW radar systems. 501–504. 21 indexed citations
17.
Ghosh, Debraj, Philip Avery, & Charbel Farhat. (2009). A FETI‐preconditioned conjugate gradient method for large‐scale stochastic finite element problems. International Journal for Numerical Methods in Engineering. 80(6-7). 914–931. 32 indexed citations
18.
Avery, Philip, et al.. (2006). Incorporation of linear multipoint constraints in domain-decomposition-based iterative solvers – Part II: Blending FETI-DP and mortar methods and assembling floating substructures. Computer Methods in Applied Mechanics and Engineering. 196(8). 1347–1368. 13 indexed citations
19.
Avery, Philip, Mahen Mahendran, & Atikah Mohd Nasir. (2000). Flexural capacity of hollow flange beams. Journal of Constructional Steel Research. 53(2). 201–223. 30 indexed citations
20.
Avery, Philip & Mahen Mahendran. (1997). Finite-Element Analysis of Hollow Flange Beams with Web Stiffeners. Journal of Structural Engineering. 123(9). 1123–1129. 2 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026