Jack J. McNamara
- Computational Mechanics top 0.5%
- Aerospace Engineering top 1%
- Statistics, Probability and Uncertainty top 0.5%
- Statistical and Nonlinear Physics top 2%
- Applied Mathematics top 2%
- Co-authors
- Peretz P. FriedmannAdam J. CullerAndrew CrowellBrent A. MillerDatta V. GaitondeKirk R. BrouwerAbhijit GogulapatiVilas Shinde
- Topics
- Computational Fluid Dynamics and Aerodynamics (83 papers)Fluid Dynamics and Turbulent Flows (64 papers)Fluid Dynamics and Vibration Analysis (32 papers)
- Journals
- Chemistry of MaterialsJournal of Fluid MechanicsComputer Methods in Applied Mechanics and Engineering
- Partner nations
- United StatesAustraliaJapan
In The Last Decade
Jack J. McNamara
130 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Computational Mechanics 1.9k
- Aerospace Engineering 1.1k
- Statistics, Probability and Uncertainty 492
- Statistical and Nonlinear Physics 394
- Applied Mathematics 387
Countries citing papers authored by Jack J. McNamara
This map shows the geographic impact of Jack J. McNamara'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 Jack J. McNamara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack J. McNamara more than expected).
Fields of papers citing papers by Jack J. McNamara
This network shows the impact of papers produced by Jack J. McNamara. 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 Jack J. McNamara. The network helps show where Jack J. McNamara may publish in the future.
Co-authorship network of co-authors of Jack J. McNamara
This figure shows the co-authorship network connecting the top 25 collaborators of Jack J. McNamara. A scholar is included among the top collaborators of Jack J. McNamara 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 Jack J. McNamara. Jack J. McNamara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 8 | |
| 12 | 2 | |
| 13 | 10 | |
| 14 | 37 | |
| 15 | COUPLED REDUCED ORDER MODEL-BASED STRUCTURAL-THERMAL PREDICTION OF HYPERSONIC PANEL RESPONSE | 3 |
| 16 | 14 | |
| 17 | 10 | |
| 18 | 4 | |
| 19 | 26 | |
| 20 | 32 |
About Jack J. McNamara
Jack J. McNamara is a scholar working on Computational Mechanics, Statistics, Probability and Uncertainty and Aerospace Engineering, having authored 138 papers that have together received 2.8k indexed citations. Recurring topics across this work include Computational Fluid Dynamics and Aerodynamics (83 papers), Fluid Dynamics and Turbulent Flows (64 papers) and Fluid Dynamics and Vibration Analysis (32 papers). The work is most often cited by research in Computational Mechanics (1.9k citations), Statistics, Probability and Uncertainty (492 citations) and Aerospace Engineering (1.1k citations). Jack J. McNamara has collaborated with scholars based in United States, Australia and Japan. Frequent co-authors include Peretz P. Friedmann, Adam J. Culler, Andrew Crowell, Brent A. Miller, Datta V. Gaitonde, Kirk R. Brouwer, Abhijit Gogulapati, Vilas Shinde, Kenneth G. Powell and Robert E. Bartels. Their work appears in journals such as Chemistry of Materials, Journal of Fluid Mechanics and Computer Methods in Applied Mechanics and Engineering.
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.