James M. Larsen

609 total citations
26 papers, 477 citations indexed

About

James M. Larsen is a scholar working on Mechanical Engineering, Mechanics of Materials and Materials Chemistry. According to data from OpenAlex, James M. Larsen has authored 26 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Mechanical Engineering, 15 papers in Mechanics of Materials and 6 papers in Materials Chemistry. Recurrent topics in James M. Larsen's work include Fatigue and fracture mechanics (12 papers), High Temperature Alloys and Creep (9 papers) and Titanium Alloys Microstructure and Properties (5 papers). James M. Larsen is often cited by papers focused on Fatigue and fracture mechanics (12 papers), High Temperature Alloys and Creep (9 papers) and Titanium Alloys Microstructure and Properties (5 papers). James M. Larsen collaborates with scholars based in United States. James M. Larsen's co-authors include Sushant K. Jha, Reji John, J. Wayne Jones, L. Christodoulou, C. J. Szczepanski, James T. Burns, Richard P. Gangloff, Theodore Nicholas, Dennis J. Buchanan and M. J. Marcinkowski and has published in prestigious journals such as Acta Materialia, Materials Science and Engineering A and Scripta Materialia.

In The Last Decade

James M. Larsen

24 papers receiving 460 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James M. Larsen United States 13 392 243 227 58 56 26 477
B. Tabernig Austria 11 567 1.4× 163 0.7× 232 1.0× 46 0.8× 49 0.9× 17 654
L. J. Ghosn United States 9 262 0.7× 188 0.8× 81 0.4× 24 0.4× 48 0.9× 19 321
Zihua Zhao China 15 417 1.1× 201 0.8× 194 0.9× 32 0.6× 103 1.8× 45 495
Sushant K. Jha United States 9 273 0.7× 212 0.9× 234 1.0× 64 1.1× 34 0.6× 17 383
W. A. Logsdon United States 13 457 1.2× 396 1.6× 195 0.9× 66 1.1× 131 2.3× 25 614
Masaaki Yamashita Japan 7 203 0.5× 278 1.1× 160 0.7× 38 0.7× 36 0.6× 29 402
R. H. Van Stone United States 8 348 0.9× 232 1.0× 229 1.0× 57 1.0× 100 1.8× 12 424
A.T. Stewart United Kingdom 6 247 0.6× 305 1.3× 209 0.9× 109 1.9× 44 0.8× 6 421
Masahiro JONO Japan 10 296 0.8× 414 1.7× 152 0.7× 53 0.9× 36 0.6× 84 500
N Parida India 12 277 0.7× 238 1.0× 108 0.5× 69 1.2× 47 0.8× 24 393

Countries citing papers authored by James M. Larsen

Since Specialization
Citations

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

Fields of papers citing papers by James M. Larsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James M. Larsen. 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 James M. Larsen. The network helps show where James M. Larsen may publish in the future.

Co-authorship network of co-authors of James M. Larsen

This figure shows the co-authorship network connecting the top 25 collaborators of James M. Larsen. A scholar is included among the top collaborators of James M. Larsen 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 James M. Larsen. James M. Larsen 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.
Larsen, James M., Matthew Grace, Andrew Baczewski, & Alicia Magann. (2023). Feedback-based Quantum Algorithms for Ground State Preparation of the Fermi-Hubbard Model. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
2.
3.
Jha, Sushant K., C. J. Szczepanski, Reji John, & James M. Larsen. (2014). Deformation heterogeneities and their role in life-limiting fatigue failures in a two-phase titanium alloy. Acta Materialia. 82. 378–395. 78 indexed citations
4.
Hutson, Alisha L., Sushant K. Jha, William J. Porter, & James M. Larsen. (2014). Activation of life-limiting fatigue damage mechanisms in Ti–6Al–2Sn–4Zr–6Mo. International Journal of Fatigue. 66. 1–10. 4 indexed citations
5.
Jha, Sushant K., Reji John, & James M. Larsen. (2013). Incorporating small fatigue crack growth in probabilistic life prediction: Effect of stress ratio in Ti–6Al–2Sn–4Zr–6Mo. International Journal of Fatigue. 51. 83–95. 23 indexed citations
6.
Burns, James T., James M. Larsen, & Richard P. Gangloff. (2011). Effect of initiation feature on microstructure-scale fatigue crack propagation in Al–Zn–Mg–Cu. International Journal of Fatigue. 42. 104–121. 53 indexed citations
7.
John, Reji, Dennis J. Buchanan, Sushant K. Jha, & James M. Larsen. (2009). Stability of shot-peen residual stresses in an α+β titanium alloy. Scripta Materialia. 61(4). 343–346. 27 indexed citations
8.
Millwater, Harry, Reji John, James M. Larsen, & Dennis J. Buchanan. (2008). Probabilistic Modeling of Residual Stress Data in IN100. 5 indexed citations
9.
Larsen, James M., et al.. (2004). Demonstration of advanced life-prediction and state-awareness technologies necessary for prognosis of turbine engine disks. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5394. 23–23. 4 indexed citations
10.
Jha, Sushant K., et al.. (2004). The role of competing mechanisms in the fatigue life variability of a nearly fully-lamellar ?-TiAl based alloy. Acta Materialia. 53(5). 1293–1304. 47 indexed citations
11.
Larsen, James M., et al.. (2003). The Role of Spectrum Loading in Damage-Tolerance Life-Management of Fracture Critical Turbine Engine Components. Defense Technical Information Center (DTIC). 2 indexed citations
12.
Harmon, David, et al.. (1999). Evaluation of the MMCLIFE 3.0 code in predicting crack growth in titanium aluminide composites. Metallurgical and Materials Transactions A. 30(2). 287–299. 2 indexed citations
13.
John, Reji, Dennis J. Buchanan, & James M. Larsen. (1998). Prediction of transverse fatigue behavior of unidirectionally reinforced metal matrix composites. Scripta Materialia. 39(11). 1529–1536. 1 indexed citations
14.
15.
Larsen, James M., et al.. (1995). Time dependent degradation of fiber/matrix interfaces under fatigue of SCS-6/timetal®21S. Scripta Metallurgica et Materialia. 33(6). 939–944. 6 indexed citations
16.
Larsen, James M., et al.. (1995). An evaluation of fiber-reinforced titanium matrix composites for advanced high-temperature aerospace applications. Metallurgical and Materials Transactions A. 26(12). 3211–3223. 47 indexed citations
17.
Larsen, James M., et al.. (1995). Effects of microstructure and temperature on fatigue crack growth in the TiAl alloy Ti-46.5Al-3Nb-2Cr-0.2W. Materials Science and Engineering A. 192-193. 457–464. 41 indexed citations
18.
Larsen, James M., et al.. (1992). An Overview of Potential Titanium Aluminide Composites in Aerospace Applications. MRS Proceedings. 273. 12 indexed citations
19.
Larsen, James M.. (1990). The Effects of Slip Character and Crack Closure on the Growth of Small Fatigue Cracks in Titanium-Aluminium Alloys. Defense Technical Information Center (DTIC). 7 indexed citations
20.
Larsen, James M. & Theodore Nicholas. (1985). Cumulative-damage modeling of fatigue crack growth in turbine engine materials. Engineering Fracture Mechanics. 22(4). 713–730. 25 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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