James Goss

2.2k total citations
53 papers, 1.8k citations indexed

About

James Goss is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Mechanical Engineering. According to data from OpenAlex, James Goss has authored 53 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Electrical and Electronic Engineering, 27 papers in Control and Systems Engineering and 22 papers in Mechanical Engineering. Recurrent topics in James Goss's work include Electric Motor Design and Analysis (42 papers), Magnetic Bearings and Levitation Dynamics (24 papers) and Magnetic Properties and Applications (21 papers). James Goss is often cited by papers focused on Electric Motor Design and Analysis (42 papers), Magnetic Bearings and Levitation Dynamics (24 papers) and Magnetic Properties and Applications (21 papers). James Goss collaborates with scholars based in United Kingdom, Italy and China. James Goss's co-authors include Mircea Popescu, Yew Chuan Chong, Dave Staton, D.A. Staton, Aldo Boglietti, D. Hawkins, James D. Widmer, Mohammad Kimiabeigi, Rafał Wróbel and Phil Mellor and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Industry Applications and Journal for the Scientific Study of Religion.

In The Last Decade

James Goss

51 papers receiving 1.7k 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 Goss United Kingdom 23 1.5k 869 728 714 173 53 1.8k
Yew Chuan Chong United Kingdom 16 1.0k 0.7× 686 0.8× 490 0.7× 438 0.6× 110 0.6× 39 1.3k
James D. Widmer United Kingdom 24 1.5k 1.0× 707 0.8× 924 1.3× 701 1.0× 206 1.2× 53 1.8k
Dave Staton United Kingdom 17 1.0k 0.7× 627 0.7× 463 0.6× 507 0.7× 80 0.5× 37 1.1k
Michele Degano United Kingdom 27 2.0k 1.3× 569 0.7× 1.1k 1.6× 700 1.0× 156 0.9× 174 2.3k
Glynn Atkinson United Kingdom 17 1.9k 1.2× 523 0.6× 1.1k 1.5× 571 0.8× 181 1.0× 64 2.2k
Silvio Vaschetto Italy 24 1.9k 1.2× 731 0.8× 849 1.2× 723 1.0× 147 0.8× 129 2.1k
Pia Lindh Finland 19 1.1k 0.7× 512 0.6× 639 0.9× 588 0.8× 81 0.5× 78 1.2k
Christof Zwyssig Switzerland 21 1.0k 0.7× 575 0.7× 667 0.9× 252 0.4× 48 0.3× 44 1.3k
Shafigh Nategh Sweden 15 776 0.5× 515 0.6× 325 0.4× 422 0.6× 72 0.4× 45 917
Rong‐Jie Wang South Africa 21 1.9k 1.3× 501 0.6× 1.4k 2.0× 652 0.9× 81 0.5× 97 2.1k

Countries citing papers authored by James Goss

Since Specialization
Citations

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

Fields of papers citing papers by James Goss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Goss

This figure shows the co-authorship network connecting the top 25 collaborators of James Goss. A scholar is included among the top collaborators of James Goss 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 Goss. James Goss 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.
Liu, Chuan, Zeyuan Xu, David Gerada, et al.. (2022). Experimental Investigation of Oil Jet Cooling in Electrical Machines With Hairpin Windings. IEEE Transactions on Transportation Electrification. 9(1). 598–608. 17 indexed citations
2.
Liu, Chuan, David Gerada, Zeyuan Xu, et al.. (2020). Estimation of Oil Spray Cooling Heat Transfer Coefficients on Hairpin Windings With Reduced-Parameter Models. IEEE Transactions on Transportation Electrification. 7(2). 793–803. 50 indexed citations
3.
Gai, Yaohui, et al.. (2020). Thermal Analysis of an Oil-Cooled Shaft for a 30 000 r/min Automotive Traction Motor. IEEE Transactions on Industry Applications. 56(6). 6053–6061. 15 indexed citations
4.
Liu, Chuan, Zeyuan Xu, David Gerada, et al.. (2019). Experimental Investigation on Oil Spray Cooling With Hairpin Windings. IEEE Transactions on Industrial Electronics. 67(9). 7343–7353. 141 indexed citations
5.
Gai, Yaohui, James D. Widmer, A. Steven, et al.. (2019). Numerical and Experimental Calculation of CHTC in an Oil-Based Shaft Cooling System for a High-Speed High-Power PMSM. IEEE Transactions on Industrial Electronics. 67(6). 4371–4380. 44 indexed citations
6.
Volpe, Giuseppe, Mircea Popescu, Fabrizio Marignetti, & James Goss. (2019). AC Winding Losses in Automotive Traction E-Machines: A New Hybrid Calculation Method. 2115–2119. 43 indexed citations
7.
Gai, Yaohui, et al.. (2019). Power Losses and Thermal Analysis of a Hollow-Shaft Rotor Cooling System. 1–6. 12 indexed citations
8.
Volpe, Giuseppe, et al.. (2019). Modified 2-D Model for 3-D Rotor Magnet Leakage Effects in PM Spoke Machines. IEEE Transactions on Industry Applications. 55(3). 3087–3096. 3 indexed citations
9.
Gai, Yaohui, Mohammad Kimiabeigi, Yew Chuan Chong, et al.. (2018). Cooling of Automotive Traction Motors: Schemes, Examples, and Computation Methods. IEEE Transactions on Industrial Electronics. 66(3). 1681–1692. 249 indexed citations
10.
Gai, Yaohui, Mohammad Kimiabeigi, Yew Chuan Chong, et al.. (2018). On the Measurement and Modeling of the Heat Transfer Coefficient of a Hollow-Shaft Rotary Cooling System for a Traction Motor. IEEE Transactions on Industry Applications. 54(6). 5978–5987. 50 indexed citations
11.
Goss, James, et al.. (2017). Improved thermal model for predicting end-windings heat transfer. 4650–4657. 12 indexed citations
12.
Volpe, Giuseppe, et al.. (2017). High-Performance Electric Motor for Motor Sport Application. 1–5. 12 indexed citations
13.
Kimiabeigi, Mohammad, B.C. Mecrow, James D. Widmer, et al.. (2016). On Selection of Rotor Support Material for a Ferrite Magnet Spoke-Type Traction Motor. IEEE Transactions on Industry Applications. 52(3). 2224–2233. 28 indexed citations
14.
Ayat, Sabrina, Rafał Wróbel, James Goss, & David Drury. (2016). Experiment informed methodology for thermal design of PM machines. Bristol Research (University of Bristol). 1–7. 22 indexed citations
15.
Kimiabeigi, Mohammad, James D. Widmer, Yi Gao, et al.. (2015). High-Performance Low-Cost Electric Motor for Electric Vehicles Using Ferrite Magnets. IEEE Transactions on Industrial Electronics. 63(1). 113–122. 118 indexed citations
16.
Popescu, Mircea, Dave Staton, Aldo Boglietti, et al.. (2015). Modern heat extraction systems for electrical machines - A review. 289–296. 60 indexed citations
17.
Goss, James, Mircea Popescu, & Dave Staton. (2013). A comparison of an interior permanent magnet and copper rotor induction motor in a hybrid electric vehicle application. 220–225. 74 indexed citations
18.
Goss, James, et al.. (2012). The design of AC permanent magnet motors for electric vehicles: a computationally efficient model of the operational envelope. Bristol Research (University of Bristol). B21–B21. 59 indexed citations
19.
Laul, J. C., et al.. (2005). Perspectives on chemical hazard characterization and analysis process at DOE. ACS Chemical Health & Safety. 13(4). 6–39. 10 indexed citations
20.
Goss, James. (1974). Camus, God, and Process Thought. Process Studies. 4(2). 114–128.

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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