R.S. Ransing

1.1k total citations
57 papers, 834 citations indexed

About

R.S. Ransing is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Computational Mechanics. According to data from OpenAlex, R.S. Ransing has authored 57 papers receiving a total of 834 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Mechanical Engineering, 19 papers in Industrial and Manufacturing Engineering and 13 papers in Computational Mechanics. Recurrent topics in R.S. Ransing's work include Manufacturing Process and Optimization (17 papers), Metal Forming Simulation Techniques (9 papers) and Metallurgy and Material Forming (8 papers). R.S. Ransing is often cited by papers focused on Manufacturing Process and Optimization (17 papers), Metal Forming Simulation Techniques (9 papers) and Metallurgy and Material Forming (8 papers). R.S. Ransing collaborates with scholars based in United Kingdom, Malaysia and Iraq. R.S. Ransing's co-authors include R. W. Lewis, D.T. Gethin, Cinzia Giannetti, Nazri Mohd Nawi, William Pao, Roland W. Lewis, A.R. Khoei, A. J. L. Crook, M. Dutko and Javier Bonet and has published in prestigious journals such as International Journal for Numerical Methods in Engineering, Journal of Materials Processing Technology and International Journal of Production Research.

In The Last Decade

R.S. Ransing

55 papers receiving 785 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
R.S. Ransing United Kingdom	17	405	174	167	125	114	57	834
Leshi Shu China	21	464 1.1×	106 0.6×	181 1.1×	100 0.8×	72 0.6×	64	1.1k
В. Д. Калыанкар India	15	626 1.5×	60 0.3×	133 0.8×	92 0.7×	79 0.7×	41	975
Stoyan Stoyanov United Kingdom	16	235 0.6×	77 0.4×	152 0.9×	102 0.8×	45 0.4×	133	875
Beom-Seon Jang South Korea	18	386 1.0×	215 1.2×	70 0.4×	241 1.9×	113 1.0×	95	927
Shaohua Dong China	17	293 0.7×	58 0.3×	71 0.4×	101 0.8×	49 0.4×	71	730
Dong-Hoon Choi South Korea	22	644 1.6×	101 0.6×	98 0.6×	357 2.9×	88 0.8×	92	1.3k
Longchao Cao China	25	1.4k 3.4×	194 1.1×	384 2.3×	247 2.0×	107 0.9×	73	1.9k
Hyun Chung South Korea	20	547 1.4×	39 0.2×	147 0.9×	161 1.3×	110 1.0×	78	1.3k
Xiaowei Yue United States	18	239 0.6×	57 0.3×	237 1.4×	83 0.7×	30 0.3×	55	796
Jüri Majak Estonia	23	236 0.6×	130 0.7×	117 0.7×	496 4.0×	32 0.3×	78	1.3k

Countries citing papers authored by R.S. Ransing

Since Specialization

Citations

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

Fields of papers citing papers by R.S. Ransing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R.S. Ransing. 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 R.S. Ransing. The network helps show where R.S. Ransing may publish in the future.

Co-authorship network of co-authors of R.S. Ransing

This figure shows the co-authorship network connecting the top 25 collaborators of R.S. Ransing. A scholar is included among the top collaborators of R.S. Ransing 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 R.S. Ransing. R.S. Ransing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ransing, R.S., et al.. (2023). A novel imputation based predictive algorithm for reducing common cause variation from small and mixed datasets with missing values. Computers & Industrial Engineering. 179. 109230–109230. 3 indexed citations

Mahmoodi, P., et al.. (2016). Comparison of point foot, collisional and smooth rolling contact models on the bifurcations and stability of bipedal walking. European Journal of Computational Mechanics. 25(3). 273–293. 7 indexed citations

Ransing, R.S., et al.. (2016). A bootstrap method for uncertainty estimation in quality correlation algorithm for risk based tolerance synthesis. Computers & Industrial Engineering. 112. 654–662. 1 indexed citations

Giannetti, Cinzia, et al.. (2016). Knowledge management and knowledge discovery for process improvement and sustainable manufacturing: a foundry case study. 7(2). 554. 4 indexed citations

Ransing, R.S., et al.. (2015). Seven Steps to Energy Efficiency for Foundries. 143(3). 24. 2 indexed citations

Mahmoodi, P., R.S. Ransing, & Michael I. Friswell. (2015). A novel mathematical formulation for predicting symmetric passive bipedal walking motion with unbalanced masses. Applied Mathematical Modelling. 40(5-6). 3895–3906. 4 indexed citations

Mahmoodi, P., R.S. Ransing, & Michael I. Friswell. (2013). Modelling the effect of ‘heel to toe’ roll-over contact on the walking dynamics of passive biped robots. Applied Mathematical Modelling. 37(12-13). 7352–7373. 17 indexed citations

Ransing, R.S., et al.. (2013). Challenges Faced by a Small Ship Yard in Integrating Computer Aided Design and Production Processes – A Real Life Case Study. 107–114.

Nawi, Nazri Mohd, et al.. (2010). BPGD-AG: A New Improvement Of Back-Propagation Neural Network Learning Algorithms With Adaptive Gain. 2(2). 4 indexed citations

10.

Dyson, P. L., et al.. (2008). Fluid Properties at Nano/Meso Scale. 7 indexed citations

11.

Ransing, R.S.. (2007). Innovations in machine learning and defect diagnostics. Cronfa (Swansea University). 1 indexed citations

12.

Nawi, Nazri Mohd, et al.. (2006). An Improved Learning Algorithm Based on The Broyden-Fletcher-Goldfarb-Shanno (BFGS) Method For Back Propagation Neural Networks. 1. 152–157. 42 indexed citations

13.

Ransing, R.S.. (2005). Review of optimization methods for casting simulation. Cronfa (Swansea University). 1 indexed citations

14.

Ransing, R.S.. (2004). International Journal of Numerical Methods of Heat and Fluid Flow: Editorial. Cronfa (Swansea University). 1 indexed citations

15.

Ransing, R.S., et al.. (2003). On the limitations of neural network techniques for analysing cause and effect relationships in manufacturing processes - A case study. WIT transactions on information and communication technologies. 29. 1 indexed citations

16.

Ransing, R.S., et al.. (2000). Powder compaction modelling via the discrete and finite element method. Materials & Design (1980-2015). 21(4). 263–269. 82 indexed citations

17.

Ransing, R.S.. (1999). Modelling and simulation of the compaction of pharmaceutical powders. Cronfa (Swansea University). 1 indexed citations

18.

Lewis, R. W., et al.. (1998). Recent developments in heat transfer and porous media. WIT transactions on engineering sciences. 20. 3 indexed citations

19.

Ransing, R.S. & R. W. Lewis. (1997). A semantically constrained neural network for manufacturing diagnosis. International Journal of Production Research. 35(9). 2639–2660. 6 indexed citations

20.

Ransing, R.S., Mukundhan Srinivasan, & R. W. Lewis. (1995). ICADA: Intelligent computer aided defect analysis for castings. Journal of Intelligent Manufacturing. 6(1). 29–40. 14 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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