K.P. Padmanaban

630 total citations
30 papers, 472 citations indexed

About

K.P. Padmanaban is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Computational Mechanics. According to data from OpenAlex, K.P. Padmanaban has authored 30 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Mechanical Engineering, 15 papers in Industrial and Manufacturing Engineering and 12 papers in Computational Mechanics. Recurrent topics in K.P. Padmanaban's work include Manufacturing Process and Optimization (15 papers), Advanced Numerical Analysis Techniques (8 papers) and Advanced Measurement and Metrology Techniques (7 papers). K.P. Padmanaban is often cited by papers focused on Manufacturing Process and Optimization (15 papers), Advanced Numerical Analysis Techniques (8 papers) and Advanced Measurement and Metrology Techniques (7 papers). K.P. Padmanaban collaborates with scholars based in India, United States and China. K.P. Padmanaban's co-authors include G. Prabhaharan, R. Krishnakumar, G. Prabhakaran, S. Selvakumar, T. Ramachandran, K. Santhy, D. Vasudevan, C. Balamurugan, V. Senthil and M. Uthayakumar and has published in prestigious journals such as International Journal of Production Research, The International Journal of Advanced Manufacturing Technology and Structural and Multidisciplinary Optimization.

In The Last Decade

K.P. Padmanaban

29 papers receiving 440 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K.P. Padmanaban India 13 303 272 98 80 75 30 472
Yann Ledoux France 13 184 0.6× 225 0.8× 75 0.8× 123 1.5× 44 0.6× 41 417
Alžbeta Sapietová Slovakia 13 140 0.5× 323 1.2× 43 0.4× 73 0.9× 46 0.6× 61 457
Huamin Zhou China 11 87 0.3× 194 0.7× 36 0.4× 65 0.8× 32 0.4× 37 335
Susana Martínez-Pellitero Spain 15 150 0.5× 512 1.9× 93 0.9× 176 2.2× 104 1.4× 45 671
Mehdi Tlija Saudi Arabia 11 214 0.7× 164 0.6× 49 0.5× 159 2.0× 77 1.0× 84 459
Huang Gao China 15 168 0.6× 413 1.5× 90 0.9× 88 1.1× 93 1.2× 20 567
Haixi Wu China 6 215 0.7× 286 1.1× 32 0.3× 269 3.4× 47 0.6× 13 421
Knut Großmann Germany 10 90 0.3× 273 1.0× 48 0.5× 46 0.6× 60 0.8× 86 374
Xuwen Jing China 12 235 0.8× 229 0.8× 19 0.2× 23 0.3× 63 0.8× 41 444
Roudy Wehbe United States 10 102 0.3× 211 0.8× 34 0.3× 95 1.2× 36 0.5× 17 431

Countries citing papers authored by K.P. Padmanaban

Since Specialization
Citations

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

Fields of papers citing papers by K.P. Padmanaban

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K.P. Padmanaban. 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 K.P. Padmanaban. The network helps show where K.P. Padmanaban may publish in the future.

Co-authorship network of co-authors of K.P. Padmanaban

This figure shows the co-authorship network connecting the top 25 collaborators of K.P. Padmanaban. A scholar is included among the top collaborators of K.P. Padmanaban 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 K.P. Padmanaban. K.P. Padmanaban 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.
Santhy, K., et al.. (2020). Influence of Mechanical Properties on Modal Analysis of Natural Fiber Reinforced Laminated Composite Trapezoidal Plates. Journal of Natural Fibers. 18(12). 2139–2155. 26 indexed citations
2.
Padmanaban, K.P., et al.. (2018). Optimisation of free vibration analysis on structural plates of fibre reinforced laminated composites. International Journal of Rapid Manufacturing. 8(1/2). 65–65. 2 indexed citations
3.
Padmanaban, K.P., et al.. (2016). Design and optimization of concurrent tolerance in mechanical assemblies using bat algorithm. Journal of Mechanical Science and Technology. 30(6). 2601–2614. 23 indexed citations
4.
Padmanaban, K.P., et al.. (2016). Experimental studies on variable compression ratio engine fuelled with cottonseed oil methyl ester biodiesel. International Journal of Oil Gas and Coal Technology. 12(1). 81–81. 6 indexed citations
5.
Padmanaban, K.P., et al.. (2015). Laminar Wall Jet Flow and Heat Transfer over a Shallow Cavity. The Scientific World JOURNAL. 2015(1). 926249–926249. 3 indexed citations
6.
Ramachandran, T., et al.. (2015). Experimental Investigation of Static and Dynamic Properties of Steel–Rubber, Cast Iron–Rubber and Epoxy Granite–Rubber as IC Engine Mount. Transactions of the Indian Institute of Metals. 68(S1). 83–86. 3 indexed citations
7.
Kanna, P. Rajesh, et al.. (2015). Numerical Investigation of Forced Convection Heat Transfer from Offset Square Cylinders Placed in a Three Dimensional Confined Channel. Applied Mechanics and Materials. 813-814. 729–735. 2 indexed citations
8.
Padmanaban, K.P., et al.. (2014). Prediction of Machining Fixture Layout through FEM and ANN and Comparison of Optimal Fixture Layouts of GA and ACA. International Review of Mechanical Engineering (IREME). 8(3). 537–546. 1 indexed citations
9.
Padmanaban, K.P., et al.. (2014). Neural Network Based Buckling Strength Prediction of Laminated Composite Plate with Central Cutout. Applied Mechanics and Materials. 592-594. 560–564. 2 indexed citations
10.
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12.
Padmanaban, K.P., et al.. (2014). Design and optimization of machining fixture layout for end-milling operation. The International Journal of Advanced Manufacturing Technology. 73(5-8). 669–679. 19 indexed citations
13.
Selvakumar, S., et al.. (2013). Machining fixture layout optimisation using genetic algorithm and artificial neural network. International Journal of Manufacturing Research. 8(2). 171–171. 19 indexed citations
14.
Selvakumar, S., et al.. (2012). Design and optimization of machining fixture layout using ANN and DOE. The International Journal of Advanced Manufacturing Technology. 65(9-12). 1573–1586. 53 indexed citations
15.
Ramachandran, T., et al.. (2012). Modeling and Analysis of IC Engine Rubber Mount Using Finite Element Method and RSM. Procedia Engineering. 38. 1683–1692. 14 indexed citations
16.
Padmanaban, K.P., et al.. (2012). Optimization of Dispersed Laminated Composite Plate for Maximum Safety Factor Using Genetic Algorithm and Various Failure Criteria. Procedia Engineering. 38. 1209–1217. 11 indexed citations
17.
Selvakumar, S., et al.. (2012). Mathematical approach for optimal machining fixture layout and clamping forces. Australian Journal of Mechanical Engineering. 10(1). 17–28. 2 indexed citations
18.
Padmanaban, K.P., et al.. (2010). Optimum design selection of jigs/fixtures using digraph and matrix methods. International Journal of Manufacturing Technology and Management. 20(1/2/3/4). 358–358. 3 indexed citations
19.
Padmanaban, K.P., et al.. (2009). Machining fixture layout design using ant colony algorithm based continuous optimization method. The International Journal of Advanced Manufacturing Technology. 45(9-10). 922–934. 64 indexed citations
20.
Padmanaban, K.P. & G. Prabhaharan. (2008). Dynamic analysis on optimal placement of fixturing elements using evolutionary techniques. International Journal of Production Research. 46(15). 4177–4214. 32 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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