Sukanta Dash

2.0k total citations
149 papers, 1.6k citations indexed

About

Sukanta Dash is a scholar working on Computational Mechanics, Aerospace Engineering and Applied Mathematics. According to data from OpenAlex, Sukanta Dash has authored 149 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Computational Mechanics, 78 papers in Aerospace Engineering and 34 papers in Applied Mathematics. Recurrent topics in Sukanta Dash's work include Computational Fluid Dynamics and Aerodynamics (87 papers), Fluid Dynamics and Turbulent Flows (46 papers) and Aerodynamics and Acoustics in Jet Flows (38 papers). Sukanta Dash is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (87 papers), Fluid Dynamics and Turbulent Flows (46 papers) and Aerodynamics and Acoustics in Jet Flows (38 papers). Sukanta Dash collaborates with scholars based in United States, India and Morocco. Sukanta Dash's co-authors include Donald Kenzakowski, John Seiner, Neeraj Sinha, David E. Wolf, Ashvin Hosangadi, B. YORK, Srinivasan Arunajatesan, Abhijit Kar, Avinash Singh Patel and Richard G. Wilmoth and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Frontiers in Plant Science.

In The Last Decade

Sukanta Dash

135 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sukanta Dash United States 21 1.2k 954 255 120 108 149 1.6k
P. K. Khosla United States 18 863 0.7× 159 0.2× 106 0.4× 71 0.6× 374 3.5× 96 1.8k
Robert E. Wilson United States 15 225 0.2× 299 0.3× 85 0.3× 115 1.0× 32 0.3× 58 779
Hao Xia United Kingdom 19 775 0.7× 554 0.6× 12 0.0× 132 1.1× 19 0.2× 95 1.1k
Huaibao Zhang China 15 215 0.2× 139 0.1× 234 0.9× 17 0.1× 40 0.4× 37 490
Aditi Sengupta India 17 499 0.4× 158 0.2× 21 0.1× 40 0.3× 154 1.4× 63 767
W. M. Rutherford United States 17 357 0.3× 205 0.2× 14 0.1× 11 0.1× 64 0.6× 61 863
Xu Zhou China 23 283 0.2× 159 0.2× 15 0.1× 64 0.5× 171 1.6× 83 1.5k
Julia Keller Switzerland 15 391 0.3× 166 0.2× 4 0.0× 60 0.5× 77 0.7× 30 690

Countries citing papers authored by Sukanta Dash

Since Specialization
Citations

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

Fields of papers citing papers by Sukanta Dash

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sukanta Dash

This figure shows the co-authorship network connecting the top 25 collaborators of Sukanta Dash. A scholar is included among the top collaborators of Sukanta Dash 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 Sukanta Dash. Sukanta Dash 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.
Dash, Sukanta. (2025). AI Shishya: Enhancing Vedic Pedagogy with Artificial Intelligence in Education 4.0.. The Journal of Educators Online. 22(1).
2.
Dash, Sukanta, et al.. (2024). Construction of Balanced Semi-Latin Rectangles in block size four: An Algorithmic Approach. Journal of Statistical Theory and Practice. 18(3). 1 indexed citations
3.
Ranjani, M., et al.. (2024). Ultrasonication-assisted polyol-osmosed persimmon candies: effect of ultrasonication and drying techniques on product quality. Sustainable Food Technology. 3(1). 322–332. 1 indexed citations
4.
Singh, Rajiv Kumar, et al.. (2024). Studies on comparison of nano-urea and prilled urea for enhancing maize (Zea mays) growth and productivity. SHILAP Revista de lepidopterología. 94(3). 325–328. 3 indexed citations
5.
Upadhyay, Pravin Kumar, Vinod Kumar Singh, G. A. Rajanna, et al.. (2023). Unveiling the combined effect of nano fertilizers and conventional fertilizers on crop productivity, profitability, and soil well-being. Frontiers in Sustainable Food Systems. 7. 20 indexed citations
6.
Rudra, Shalini Gaur, et al.. (2023). Baked crisps from Indian biofortified lentils: Effect of seed coat on rheology, texture and composition. Applied Food Research. 4(1). 100380–100380. 5 indexed citations
7.
Kundu, Aditi, Anirban Dutta, Abhishek Mandal, et al.. (2021). A Comprehensive in vitro and in silico Analysis of Nematicidal Action of Essential Oils. Frontiers in Plant Science. 11. 614143–614143. 58 indexed citations
8.
Dutta, Anirban, Abhishek Mandal, Aditi Kundu, et al.. (2021). Deciphering the Behavioral Response of Meloidogyne incognita and Fusarium oxysporum Toward Mustard Essential Oil. Frontiers in Plant Science. 12. 714730–714730. 22 indexed citations
9.
Patel, Avinash Singh, et al.. (2021). Process optimization for the supercritical carbondioxide extraction of lycopene from ripe grapefruit (Citrus paradisi) endocarp. Scientific Reports. 11(1). 10273–10273. 31 indexed citations
10.
Patel, Avinash Singh, Abhijit Kar, Sukanta Dash, & Sanjaya K. Dash. (2019). Supercritical fluid extraction of β-carotene from ripe bitter melon pericarp. Scientific Reports. 9(1). 19266–19266. 32 indexed citations
11.
Dash, Sukanta, et al.. (2009). An Empirical Investigation on Classical Clustering Methods. SSRN Electronic Journal. 1 indexed citations
12.
Seiner, John, Sukanta Dash, & Donald Kenzakowski. (1999). Historical survey on enhanced mixing in scramjet engines. 22 indexed citations
13.
Kenzakowski, Donald, B. YORK, & Sukanta Dash. (1997). Computational simulation of ejection seat aerodynamics with rocket propulsive effects. 3 indexed citations
14.
Dash, Sukanta, et al.. (1993). Recent developments in the simulation of steady and transient transverse jet interactions for missile, rotorcraft, and propulsive applications. In AGARD. 5 indexed citations
15.
Hosangadi, Ashvin, B. YORK, Neeraj Sinha, & Sukanta Dash. (1993). Progress in transient interior ballistic flowfield simulations usingmulti-dimensional upwind/implicit numerics. 29th Joint Propulsion Conference and Exhibit. 5 indexed citations
16.
Dash, Sukanta & Neeraj Sinha. (1992). Exhaust plumes and their interaction with missile airframes - A new viewpoint. NASA STI/Recon Technical Report A. 92. 649–756. 6 indexed citations
17.
Dash, Sukanta & David E. Wolf. (1984). Fully-coupled analysis of jet mixing problems. Part 1. Shock-capturing model, SCIPVIS. NASA STI Repository (National Aeronautics and Space Administration). 84. 15425. 10 indexed citations
18.
Dash, Sukanta, et al.. (1978). Shock capturing finite-difference and characteristic reference plane techniques for the prediction of three-dimensional nozzle-exhaust flowfields. NASA STI Repository (National Aeronautics and Space Administration). 78. 25355. 1 indexed citations
19.
Dash, Sukanta, et al.. (1978). A computational model for the prediction of jet entrainment in the vicinity of nozzle boattails (The BOAT code). NASA STI Repository (National Aeronautics and Space Administration). 79. 14326. 21 indexed citations
20.
Dash, Sukanta, et al.. (1975). An improved numerical procedure for the parametric optimization of three dimensional scramjet nozzles. NASA STI/Recon Technical Report N. 75. 29359. 1 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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