Arvind Keprate

479 total citations
52 papers, 299 citations indexed

About

Arvind Keprate is a scholar working on Mechanical Engineering, Mechanics of Materials and Statistics, Probability and Uncertainty. According to data from OpenAlex, Arvind Keprate has authored 52 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Mechanical Engineering, 24 papers in Mechanics of Materials and 10 papers in Statistics, Probability and Uncertainty. Recurrent topics in Arvind Keprate's work include Fatigue and fracture mechanics (20 papers), Structural Integrity and Reliability Analysis (18 papers) and Non-Destructive Testing Techniques (11 papers). Arvind Keprate is often cited by papers focused on Fatigue and fracture mechanics (20 papers), Structural Integrity and Reliability Analysis (18 papers) and Non-Destructive Testing Techniques (11 papers). Arvind Keprate collaborates with scholars based in Norway, India and United States. Arvind Keprate's co-authors include R. M. Chandima Ratnayake, Shankar Sankararaman, Subhamoy Sen, Knut Øvsthus, M. Salman Siddiqui, Gunjan Soni, Maneesh Singh, Arvind Kumar Bhatt, Vijay Kumar Thakur and Murari Lal Mittal and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Energy.

In The Last Decade

Arvind Keprate

46 papers receiving 292 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arvind Keprate Norway 11 127 107 46 45 39 52 299
Aihua Liu China 14 98 0.8× 64 0.6× 97 2.1× 91 2.0× 51 1.3× 34 513
Matthew Collette United States 13 122 1.0× 84 0.8× 142 3.1× 110 2.4× 80 2.1× 41 447
Hengfei Yang China 6 49 0.4× 61 0.6× 87 1.9× 80 1.8× 13 0.3× 9 246
Zhiqiang Hou China 11 86 0.7× 33 0.3× 66 1.4× 15 0.3× 67 1.7× 47 382
Haitao Bian China 10 73 0.6× 54 0.5× 21 0.5× 136 3.0× 36 0.9× 24 326
Renren Zhang China 11 180 1.4× 39 0.4× 151 3.3× 73 1.6× 73 1.9× 19 382
Guang‐Jun Jiang China 11 111 0.9× 41 0.4× 39 0.8× 21 0.5× 15 0.4× 37 315
Matti Niclas Scheu United Kingdom 8 70 0.6× 54 0.5× 74 1.6× 40 0.9× 91 2.3× 12 356
Penghui Lin Singapore 9 53 0.4× 29 0.3× 23 0.5× 124 2.8× 53 1.4× 17 307
Sidum Adumene Nigeria 13 193 1.5× 66 0.6× 227 4.9× 82 1.8× 138 3.5× 46 547

Countries citing papers authored by Arvind Keprate

Since Specialization
Citations

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

Fields of papers citing papers by Arvind Keprate

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arvind Keprate

This figure shows the co-authorship network connecting the top 25 collaborators of Arvind Keprate. A scholar is included among the top collaborators of Arvind Keprate 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 Arvind Keprate. Arvind Keprate 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.
Mian, Haris Hameed, Fadi Al Machot, Himayat Ullah, Arvind Keprate, & Muhammad Shoaib Siddiqui. (2025). Advances in computational intelligence for floating offshore wind turbines aerodynamics: Current state review and future potential. Renewable and Sustainable Energy Reviews. 224. 116098–116098. 3 indexed citations
2.
Komulainen, Tiina M., et al.. (2025). Comparison of ML and ASM models for effluent nutrient estimation in the Hias Process. Linköping electronic conference proceedings. 211.
3.
Soni, Gunjan, et al.. (2025). Reliability assessment of supply chain digital twin: an integrated Markov Chain and Bayesian Network approach. Life Cycle Reliability and Safety Engineering. 14(4). 665–678.
4.
5.
Solanki, Preeti, Chayanika Putatunda, Abhishek Walia, et al.. (2024). Recent advancements in biomass to bioenergy management and carbon capture through artificial intelligence integrated technologies to achieve carbon neutrality. Sustainable Energy Technologies and Assessments. 73. 104123–104123. 12 indexed citations
6.
Keprate, Arvind, et al.. (2024). Characterizing Damage in Wind Turbine Mooring Using a Data-Driven Predictor Model within a Particle Filtering Estimation Framework. PHM Society European Conference. 8(1). 8–8. 1 indexed citations
7.
Sharma, Nikhil, et al.. (2024). Multi-Objective Optimization for Economic and Environmental Sustainability in Apparel E-commerce Reverse Logistics. International Journal of Mathematical Engineering and Management Sciences. 9(1). 111–128. 1 indexed citations
8.
Keprate, Arvind, et al.. (2024). Towards Efficient Operation and Maintenance of Wind Farms: Leveraging AI for Minimizing Human Error. PHM Society European Conference. 8(1). 9–9. 1 indexed citations
9.
Siddiqui, M. Salman, Abdul Waheed Badar, Liang Yang, Muhammad Saeed, & Arvind Keprate. (2024). Qualitative Investigation of Wake Composition in Offshore Wind Turbines: A Combined Computational and Statistical Analysis of Inner and Outer Blade Sections. SHILAP Revista de lepidopterología. 487. 1001–1001.
10.
Mian, Haris Hameed, et al.. (2024). Predictive Modeling of Semi-Submersible Floater Motion Using Bi-LSTM Model. Journal of Physics Conference Series. 2875(1). 12029–12029. 1 indexed citations
11.
Keprate, Arvind, et al.. (2024). Data-driven approaches for deriving a soft sensor in a district heating network. Energy. 292. 130426–130426. 3 indexed citations
12.
13.
Singh, Maneesh, et al.. (2023). Fault detection of a wind turbine generator bearing using interpretable machine learning. Frontiers in Energy Research. 11. 10 indexed citations
14.
Komulainen, Tiina M., et al.. (2023). Estimation of effluent nutrients in municipal MBBR process. Linköping electronic conference proceedings. 2 indexed citations
15.
Keprate, Arvind, et al.. (2021). Exploratory Data Analysis of the N-CMAPSS Dataset for Prognostics. 2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). 1114–1121. 8 indexed citations
16.
Keprate, Arvind & R. M. Chandima Ratnayake. (2019). Vibration Induced Fatigue Integrity Evaluation of Small Bore Piping Using Belief network. The 29th International Ocean and Polar Engineering Conference. 1 indexed citations
17.
Farmanbar, Mina, et al.. (2019). A web based solution to track trawl vessel activities over pipelines in Norwegian Continental Shelf. IOP Conference Series Materials Science and Engineering. 700(1). 12037–12037. 2 indexed citations
18.
Keprate, Arvind & R. M. Chandima Ratnayake. (2019). Data Mining for Estimating Fatigue Strength Based on Composition and Process Parameters. 4 indexed citations
19.
Keprate, Arvind & R. M. Chandima Ratnayake. (2018). Remaining Fatigue Life Prediction of Topside Piping Using Response Surface Models. 40. 237–241. 4 indexed citations
20.
Keprate, Arvind & R. M. Chandima Ratnayake. (2017). Using gradient boosting regressor to predict stress intensity factor of a crack propagating in small bore piping. 1331–1336. 23 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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