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Faculty Profile

Dr. Prabhakar Sharma

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Assistant Professor - Mechanical Engineering at Guru Nanak Dev DSEU Rohini Campus (formerly known as Guru Nanak Dev Institute of Technology, Rohini, Delhi)
  • Ph. D. – Mechanical Engineering, Deenbandhu Chhotu Ram University Of Science And Technology, Murthal
  • M.Tech. – Thermal Engineering, Jawaharlal Nehru Technological University, Hyderabad
  • B. Tech. – Mechanical Engineering, Birla Institute of Technology, Mesra

Dr. Prabhakar Sharma has more than 27 years of experience. He has served in the Aircraft Maintenance and Maintenance Management Industry with the Govt of India for 15 years and as a faculty of Mechanical Engineering with the Directorate of Training and Technical Education, Delhi for the last 11 years. His research area includes Biomass Gasification, Renewable Energy, the use of Artificial Intelligence, and Machine learning in Renewable Energy.

Dr. Sharma has performed various allied duties such as Examination In-charge, Thermal Engineering Lab In-charge, and In-charge of Academic Cell.

Courses Taught

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  • Material Science
  • Thermal Engineering
  • Machine Design
  • IC Engines
  • Machine Drawing
  • Industrial Engineering and Management

Research & Publications

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  • Sharma, P. (2020). Gene expression programming-based model prediction of performance and emission characteristics of a diesel engine fueled with linseed oil biodiesel/diesel blends: An artificial intelligence approach. Energy Sources, Part A: Recovery, Utilization and Environmental Effects. https://doi.org/10.1080/15567036.2020.1829204 
  • Sharma, P. (2021). Prediction-Optimization of the Effects of Di-Tert Butyl Peroxide-Biodiesel Blends on Engine Performance and Emissions Using Multi-Objective Response Surface Methodology (MORSM). Journal of Energy Resources Technology, 1–26. https://doi.org/10.1115/1.4052237 
  • Sharma, P., Chhillar, A., Said, Z., & Memon, S. (2021). Exploring the exhaust emission and efficiency of algal biodiesel powered compression ignition engine: Application of box–behnken and desirability based multi‐objective response surface methodology. Energies, 14(18), 1–22. https://doi.org/10.3390/en14185968 
  • Sharma, P., & Sahoo, B. B. (2022a). An ANFIS-RSM based modeling and multi-objective optimization of syngas powered dual-fuel engine. International Journal of Hydrogen Energy. https://doi.org/10.1016/J.IJHYDENE.2022.04.093 
  • Sharma, P., & Sahoo, B. B. (2022b). Precise prediction of performance and emission of a waste derived Biogas–Biodiesel powered Dual–Fuel engine using modern ensemble Boosted regression Tree: A critique to Artificial neural network. Fuel, 321, 124131. https://doi.org/10.1016/j.fuel.2022.124131 
  • Sharma, P., Sahoo, B. B., Said, Z., Hadiyanto, H., Nguyen, X. P., Nižetić, S., Huang, Z., Hoang, A. T., & Li, C. (2022). Application of machine learning and Box-Behnken design in optimizing engine characteristics operated with a dual-fuel mode of algal biodiesel and waste-derived biogas. International Journal of Hydrogen Energy. https://doi.org/10.1016/J.IJHYDENE.2022.04.152 
  • Sharma, P., Said, Z., Memon, S., Elavarasan, R. M., Khalid, M., Nguyen, X. P., Arıcı, M., Hoang, A. T., & Nguyen, L. H. (n.d.). Comparative evaluation of AI-based intelligent GEP and ANFIS models in prediction of thermophysical properties of Fe3O4-coated MWCNT hybrid nanofluids for potential application in energy systems. International Journal of Energy Research, n/a(n/a). https://doi.org/https://doi.org/10.1002/er.8010 
  • Sharma, P., & Sharma, A. K. (2020). Experimental Evaluation of Thermal and Combustion Performance of a DI Diesel Engine Using Waste Cooking Oil Methyl Ester and Diesel Fuel Blends. Smart Innovation, Systems and Technologies. https://doi.org/10.1007/978-981-15-2647-3_50 
  • Sharma, P., & Sharma, A. K. (2021a). AI-Based Prognostic Modeling and Performance Optimization of CI Engine Using Biodiesel-Diesel Blends. International Journal of Renewable Energy Resources, 11(2), 701–708. 
  • Sharma, P., & Sharma, A. K. (2021b). Application of Response Surface Methodology for Optimization of Fuel Injection Parameters of a Dual Fuel Engine Fuelled with Producer Gas- Biodiesel blends. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 00(00), 1–18. https://doi.org/10.1080/15567036.2021.1892883 
  • Sharma, P., & Sharma, A. K. (2021c). Combustion and Thermal Performance of Dual Fuel Engine : Influence of Controlled Producer Gas Substitution with Pilot B20 ( WCOME Biodiesel – Diesel ) Blending. Lecture Notes in Mechanical Engineering, 20, 341–353.
  • Sharma, P., & Sharma, A. K. (2021d). Statistical and Continuous Wavelet Transformation-Based Analysis of Combustion Instabilities in a Biodiesel-Fueled Compression Ignition Engine. Journal of Energy Resources Technology, 144(3). https://doi.org/10.1115/1.4051340 
  • Rajamoorthy, R., Arunachalam, G., Devendiran, R., Ahmadi, P., Pandiyan, S., Panchal, H., Kazem, H. A., & Sharma, P. (2022). Environmental Effects A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44(2), 3555–3575. https://doi.org/10.1080/15567036.2022.2067268 
  • Said, Z., Cakmak, N. K., Sharma, P., Sundar, L. S., Inayat, A., Keklikcioglu, O., & Li, C. (2022). Synthesis, stability, density, viscosity of ethylene glycol-based ternary hybrid nanofluids: Experimental investigations and model -prediction using modern machine learning techniques. Powder Technology, 117190. https://doi.org/10.1016/J.POWTEC.2022.117190 
  • Said, Z., Rahman, S., Sharma, P., Amine Hachicha, A., & Issa, S. (2022). Performance characterization of a solar-powered shell and tube heat exchanger utilizing MWCNTs/Water-based nanofluids: An experimental, Numerical, and Artificial Intelligence approach. Applied Thermal Engineering, 118633. https://doi.org/10.1016/j.applthermaleng.2022.118633 
  • Said, Z., Sharma, P., Syam Sundar, L., Afzal, A., & Li, C. (2021). Synthesis, stability, thermophysical properties and AI approach for predictive modelling of Fe3O4 Coated MWCNT Hybrid Nanofluids. Journal of Molecular Liquids, 117291. https://doi.org/10.1016/J.MOLLIQ.2021.117291 
  • Said, Z., Sharma, P., Tiwari, A. K., Le, V. V., Huang, Z., Bui, V. G., & Hoang, A. T. (2022). Application of novel framework based on ensemble boosted regression trees and Gaussian process regression in modelling thermal performance of small-scale organic rankine cycle using hybrid nanofluid. Journal of Cleaner Production, 132194. https://doi.org/10.1016/j.jclepro.2022.132194 
  • Sharma, P., Le, M. P., Chhillar, A., Said, Z., Deepanraj, B., Cao, D. N., Bandh, S. A. & Hoang, A. T. (2022). Using response surface methodology approach for optimizing performance and emission parameters of diesel engine powered with ternary blend of Solketal-biodiesel-diesel. Sustainable Energy Technologies and Assessments, 52, 102343. https://doi.org/10.1016/J.SETA.2022.102343 
  • Said, Z., Nguyen, T. H., Sharma, P., Li, C., Ali, H. M., Nguyen, V. N., Pham, V. V., Ahmed, S. F., Van, D. N. & Truong, T. H. (2022). Multi-attribute optimization of sustainable aviation fuel production-process from microalgae source. Fuel, 324, 124759. https://doi.org/10.1016/J.FUEL.2022.124759 
  • Sharma, P. (2021c). Artificial intelligence‐based model prediction of biodiesel‐fueled engine performance and emission characteristics: A comparative evaluation of gene expression programming and artificial neural network. Heat Transfer, 50(6), 5563–5587. https://doi.org/10.1002/htj.22138 
  • Sharma, P. (2020). Gene expression programming-based model prediction of performance and emission characteristics of a diesel engine fueled with linseed oil biodiesel/diesel blends: An artificial intelligence approach. Energy Sources, Part A: Recovery, Utilization and Environmental Effects. https://doi.org/10.1080/15567036.2020.1829204
  • Sharma, P. (2021). Prediction-Optimization of the Effects of Di-Tert Butyl Peroxide-Biodiesel Blends on Engine Performance and Emissions Using Multi-Objective Response Surface Methodology (MORSM). Journal of Energy Resources Technology, 1–26. https://doi.org/10.1115/1.4052237 Sharma, P.,
  • Chhillar, A., Said, Z., & Memon, S. (2021). Exploring the exhaust emission and efficiency of algal biodiesel powered compression ignition engine: Application of box–behnken and desirability based multi‐objective response surface methodology. Energies, 14(18), 1–22. https://doi.org/10.3390/en14185968
  • Sharma, P., & Sahoo, B. B. (2022a). An ANFIS-RSM based modeling and multi-objective optimization of syngas powered dual-fuel engine. International Journal of Hydrogen Energy. https://doi.org/10.1016/J.IJHYDENE.2022.04.093
  • Sharma, P., & Sahoo, B. B. (2022b). Precise prediction of performance and emission of a waste derived Biogas–Biodiesel powered Dual–Fuel engine using modern ensemble Boosted regression Tree: A critique to Artificial neural network. Fuel, 321, 124131. https://doi.org/10.1016/j.fuel.2022.124131 Sharma, P., Sahoo, B. B., Said, Z.,
  • Hadiyanto, H., Nguyen, X. P., Nižetić, S., Huang, Z., Hoang, A. T., & Li, C. (2022). Application of machine learning and Box-Behnken design in optimizing engine characteristics operated with a dual-fuel mode of algal biodiesel and waste-derived biogas. International Journal of Hydrogen Energy. https://doi.org/10.1016/J.IJHYDENE.2022.04.152
  • Sharma, P., Said, Z., Memon, S., Elavarasan, R. M., Khalid, M., Nguyen, X. P., Arıcı, M., Hoang, A. T., & Nguyen, L. H. (n.d.). Comparative evaluation of AI-based intelligent GEP and ANFIS models in prediction of thermophysical properties of Fe3O4-coated MWCNT hybrid nanofluids for potential application in energy systems. International Journal of Energy Research, n/a(n/a). https://doi.org/https://doi.org/10.1002/er.8010
  • Sharma, P., & Sharma, A. K. (2020). Experimental Evaluation of Thermal and Combustion Performance of a DI Diesel Engine Using Waste Cooking Oil Methyl Ester and Diesel Fuel Blends. Smart Innovation, Systems and Technologies. https://doi.org/10.1007/978-981-15-2647-3_50
  • Sharma, P., & Sharma, A. K. (2021a). AI-Based Prognostic Modeling and Performance Optimization of CI Engine Using Biodiesel-Diesel Blends. International Journal of Renewable Energy Resources, 11(2), 701–708.
  • Sharma, P., & Sharma, A. K. (2021b). Application of Response Surface Methodology for Optimization of Fuel Injection Parameters of a Dual Fuel Engine Fuelled with Producer Gas- Biodiesel blends. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 00(00), 1–18. https://doi.org/10.1080/15567036.2021.1892883