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All Journal Journal of Emerging Science and Engineering International Journal of Renewable Energy Development
Paramasivam, Prabhu
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Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science

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Journal : Journal of Emerging Science and Engineering

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Soft computing-based modelling and optimization of NOx emission from a variable compression ratio diesel engine Paramasivam, Prabhu; Naima, Khatir; Dzida, Marek
Journal of Emerging Science and Engineering Vol. 2 No. 2 (2024)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2024.e21

Abstract

Machine learning method and statistical method used for model prediction and optimization of third generation biodiesel-diesel blend powered variable compression engine High R2 values of 0.9998 and 0.9994 were observed in the training and testing phase of the model, respectively, indicating that The results confirm the robustness of the forecasting system. It was shown that the model accuracy means squared errors remained low at 0.0002 and 0.0014. These results were then confirmed by desirability-based optimization, which succeeded in achieving the values of the set parameters It should be noted that the compression ratio (CR), fuel injection pressure, and engine load were optimized to meet the defined parameters, resulting in a NOx emissions reduction as 222.8 ppm. The research illustrates the efficacy of desirability-based optimization in attaining targeted performance targets across important engine parameters whilst also reducing the impact on the environment.
Co-Authors Cao, Dao Nam Duong, Minh Thai Dzida, Marek Elvis Adril Le, Huu Cuong Le, Minh Xuan Le, Thanh Tuan Luong, Cong Nho Naima, Khatir Nguyen, Anh Quan Nguyen, Du Nguyen, Phuoc Quy Phong Nguyen, Quang Chien Nguyen, Van Quy Tran, Minh Ho Tran, Viet Dung