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All Journal Journal of Emerging Science and Engineering
Sharma, Prabhakar
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Engineering Environmental Science

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Optimized conversion of waste vegetable oil to biofuel with Meta heuristic methods and design of experiments Dong, Van Huong; Sharma, Prabhakar
Journal of Emerging Science and Engineering Vol. 1 No. 1 (2023)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2023.4

Abstract

Biodiesel generated from waste cooking oil (WCO) shows enormous potential for accomplishing SDGs and embracing circular economy principles. This strategy coincides with SDGs 7 and 12, which promote clean energy along with ethical consumerism, by converting waste cooking oil into biofuel. It reduces dependency on fossil fuels, reduces emissions, and promotes sustainable energy sources. Furthermore, using WCO biodiesel adheres to the circular economy concept, reducing waste and pollution while conserving resources (SDGs 12, 14, and 15). To optimize this process, a hybrid technique comprising RSM, ANOVA, and particle swarm optimization is being explored. Researchers achieved 90% biodiesel production employing this technology, encouraging both eco-friendly energy and resource-efficient practices. The optimized parameters produced remarkable results: 82.98% biodiesel generation with a reaction time of 101 minutes, 2% catalyst, and a methanol-to-oil ratio of 20%, demonstrating the potential of this integrated strategy.
Digital twins for internal combustion engines: A brief review Tran, Viet Dung; Sharma, Prabhakar; Nguyen, Lan Huong
Journal of Emerging Science and Engineering Vol. 1 No. 1 (2023)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2023.5

Abstract

The adoption of digital twin technology in the realm of internal combustion (IC) engines has been attracting a lot of interest. This review article offers a comprehensive summary of digital twin applications and effects in the IC engine arena. Digital twins, which are virtual counterparts of real-world engines, allow for real-time monitoring, diagnostics, and predictive modeling, resulting in improved design, development, and operating efficiency. This abstract digs into the creation of a full virtual depiction of IC engines using data-driven models, physics-based simulations, and IoT sensor data. The study looks at how digital twins can potentially be used throughout the engine's lifespan, including design validation, performance optimization, and condition-based maintenance. This paper emphasizes the critical role of digital twins in revolutionizing IC engine operations, resulting in enhanced reliability, decreased downtime, and enhanced emissions control through a methodical analysis of significant case studies and innovations.
Co-Authors Dong, Van Huong Nguyen, Lan Huong Tran, Viet Dung