Abstract
Introduction: The expanding need for fossil fuels emphasizes the necessity to comprehend renewable energy sources.
Methods: This study examined the performance of a single-cylinder diesel engine using Jatropha biodiesel and aluminum dioxide—the research aimed to evaluate engine reactivity to compression ratio and load variations. The experiment employed with varitaion compression ratios.
Results: This study used the Response Surface Methodology to find the best Brake Specific Fuel Consumption performance indicator location. The researchers used a Central Composite Design setup for analysis. A regression model employing the response surface approach was then created to predict fuel phase-out likelihood.
Conclusion: This study examines multiple factors' effect and highlights the potential for patentable innovations in renewable fuel applications. According to studies, Jatropha biodiesel and its blends may improve engine efficiency and lower brake-specific fuel consumption compared to diesel fuel. Minor input parameter modifications are needed to gain these benefits.
Keywords: Performance, Al2O3, parametric optimization, RSM, brake specific fuel consumption (BSFC), jatropha biodiesel.
Call for Papers in Thematic Issues
Advances in Micromanufacturing Processes.
This special issue welcomes original high-quality research papers in the areas of traditional and advanced Micromanufacturing Science and Technology. To name some of the areas but not limited to, are as follows: Micromachining, Nanofinishing, Microjoining, Microforming, Microforging, Microcasting, Additive microfabrication, High aspect ratio fabrication, Lithography, LIGA, Micro- / nano-metrology, Micro ...read more
Bio-inspired Optoelectronics for Solar Energy Conversion
The development and manufacture of micro/nanostructures on optoelectronic materials and protection layers to provide a range of capabilities have been made possible by bio-inspiration and advancements in nanomanufacturing methods. These designed surfaces may be employed in both conventional rigid structures and the new flexible variants in numerous optoelectronic devices, including ...read more
Data-Driven Optimization of Manufacturing Processes using Machine Learning and Data Visualization
This special issue explores the transformative impact of data-driven optimization in the aerospace sector and manufacturing process, where complex, multipurpose challenges arise. As manufacturing digitizes, modest and medium-sized businesses encounter issues such as lack of expertise, funding, and varied, opaque data formats. Machine learning and big data methodologies offer solutions ...read more
Digital Twins in Industrial Networks for Predictive Maintenance Using Neural Networks
Predictive maintenance, supported by digital twins, enhances industry profitability, safety, and sustainability. Digital twins—accurate digital replicas of physical systems—provide real-time data for predicting asset wear and ensuring efficient maintenance. Integrating IoT enables seamless communication between digital and physical systems, enhancing predictive capabilities. Digital twins aid in preventing service erosion and ...read more
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