Year: 2024
Type: article
Abstract: The automotive industry faces increasing pressure to mitigate environmental impacts while maintaining optimal engine performance.This study explores the potential of diesel-plastic blends as a sustainable solution to address both challenges.Using a Regression Analysis Approach, the research aims to optimize Compression Ignition (CI) engine performance and reduce emissions through systematic experimentation and statistical modeling.The study begins with a comprehensive literature review, highlighting the urgent need for alternative fuels and the abundance of plastic waste.The rationale for investigating diesel-plastic blends is grounded in their potential to repurpose plastic waste while enhancing engine efficiency.The primary objectives include assessing blend feasibility, analyzing performance metrics, and identifying optimal blend ratios.Methodologically, the study involves blend formulation, experimental testing, regression analysis, and optimization.Various diesel-plastic blends are formulated with different ratios of recycled plastic waste.Engine performance and emissions testing are conducted using a CI engine equipped with advanced instrumentation.Statistical regression models are then developed to analyze the relationships between fuel composition, engine behavior, and emissions characteristics.Finally, optimal blend ratios are determined to achieve maximum combustion efficiency and minimum emissions.The significance of this research lies in its potential to offer a sustainable solution to plastic waste management and fossil fuel dependency.By leveraging recycled plastics as a fuel source, the automotive industry can reduce environmental impacts and pave the way for a greener transportation future.In conclusion, the study underscores the importance of alternative fuels in achieving environmental sustainability and optimizing engine performance.Through rigorous experimentation and statistical modeling, diesel-plastic blends emerge as a promising avenue for enhancing CI engine efficiency while mitigating environmental harm.
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4401506306