Performance and emissions of gas turbine engines fueled with karanja oil-based biofuel blends: a machine learning approach using Lasso regression DOI
Ghadah Aldehim, Randa Allafi,

Abdulwhab Alkharashi

et al.

Aircraft Engineering and Aerospace Technology, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Purpose This study aims to investigate the performance and emission characteristics of gas turbine engines operating on biofuel blends derived from karanja oil as a potential alternative conventional Jet-A fuel. Design/methodology/approach The tested three blends: JA20 (20% oil, 80% Jet-A), JA30 (30% 70% Jet-A) JA40 (40% 60% diesel). Engine parameters, including thrust output, thrust-specific fuel consumption (TSFC) inlet temperature (TIT), were measured at engine speeds ranging 30,000 80,000 rpm. Exhaust emissions carbon monoxide (CO), dioxide (CO 2 ) nitrogen oxides (NOx) analyzed using analyzer. Additionally, Lasso regression model was used predict micro (MGT) based experimental data. Findings Increasing content in reduced overall increased TSFC lowered TIT compared blend exhibited most significant reduction, with 20% decrease 7.5% increase 4.1% TIT. However, consistently resulted lower CO, CO NOx fuel, reductions up 36%, 6.9% 13.6%, respectively, for blend. effectively captured influence speed composition emissions, achieving an R ² 0.95 0.94 predictions. Originality/value provides insights into feasibility oil-based biofuels engines, demonstrating their reduce while highlighting tradeoffs performance. use predicting offers novel approach assessing MGTs.

Language: Английский

Overview of thermal and analytical characterization techniques for biofuels and its blends DOI
Abdulwasiu Muhammed Raji, Brady Manescau, Khaled Chetehouna

et al.

Journal of Thermal Analysis and Calorimetry, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

Language: Английский

Citations

0
Performance and emissions of gas turbine engines fueled with karanja oil-based biofuel blends: a machine learning approach using Lasso regression DOI
Ghadah Aldehim, Randa Allafi,

Abdulwhab Alkharashi

et al.

Aircraft Engineering and Aerospace Technology, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Purpose This study aims to investigate the performance and emission characteristics of gas turbine engines operating on biofuel blends derived from karanja oil as a potential alternative conventional Jet-A fuel. Design/methodology/approach The tested three blends: JA20 (20% oil, 80% Jet-A), JA30 (30% 70% Jet-A) JA40 (40% 60% diesel). Engine parameters, including thrust output, thrust-specific fuel consumption (TSFC) inlet temperature (TIT), were measured at engine speeds ranging 30,000 80,000 rpm. Exhaust emissions carbon monoxide (CO), dioxide (CO 2 ) nitrogen oxides (NOx) analyzed using analyzer. Additionally, Lasso regression model was used predict micro (MGT) based experimental data. Findings Increasing content in reduced overall increased TSFC lowered TIT compared blend exhibited most significant reduction, with 20% decrease 7.5% increase 4.1% TIT. However, consistently resulted lower CO, CO NOx fuel, reductions up 36%, 6.9% 13.6%, respectively, for blend. effectively captured influence speed composition emissions, achieving an R ² 0.95 0.94 predictions. Originality/value provides insights into feasibility oil-based biofuels engines, demonstrating their reduce while highlighting tradeoffs performance. use predicting offers novel approach assessing MGTs.

Language: Английский

Citations

0