A gas information adaptive deep learning network combined with an electronic nose to identify the egg quality at different storage periods

Journal of the Taiwan Institute of Chemical Engineers, Journal Year: 2025, Volume and Issue: 169, P. 105959 - 105959

Published: Jan. 14, 2025

Language: Английский

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Spirulina microalgae slurry as the potential substitute for fossil fuels containing MgO nanoparticles as oxygenated additives

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Techno-economic perspective on the use of pyrolysis oil from digestate in spark-ignition engines

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

Published: March 25, 2025

Purpose Fermentation residues from biogas plants (digestate) represent an abundant source of lignocellulose-based biowaste with consistent quality and quantity throughout the year. Given that popularity digestate pyrolysis for production biochar is growing worldwide, increasing number obtain oil as a by-product which economically lucrative uses are urgently sought. The purpose this paper to investigate techno-economic aspects such efforts. Design/methodology/approach In current study, was mixed conventional fossil fuel in various proportions tested at wide range engine speed varying 1,400 rpm 2,800 estimate effects blends on performance emissions. key parameters torque, power, specific consumption, exhaust gas temperature emissions (CO, CO 2 , HC NO x ) were determined operating conditions, results trained using Gradient Boosting Regressor (GBR) model. This research both experimental analysis GBR model evaluate find effect bio-oil. Findings Experimental reveal increased content reduces torque power by 10% 9%. Meanwhile, consumption 4%. Nevertheless, shows significant reductions CO, oil-based blends. However, 3% because higher combustion temperatures. Originality/value Based comparison actual predicted data, it clear highly efficient spark ignition engines. Pyrolysis could mean savings costs well reduction carbon footprint and, thus, contribute concept circular economy.

Language: Английский

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Impact of Al2O3, CaO, and Fe2O3 additives on spirulina biodiesel blends in a comparative compression ignition engine study

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

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Experimental investigation and machine learning prediction of thrust, fuel consumption, and emissions for micro gas turbine engine fueled with biofuel and hydrogen- A comparative study of linear regression and LSTM model

Journal of the Taiwan Institute of Chemical Engineers, Journal Year: 2025, Volume and Issue: unknown, P. 106104 - 106104

Published: April 1, 2025

Language: Английский

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Performance and emissions of gas turbine engines fueled with karanja oil-based biofuel blends: a machine learning approach using Lasso regression

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

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Machine learning models for biogas potential in sustainable aviation: XGBoost, random forest and ridge regression

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

Published: April 28, 2025

Purpose This study aims to focus on the performance and emissions characteristics of different combinations biofuel blends in aviation engines using machine learning models. The paper discusses both energy reduction, so it can be clarified title abstract. Design/methodology/approach tested were B10 (10% microalgae, 90% Jet A fuel), BB10 biodiesel, 10% biogas, 80% B30 (30% 70% fuel) BB30 60% respectively. All are already previous study, results trained ML models here, comparison was made.The used XGBoost, random forest ridge regression. These actual data thrust, thrust specific fuel consumption (TSFC), turbine inlet temperature (TIT), nitrogen oxides (NOx) emissions, carbon monoxide (CO) dioxide (CO 2 ) emissions. Trained evaluated experimental data, their is assessed based root mean squared error, absolute error R-squared ( R metrics. Findings From results, clear that model emerges as most effective predicting TIT CO by reporting low high . On other hand, regression outperforms TSFC, NOx Considering all capture movements reduced increased TSFC slightly higher TIT. Meanwhile, have ability lower NOx, for biodiesel compared fuel. also specifying would add clarity since focuses continuous numerical outputs. Practical implications Based predictions from models, support understanding decision-making processes selection engine optimization. Originality/value main objective provide insights into potential alternative fuels various critical parameters, including

Language: Английский

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Assessing the performance, and emissions characteristics of a diesel engine fueled with soya seed biodiesel blended with oxy-hydrogen

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Language: Английский

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Performance and emission analysis of Scenedesmus dimorphus-based biodiesel with hydrogen as fuel in an unmodified compression ignition engine

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

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