Numerical study on the effects of spark plug position and ignition timing on the performance of hydrogen direct-injection oval rotary engine under different excess air ratio conditions DOI
Changwei Ji, Yadong Deng, Jinxin Yang

et al.

Energy, Journal Year: 2024, Volume and Issue: unknown, P. 134246 - 134246

Published: Dec. 1, 2024

Language: Английский

Evaluation of machine learning algorithms on hydrogen boosted homogeneous charge compression ignition engine operation for performance and emission prediction DOI

S. Sathishkumar,

M. Mohamed Ibrahim

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

1
Synergistic effect of nano additives for combustion and emission mitigation in a hydrogen-enriched CI engine using cocos nucifera oil methyl ester DOI

Thiruselvam Krishnamoorthi,

K. Rajesh,

R. Sathiyamoorthi

et al.

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 109, P. 1253 - 1265

Published: Feb. 17, 2025

Language: Английский

Citations

1
Neural Network-Based Prediction of Levoglucosan Yield: A Novel Modeling Approach DOI
Jingjing Ma, Shuai Zhang, Xiangjun Liu

et al.

Energy, Journal Year: 2025, Volume and Issue: 320, P. 135396 - 135396

Published: March 1, 2025

Language: Английский

Citations

0
Analysis of combustion characteristics of a diesel engine run on ternary blends using machine learning algorithms DOI Open Access

Jakeer Hussain Shaik,

Naseem Khayum, Krishna Kumar Pandey

et al.

Environmental Progress & Sustainable Energy, Journal Year: 2025, Volume and Issue: unknown

Published: March 21, 2025

Abstract Diesel engines are vital in industries, such as transportation, agriculture, and power generation. Enhancing fuel efficiency reducing emissions these critical goals, machine learning (ML) techniques offer novel solutions for achieving them. This study investigates the use of ML models, specifically random forest regression (RFR) polynomial (PR) to predict key combustion characteristics, namely cylinder pressure heat release rate (HRR), a dual‐fuel diesel engine powered by ternary blend (TB) acetylene. The experimental setup involved modifying conventional operate mode, using TB comprising 70% diesel, 20% waste cooking oil biodiesel (WCOB), 10% methanol volume. head, piston crown, intake/exhaust valves were coated with partially stabilized zirconia (PSZ) improve efficiency. RFR model achieved an impressive R 2 score 0.9987 0.9878 HRR predictions, corresponding mean absolute error (MAE) values 0.124 0.021, indicating high predictive accuracy minimal deviation from values. PR model, while capturing some nonlinear trends, performed less reliably, scores 0.7689 0.6720 HRR. These results underscore model's robustness predicting complex behavior, offering reliable, cost‐effective approach optimize emission reduction engines. findings suggest that implementing particularly RFR, can aid tuning parameters sustainable blends, contributing reduced greenhouse gas improved

Language: Английский

Citations

0
Blue hydrogen production using palladium membrane in a zero-emission energy system by carbon dioxide capturing DOI
Parisa Mojaver, Shahram Khalilarya

Energy, Journal Year: 2024, Volume and Issue: unknown, P. 134142 - 134142

Published: Dec. 1, 2024

Language: Английский

Citations

2
Numerical study on the effects of spark plug position and ignition timing on the performance of hydrogen direct-injection oval rotary engine under different excess air ratio conditions DOI
Changwei Ji, Yadong Deng, Jinxin Yang

et al.

Energy, Journal Year: 2024, Volume and Issue: unknown, P. 134246 - 134246

Published: Dec. 1, 2024

Language: Английский

Citations

2