Innovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel engines
Abstract Artificial intelligence-based technologies are rapidly advancing and significantly influencing the engineering sector, particularly in the automotive industry, through AI-driven neural network tools and Sankey diagrams. Meanwhile, the depletion of fossil fuels and rising emissions have push...
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-98201-x |
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| author | Mohammed Al Awadh Mohammad Imtiyaz Gulbarga |
| author_facet | Mohammed Al Awadh Mohammad Imtiyaz Gulbarga |
| author_sort | Mohammed Al Awadh |
| collection | DOAJ |
| description | Abstract Artificial intelligence-based technologies are rapidly advancing and significantly influencing the engineering sector, particularly in the automotive industry, through AI-driven neural network tools and Sankey diagrams. Meanwhile, the depletion of fossil fuels and rising emissions have pushed global efforts towards renewable and clean fuel solutions. Hydrogen, as a key clean fuel, has garnered considerable research interest. Combining hydrogen with biomass-derived fuels has gained attention due to its dual benefits of addressing biomass waste disposal and alleviating hydrogen storage and safety concerns. This study focuses on the production of aquatic plant oil (duckweed bio-oil) and its combination with hydrogen gas, evaluating their effects on the performance of a Reactivity Controlled Compression Ignition (RCCI) engine. The results revealed that the H40 blend demonstrated a 1% higher brake thermal efficiency (BTE) than diesel, along with emission reductions of 40% for HC, 6% for NOx, 27% for CO, and 14% for smoke. The results were further validated using an Artificial Neural Network (ANN) and a Sankey diagram. The ANN achieved low RMSE values (0.9965–0.9996) and MPAE values within 4%, while the Sankey diagram effectively illustrated energy distribution with minimal loss. These findings highlight the potential of hydrogen-enriched fuels for future internal combustion engines. |
| format | Article |
| id | doaj-art-39dacb7b7a2d4ebd9d3e6455a8de5168 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-39dacb7b7a2d4ebd9d3e6455a8de51682025-08-20T01:47:33ZengNature PortfolioScientific Reports2045-23222025-04-0115112210.1038/s41598-025-98201-xInnovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel enginesMohammed Al Awadh0Mohammad Imtiyaz Gulbarga1Department of Industrial Engineering, College of Engineering, King Khalid UniversityFaculty of Engineering and Informatics, Department of Computer Science & Engineering, Ala-Too International UniversityAbstract Artificial intelligence-based technologies are rapidly advancing and significantly influencing the engineering sector, particularly in the automotive industry, through AI-driven neural network tools and Sankey diagrams. Meanwhile, the depletion of fossil fuels and rising emissions have pushed global efforts towards renewable and clean fuel solutions. Hydrogen, as a key clean fuel, has garnered considerable research interest. Combining hydrogen with biomass-derived fuels has gained attention due to its dual benefits of addressing biomass waste disposal and alleviating hydrogen storage and safety concerns. This study focuses on the production of aquatic plant oil (duckweed bio-oil) and its combination with hydrogen gas, evaluating their effects on the performance of a Reactivity Controlled Compression Ignition (RCCI) engine. The results revealed that the H40 blend demonstrated a 1% higher brake thermal efficiency (BTE) than diesel, along with emission reductions of 40% for HC, 6% for NOx, 27% for CO, and 14% for smoke. The results were further validated using an Artificial Neural Network (ANN) and a Sankey diagram. The ANN achieved low RMSE values (0.9965–0.9996) and MPAE values within 4%, while the Sankey diagram effectively illustrated energy distribution with minimal loss. These findings highlight the potential of hydrogen-enriched fuels for future internal combustion engines.https://doi.org/10.1038/s41598-025-98201-xHydrogen combustionFourth generation fuelIC engineRCCI engineBiofuel |
| spellingShingle | Mohammed Al Awadh Mohammad Imtiyaz Gulbarga Innovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel engines Scientific Reports Hydrogen combustion Fourth generation fuel IC engine RCCI engine Biofuel |
| title | Innovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel engines |
| title_full | Innovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel engines |
| title_fullStr | Innovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel engines |
| title_full_unstemmed | Innovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel engines |
| title_short | Innovative AI analysis and experimental study of hydrogen- enriched clean fuel in modern fossil fuel engines |
| title_sort | innovative ai analysis and experimental study of hydrogen enriched clean fuel in modern fossil fuel engines |
| topic | Hydrogen combustion Fourth generation fuel IC engine RCCI engine Biofuel |
| url | https://doi.org/10.1038/s41598-025-98201-x |
| work_keys_str_mv | AT mohammedalawadh innovativeaianalysisandexperimentalstudyofhydrogenenrichedcleanfuelinmodernfossilfuelengines AT mohammadimtiyazgulbarga innovativeaianalysisandexperimentalstudyofhydrogenenrichedcleanfuelinmodernfossilfuelengines |