Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence
The exhaustive nature of petroleum products triggers the obstacles of scarcity, economic imbalance, and environmental depletion. It is difficult to avoid their usage all of a sudden and switch to clean electric prime movers. Under all these circumstances, the researchers may initiate their investiga...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/7954488 |
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| author | Tarun Kumar Kotteda Rama Bhadri Raju Chekuri B. Naga Raju Prasada Raju Kantheti S. Balakumar |
| author_facet | Tarun Kumar Kotteda Rama Bhadri Raju Chekuri B. Naga Raju Prasada Raju Kantheti S. Balakumar |
| author_sort | Tarun Kumar Kotteda |
| collection | DOAJ |
| description | The exhaustive nature of petroleum products triggers the obstacles of scarcity, economic imbalance, and environmental depletion. It is difficult to avoid their usage all of a sudden and switch to clean electric prime movers. Under all these circumstances, the researchers may initiate their investigations on alternative fuels for preeminent solution. The present study covers the performance and emissions of a single cylinder, four-stroke, diesel engine fueled with Pongamia pinnata and Calophyllum inophyllum biodiesels added with n-butanol additive at various proportions. In this investigation, the piston has been coated with ceramic material with a thickness of 200 µm topcoat. The blends have been tested at 1500 rpm speed and rated compression ratio of 17.5 : 1 at various operating loads. A comparative result analysis has been made on the engine parameters operated by diesel and showed that mechanical efficiency gradually increases with a percentile increment of n-butanol in the blend. Moreover, emissions such as CO, CO2, NOx, and opacity were found to be reduced for the samples having high amount of n-butanol, whereas HC emissions slightly increased. In addition, all the exhaust gases have been predicted by using second-order polynomial equations generated and artificial Intelligence technique, and the comparative analysis has been made. It has been identified that ANN showed an average accuracy of prediction superior than regression analysis. |
| format | Article |
| id | doaj-art-badbedd4e5ed4fde93348f6f5a689d05 |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-badbedd4e5ed4fde93348f6f5a689d052025-02-03T01:27:23ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422021-01-01202110.1155/2021/79544887954488Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial IntelligenceTarun Kumar Kotteda0Rama Bhadri Raju Chekuri1B. Naga Raju2Prasada Raju Kantheti3S. Balakumar4Department of Mechanical Engineering, Sagi Rama Krishnam Raju Engineering College, Bhimavaram, Andhra Pradesh, IndiaDepartment of Mechanical Engineering, Sagi Rama Krishnam Raju Engineering College, Bhimavaram, Andhra Pradesh, IndiaDepartment of Mechanical Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, IndiaDepartment of Mechanical Engineering, Sagi Rama Krishnam Raju Engineering College, Bhimavaram, Andhra Pradesh, IndiaArba Minch University, Arbaminch, EthiopiaThe exhaustive nature of petroleum products triggers the obstacles of scarcity, economic imbalance, and environmental depletion. It is difficult to avoid their usage all of a sudden and switch to clean electric prime movers. Under all these circumstances, the researchers may initiate their investigations on alternative fuels for preeminent solution. The present study covers the performance and emissions of a single cylinder, four-stroke, diesel engine fueled with Pongamia pinnata and Calophyllum inophyllum biodiesels added with n-butanol additive at various proportions. In this investigation, the piston has been coated with ceramic material with a thickness of 200 µm topcoat. The blends have been tested at 1500 rpm speed and rated compression ratio of 17.5 : 1 at various operating loads. A comparative result analysis has been made on the engine parameters operated by diesel and showed that mechanical efficiency gradually increases with a percentile increment of n-butanol in the blend. Moreover, emissions such as CO, CO2, NOx, and opacity were found to be reduced for the samples having high amount of n-butanol, whereas HC emissions slightly increased. In addition, all the exhaust gases have been predicted by using second-order polynomial equations generated and artificial Intelligence technique, and the comparative analysis has been made. It has been identified that ANN showed an average accuracy of prediction superior than regression analysis.http://dx.doi.org/10.1155/2021/7954488 |
| spellingShingle | Tarun Kumar Kotteda Rama Bhadri Raju Chekuri B. Naga Raju Prasada Raju Kantheti S. Balakumar Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence Advances in Materials Science and Engineering |
| title | Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence |
| title_full | Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence |
| title_fullStr | Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence |
| title_full_unstemmed | Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence |
| title_short | Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence |
| title_sort | analysis on emissions and performance of ceramic coated diesel engine fueled with novel blends using artificial intelligence |
| url | http://dx.doi.org/10.1155/2021/7954488 |
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