Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel
In the present research work, a neural network model has been developed to predict the exhaust emissions and performance of a compression ignition engine. The significance and novelty of the work, with respect to existing literature, is the application of sensitivity analysis and an artificial neura...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-09-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/11/9/2410 |
| _version_ | 1798025421021773824 |
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| author | Farzad Jaliliantabar Barat Ghobadian Gholamhassan Najafi Talal Yusaf |
| author_facet | Farzad Jaliliantabar Barat Ghobadian Gholamhassan Najafi Talal Yusaf |
| author_sort | Farzad Jaliliantabar |
| collection | DOAJ |
| description | In the present research work, a neural network model has been developed to predict the exhaust emissions and performance of a compression ignition engine. The significance and novelty of the work, with respect to existing literature, is the application of sensitivity analysis and an artificial neural network (ANN) simultaneously in order to predict the engine parameters. The inputs of the model were engine load (0, 25, 50, 75 and 100%), engine speed (1700, 2100, 2500 and 2900 rpm) and the percent of biodiesel fuel derived from waste cooking oil in diesel fuel (B0, B5, B10, B15 and B20). The relationship between the input parameters and engine cylinder performance and emissions can be determined by the network. The global sensitivity analysis results show that all the investigated factors are effective on the created model and cannot be ignored. In addition, it is found that the most emissions decreased while using biodiesel fuel in the compression ignition engine. |
| first_indexed | 2024-04-11T18:18:47Z |
| format | Article |
| id | doaj.art-504f092c571e4f0fb084b7d4e8bb531a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T18:18:47Z |
| publishDate | 2018-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-504f092c571e4f0fb084b7d4e8bb531a2022-12-22T04:09:49ZengMDPI AGEnergies1996-10732018-09-01119241010.3390/en11092410en11092410Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel FuelFarzad Jaliliantabar0Barat Ghobadian1Gholamhassan Najafi2Talal Yusaf3Mechanics of Biosystems Engineering Department, Tarbiat Modares University, Tehran 14115-336, IranMechanics of Biosystems Engineering Department, Tarbiat Modares University, Tehran 14115-336, IranMechanics of Biosystems Engineering Department, Tarbiat Modares University, Tehran 14115-336, IranOffice of the Pro Vice-Chancellor, Federation University, Ballarat, VIC 3350, AustraliaIn the present research work, a neural network model has been developed to predict the exhaust emissions and performance of a compression ignition engine. The significance and novelty of the work, with respect to existing literature, is the application of sensitivity analysis and an artificial neural network (ANN) simultaneously in order to predict the engine parameters. The inputs of the model were engine load (0, 25, 50, 75 and 100%), engine speed (1700, 2100, 2500 and 2900 rpm) and the percent of biodiesel fuel derived from waste cooking oil in diesel fuel (B0, B5, B10, B15 and B20). The relationship between the input parameters and engine cylinder performance and emissions can be determined by the network. The global sensitivity analysis results show that all the investigated factors are effective on the created model and cannot be ignored. In addition, it is found that the most emissions decreased while using biodiesel fuel in the compression ignition engine.http://www.mdpi.com/1996-1073/11/9/2410ANNemissionMLPsensitivity analysiswaste cooking oil biodieselperformance |
| spellingShingle | Farzad Jaliliantabar Barat Ghobadian Gholamhassan Najafi Talal Yusaf Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel Energies ANN emission MLP sensitivity analysis waste cooking oil biodiesel performance |
| title | Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel |
| title_full | Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel |
| title_fullStr | Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel |
| title_full_unstemmed | Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel |
| title_short | Artificial Neural Network Modeling and Sensitivity Analysis of Performance and Emissions in a Compression Ignition Engine Using Biodiesel Fuel |
| title_sort | artificial neural network modeling and sensitivity analysis of performance and emissions in a compression ignition engine using biodiesel fuel |
| topic | ANN emission MLP sensitivity analysis waste cooking oil biodiesel performance |
| url | http://www.mdpi.com/1996-1073/11/9/2410 |
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