Numerical investigation on the effect of water in the reduction of diesel engine exhaust emissions using a novel ionic chemical kinetics mechanism

Mohammadi, Milad; Neshat, Elaheh

doi:10.1007/s11356-021-12904-y

Cited by 4 publications

(1 citation statement)

References 71 publications

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“…Mohammadi and Neshat 10 investigated the role of water in exhaust emission reduction. W/D mixture with four different % of water content is supplied to the engine cylinder and tested against soot and NO x and found that a reduction in NO x emission, a reduction in engine cylinder temperature.…”

Section: Introductionmentioning

confidence: 99%

Effect of hybrid nanoparticles MgO and Al₂O₃ added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization

Patel¹,

Dhiman

2022

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The automotive sector is one of the top energy consumers globally compared with any other sector where oil plays the main role. According to http://statista.com (an online platform that displays the stats on oil consumption and reserves), in 2016, the demand for crude oil was about 85.3 million barrels per day worldwide. In 2019, the demand almost reached 100 barrels per day, and then it was reduced to 91 million per day during the 2020 global COVID‐19 crisis. However, it was predicted that the global crude oil requirements will exceed 100 million barrels per day by 2023 and will continue to raise. Also, geographically, not all countries worldwide have the oil reservoirs or the technology to extract oil from the reservoirs. Although the oil demand worldwide is increasing every year, researchers have estimated that there are only 47 years of oil left on the planet earth if the current oil consumption will raise this way. Researchers are looking for finding alternative fuels, such as electrochemical energy (electric vehicles), biodiesel, electricity, ethanol, hydrogen, natural gas, propane, emerging fuels, or the use of such fuels in the existing engines to minimize the use of nonrenewable energy resources. However, researchers are also looking more at fuels based on hybrid nanoparticles added to emulsified fuels. Due to the limitations of utilizing electrochemical energy or biofuels include high charging time, limited millage, harmful exhaust emissions, complicated production process, engine efficiency, the cost of fuel, and the advantages over hybrid nanoparticles added emulsified fuels than biofuels. Hence, after going through numerous researches, in this present experimentation, “hybrid nanoparticles (MgO and Al2O3) added water‐in‐diesel emulsion” are formulated to enhance the quality of emission and improve the performance of the compression ignition engine. The best combination of diesel, MgO, and Al2O3, a water‐in‐diesel (W/D) emulsion blend, is proposed. The results were further validated using deep neural network‐based spotted hyena optimization (DNN‐SHO) prediction and compared with traditional machine learning approaches artificial neural network (ANN), convolution neural network (CNN), regression‐based network (RBN), recurrent neural network (RNN), and DNN. As a result, the best proportions of the proposed nanoparticles added into the W/D bend are identified to be 10% W/D, 50 ppm of MgO, and 50 ppm of Al2O in terms of engine performance and emission characteristics brake thermal efficiency 30.7%, brake‐specific fuel consumption 0.29 kg/kW‐h, CO 0.027 vol%, NOx 855 ppm vol, and HC 12 ppm vol. Besides this, the DNN‐SHO‐based validated outcomes are in good agreement with the experimental values and outperformed other traditional approaches ANN, CNN, RBN, RNN, and DNN used in this study.

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Section: Introductionmentioning

confidence: 99%

Effect of hybrid nanoparticles MgO and Al₂O₃ added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization

Patel¹,

Dhiman

2022

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Improvement of the recoverable waste energy and reduction of the exhaust emissions in a diesel engine through the water injection

Neshat

Asghari

2022

Int. J. Environ. Sci. Technol.

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Effect of direct water injection timing on cycle performance and emissions characteristics within a CI-ICRC engine

Kang¹,

Yang²,

Feng³

et al. 2023

Alexandria Engineering Journal

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Numerical investigation on the effect of water in the reduction of diesel engine exhaust emissions using a novel ionic chemical kinetics mechanism

Cited by 4 publications

References 71 publications

Effect of hybrid nanoparticles MgO and Al₂O₃ added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization

Effect of hybrid nanoparticles MgO and Al₂O₃ added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization

Improvement of the recoverable waste energy and reduction of the exhaust emissions in a diesel engine through the water injection

Effect of direct water injection timing on cycle performance and emissions characteristics within a CI-ICRC engine

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Numerical investigation on the effect of water in the reduction of diesel engine exhaust emissions using a novel ionic chemical kinetics mechanism

Cited by 4 publications

References 71 publications

Effect of hybrid nanoparticles MgO and Al2O3 added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization

Effect of hybrid nanoparticles MgO and Al2O3 added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization

Improvement of the recoverable waste energy and reduction of the exhaust emissions in a diesel engine through the water injection

Effect of direct water injection timing on cycle performance and emissions characteristics within a CI-ICRC engine

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Product

Resources

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Effect of hybrid nanoparticles MgO and Al₂O₃ added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization

Effect of hybrid nanoparticles MgO and Al₂O₃ added water‐in‐diesel emulsion fueled diesel engine using hybrid deep neural network‐based spotted hyena optimization