scholarly journals An Artificial Neural Network and Taguchi Integrated Approach to the Optimization of Performance and Emissions of Direct Injection Diesel Engine

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Venkata Narayana Beeravelli ◽  
Ratnam Chanamala ◽  
Uma Maheswara Rao Rayavarapu ◽  
Prasada Rao Kancherla
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Diesel Engine ◽  
Direct Injection ◽  
Integrated Approach ◽  
Direct Injection Diesel Engine ◽  
Performance And Emissions ◽  
Artificial Neural

scholarly journals Prediction ofNOxEmissions from a Direct Injection Diesel Engine Using Artificial Neural Network

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
J. Mohammadhassani ◽  
Sh. Khalilarya ◽  
M. Solimanpur ◽  
A. Dadvand
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Diesel Engine ◽  
Fuel Injection ◽  
Error Function ◽  
Direct Injection ◽  
Direct Injection Diesel Engine ◽  
Air Temperatures ◽  
Test Engine ◽  
Artificial Neural

In the present study, artificial neural network is used to model the relationship between NOxemissions and operating parameters of a direct injection diesel engine. To provide data for training and testing the network, a 6-inline-cylinder, four-stroke, diesel test engine is used and tested for various engine speeds, mass fuel injection rates, and intake air temperatures. 80% of a total of 144 obtained experimental data is employed for training process. In addition, 10% of the data (randomly selected) is used for network validation and the remaining data is employed for testing the accuracy of the network. The mean square error function is used for evaluating the performance of the network. The results show that the artificial neural network can efficiently be used to predict NOxemissions from the tested engine with about 10% error.

Explorative Investigation on Cashew Nut Shell Liquid Biodiesel blended with Ethanol and Hydrogen in Direct Injection (DI) Diesel Engine and prediction through Artificial Neural Network

2021 ◽  
Author(s):  
Thanigaivelan V ◽  
Lavanya R
Keyword(s):  
Diesel Engine ◽  
Diesel Fuel ◽  
Direct Injection ◽  
Cashew Nut Shell Liquid ◽  
Single Cylinder ◽  
Direct Injection Diesel Engine ◽  
Cashew Nut ◽  
Di Diesel Engine ◽  
Artificial Neural ◽  
Cashew Nut Shell

Abstract Emission from the DI diesel engine is series setback for environment viewpoint. Intended for that investigates for alternative biofuel is persuaded. The important hitches with the utilization of biofuels and their blends in DI diesel engines are higher emanations and inferior brake-thermal efficiency as associated to sole diesel fuel. In this effort, Cashew nut shell liquid (CNSL) biodiesel, hydrogen and ethanol (BHE) mixtures remained verified in a direct-injection diesel engine with single cylinder to examine the performance and discharge features of the engine. The ethanol remained supplemented 5%, 10% and 15% correspondingly through enhanced CNSL as well as hydrogen functioned twin fuel engine. The experiments done in a direct injection diesel engine with single-cylinder at steadystate conditions above the persistent RPM (1500RPM). Throughout the experiment, emissions of pollutants such as fuel consumption rate (SFC), hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NOx) and pressure of the fuel were also measured. cylinders. The experimental results show that, compared to diesel fuel, the braking heat of the biodiesel mixture is reduced by 26.79-24% and the BSFC diminutions with growing addition of ethanol from the CNSL hydrogen mixture. The BTE upsurges thru a rise in ethanol proportion with CNSL hydrogen mixtures. Finally, the optimum combination of ethanol with CNSL hydrogen blends led to the reduced levels of HC and CO emissions with trivial upsurge in exhaust gas temperature and NOx emissions. This paper reconnoiters the routine of artificial neural networks (ANN) to envisage recital, ignition and discharges effect.

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