scholarly journals Heat Transfer Study on a DI Diesel Engine using Diesel and Biodiesel Fuels

2019 ◽  
Vol 9 (1) ◽  
pp. 69-76
Author(s):  
Lingeshwaran. G. S et al., Lingeshwaran. G. S et al., ◽  
2020 ◽  
Author(s):  
Sibi Pugalenthi ◽  
Raghunath Adimoolam Ganesan ◽  
Raghu Palani

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4421 ◽  
Author(s):  
Karami ◽  
Rasul ◽  
Khan ◽  
Anwar

Biodiesel is an alternative fuel for diesel engine. Considering the differences between diesel and biodiesel fuels, the engine condition should be modified based on the fuel or fuel blends to achieve optimum performance. This study presented a performance analysis of a direct-injected (DI) diesel engine with a dynamometer fueled with diesel-tomato seed biodiesel (TSOB) blends employing ANOVA and universal nonlinear model based on ANN. The experiments were carried out under conditions of some independent variables including different engine loads (0, 50, 100%) and speed (1800, 2150, and 2500 rpm) for four diesel-biodiesel combinations (B0, B5, B10, and B20). In this research, the effect of these factors on dependent variables including power, torque, SFC, FC, and Exhaust Gas Temperature (EGT) are investigated. Duncan′s multi-domain test at a significance level of R < 0.01 shows that the highest and lowest of the torque and power are produced from B5 and B20, respectively. These results show that the lowest EGT of 613 K is related to B20 and the highest EGT is related to B5 and B10. The regression models showed that the torque decreases with increasing the engine speed and biodiesel percentage. These results also show that the highest and the lowest SFC is related to B0 and B20, respectively. The ANN model shows high capability of predicting the engine performance parameters and emissions, without running costly and time-consuming experiments with the histogram error of 0.004 and R = 0.96. It also proved that ANN is a non-linear model of choice to deal with these data, instead of multivariate linear regression employed for preliminary analysis.


Author(s):  
Carl Hergart ◽  
Norbert Peters

Abstract Due to the wide spectrum of turbulent and chemical length- and time scales occurring in a HSDI diesel engine, capturing the correct physics and chemistry underlying combustion poses a tremendous modeling challenge. The processes related to the two-phase flow in a DI diesel engine add even more complexity to the total modeling effort. The Representative Interactive Flamelet (RIF) model has gained widespread attention owing to its ability of correctly describing ignition, combustion and pollutant formation phenomena. This is achieved by incorporating very detailed chemistry for the gas phase as well as the soot particle growth and oxidation, without imposing any significant computational penalty. The model, which is based on the laminar flamelet concept, treats a turbulent flame as an ensemble of thin, locally one-dimensional flame structures, whose chemistry is fast. A potential explanation for the significant underprediction of part load soot observed in previous studies applying the model is the neglect of wall heat losses in the flamelet chemistry model. By introducing an additional source term in the flamelet temperature equation, directly coupled to the wall heat transfer predicted by the CFD-code, flamelets exposed to walls are assigned heat losses of various magnitudes. Results using the model in three-dimensional simulations of the combustion process in a small-bore direct injection diesel engine indicate that the experimentally observed emissions of soot may have their origin in flame quenching at the relatively cold combustion chamber walls.


2006 ◽  
Author(s):  
J. Patterson ◽  
M. G. Hassan ◽  
A. Clarke ◽  
G. Shama ◽  
K. Hellgardt ◽  
...  

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