Solubility limitations of residual steryl glucosides, saturated monoglycerides and glycerol in commercial biodiesel fuels as determinants of filter blockages

Author(s):  
Richard W. Heiden ◽  
Sigurd Schober ◽  
Martin Mittelbach
2010 ◽  
Vol 5 (4) ◽  
pp. 19-22
Author(s):  
A. Gopinath ◽  
◽  
Sukumar Puhan ◽  
Nagarajan . ◽  
◽  
...  

2021 ◽  
pp. 146808742199863
Author(s):  
Aishvarya Kumar ◽  
Ali Ghobadian ◽  
Jamshid Nouri

This study assesses the predictive capability of the ZGB (Zwart-Gerber-Belamri) cavitation model with the RANS (Reynolds Averaged Navier-Stokes), the realizable k-epsilon turbulence model, and compressibility of gas/liquid models for cavitation simulation in a multi-hole fuel injector at different cavitation numbers (CN) for diesel and biodiesel fuels. The prediction results were assessed quantitatively by comparison of predicted velocity profiles with those of measured LDV (Laser Doppler Velocimetry) data. Subsequently, predictions were assessed qualitatively by visual comparison of the predicted void fraction with experimental CCD (Charged Couple Device) recorded images. Both comparisons showed that the model could predict fluid behavior in such a condition with a high level of confidence. Additionally, flow field analysis of numerical results showed the formation of vortices in the injector sac volume. The analysis showed two main types of vortex structures formed. The first kind appeared connecting two adjacent holes and is known as “hole-to-hole” connecting vortices. The second type structure appeared as double “counter-rotating” vortices emerging from the needle wall and entering the injector hole facing it. The use of RANS proved to save significant computational cost and time in predicting the cavitating flow with good accuracy.


Author(s):  
SUNNY SONI ◽  
MADHU AGARWAL

Biodiesel is a renewable liquid fuel made from natural, renewable biological sources such as edible and non edible oils. Over the last years, biodiesel has gained more market due to its benefits and because it appears as the natural substitute for diesel. Reasons for growing interest in biodiesel include its potential for reducing noxious emissions, potential contributions to rural economic development, as an additional demand center for agricultural commodities, and as a way to reduce reliance on foreign oil. Biodiesel was prepared from soybean oil by transesterification with methanol in the presence of cement clinker. Cement clinker was examined as a catalyst for a conversion of soybean oil to fatty acid methyl esters (FAMEs). It can be a promising heterogeneous catalyst for the production of biodiesel fuels from soybean oil because of high activity in the conversion and no leaching in the transesterification reaction. The reaction conditions were optimized. A study for optimizing the reaction parameters such as the reaction temperature, and reaction time, was carried out. The catalyst cement clinker composition was characterized by XRF. The results demonstrate that the cement clinker shows high catalytic performance & it was found that the yield of biodiesel can reach as high as 84.52% after 1 h reaction at 65°C, with a 6:1 molar ratio of methanol to oil, 21 wt% KOH/cement clinker as catalyst.


2016 ◽  
Vol 3 (1) ◽  
pp. 19-25
Author(s):  
T. Petkov ◽  
Z. Mustafa ◽  
S. Sotirov ◽  
R. Milina ◽  
M. Moskovkina

Abstract A chemometric approach using artificial neural network for clusterization of biodiesels was developed. It is based on artificial ART2 neural network. Gas chromatography (GC) and Gas Chromatography - mass spectrometry (GC-MS) were used for quantitative and qualitative analysis of biodiesels, produced from different feedstocks, and FAME (fatty acid methyl esters) profiles were determined. Totally 96 analytical results for 7 different classes of biofuel plants: sunflower, rapeseed, corn, soybean, palm, peanut, “unknown” were used as objects. The analysis of biodiesels showed the content of five major FAME (C16:0, C18:0, C18:1, C18:2, C18:3) and those components were used like inputs in the model. After training with 6 samples, for which the origin was known, ANN was verified and tested with ninety “unknown” samples. The present research demonstrated the successful application of neural network for recognition of biodiesels according to their feedstock which give information upon their properties and handling.


2015 ◽  
Vol 34 ◽  
pp. 7-14
Author(s):  
Prithviraj Bhandare ◽  
G.R. Naik

Fossil fuel resources are decreasing daily while biodiesel fuels are attracting increasing attention worldwide as blending components or direct replacements for diesel fuel in vehicle engines. In this experiment the seed oils of 30 Neem (Azadirachta indica. A. juss) biotypes were screened and evaluated for their physio-chemical parameters for oil content, biodiesel yield, density, viscosity, iodine value , free fatty acid and saponification value. Hence the neem seed oil tested in this current study could be the potential sources of raw material for biodiesel production.


2013 ◽  
Author(s):  
John Johnson ◽  
Jeffrey Naber ◽  
Gordon Parker ◽  
Song-Lin Yang ◽  
Andrews Stevens ◽  
...  

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