A Comparison of Soybean Oil Methyl Ester and Diesel Sprays behavior and atomization characteristics

The present numerical study compares between spray characteristics of diesel and soybean oil methyl ester (SME biodiesel) under non-evaporating sprays. The spray structure of diesel and biodiesel fuel (soybean oil) in a common rail injection system are investigated and compared with that of available experimental data used image processing and atomization performance analysis. The proposed approach for the liquid phase based on the statistical properties of sprays be used to describe the liquid and gas phases in an Eulerian-Eulerian approach. The main concept for this model is the possibility of describing a poly disperse spray by using moments of a drop number size distribution function. The main reason for less spray tip penetration in the (SME) comparing with diesel because a larger droplet diameters is the higher density, viscosity and surface tension of (SME). The effect of fuel properties on the near nozzle structure is studied. The comparisons are referring that the spray drag, breakup and collision processes are promoted.


1.Introduction:
Environmental interest and energy conservation have become crucial issues in industrial and automotive fields. Therefore alternative fuel resources are being passively researched as part of an effort to reduce the side effects of emissions and environmental problems. The common understanding of the necessity to use a clean, biodegradable and renewable fuel as alternative fuel has led to present the biodiesel as outstanding solution for the energy security and environment problems. During the last two decades, a big effort has been spent on the effect of alternative fuel properties. In the same way, biodiesel can improve the thermal efficiency through the optimum combustion process and reduced exhaust emission characteristics of diesel engine which is affected by fuel properties and spray atomization characteristics. Applicative research based on using different biofuels expressed that the fuel with higher density, viscosity and surface tension gives shorter spray tip penetration and large cone angle [1][2][3][4][5].
Experimental and numerical work have been carried out by Park et al. [6] to study the spray and atomization characteristics of an undiluted biodiesel fuel. They used a visualization system to analyses spray tip penetration, spray area and centroid variations while the droplet size and droplet distribution was obtained using a droplet measuring system. The numerical part had been implemented by using KIVA-3V code. They found when the injection pressure increases the injection delay decreased because of the increase of spray fuel b y injection pressure.
Majhool and ALJeebori . [7] studied numerically the modelling of spray of biodiesel in terms of spray moment framework. In their investigations were conducted for biodiesel spray under transient engine conditions. The spray tip penetration of biodiesel had been studied in a comparison with diesel fuel in a diesel engine under transient engine conditions. The predicted results were compared with experimental data with a chosen case for highly ambient pressure.
The study used the Eulerian-Eulerian approach for the two phase flow simulation. In the validated computer programme both used liquid fuels are treated in terms of spray moments of drop size distribution. One parameter was chosen for the analysis and to study the spray characteristics through the examination and tracking the behaviour of the biodiesel.

Moments theory
Beck and Watkins [8] presented their approach based on the droplet number size distribution, n(r), is defined as a multiple of the droplet number probability distribution of droplet radius as below where N (r) is the droplet number probability distribution. The integral over all droplets provides the total number of droplets per unit total volume (not unit liquid volume). This can be defined as below: This is the first moment of the distribution function. In this approach, the three remaining distribution function moments are defined as below: At a particular point in space and time, Q0,is the total number of drops present, Q1, is the total volume of the drops, all quantities within a unit volume of the gas/liquid mixture. The fourth moment is related to the liquid volume fraction via the following relation E62 droplet diameters from D10 to the Sauter mean diameter D32, as, by definition

Gamma distribution
The general gamma number size distribution is given by and where distribution of the drops. This is defined by r 32 = Q3/Q2. For numerical calculations, the gamma function can be approximated by [9]: E63 with an error of at most 1% for values of k > 1.0. With three moments calculated through transport equations, there are two parameters (Q3/Q2 =r32)and (Q2/Q1) available to determine r32and k. Insertion of (18) into (2)and partial integration leads to hence, setting i = 1, and Q0 is calculated from equation (21), by setting i = 0. The gamma distribution is defined for all k > 0. However, in practice there are a number of restrictions that must be applied, arising from the sub-models employed; in particular, the drag model break-up and collision models used. The sub-models are derived in details in [10].

Transport equations
The convection velocity required is thus seen to be the expected moment average value  This tests is carried out for different initial gas phase pressures but one case here is adopted as E65 shown in table 1 where the initial gas temperature is 293 K. Table 2 shows adopted biodiesel properties which are given by Kim et al. [13].

The complete algorithm
The solution algorithm is based on the PISO algorithm of Issa [14], with the liquid phase -phase drag, breakup and collision source terms are evaluated.

E66
The transport equations for the moments Q1, Q2and Q3of the drop size distribution and for the liquid are solved. The void fraction is updated.

Results and discussions
Before considering the computational results extracting from the in-house code written in FORTRAN-2003. The code is able to read structured or unstructured grid created by GAMBIT with neutral extension. GAMBIT software is used for supplying strategy for increasing grid refinement based on enlarge grid resolution at certain places by increase the number of intervals or the compression ratio. Figure ( Now the aim of this study will start by comparing three mainly parameters to characterized Soybean Oil Methyl Ester (SME). Firstly, Figure (3) shows the liquid volume faction at time 2 msec. To figure out the distribution of the liquid volume fraction, the axial direction was chosen to illustrate the way in which the liquid droplets are spread out. From this contour plot the liquid volume or concentration increases near the injector due to the liquid mass has been injected for 1.2 msec. whereas it can be noticed that at the front of the spray as the less concentration is found because it is associated with the atomization processes. The liquid volume fraction in diesel exhibited more penetration and wide cone angle than the (SME). This is because, the most important reason described here in this work is the fuel physical properties. For example the fuel density can be affected on the atomization process and spray tip penetration by decelerating the injection delay time as will be presented below. After the start of injection of liquid, the smaller droplets were seen to move towards the Centre of spray because of the entrained gas velocity induced by the spray. Also the Sauter mean E68 diameter can be defined as (SMD=Q3/Q2). That explain the highest values can be found at the axis of symmetry.
In order to achieve as good comparison as possible with the data, the inlet conditions were matched as closely as possible to the data given by Kim et al [14]. In particular, the variation of injection pressure with time was overcome by using the injection pressure profile to minimize the error of a few percent by using the injection profile. In the first 0.2 ms the injection pressure rises linearly with time from an initial value of 40 MPa to its maximum value of 50 MPa. As a consequence the computed injection velocity follows similar trends. injection. A constant value of discharge coefficient was set at 0.7. The axial profile shows that the maximum velocity occurs at the core of the spray (at the axis of symmetry). That is because large droplets which are heaviest (biggest momentum) are found here.

Conclusions
The aim of this study is to perform an optimal numerical simulation for biodiesel spray in a common rail diesel engine. As is apparent from methods of computational, the advanced numerical techniques can perform well as compared with the experimental data. The conclusions that are obtained by this work are as follows: 1. The spray tip penetration simulated results presented the good consistent with the experimental results. The liquid volume fraction and surface area concepts (based on spray moment theory) can cope with interactions between the two-phases with less computational effort and more efficiently.
2. One of the main advantages to use the numerical simulation will be appeared here. The computational calculations can provide the comparison with the experiment by adding the range of droplet sizes.