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Technical Paper

Physical Properties of Bio-Diesel and Implications for Use of Bio-Diesel in Diesel Engines

2007-10-29
2007-01-4030
In this study we identify components of a typical biodiesel fuel and estimate both their individual and mixed thermo-physical and transport properties. We then use the estimated mixture properties in computational simulations to gauge the extent to which combustion is modified when biodiesel is substituted for conventional diesel fuel. Our simulation studies included both conventional diesel combustion (DI) and premixed charge compression ignition (PCCI). Preliminary results indicate that biodiesel ignition is significantly delayed due to slower liquid evaporation, with the effects being more pronounced for DI than PCCI. The lower vapor pressure and higher liquid heat capacity of biodiesel are two key contributors to this slower rate of evaporation. Other physical properties are more similar between the two fuels, and their impacts are not clearly evident in the present study.
Technical Paper

On the Use of Thermodynamic Modeling for Predicting Cycle-to-Cycle Variations in a SI Engine under Lean Conditions

2005-10-24
2005-01-3802
We propose a procedure by which a two-zone thermodynamic model combined with a flame propagation sub-model can used for predicting the cycle-to-cycle variations of combustion in a spark ignition (SI) engine operating at very lean and high exhaust gas residual conditions. Under such conditions, the variations have been shown to consist of both deterministic and stochastic components. The deterministic component is inherent to the non-linear nature of the combustion efficiency variation with equivalence ratio (or dilution level) while the stochastic component results primarily from noise associated with the parameters (that are inevitable in a mechanical system) that affect combustion. Since the overall dynamics of the instabilities are driven by the low order deterministic component, if a model can be made to capture this component, the stochastic component is easily modeled by adding noise to the parameters.
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