282616 Modeling Properties of Biodiesel Blends

Thursday, November 1, 2012: 10:10 AM
322 (Convention Center )
Sevana Baghdasarian, Chemical and Materials Engineering, California State Polytechnic University-Pomona, Pomona, CA and Sabyasachi Sen, Chemical and Materials Engineering , California State Polytechnic University-Pomona, Pomona, CA

Recent environmental and economic considerations have led to significant interest in biodiesels, which are an important part of the rapidly expanding quest for green energy. Biodiesels are of plant- or animal-origin and are, typically, triglycerides transformed into methyl esters. Unfortunately, on account of differences in key properties pertaining to engine performance (e.g., density, viscosity, cold flow properties), a diesel fuel cannot be completely (100%) substituted by biodiesel (B100). Usually, this problem is resolved by blending diesels (of mineral origin, commonly #2 diesel) with appropriate biodiesels for use in internal combustion engines. Currently, blend rations of 5% biodiesel with 95% diesel (B05) are commonly used. Improved understanding of the composition-dependence of such diesel-biodiesel blends will go a long way in enabling the use of higher biodiesel blend rations in the future of green energy.

Many chemists and engineers around the globe are studying the effect of blending biodiesels with diesels upon fuel properties. There is now a significant (and rapidly growing) body of recent literature reporting properties of different binary and ternary systems involving blends of various diesels and biodiesels. On the other hand, just a few publications have been recognized to have focused on the modeling properties of such blends. Moreover, the proposed models for predicting such properties of blends have worked out well on the binary systems but not on the systems composing of 3 or more (i.e., multi-component) components. For example, one of the most commonly used models (the Redlich-Kister equation) has been found to be very successful in modeling the properties of many binary blends. However, the framework of this model does easily extend to model multi-component systems. On the other hand, employing VBMR will enable the modeling of multi-component biodiesel blends.

The current investigation models the effect of blending a biodiesel (or set of several biodiesels) with a diesel (or a mixture of several diesels). It enhances the application of the “Virial-Based Mixing Rules” (VBMR) model to correlate the properties of such blends based on “pure component properties” of the constituents, as well as the binary and ternary (even quaternary) interaction parameters. The corollary of this investigation is the creation of a database of interaction coefficients (representing the mixing behavior of various blend systems). These parameters will enable the prediction of the properties of unknown blends.


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