Vapor pressure (Pvap), heat of vaporization (ΔHvap), liquid heat capacity (Cpl), and ideal gas heat capacity (Cpig) are important properties for process design and optimization. This work focuses on improving the thermodynamic consistency and accuracy of the aforementioned properties since these can drastically affect the reliability, safety, and profitability of chemical processes. They can be measured for pure organic compounds from the triple point, through the normal boiling point, and up to the critical point. Additionally, ΔHvap is proportional to the derivative of vapor pressure with respect to temperature through the Clapeyron equation, and the difference between Cpl and Cpig is proportional to the derivative of heat of vaporization with respect to temperature. In order to improve temperature-dependent correlations, all the properties were analyzed simultaneously. First, a temperature-dependent error model was developed using several versions of the Riedel and Wagner Pvap correlations. The ability of each correlation to match Cpl data was determined for 5 well-known compounds. The Riedel equation performed better than the Wagner equation when the best form was used. Second, the Riedel equation form was further modified, and the best correlation form was found for about 50 compounds over 7 families. This led to the development of a new vapor pressure prediction method using different Riedel equation forms to fit Pvap, ΔHvap, and Cpl data simultaneously. Seventy compounds were tested, and the error compared to liquid heat capacity data dropped from 10% with previous methods to 3% with this new prediction method. Additionally a differential scanning calorimeter (DSC) was purchased, and melting points (Tm), enthalpies of fusion (ΔHfus), and liquid heat capacities (Cpl) were measured for over twenty compounds. For many of these compounds, the vapor pressure data and critical constants were re-evaluated, and new vapor pressure correlations were recommended that were thermodynamically consistent with measured liquid heat capacity data. The Design Institute for Physical Properties (DIPPR) recommends best constants and temperature-dependent values for pure compounds. These improvements were added to DIPPR procedures, and over 200 compounds were re-analyzed so that the temperature-dependent correlations for Pvap, ΔHvap, Cpig, and Cpl became more internally consistent. Recommendations were made for the calculation procedures of these properties for the DIPPR database.

To optimize biodiesel manufacturing, many reported studies have built simulation models to quantify the relationship between operating conditions and process performance. For mass and energy balance simulations, it is essential to know the four fundamental thermophysical properties of the feed oil: liquid density (Ï L), vapor pressure (Pvap), liquid heat capacity (CpL), and heat of vaporization (Î Hvap). Additionally, to characterize the fuel qualities, it is critical to develop quantitative correlations to predict three biodiesel properties, namely, viscosity, cetane number, and flash point. Also, to ensure the operability of biodiesel in cold weather, one needs to quantitatively predict three low-temperature flow properties: cloud point (CP), pour point (PP), and cold filter plugging point (CFPP). This article presents the results from a comprehensive evaluation of the methods for predicting these four essential feed oil properties and six key biodiesel fuel properties. We compare the predictions to reported experimental data and recommend the appropriate prediction methods for each property based on accuracy, consistency, and generality. Of particular significance are (1) our presentation of simple and accurate methods for predicting the six key fuel properties based on the number of carbon atoms and the number of double bonds or the composition of total unsaturated fatty acid methyl esters (FAMEs) and (2) our posting of the Excel spreadsheets for implementing all of the evaluated accurate prediction methods on our group website (www.design.che.vt.edu) for the reader to download without charge. / Master of Science