Estimation of Thermodynamic Properties

1. Estimation of Thermodynamic Properties Auburn University Robert Kline 1/19/12

2. Overview • Why? • How? • Data Regression • Analogous Systems • Estimation

3. Why? • Pure component data exists for most commercially interesting chemicals • Can be estimated for new chemicals • Mixture data is available for a small fraction of all binary pairs • Interaction parameters (activity and fugacity coefficients) are critical model chemical processes

4. Data Regression • Sources of data • Journals • Compilations (DECHEMA, Horsley) • Internal Reports • Measurements • Data quality • Not all data is created equally • GC Technology (1970s +) greatly increased liquid composition accuracy

5. Data Regression • When should you have it measured? • If it is a critical split between important chemicals • Products with close boiling components • Key splits in columns • If the presence of an azeotrope will render a separation infeasible

6. Data Regression • How to regress? • Use ASPEN • Set mode to Data Regression under Setup • Create a new Data Set under Properties • Create a new Regression Set under Properties • Run the Regression • Set mode back to Flowsheet Simulation under Setup

7. Analogous Systems • Sometimes an unknown system is like a known system (butyl acetate + water vs isobutyl acetate + water) • Two options • Use the same parameters (if the boiling points are similar) • Use the same infinite dilution activity coefficients and regress new parameters

8. Estimation O OH CH2 C H3C H3C O CH2 CH3 • UNIFAQ • Group contribution method • Breaks down the molecule into chunks called groups • Calculates activity coefficients based on group concentrations instead of molecule concentrations • Estimates data and regresses your parameters • Can be reasonably accurate, but you should always review the results to make sure it makes sense