Choosing a Thermodynamic Model for Use in Simulation 

     Process simulators are great aren't they? If you ever had to solve a material balance around a distillation column by hand (or even with a spreadsheet) you can really appreciate these complex programs. The important thing to remember is that these programs don't know everything. All to often students place blind faith in simulator results. If you don't enter actual experimental data, the simulation will use a thermodynamic model to predict chemical interaction properties. If you're lucky, the simulator may already be set on a model that accurately predicts your system. If not, you might as well throw your computer out a window!

To illustrate the importance of these thermodynamic models, we will examine distillation and VLE.

     First, if you have reliable experimental data....use it! When inputted properly into your simulator, the proper activity coefficients model can calculate the appropriate coefficients to be used to predict the system's behavior at other conditions. If real data is not available, there are some guidelines to follow to help you choose the proper activity coefficient model. We will compare five popular models and their strengths. The models are the NRTL, Wilson, SRK, UNIQUAC, and UNIFAC models. Before we compare, let's define what makes a system "non-ideal". Non-ideality is due to the interaction between molecules due to intermolecular forces. The following groups all contribute to non-ideality hydroxyl groups (-OH), ketone groups (-C=O), aldehyde groups (-CHO), halogens (-Cl, -Br), and carboxylic acid groups (-COOH).

     As an example we will compare how each model predicts the VLE behavior of a MTBE-methanol mixture at atmospheric pressure. This system can be classified as being slightly to moderately non-ideal. As you can see by the graphs below, if someone would have used the SRK method to predict this behavior, the result would have been....well....not good! Mr. Henry Z. Kister gave a good example of why there is no replacement for engineering judgement in his book entitled Distillation Design (McGraw Hill 1992):

     About 15 years ago I was applying a leading and very well known literature correlation as part of my graduate thesis. I punched in keys and the computer printed out results. For some reason the results did not look right. Upon investigation, I discovered the unbelievable: the correlation just did not work for my case. Not that the correlation was bad; over many years, it gained a very healthy reputation. It just happened that it had limitations, just like every other correlation. The limitations of this correlation were fairly well explored, but a quarter of a century after it was derived, I found the hard way that it had one more limitation which remained hidden over all these years.