# (314g) Thermodynamic Consistency-Based Validation Approach for Equation of State Methods in Process Simulators

Authors:
Schneider Electric
Invensys/SimSci-Esscor
Schneider Electric
Schneider Electric

1.Objectives

Development of physical property estimation module
on process simulators requires proper validation approaches to confirm that the
entire process of derivation and programing of a number of equations has been correctly
performed. Conventional approaches, such as comparison between analytical solutions
and numerical solutions, can be applicable to each step in the process. However,
recent equations of state (EOS) method involve huge numbers of complex
equations and steps in the process, and eventually require increased efforts
for validation. So, this work seeks for a new validation approach which can
check consistency between input and output of the EOS methods to detect any error
in the entire process.

2. Methodology

Extensive variables such as Gibbs energy show 1st
order homogeneousness. For example residual Gibbs energy at constant
temperature and pressure can be expressed by the following equation using its
composition derivatives.

Applying similar concept to excess Gibbs energy
yields the well-known Gibbs-Duhem equation for activity coefficient, which has
been applied to variation of experimental data.  In this work, we discuss
validation approach based on Eq.(1) for EOS methods in process simulators.

3.Proposed Approach

Many of recent EOSs are described with residual
Helmholtz energy at constant temperature and volume (Ares,T,V). Prediction of physical properties often
get through density calculation at first, followed by that for fugacity
coefficients. This work proposed a validation approach which checked that the
following two procedures gave exactly the same value for residual Gibbs energy at
constant temperature and pressure (Gres,T,P).

1)Direct calculation from Ares,T,V

The following equation was directly obtained
from the definition of Gres,T,P and Ares,T,V.  2)Calculation from fugacity
coefficient.

Just substituting fugacity coefficient
into Eq.(1) yielded;

The dimensionless value of (Gres,T,P /nRT)
by Eq.(2) must match that of Eq.(3), if all the derivation and programing of
fugacity coefficient and density from EOS is perfect,
and if the convergence tolerance for density is enough small.

4.Example Case

For the purpose of testing the approach,
a standalone program for predicting vapor-liquid equilibrium (VLE) using
Huron-Vidal method1) was created to confirm the ability of the above
validation approach. When all the derivation and the programing had been
perfectly done, (Gres,T,P /nRT)  calculated
by Eq.(2) perfectly matched that of Eq.(3) in a
precision limit of computation. The deviation was less than a value typically
like 1.0x10-15[-] (depending on calculation
environment).

When we have intentionally bought an error
into the derivation, or have intentionally eased the convergence tolerance for
density, significant deviation in a magnitude of 1.0x10-3[-](depending
on calculation environment) was found between
the values of (Gres,T,P
/nRT), even when the calculated VLE did not alter a lot by the
introduction of the error. Eventually the test results indicated that the above
validation approach was enough sensitive to detect errors.

5.Conclusions

We have established a software validation approach
based on thermodynamic consistency to confirm that the entire process of the derivation
and the programing was perfectly conducted in prediction modules for phase
equilibrium. The approach turned out to be enough sensitive to detect error,
and eventually contribute a lot to ensuring the software quality.

[Nomenclature]

(Alphabet) A: Helmholtz energy, G: Gibbs energy, n:
quantity, R: Gas constant, T: Temperature, V: volume, x: mole fraction, Z:
Compressibility factor, ∅: Fugacity coefficient

(Subscript)  i: component identification
number, ig: ideal gas, res: residual

[Literature Cited]

1) Marie-Jose Huron and Jean Vidal; Fluid Phase
Equil.3,255-271(1979)

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