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The volume translation technique and the adjustment of binary iteration parameters were applied to fit the generated data.
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Initially, new binary interaction parameters were estimated for (CO2 + glycol) binary mixtures.
Also, the corresponding binary interaction parameters were regressed.
In each of the iteration, Model parameters were randomly sampled across their respective distribution range.
With the aforementioned iteration method, two parameters were estimated: the blood fraction and the lipid fraction.
The Markov Chain Monte Carlo (MCMC) sampling algorithm was run for an initial 1000 iterations before model parameters were monitored for a further 1000 iterations.
At each iteration, less and less stringent parameters were used because each iteration added constraints to the subsequent one.
The binary NRTL and UNIQUAC interaction parameters were obtained.
All these parameters were binary variables.
Five million iterations were performed, of which the model parameters were sampled every 1000 iterations.
For all runs, the first half of the iterations was discarded as burn-ins, and parameters were sampled every 100 iterations during the second half.
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