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Two models, predicting viscosity separately from frying conditions and chemical composition, are established, both with an overall accuracy of greater than 95.0%.
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The comparison indicates that this new empirical model can predict viscosity of natural gas with average absolute relative deviation percentage AARD of 2.173.
The problem formulation integrates product quality, as assessed by customers, a model predicting lotion viscosity as a function of its composition and a process model linking process design and operation with lotion composition and microstructure.
Therefore, model (8) can be used to predict viscosity as a function of the n- and iso-paraffin components and carbon number distribution, within the experimental range specified.
The viscosity model can thus be used with confidence to predict viscosity as a function of the i:n mass ratio and carbon number distribution.
Therefore, the existing viscosity models developed for stable and homogeneous emulsions cannot accurately predict viscosity of this kind of liquid-liquid mixtures.
We have made a program mainly based on the PR-EOS to predict viscosity and density together, and the viscosity model of a program presented by Guo (Guo et al. 1999) and based on the PR-EOS.
To check the ability of the proposed viscosity model to present all experimental data, cross plots of the measured and predicted viscosity values were used.
Compositional data of heavy oil viscosity has been used to compare predicted viscosity from the proposed correlation with that from Lorenz Bray Clark (LBC) and Pederson models.
Thereby, an improved rheological model multiplied by a degradation term was proposed that can be effectively used to predict viscosity change in porous media.
The validation showed that this model predicts concrete viscosity with an error of about ±11%.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com