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The modeling gives a visual insight into the effect of cooling conditions on this transformation.
Pore network modeling gives a reasonable prediction of fluid flow properties at pore scale, and offers the flexibility of studying macroscopic properties relationship with pore structure and geometries.
Comparing the dynamic responses between the experimental results and numerical simulations, the dynamic modeling gives a wonderful interpretation of a slider-crank mechanism.
The combination of the MIC with hierarchical Bayesian modeling gives a powerful method for distinguishing serial and parallel processing at both individual and group levels, even with a limited number of participants and trials.
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Comparing the frequency of the extreme event in each set of models gives a measure of how heavily global warming has loaded the extreme weather dice - or not.
This model gives a process transfer function (Laplace domain).
The model gives a good prediction of the paraffin distribution.
The proposed model gives a better agreement with these experimental results compared to previous models.
As shown in Fig. 3a, the parallel flow model gives a good fit to production data.
Empirical modelling gives a satisfactory agreement between experimental and calculated values.
This model gives a quantitative relationship between the fracture toughness and temperature.
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