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The distributions of the mean pressure coefficient using these two types of k−ε−φ turbulence model are improved dramatically compared with those using the standard k−ε turbulence model.
It is shown that after uncertainty minimization against a selected set of n-dodecane combustion data, the predictions of the resulting optimized model are improved notably for all existing n-dodecane data sets tested, including those of the current flow reactor study that were not part of the optimization target list.
The motivation to perform ultrasound, the effectiveness, and the enjoyment of this training model are improved.
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Here, we ask how much the final models are improved if improved contact predictions are used.
Numerical model was improved with respect to the experimental findings.
After refinement by low-throughput experiment validation, the performance of the model was improved.
By increasing the dimension of the 2-dimensional spatial trend function, the model was improved significantly.
Taking this phenomenon into account, Athy's exponential model was improved (Li and Kong 2001).
After calibration, the accuracy of the one-machine model was improved under different conditions.
The spatial resolution of the HIRB model was improved for this purpose.
Compared with the previous Tri-linear model, this model is improved on three aspects.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com