For decades, traditional scale-modeling techniques have been relying on first-principles models (FPMs). FPMs have been used to find non-dimensional numbers (PIs) and identify normalized underlying forces and energies behind the phenomenon in focus. The two main challenges with FPM-based PIs extraction are finding the relevant PIs and proper correlations between PIs. The emergence and surge of data-driven modeling (DDM) provide a new opportunity to leverage experimental data in model development across scales/plants. In this paper, first, the two mentioned issues in PIs development will be elaborated to reveal the gap, and second, a new insight into scale modeling and similarity concepts will be presented. Then, to showcase the presented framework for a two-fluid spray nozzle case study, DDM techniques will be synergized with FPMs to obtain a robust relationship between relevant properties of the model spray and atomization parameters.
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"Data-driven tools guided by first-principles for scale modeling,"
Progress in Scale Modeling, an International Journal: Vol. 2:
1, Article 1.
Available at: https://uknowledge.uky.edu/psmij/vol2/iss1/1
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