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    Flow Pattern Transition in Pipes Using Data-Driven and Physics-Informed Machine Learning 

    Source: Journal of Fluids Engineering:;2020:;volume( 143 ):;issue: 003:;page 031401-1
    Author(s): Quintino, André Mendes; da Rocha, Davi Lôtfi Lavôr Navarro; Fonseca Júnior, Roberto; Rodriguez, Oscar Mauricio Hernandez
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Flow pattern is an important engineering design factor in two-phase flow in the chemical, nuclear, and energy industries, given its effects on pressure drop, holdup, and heat and mass transfer. The prediction of two-phase ...
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