Interfacial modeling is of widespread interest in manufacturing, imaging, and scientific applications. Presented here is an interfacial reconstruction method designed for use in Computational Fluid Dynamics (CFD) simulations of nucleate boiling, yet it is more broadly applicable. Nucleate boiling is vital in current and emerging technologies due to the high heat transfer at low temperature. A challenge for multiphase CFD simulation with phase change mass flux is the competing interests of quality mass transfer conservation, resolution of interfaces, and computational time/power. This Piecewise Linear Interface Calculation-Analytic Size Based (PLIC-ASB) method was developed to mitigate this problem in the volume of fluid simulation method so that all three ends could be achieved simultaneously. Research consisted of a cyclical process of testing in an expanding parameter space to ensure improvement to the PLIC-ASB, the CFD simulation, or the testing itself. This parameter space includes data from: theoretical, numerical, and empirical sources; interface methods, and op- tions (e.g. gradient methods); integration routine sensitivity analysis, and alternate software instantiation. The main findings are: (1) the PLIC-ASB yields high levels of accuracy that converge to theoretical and empirical results as the mesh size is refined. The relative error reduction tends to be over 70% compared to the relevant industry standard. (2) The PLIC-ASB exceeded the design parameters. Symbolic formulation converts easily to code and its exactness permits a sharp interface. (3) The PLIC-ASB was less prone to error due to gradient method changes.
Library of Congress Subject Headings
Interfaces (Physical sciences)--Mathematics; Multiphase flow--Mathematical models; Nucleate boiling--Mathematical models; Computational fluid dynamics
Microsystems Engineering (Ph.D.)
Department, Program, or Center
Microsystems Engineering (KGCOE)
Shipkowski, Simon P., "A Novel Analytic Linear Interface Calculation and Its Use in Computational Fluid Dynamics for Enhanced Multiphase Modeling" (2023). Thesis. Rochester Institute of Technology. Accessed from
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