Intrusive uncertainty quantification method for simulations of gas-liquid multiphase flows

Abstract

Simulations of fluid dynamics play an increasingly important role in the development of new technology. For example, engineers may need to simulate an atomizing jet to create a better direct injection system for improving fuel economy in a vehicle, or to more efficiently spray water for building fire mitigation systems. The increased use of computational fluid dynamics requires improvements in methodology to improve simulation efficiency and accuracy. We can extract a great deal from these models, including uncertainty information. Although simulation of gas-liquid multiphase flow scenarios are common, most are deterministic in nature. Model parameters, like fluid density or viscosity, are assumed to be known and fixed. But this is not usually the case, and a research gap exists for uncertainty analysis in these simulations. For efficient performance, an intrusive approach is used to create a multiphase solver capable of uncertainty analysis. Variables of interest, such as velocity and pressure, are converted into stochastic variables which are allowed to vary in an added uncertainty dimension. Variability is then added to fluid parameters or initial/boundary conditions and a simulation is run which produces stochastic results. To verify the solver, several cases are presented which compare the ability of the solver against analytic solutions. Once satisfied with the ability of the solver, we can answer questions about more complex scenarios. For instance, we may question how uncertainty about the surface tension force may affect the atomization of a jet and find that fluids with a lower surface tension coefficient breakup sooner (as expected). We could also consider scenarios that may not have such an obvious outcome, such as imposing uncertainty about the density ratio for an atomizing jet to determine the effect of running simulations at low vs high density ratios. multiUQ is capable of producing accurate results of real world situations. As a tool it can provide additional insight into understanding complicated multiphase flow systems.