Search for: All records

Assessing the effects of input uncertainty on simulation results for multiphase flows will allow for more robust engineering designs and improved devices. For example, in atomizing jets, surface tension plays a critical role in determining when and how coherent liquid structures break up. Uncertainty in the surface tension coefficient can lead to uncertainty in spray angle, drop size, and velocity distribution. Uncertainty quantification (UQ) determines how input uncertainties affect outputs, and the approach taken can be classified as non-intrusive or intrusive. A classical, non-intrusive approach is the Monte-Carlo scheme, which requires multiple simulation runs using samples from a distribution of inputs. Statistics on output variability are computed from the many simulation outputs. While non-intrusive schemes are straightforward to implement, they can quickly become cost prohibitive, suffer from convergence issues, and have problems with confounding factors, making it difficult to look at uncertainty in multiple variables at once. Alternatively, an intrusive scheme inserts stochastic (uncertain) variables into the governing equations, modifying the mathematics and numerical methods used, but possibly reducing computational cost. In this work, we extend UQ methods developed for single-phase flows to handle gas-liquid multiphase dynamics by developing a stochastic conservative level set approach and a stochastic continuous surface tension method. An oscillating droplet and a 2-D atomizing jet are used to test the method. In these test cases, uncertainty about the surface tension coefficient and initial starting position will be explored, including the impact on breaking/ merging interfaces.