Skip navigation

On the influence of uncertainty in computational simulations of a high-speed jet flow from an aircraft exhaust

On the influence of uncertainty in computational simulations of a high-speed jet flow from an aircraft exhaust

Granados-Ortiz, Francisco-Javier, Arroyo, Carlos Perez, Puigt, Guillaume, Lai, Choi-Hong ORCID: 0000-0002-7558-6398 and Airiau, Christophe (2018) On the influence of uncertainty in computational simulations of a high-speed jet flow from an aircraft exhaust. Computers & Fluids, 180. pp. 139-158. ISSN 0045-7930 (doi:https://doi.org/10.1016/j.compfluid.2018.12.003)

[img] PDF (Author Accepted Manuscript)
22389 LAI On_the_Influence_of_Uncertainty_in_Computational_Simulations_2018.pdf - Accepted Version
Restricted to Repository staff only until 15 December 2019.

Download (3MB) | Request a copy

Abstract

A classic approach to Computational Fluid Dynamics (CFD) is to perform simulations with a fixed set of variables in order to account for parameters and boundary conditions. However, experiments and real-life performance are subject to variability in their conditions. In recent years, the interest of performing simulations under uncertainty is increasing, but this is not yet a common rule, and simulations with lack of information are still taking place. This procedure could be missing details such as whether sources of uncertainty affect dramatic parts in the simulation of the flow. One of the reasons of avoiding to quantify uncertainties is that they usually require to run an unaffordable number of CFD simulations to develop the study.

To face this problem, Non-Intrusive Uncertainty Quantification (UQ) has been applied to 3D Reynolds-Averaged Navier-Stokes simulations of an under-expanded jet from an aircraft exhaust with the Spalart-Allmaras turbulent model, in order to assess the impact of inaccuracies and quality in the simulation. To save a large number of computations, sparse grids are used to compute the integrals and built surrogates for UQ. Results show that some regions of the jet plume can be more sensitive than others to variance in both physical and turbulence model parameters. The Spalart-Allmaras turbulent model is demonstrated to have an accurate performance with respect to other turbulent models in RANS, LES and experimental data, and the contribution of a large variance in its parameter is analysed. This investigation explicitly outlines, exhibits and proves the details of the relationship between diverse sources of input uncertainty, the sensitivity of different quantities of interest to said uncertainties and the spatial distribution arising due to their propagation in the simulation of the high-speed jet flow. This analysis represents first numerical study that provides evidence for this heuristic observation.

Item Type: Article
Uncontrolled Keywords: Uncertainty, Sensitivity, CFD, Jets, RANS
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Mathematical Sciences
Last Modified: 17 May 2019 10:49
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: GREAT 1
URI: http://gala.gre.ac.uk/id/eprint/22389

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics