Bayesian estimates of parameter variability in the k − ε turbulence model
dc.contributor.author | EDELING, Wouter Nico |
dc.contributor.author
hal.structure.identifier | CINNELLA, Paola
|
dc.contributor.author | DWIGHT, Richard P. |
dc.contributor.author | BIJL, H. |
dc.date.accessioned | 2015 |
dc.date.available | 2015 |
dc.date.issued | 2014 |
dc.date.submitted | 2015 |
dc.identifier.issn | 0021-9991 |
dc.identifier.uri | http://hdl.handle.net/10985/10077 |
dc.description.abstract | In this paper we are concerned with obtaining estimates for the error in Reynolds-Averaged Navier-Stokes (RANS) simulations based on the Launder-Sharma k−ε turbulence closure model, for a limited class of flows. In particular we search for estimates grounded in uncertainties in the space of model closure coeffi-cients, for wall-bounded flows at a variety of favourable and adverse pressure gradients. In order to estimate the spread of closure coefficients which repro-duces these flows accurately, we perform 13 separate Bayesian calibrations – each at a different pressure gradient – using measured boundary-layer velocity profiles, and a statistical model containing a multiplicative model inadequacy term in the solution space. The results are 13 joint posterior distributions over coefficients and hyper-parameters. To summarize this information we compute Highest Posterior-Density (HPD) intervals, and subsequently represent the to-tal solution uncertainty with a probability-box (p-box). This p-box represents both parameter variability across flows, and epistemic uncertainty within each calibration. A prediction of a new boundary-layer flow is made with uncer-tainty bars generated from this uncertainty information, and the resulting error estimate is shown to be consistent with measurement data. |
dc.description.sponsorship | ANR UFO |
dc.language.iso | en |
dc.publisher | Elsevier |
dc.rights | Post-print |
dc.title | Bayesian estimates of parameter variability in the k − ε turbulence model |
ensam.embargo.terms | 3 Months |
dc.identifier.doi | 10.1016/j.jcp.2013.10.027 |
dc.typdoc | Article dans une revue avec comité de lecture |
dc.localisation | Centre de Paris |
dc.subject.hal | Mathématique: Probabilités |
dc.subject.hal | Sciences de l'ingénieur: Mécanique: Mécanique des fluides |
ensam.audience | Internationale |
ensam.page | 73-94 |
ensam.journal | Journal of Computational Physics |
ensam.volume | 258 |
hal.status | unsent |
dc.identifier.eissn | 1090-2716 |