Handle URI:
http://hdl.handle.net/10754/624104
Title:
Multiphase flows in complex geometries: a UQ perspective
Authors:
Icardi, Matteo ( 0000-0003-3924-3117 )
Abstract:
Nowadays computer simulations are widely used in many multiphase flow applications involving interphases, dispersed particles, and complex geometries. Most of these problems are solved with mixed models composed of fundamental physical laws, rigorous mathematical upscaling, and empirical correlations/closures. This means that classical inference techniques or forward parametric studies, for example, becomes computationally prohibitive and must take into account the physical meaning and constraints of the equations. However mathematical techniques commonly used in Uncertainty Quantification can come to the aid for the (i) modeling, (ii) simulation, and (iii) validation steps. Two relevant applications for environmental, petroleum, and chemical engineering will be presented to highlight these aspects and the importance of bridging the gaps between engineering applications, computational physics and mathematical methods. The first example is related to the mathematical modeling of sub-grid/sub-scale information with Probability Density Function (PDF) models in problems involving flow, mixing, and reaction in random environment. After a short overview of the research field, some connections and similarities with Polynomial Chaos techniques, will be investigated. In the second example, averaged correlations laws and effective parameters for multiphase flow and their statistical fluctuations, will be considered and efficient computational techniques, borrowed from high-dimensional stochastic PDE problems, will be applied. In presence of interfacial flow, where small spatial scales and fast time scales are neglected, the assessment of robustness and predictive capabilities are studied. These illustrative examples are inspired by common problems arising, for example, from the modeling and simulation of turbulent and porous media flows.
KAUST Department:
Computer, Electrical and Mathematical Sciences & Engineering (CEMSE)
Conference/Event name:
Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)
Issue Date:
7-Jan-2015
Type:
Presentation
Additional Links:
http://mediasite.kaust.edu.sa/Mediasite/Play/3b1ab410b64f486aa6f3162c7baed8fa1d?catalog=ca65101c-a4eb-4057-9444-45f799bd9c52
Appears in Collections:
Presentations; Conference on Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)

Full metadata record

DC FieldValue Language
dc.contributor.authorIcardi, Matteoen
dc.date.accessioned2017-06-05T08:35:48Z-
dc.date.available2017-06-05T08:35:48Z-
dc.date.issued2015-01-07-
dc.identifier.urihttp://hdl.handle.net/10754/624104-
dc.description.abstractNowadays computer simulations are widely used in many multiphase flow applications involving interphases, dispersed particles, and complex geometries. Most of these problems are solved with mixed models composed of fundamental physical laws, rigorous mathematical upscaling, and empirical correlations/closures. This means that classical inference techniques or forward parametric studies, for example, becomes computationally prohibitive and must take into account the physical meaning and constraints of the equations. However mathematical techniques commonly used in Uncertainty Quantification can come to the aid for the (i) modeling, (ii) simulation, and (iii) validation steps. Two relevant applications for environmental, petroleum, and chemical engineering will be presented to highlight these aspects and the importance of bridging the gaps between engineering applications, computational physics and mathematical methods. The first example is related to the mathematical modeling of sub-grid/sub-scale information with Probability Density Function (PDF) models in problems involving flow, mixing, and reaction in random environment. After a short overview of the research field, some connections and similarities with Polynomial Chaos techniques, will be investigated. In the second example, averaged correlations laws and effective parameters for multiphase flow and their statistical fluctuations, will be considered and efficient computational techniques, borrowed from high-dimensional stochastic PDE problems, will be applied. In presence of interfacial flow, where small spatial scales and fast time scales are neglected, the assessment of robustness and predictive capabilities are studied. These illustrative examples are inspired by common problems arising, for example, from the modeling and simulation of turbulent and porous media flows.en
dc.relation.urlhttp://mediasite.kaust.edu.sa/Mediasite/Play/3b1ab410b64f486aa6f3162c7baed8fa1d?catalog=ca65101c-a4eb-4057-9444-45f799bd9c52en
dc.titleMultiphase flows in complex geometries: a UQ perspectiveen
dc.typePresentationen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences & Engineering (CEMSE)en
dc.conference.dateJanuary 6-9, 2015en
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)en
dc.conference.locationKAUSTen
kaust.authorIcardi, Matteoen
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