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Conference Paper: A Dynamically Bi-Orthogonal Method for Time-Dependent Stochastic Partial Differential Equation
Title | A Dynamically Bi-Orthogonal Method for Time-Dependent Stochastic Partial Differential Equation |
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Authors | |
Issue Date | 2016 |
Publisher | Society for Industrial and Applied Mathematics. |
Citation | SIAM Conference on Uncertainty Quantification, Lausanne, Switzerland, 5-8 April 2016 How to Cite? |
Abstract | We propose a dynamically bi-orthogonal method (DyBO) to study time dependent stochastic partial differential equations (SPDEs). The objective of our method is to exploit some intrinsic sparse structure in the stochastic solution by constructing the sparsest representation of the stochastic solution via a bi-orthogonal basis. In this talk, we derive an equivalent system that governs the evolution of the spatial and stochastic basis in the KL expansion. Several numerical experiments will be provided to demonstrate
the effectiveness of the DyBO method. |
Description | Session MS3: Uncertainty Quantification for Hyperbolic and Kinetic Equations - Part I of II |
Persistent Identifier | http://hdl.handle.net/10722/236555 |
DC Field | Value | Language |
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dc.contributor.author | Zhang, Z | - |
dc.date.accessioned | 2016-11-25T10:19:05Z | - |
dc.date.available | 2016-11-25T10:19:05Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | SIAM Conference on Uncertainty Quantification, Lausanne, Switzerland, 5-8 April 2016 | - |
dc.identifier.uri | http://hdl.handle.net/10722/236555 | - |
dc.description | Session MS3: Uncertainty Quantification for Hyperbolic and Kinetic Equations - Part I of II | - |
dc.description.abstract | We propose a dynamically bi-orthogonal method (DyBO) to study time dependent stochastic partial differential equations (SPDEs). The objective of our method is to exploit some intrinsic sparse structure in the stochastic solution by constructing the sparsest representation of the stochastic solution via a bi-orthogonal basis. In this talk, we derive an equivalent system that governs the evolution of the spatial and stochastic basis in the KL expansion. Several numerical experiments will be provided to demonstrate the effectiveness of the DyBO method. | - |
dc.language | eng | - |
dc.publisher | Society for Industrial and Applied Mathematics. | - |
dc.relation.ispartof | SIAM Conference on Uncertainty Quantification, 2016 | - |
dc.title | A Dynamically Bi-Orthogonal Method for Time-Dependent Stochastic Partial Differential Equation | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Zhang, Z: zhangzw@hku.hk | - |
dc.identifier.authority | Zhang, Z=rp02087 | - |
dc.identifier.hkuros | 270006 | - |