Numerical Methods for Stochastic Partial Differential Equations

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This is the final report of a Laboratory Directed Research and Development (LDRD) project at the Los Alamos National laboratory (LANL). The objectives of this proposal were (1) the development of methods for understanding and control of spacetime discretization errors in nonlinear stochastic partial differential equations, and (2) the development of new and improved practical numerical methods for the solutions of these equations. The authors have succeeded in establishing two methods for error control: the functional Fokker-Planck equation for calculating the time discretization error and the transfer integral method for calculating the spatial discretization error. In addition they have developed ... continued below

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Sharp, D.H.; Habib, S. & Mineev, M.B. July 8, 1999.

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Description

This is the final report of a Laboratory Directed Research and Development (LDRD) project at the Los Alamos National laboratory (LANL). The objectives of this proposal were (1) the development of methods for understanding and control of spacetime discretization errors in nonlinear stochastic partial differential equations, and (2) the development of new and improved practical numerical methods for the solutions of these equations. The authors have succeeded in establishing two methods for error control: the functional Fokker-Planck equation for calculating the time discretization error and the transfer integral method for calculating the spatial discretization error. In addition they have developed a new second-order stochastic algorithm for multiplicative noise applicable to the case of colored noises, and which requires only a single random sequence generation per time step. All of these results have been verified via high-resolution numerical simulations and have been successfully applied to physical test cases. They have also made substantial progress on a longstanding problem in the dynamics of unstable fluid interfaces in porous media. This work has lead to highly accurate quasi-analytic solutions of idealized versions of this problem. These may be of use in benchmarking numerical solutions of the full stochastic PDEs that govern real-world problems.

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Medium: P; Size: vp.

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OSTI as DE00759177

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  • Other Information: PBD: 8 Jul 1999

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  • Report No.: LA-UR-99-3185
  • Grant Number: W-7405-ENG-36
  • DOI: 10.2172/759177 | External Link
  • Office of Scientific & Technical Information Report Number: 759177
  • Archival Resource Key: ark:/67531/metadc710592

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  • July 8, 1999

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  • Sept. 12, 2015, 6:31 a.m.

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  • March 23, 2016, 10:46 a.m.

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Sharp, D.H.; Habib, S. & Mineev, M.B. Numerical Methods for Stochastic Partial Differential Equations, report, July 8, 1999; New Mexico. (digital.library.unt.edu/ark:/67531/metadc710592/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.