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Optimization-based modeling with applications to transport: Part 3. Computational studies

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Ridzal, Denis R.; Young, Joseph G.; Bochev, Pavel B.; Peterson, Kara J.

This paper is the final of three related articles that develop and demonstrate a new optimization-based framework for computational modeling. The framework uses optimization and control ideas to assemble and decompose multiphysics operators and to preserve their fundamental physical properties in the discretization process. One application of the framework is in the formulation of robust algorithms for optimization-based transport (OBT). Based on the theoretical foundations established in Part 1 and the optimization algorithm for the solution of the remap subproblem, derived in Part 2, this paper focuses on the application of OBT to a set of benchmark transport problems. Numerical comparisons with two other transport schemes based on incremental remapping, featuring flux-corrected remap and the linear reconstruction with van Leer limiting, respectively, demonstrate that OBT is a competitive transport algorithm. © 2012 Springer-Verlag.

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TYPE Conference YEAR 2012
OSTIScopus

Numerical study of a matrix-free trust-region SQP method for equality constrained optimization

Ridzal, Denis R.; Aguilo Valentin, Miguel A.

This is a companion publication to the paper 'A Matrix-Free Trust-Region SQP Algorithm for Equality Constrained Optimization' [11]. In [11], we develop and analyze a trust-region sequential quadratic programming (SQP) method that supports the matrix-free (iterative, in-exact) solution of linear systems. In this report, we document the numerical behavior of the algorithm applied to a variety of equality constrained optimization problems, with constraints given by partial differential equations (PDEs).

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TYPE SAND Report YEAR 2011
OSTIDOI

A toolbox for a class of discontinuous Petrov-Galerkin methods using trilinos

Ridzal, Denis R.; Bochev, Pavel B.

The class of discontinuous Petrov-Galerkin finite element methods (DPG) proposed by L. Demkowicz and J. Gopalakrishnan guarantees the optimality of the solution in an energy norm and produces a symmetric positive definite stiffness matrix, among other desirable properties. In this paper, we describe a toolbox, implemented atop Sandia's Trilinos library, for rapid development of solvers for DPG methods. We use this toolbox to develop solvers for the Poisson and Stokes problems.

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TYPE SAND Report YEAR 2011
DOIOSTI

Formulation, analysis and numerical study of an optimization-based conservative interpolation (remap) of scalar fields for arbitrary Lagrangian-Eulerian methods

Journal of Computational Physics

Bochev, Pavel; Ridzal, Denis R.; Scovazzi, Guglielmo S.; Shashkov, Mikhail

We develop and study the high-order conservative and monotone optimization-based remap (OBR) of a scalar conserved quantity (mass) between two close meshes with the same connectivity. The key idea is to phrase remap as a global inequality-constrained optimization problem for mass fluxes between neighboring cells. The objective is to minimize the discrepancy between these fluxes and the given high-order target mass fluxes, subject to constraints that enforce physically motivated bounds on the associated primitive variable (density). In so doing, we separate accuracy considerations, handled by the objective functional, from the enforcement of physical bounds, handled by the constraints. The resulting OBR formulation is applicable to general, unstructured, heterogeneous grids. Under some weak requirements on grid proximity, but not on the cell types, we prove that the OBR algorithm is linearity preserving in one, two and three dimensions. The paper also examines connections between the OBR and the recently proposed flux-corrected remap (FCR), Liska et al. [1]. We show that the FCR solution coincides with the solution of a modified version of OBR (M-OBR), which has the same objective but a simpler set of box constraints derived by using a "worst-case" scenario. Because M-OBR (FCR) has a smaller feasible set, preservation of linearity may be lost and accuracy may suffer for some grid configurations. Our numerical studies confirm this, and show that OBR delivers significant increases in robustness and accuracy. Preliminary efficiency studies of OBR reveal that it is only a factor of 2.1 slower than FCR, but admits 1.5 times larger time steps. © 2011 Elsevier Inc.

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TYPE Journal Article YEAR 2011
ScopusOSTI
Results 101–125 of 136
Results 101–125 of 136