Gradient-based Constrained Optimization Using a Database of Linear Reduced-Order Models
| Autor: | Youngsoo Choi, Charbel Farhat, Spenser Anderson, Gabriele Boncoraglio, David Amsallem |
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| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Physics and Astronomy (miscellaneous)
Computer science G.1.6 E.4 G.1.8 G.1.1 G.1.2 Parameter space computer.software_genre Projection (linear algebra) G.1.10 FOS: Mathematics Mathematics - Numerical Analysis Pointwise Numerical Analysis Partial differential equation Database Applied Mathematics Constrained optimization Numerical Analysis (math.NA) Aeroelasticity Computer Science Applications Computational Mathematics Nonlinear system Modeling and Simulation Reduction (mathematics) computer |
| Popis: | A methodology grounded in model reduction is presented for accelerating the gradient-based solution of a family of linear or nonlinear constrained optimization problems where the constraints include at least one linear Partial Differential Equation (PDE). A key component of this methodology is the construction, during an offline phase, of a database of pointwise, linear, Projection-based Reduced-Order Models (PROM)s associated with a design parameter space and the linear PDE(s). A parameter sampling procedure based on an appropriate saturation assumption is proposed to maximize the efficiency of such a database of PROMs. A real-time method is also presented for interpolating at any queried but unsampled parameter vector in the design parameter space the relevant sensitivities of a PROM. The practical feasibility, computational advantages, and performance of the proposed methodology are demonstrated for several realistic, nonlinear, aerodynamic shape optimization problems governed by linear aeroelastic constraints. |
| Databáze: | OpenAIRE |
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