A modeling approach to transitional channel flow

Sahan, Rıdvan A.; Güneş, Hasan; Liakopoulos, A.

doi:10.1016/s0045-7930(97)00016-9

Cited by 8 publications

(2 citation statements)

References 27 publications

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“…Surrogate functions and reducedorder meta-models have also been used in the field of control systems to reduce the order of the overall transfer function [26]. A very popular physics-based meta-modeling technique consists of carrying out the approximation on the full vector fields using PCA and Galerkin projection [1] in CFD [21,27] as well as in structural analysis [12] and has been successfully applied to a number of areas such as flow modeling [23,13], optimal flow control [21], aerodynamics design optimization [18,11] or structural mechanics [14]. In [7], a snapshot-weighting scheme introduced using vector sensitivities as system snapshots to compute a robust reduced order model well-suited to optimization.…”

Section: Introductionmentioning

confidence: 99%

A Diffuse-Morphing Algorithm for Shape Optimization

Raghavan¹,

Breitkopf²,

Villon³

2014

Proceedings of 10th World Congress on Computational Mechanics

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Shape optimization typically involves geometries characterized by several dozen design variables and a possibly high number of explicit/implicit constraints restricting the design space to admissible shapes. In this work, instead of working with parametrized CAD models, the idea is to interpolate between admissible instances of finite element/CFD meshes. We show that a properly chosen surrogate model can replace the numerous geometry-based design variables with a more compact set permitting a global understanding of the admissible shapes spanning the design domain, thus reducing the size of the optimization problem. To this end, we present a two-level mesh parametrization approach for the design domain geometry based on Diffuse Approximation in a properly chosen locally linearized space, and replace the geometry-based variables with the smallest set of variables needed to represent a manifold of admissible shapes for a chosen precision. We demonstrate this approach in the problem of designing the section of an A/C duct to maximize the permeability evaluated using CFD.

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Section: Introductionmentioning

confidence: 99%

A Diffuse-Morphing Algorithm for Shape Optimization

Raghavan¹,

Breitkopf²,

Villon³

2014

Proceedings of 10th World Congress on Computational Mechanics

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“…A popular physics-based meta-modeling technique consists of carrying out the approximation on the full vector fields using PCA and Galerkin projection [5] in CFD [6] as well as in structural analysis [7]. This approach has been successfully applied to a number of areas such as flow modeling [8,9] optimal flow control [10], aerodynamics design optimization [11] or structural mechanics [12]. However, this requires manipulation of the input variablesV .…”

Section: Introduction Literature Reviewed and Motivation For Researchmentioning

confidence: 99%

Towards simultaneous reduction of both input and output spaces for interactive simulation-based structural design

Raghavan¹,

Xia²,

Breitkopf³

et al. 2013

Computer Methods in Applied Mechanics and Engineering

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International audienceEngineering design problems generally involve a high-dimensional input space of design variables yielding an output space by means of costly high-fidelity evaluations. In order to decrease the overall cost, reduced-order models for the output space such as Proper Orthogonal Decomposition (POD) and Proper Generalized Decomposition (PGD) are an active area of research. However, little research has been conducted into alleviating the problems associated with a high-dimensional input space. In addition to higher dimensionality being an impediment to efficient design by itself, complex shapes involve a high number of explicit/implicit constraints restricting the design space. Geometric parameterization methods in traditional CAD present difficulties in expressing these constraints leading to a high failure rate and the generation of inadmissible shapes. In this paper, we propose a simultaneous meta-modeling protocol for both input and output spaces. We perform a reparametrization of the input space using constrained shape interpolation by introducing the concept of an alpha-manifold of admissible meshed shapes. The output space is reduced using constrained Proper Orthogonal Decomposition. By simultaneously using metamodeling for both spaces, we facilitate interactive design space exploration for the purpose of design. The proposed approach is applied to the industrial problem of designing a car engine intake port

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