On Shape Deformation Techniques for Simulation-Based Design Optimization

Sieger, Daniel; Menzel, Stefan; Botsch, Mario

doi:10.1007/978-3-319-06053-8_14

Cited by 33 publications

(23 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For a deeper insight, see Lassila and Rozza (2010); Koshakji, Quarteroni, and Rozza (2013); Forti and Rozza (2014) and Sieger, Menzel, and Botsch (2015) for an application very similar to ours. A comprehensive dissertation on different geometry deformation techniques (in particular FFD based techniques) can be found in Anderson, Aftosmis, and Nemec (2012).…”

Section: Geometry Morphingmentioning

confidence: 66%

Free-form deformation, mesh morphing and reduced-order methods: enablers for efficient aerodynamic shape optimisation

Salmoiraghi

Scardigli

Telib

et al. 2018

International Journal of Computational Fluid Dynamics

View full text Add to dashboard Cite

In this work we provide an integrated pipeline for the model order reduction of turbulent flows around parametrised geometries in aerodynamics. In particular, Free-Form Deformation is applied for geometry parametrisation, whereas two different reduced-order models based on Proper Orthogonal Decomposition (POD) are employed in order to speed-up the full-order simulations: the first method exploits POD with interpolation, while the second one is based on domain decomposition. For the sampling of the parameter space, we adopt a Greedy strategy coupled with Constrained Centroidal Voronoi Tessellations, in order to guarantee a good compromise between space exploration and exploitation.The proposed framework is tested on an industrially relevant application, i.e. the front-bumper morphing of the DrivAer car model, using the finite-volume method for the full-order resolution of the Reynolds-Averaged Navier-Stokes equations.

show abstract

Section: Geometry Morphingmentioning

confidence: 66%

Free-form deformation, mesh morphing and reduced-order methods: enablers for efficient aerodynamic shape optimisation

Salmoiraghi

Scardigli

Telib

et al. 2018

International Journal of Computational Fluid Dynamics

View full text Add to dashboard Cite

show abstract

“…Such techniques avoid re-meshing the simulation domain, speeding up the optimization process. Several cases of optimization using morphing techniques are published in the literature [16][17][18]22]. For our experiments, we implemented the free form deformation (FFD) method presented in [21].…”

Section: Efficient Oversampling Strategies For Improved Vehicle Mesh mentioning

confidence: 99%

On the Performance of Oversampling Techniques for Class Imbalance Problems

Kong

Rios

Kowalczyk

et al. 2020

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Although over 90 oversampling approaches have been developed in the imbalance learning domain, most of the empirical study and application work are still based on the "classical" resampling techniques. In this paper, several experiments on 19 benchmark datasets are set up to study the efficiency of six powerful oversampling approaches, including both "classical" and new ones. According to our experimental results, oversampling techniques that consider the minority class distribution (new ones) perform better in most cases and RACOG gives the best performance among the six reviewed approaches. We further validate our conclusion on our real-world inspired vehicle datasets and also find applying oversampling techniques can improve the performance by around 10%. In addition, seven data complexity measures are considered for the initial purpose of investigating the relationship between data complexity measures and the choice of resampling techniques. Although no obvious relationship can be abstracted in our experiments, we find F1v value, a measure for evaluating the overlap which most researchers ignore, has a strong negative correlation with the potential AUC value (after resampling).

show abstract

“…In CAE, B-splines and NURBS (Non-uniform rational B-splines) play a major role, as they allow the modification of shapes at different scales with few parameters. Shape deformation techniques with free form deformation (FFD) as a most prominent splinebased method directly alter the node points of an underlying geometric mesh which make them very flexible in terms of choosing a reasonable number of parameters and introducing locality on the deformations [6], [7]. Here, the geometry is embedded in a lattice of control points, the so-called control volume, and the shape is modified and optimized by moving selected control points in 3D space [7].…”

Section: Related Literaturementioning

confidence: 99%

“…Shape deformation techniques with free form deformation (FFD) as a most prominent splinebased method directly alter the node points of an underlying geometric mesh which make them very flexible in terms of choosing a reasonable number of parameters and introducing locality on the deformations [6], [7]. Here, the geometry is embedded in a lattice of control points, the so-called control volume, and the shape is modified and optimized by moving selected control points in 3D space [7]. Zhang et al [6] show that the defined dimensionality of a problem for shape optimization can restrict the optimal design.…”

Section: Related Literaturementioning

confidence: 99%

Optimal Evolutionary Optimization Hyper-parameters to Mimic Human User Behavior

Saha

Rios

Minku

et al. 2019

2019 IEEE Symposium Series on Computational Intelligence (SSCI)

Self Cite

View full text Add to dashboard Cite

Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

show abstract

On Shape Deformation Techniques for Simulation-Based Design Optimization

Cited by 33 publications

References 29 publications

Free-form deformation, mesh morphing and reduced-order methods: enablers for efficient aerodynamic shape optimisation

Free-form deformation, mesh morphing and reduced-order methods: enablers for efficient aerodynamic shape optimisation

On the Performance of Oversampling Techniques for Class Imbalance Problems

Optimal Evolutionary Optimization Hyper-parameters to Mimic Human User Behavior

Contact Info

Product

Resources

About