Model hierarchies in space-mapping optimization: Feasibility study for transport processes

Marheineke, Nicole; Pinnau, René

doi:10.3233/jcm-2012-0404

Cited by 9 publications

(8 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Approximation-based approaches have gained attention as they bridge the gap between analytic and numerical approaches in manifold engineering disciplines [8][9][10][11]. Examples of such approaches are kriging, response surface, space mapping, and artificial neural networks [12][13][14].…”

Section: New Tools For Shorter System Development Cyclesmentioning

confidence: 99%

Performance improvements of auxiliary drives for automotive pump and fan applications

Muetze

Leitner

Gruebler

et al. 2020

Elektrotech. Inftech.

View full text Add to dashboard Cite

The need to increase electrification in the automotive industry has been well recognized. Overshadowed by their larger counterparts used for the car's traction is the increasing number of small electric drives used in automotive applications. As a matter of fact, up to 100 of such drives are used within a typical mid-sized car. This includes performance-, safety-, and comfort-related auxiliary drives, of which around 10 % are used as parts of pumping and fan systems. With such "small drives," i.e., fractional horsepower (FHP) drives at the lower end of the power spectrum, volume, mass, and efficiency have so far only been attributed secondary importance. Yet, the increasing demands on the automotive industry have also resulted in renewed interest not only in the performance parameters of these auxiliary drives, such as energy conversion efficiency, size, and cost, but also in electromagnetic emission, noise, and fault tolerance. This survey article presents selected results on recent achievements in these rather new fields of research and outlines fundamental research questions.

show abstract

Section: New Tools For Shorter System Development Cyclesmentioning

confidence: 99%

Performance improvements of auxiliary drives for automotive pump and fan applications

Muetze

Leitner

Gruebler

et al. 2020

Elektrotech. Inftech.

View full text Add to dashboard Cite

show abstract

“…Leaning on the classification from [1], model hierarchies can be categorized into three broad types: physical-based, algebraic-based and grid-based. Therefore, it is often beneficial to use surrogate models in order to improve efficiency.…”

Section: Multi-fidelity Optimizationmentioning

confidence: 99%

“…These models can be drawn from a model hierarchy. Leaning on the classification from [1], model hierarchies can be categorized into three broad types: physical-based, algebraic-based and grid-based. For example, projection-based model order reduction techniques deliver an algebraic-based model hierarchy.…”

Section: Multi-fidelity Optimizationmentioning

confidence: 99%

Multi‐Fidelity Optimization using Reduced Order Models

Tolle

Marheineke

2019

Proc Appl Math and Mech

Self Cite

View full text Add to dashboard Cite

Optimal control problems constrained to nonlinear partial differential equations appear in many applications. Because the discretization of these problems leads to large-scale systems, a direct approach is not always viable. We consider the aggressive space-mapping approach using surrogate models derived with the help of model order reduction techniques in order to efficiently solve such problems, while maintaining an acceptable accuracy. Numerical results based on a medical application (laser-induced thermotherapy) are used to evaluate the effectiveness of the proposed approach.In many applications, the direct solution of optimal control problems is not always viable, due to the associated computational costs. Therefore, it is often beneficial to use surrogate models in order to improve efficiency. These models can be drawn from a model hierarchy. Leaning on the classification from [1], model hierarchies can be categorized into three broad types: physical-based, algebraic-based and grid-based. For example, projection-based model order reduction techniques deliver an algebraic-based model hierarchy. While one could simply optimize with respect to a coarse (cheap) model in order to reduce the computational effort at the cost of accuracy, the space-mapping approach offers a more elegant solution by aligning the optimization of a fine (accurate) model with a coarse one.Assuming that a fine and coarse model f and c, respectively, are available, then the space-mapping function p : U f → U c ,

show abstract

“…The space-mapping technique [1,4] aligns a (fast) coarse model c : U c → R m with an (exact) fine model f : U f → R m with the help of the space mapping function…”

Section: Space-mappingmentioning

confidence: 99%

Efficient Therapy Planning via Model Reduction for Laser-Induced Interstitial Thermotherapy

Tolle

Marheineke

2018

Preprint

Self Cite

View full text Add to dashboard Cite

We investigate the planning of minimally invasive tumor treatments via laser-induced thermotherapy. The goal is to control the laser in order to obtain an optimal treatment, e.g. eradicating the tumor, while leaving as much healthy tissue unharmed as possible. To this end, we define a PDE-constrained optimal control problem. As these problems are usually computationally expensive, we propose a simplified modeling approach using reduced-order models. Numerical results illustrate the viability of our approach.

show abstract

Model hierarchies in space-mapping optimization: Feasibility study for transport processes

Cited by 9 publications

References 23 publications

Performance improvements of auxiliary drives for automotive pump and fan applications

Performance improvements of auxiliary drives for automotive pump and fan applications

Multi‐Fidelity Optimization using Reduced Order Models

Efficient Therapy Planning via Model Reduction for Laser-Induced Interstitial Thermotherapy

Contact Info

Product

Resources

About