Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F28645413%3A_____%2F17%3AN0000001" target="_blank" >RIV/28645413:_____/17:N0000001 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/7969486/" target="_blank" >https://ieeexplore.ieee.org/document/7969486/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CEC.2017.7969486" target="_blank" >10.1109/CEC.2017.7969486</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system

Popis výsledku v původním jazyce

We tackle three different challenges in solving a real-world industrial problem: formulating the optimization problem, connecting different simulation tools and dealing with computationally expensive objective functions. The problem to be optimized is an air intake ventilation system of a tractor and involves computational fluid dynamics (CFD) simulations. We describe the modeling of the system and its numerical evaluation with different commercial software to obtain three expensive objective functions. To obtain solutions in few function evaluations, a recently proposed surrogate-assisted evolutionary algorithm K-RVEA is applied. The diameters of four different outlets of the ventilation system are considered as decision variables. From the set of nondominated solutions generated by K-RVEA, a decision maker having substance knowledge selected the final one based on his preferences. The final selected solution has better objective function values compared to the baseline solution of the initial design. A comparison of solutions with K-RVEA and RVEA (which does not use surrogates) is also performed to show the potential of using surrogates.

Název v anglickém jazyce

Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system

Popis výsledku anglicky

We tackle three different challenges in solving a real-world industrial problem: formulating the optimization problem, connecting different simulation tools and dealing with computationally expensive objective functions. The problem to be optimized is an air intake ventilation system of a tractor and involves computational fluid dynamics (CFD) simulations. We describe the modeling of the system and its numerical evaluation with different commercial software to obtain three expensive objective functions. To obtain solutions in few function evaluations, a recently proposed surrogate-assisted evolutionary algorithm K-RVEA is applied. The diameters of four different outlets of the ventilation system are considered as decision variables. From the set of nondominated solutions generated by K-RVEA, a decision maker having substance knowledge selected the final one based on his preferences. The final selected solution has better objective function values compared to the baseline solution of the initial design. A comparison of solutions with K-RVEA and RVEA (which does not use surrogates) is also performed to show the potential of using surrogates.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20301 - Mechanical engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Evolutionary Computation (CEC), 2017 IEEE Congress on

ISBN

978-1-5090-4602-7

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

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Název nakladatele

IEEE

Místo vydání

—

Místo konání akce

San Sebastian, Spain

Datum konání akce

5. 6. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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