*Geometry optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F14%3A00228478" target="_blank" >RIV/68407700:21110/14:00228478 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

*Geometry optimization

Popis výsledku v původním jazyce

*This report describes a methodology for the WP3 - Geometry optimization. The deterministic optimization procedures have been already described in reports of WP1 and WP2. Therefore, Robust/Reliability (Design) Optimization methodologies are investigatedin this work. In other words, the inclusion of probabilistic descriptions of Noise parametersare presented. Reliability-based design optimization (RBDO) is a research area that tries to optimize structures under assumption of uncertainties. Usually, theobjective function (e.g. a structure weight, a maximal displacement etc.) is to be minimized with respect to constraints in which the probabilistic approach is included. It is hard or nearly impossible to create an analytical probabilistic approach on real structures thus some alternative method should be used. Our solution utilizes a surrogate-based Monte Carlo approach which is enhanced by an adaptive Design of (Computer) Experiments (DoE). As the model is enumerated many times, it is

Název v anglickém jazyce

*Geometry optimization

Popis výsledku anglicky

*This report describes a methodology for the WP3 - Geometry optimization. The deterministic optimization procedures have been already described in reports of WP1 and WP2. Therefore, Robust/Reliability (Design) Optimization methodologies are investigatedin this work. In other words, the inclusion of probabilistic descriptions of Noise parametersare presented. Reliability-based design optimization (RBDO) is a research area that tries to optimize structures under assumption of uncertainties. Usually, theobjective function (e.g. a structure weight, a maximal displacement etc.) is to be minimized with respect to constraints in which the probabilistic approach is included. It is hard or nearly impossible to create an analytical probabilistic approach on real structures thus some alternative method should be used. Our solution utilizes a surrogate-based Monte Carlo approach which is enhanced by an adaptive Design of (Computer) Experiments (DoE). As the model is enumerated many times, it is

Druh

V_souhrn - Souhrnná výzkumná zpráva

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2014

Kód důvěrnosti údajů

C - Předmět řešení projektu podléhá obchodnímu tajemství (§ 504 Občanského zákoníku), ale název projektu, cíle projektu a u ukončeného nebo zastaveného projektu zhodnocení výsledku řešení projektu (údaje P03, P04, P15, P19, P29, PN8) dodané do CEP, jsou upraveny tak, aby byly zveřejnitelné.

Počet stran výsledku

14

Místo vydání

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Název nakladatele resp. objednatele

Astrium GmbH, Business Unit Space Transportation

Verze

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