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Towards Robust Sustainable System Design: An Engineering Inspired Approach

Holl, Mario ; Pelz, Peter F. (2022)
Towards Robust Sustainable System Design: An Engineering Inspired Approach.
35th International Modal Analysis Conference (IMAC). Anaheim, California, USA (30.01.–02.02.2017)
doi: 10.26083/tuprints-00020888
Conference or Workshop Item, Secondary publication, Postprint

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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Towards Robust Sustainable System Design: An Engineering Inspired Approach
Language: English
Date: 2022
Place of Publication: Darmstadt
Year of primary publication: 2017
Publisher: Springer
Book Title: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics 2017
Series: Conference Proceedings of the Society for Experimental Mechanics Series
Series Volume: 3
Event Title: 35th International Modal Analysis Conference (IMAC)
Event Location: Anaheim, California, USA
Event Dates: 30.01.–02.02.2017
DOI: 10.26083/tuprints-00020888
Corresponding Links:
Origin: Secondary publication service

An engineering inspired method called multi-pole system analysis (MPSA) is presented and applied to an innovative wind-energy converter. The method offers a consecutive and structured guideline to determine optimal system designs in the tense interrelations of sustainability requirements, e.g. energetic efficiency, economic profitability and environmental quality. The method consists of the four steps of (1) system synthesis, (2) system analysis under uncertainty, (3) stochastic system optimization and (4) sensitivity analysis and addresses the involved uncertainty due to lack of information in the early stage of system design. As the results indicate, only a simultaneous consideration of the involved domains can truly lead to an optimal system design. By incorporating uncertainty aspects within the second step of the method and performing stochastic optimization, the disadvantage of missing robustness of previous deterministic optimal systems is overcome.

Status: Postprint
URN: urn:nbn:de:tuda-tuprints-208885
Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 16 Department of Mechanical Engineering > Institute for Fluid Systems (FST) (since 01.10.2006)
Date Deposited: 29 Apr 2022 12:34
Last Modified: 27 Mar 2023 11:28
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/20888
PPN: 495503878
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