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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/116233

    Title: Robust Topology Optimization of Solid Continua for Peak Response Serviceability to Uncertain Quasi-Static Loads with Temporal Correlation
    Authors: Chien-Kai Wang;Ping-Liang Ko
    Keywords: Robust topology optimization;Peak response serviceability;Loading uncertainty;Temporally correlated quasi-static loads;Design sensitivity analysis
    Date: 2019-02-26
    Issue Date: 2019-04-13 12:10:22 (UTC+8)
    Publisher: Springer Berlin Heidelberg
    Abstract: A robust topology optimization methodology for solid continua having peak response serviceability to uncertain quasi-static loads with temporal correlation is developed in this paper. The proposed optimization methodology supplies analytical sensitivity assessment of peak responses of design continua associated with material distributions. In order for the topology optimization results to be validated, statistical investigations are performed to estimate probabilities of failure that fluctuating peak responses of such optimized designs exceed certain specified amounts. The computational results confirm that topological material distributions of optimized solids or structures with maximum peak response serviceability highly depend on temporal correlation degrees of uncertain stationary load sequences of long-term processes. Furthermore, conventional topology optimization of solid continua subjected to deterministic loads is also compared with the aforementioned optimized material distributions regarding uncertain loads. As a consequence, an effective computation framework for solving robust topology optimization problems under loading uncertainty can be established based on the proposed methodology. The robust topology optimization developed in this study thus provides a powerful tool for investigating efficient designs of solids and structures under uncertain loading conditions for fundamental mechanics, applied engineering, and multidisciplinary sciences research.
    Relation: Structural and Multidisciplinary Optimization 60(2), p.443–460
    DOI: 10.1007/s00158-019-02218-6
    Appears in Collections:[Graduate Institute & Department of Civil Engineering] Journal Article

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