Microstructures significantly impact the performance of sensitively engineered components, such as wireless impact detectors used in military vehicles or sensors used in aircrafts. These components can operate safely only within a certain range of frequencies, and frequencies outside that range can lead to instability because of resonance. This paper addresses optimization of the microstructure design to maximize the yield stress of a galfenol beam under vibration tuning constraints defined for the first torsional and bending natural frequencies by using a data-driven solution scheme. In this study, two carefully designed algorithms are used to sample the entire microstructure space. Classical optimization techniques often lead to a unique microstructural solution rather than yielding the complete space of optimal microstructures. Multiple optimal solutions are imperative for the practicality of design because conventional low-cost manufacturing processes can generate only a limited set of microstructures. The current data sampling-based methodology outperforms or is on par with other optimization techniques but also provides numerous near-optimal solutions, which is two to three orders of magnitude more than previous methods. Consequently, the proposed framework delivers a spectrum of optimal solutions in the microstructure space that can accelerate material development and reduce manufacturing costs.


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    Titel :

    Data Sampling Schemes for Microstructure Design with Vibrational Tuning Constraints


    Beteiligte:
    Paul, Arindam (Autor:in) / Acar, Pinar (Autor:in) / Liu, Ruoqian (Autor:in) / Liao, Wei-Keng (Autor:in) / Choudhary, Alok (Autor:in) / Sundararaghavan, Veera (Autor:in) / Agrawal, Ankit (Autor:in)

    Erschienen in:

    AIAA Journal ; 56 , 3 ; 1239-1250


    Erscheinungsdatum :

    2018-02-15


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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