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Zonal Reduced-Order Modeling of Unsteady Flow Field

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Book cover Computational and Experimental Simulations in Engineering (ICCES 2019)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 75))

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Abstract

The utilization of real-world data in cyberspace is becoming attractive in various fields due to the massive growth of sensing and networking technologies. It is expected to utilize such a data-rich environment to improve engineering simulations in computer-aided engineering (CAE). Data assimilation is one of methodologies to statistically integrate a numerical model and measurement data, and it is expected to be a key technology to take advantage of measured data in CAE. However, the additional cost of data assimilation is not always affordable in CAE simulations. In this study, we consider the cost reduction of numerical flow simulation with the help of a reduced-order model, which encodes a flow field into a low-dimensional representation. Since the prediction accuracy of existing ROMs are limited in complex flow fields, we investigate here a zonal hybrid approach of a full-order model and a reduced-order model.

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Acknowledgements

This work was partially supported by a Grant-in-Aid for Scientific Research on Innovative Areas (No. 16H015290) from the Ministry of Education, Culture, Sports, Science and Technology of Japan.

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Authors and Affiliations

  1. National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, 305-8564, Japan

    Takashi Misaka

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  1. Takashi Misaka
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Correspondence to Takashi Misaka .

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Editors and Affiliations

  1. Department of Mechanical Engineering, Tokyo University of Science, Noda, Chiba, Japan

    Hiroshi Okada

  2. Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, USA

    Satya N. Atluri

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Misaka, T. (2020). Zonal Reduced-Order Modeling of Unsteady Flow Field. In: Okada, H., Atluri, S. (eds) Computational and Experimental Simulations in Engineering. ICCES 2019. Mechanisms and Machine Science, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-030-27053-7_41

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  • DOI: https://doi.org/10.1007/978-3-030-27053-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27052-0

  • Online ISBN: 978-3-030-27053-7

  • eBook Packages: EngineeringEngineering (R0)

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