Data-driven reduced order modeling of flows around two-dimensional bluff bodies of various shapes

Kazuto Hasegawa, Kai Fukami, Takaaki Murata, Koji Fukagata

研究成果: Conference contribution

抜粋

We propose a reduced order model for predicting unsteady flows using a data-driven method. As preliminary tests, we use two-dimensional unsteady flow around bluff bodies with different shapes as the training datasets obtained by direct numerical simulation (DNS). Our machine-learned architecture consists of two parts: Convolutional Neural Network-based AutoEncoder (CNN-AE) and Long Short Term Memory (LSTM), respectively. First, CNN-AE is used to map into a low-dimensional space from the flow field data. Then, LSTM is employed to predict the temporal evolution of the low-dimensional data generated by CNN-AE. Proposed machine-learned reduced order model is applied to two-dimensional circular cylinder flows at various Reynolds numbers and flows around bluff bodies of various shapes. The flow fields reconstructed by the machine-learned architecture show reasonable agreement with the reference DNS data. Furthermore, it can be seen that our machine-learned reduced order model can successfully map the high-dimensional flow data into low-dimensional field and predict the flow fields against unknown Reynolds number fields and shapes of bluff body. As concluding remarks, we discuss the extension study of machine-learned reduced order modeling for various applications in experimental and computational fluid dynamics.

元の言語English
ホスト出版物のタイトルComputational Fluid Dynamics
出版者American Society of Mechanical Engineers (ASME)
ISBN(電子版)9780791859032
DOI
出版物ステータスPublished - 2019 1 1
イベントASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019 - San Francisco, United States
継続期間: 2019 7 282019 8 1

出版物シリーズ

名前ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019
2

Conference

ConferenceASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019
United States
San Francisco
期間19/7/2819/8/1

ASJC Scopus subject areas

  • Fluid Flow and Transfer Processes

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  • これを引用

    Hasegawa, K., Fukami, K., Murata, T., & Fukagata, K. (2019). Data-driven reduced order modeling of flows around two-dimensional bluff bodies of various shapes. : Computational Fluid Dynamics (ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference, AJKFluids 2019; 巻数 2). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/AJKFluids2019-5079