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Handbook of Dynamic Data Driven Applications Systems pp 163–180Cite as

A Computational Steering Framework for Large-Scale Composite Structures: Part I—Parametric-Based Design and Analysis

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Abstract

Recent advances in simulation, optimization, structural health monitoring, and high-performance computing create a unique opportunity to combine the developments in these fields to formulate a Dynamic Data-Driven Applications Systems (DDDAS) Interactive Structure Composite Element Relation Network (DISCERN) framework. DISCERN consists of the following items and features: a structural health monitoring (SHM) system, an advanced structural modeling and fluid-structure interaction (FSI) simulation, sensitivity analysis, optimization and control modules. High-performance computing (HPC) is employed to enhance the efficiency and effectiveness of the system. The intended application of the DISCERN framework is the analysis of medium-to-large-scale composite structures. These include aerospace structures, such as military aircraft fuselage and wings, helicopter blades, and unmanned aerial vehicles, and civil structures, such as wind turbine blades and towers. The proposed DISCERN framework continuously and dynamically integrates the SHM data into the analysis of these structures. This capability allows one to: (1) Shelter the structures from excessive stress levels during operation; (2) Make informed decisions to perform structural maintenance and repair; and (3) Predict the remaining fatigue life of the structure. In Part I we present the computational framework for parametric-based design and analysis of these structures, and in Part II we discuss the optimization and control modules within the proposed DISCERN framework, including the integration of the FSI simulations.

Keywords

  • Adjoint-based control
  • Continuum damage model
  • Isogeometric analysis
  • Kirchhoff–Love shells
  • Progressive damage
  • Fatigue damage

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Acknowledgements

This work was supported by the AFOSR Grant FA9550-12-1-0005, AFOSR Grant FA9550-16-1-0131, ARO grant No. W911NF-14-1-0296. The authors greatly acknowledge this support.

Author information

Authors and Affiliations

  1. Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB, Canada

    A. Korobenko

  2. Department of Mechanical Engineering, Iowa State University, Ames, IA, USA

    M. -C. Hsu

  3. School of Engineering, Brown University, Providence, RI, USA

    Y. Bazilevs

Authors
  1. A. Korobenko
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  2. M. -C. Hsu
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  3. Y. Bazilevs
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Corresponding author

Correspondence to A. Korobenko .

Editor information

Editors and Affiliations

  1. Air Force Office of Scientific Research, Arlington, VA, USA

    Erik P. Blasch

  2. InfoSymbiotics Systems Society, Boston, MA, USA

    Dr. Frederica Darema

  3. Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Dr. Sai Ravela

  4. Air Force Research Lab, Rome, NY, USA

    Dr. Alex J. Aved

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Korobenko, A., Hsu, M.C., Bazilevs, Y. (2022). A Computational Steering Framework for Large-Scale Composite Structures: Part I—Parametric-Based Design and Analysis. In: Blasch, E.P., Darema, F., Ravela, S., Aved, A.J. (eds) Handbook of Dynamic Data Driven Applications Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-74568-4_8

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  • DOI: https://doi.org/10.1007/978-3-030-74568-4_8

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