Multiple shooting shadowing for sensitivity analysis of chaotic dynamical systems
Name
Wang_Multiple shooting.pdf
Description
Submitted version
Size
1.05 MB
Format
Adobe PDF
Checksum (MD5)
3f800aa2d01f610df11b9937dea20439
Author(s)
Blonigan, Patrick J
Wang, Qiqi
Date Issued
2018
Journal
Journal of Computational Physics
Publisher
Elsevier BV
Version
Original manuscript
Abstract
© 2017 Elsevier Inc. Sensitivity analysis methods are important tools for research and design with simulations. Many important simulations exhibit chaotic dynamics, including scale-resolving turbulent fluid flow simulations. Unfortunately, conventional sensitivity analysis methods are unable to compute useful gradient information for long-time-averaged quantities in chaotic dynamical systems. Sensitivity analysis with least squares shadowing (LSS) can compute useful gradient information for a number of chaotic systems, including simulations of chaotic vortex shedding and homogeneous isotropic turbulence. However, this gradient information comes at a very high computational cost. This paper presents multiple shooting shadowing (MSS), a more computationally efficient shadowing approach than the original LSS approach. Through an analysis of the convergence rate of MSS, it is shown that MSS can have lower memory usage and run time than LSS.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.JCP.2017.10.032
