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Data assimilation in 2D nonlinear coupled sound and heat flow, using a stabilized explicit finite difference scheme marched backward in time

Published

Author(s)

Alfred Carasso

Abstract

This paper considers the ill-posed data assimilation problem associated with hyper- bolic/parabolic systems describing 2D coupled sound and heat flow. Given hypothetical data at time T > 0, that may not correspond to an actual solution of the dissipative system at time T , initial data at time t = 0 are sought that can evolve, through the dissipative system, into a useful approximation to the desired data at time T . That may not always be possible. A stabilized explicit finite difference scheme, marching backward in time, is developed and applied to nonlinear examples in non rectan- gular regions. Stabilization is achieved by applying a compensating smoothing operator at each time step, to quench the instability. Analysis of convergence is restricted to the transparent case of linear, autonomous, selfadjoint spatial differential operators. However, the actual computational scheme can be applied to more general problems. Data assimilation is illustrated using 512 × 512 pixel images. Such images are associated with highly irregular non smooth intensity data that severely challenge ill-posed reconstruction procedures. Successful and unsuccessful examples are presented.
Citation
Technical Note (NIST TN) - 2322
Report Number
2322

Keywords

Coupled sound and heat flow backward in time, stabilized explicit marching schemes, error bounds, numerical experiments.

Citation

Carasso, A. (2024), Data assimilation in 2D nonlinear coupled sound and heat flow, using a stabilized explicit finite difference scheme marched backward in time, Technical Note (NIST TN), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.TN.2322, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959020 (Accessed December 25, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created December 13, 2024