Imperial College London
Alternate

ProfessorMatthewPiggott

Faculty of Engineering, Department of Earth Science & Engineering

Professor of Computational Geoscience and Engineering
 
 
 
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Contact

 

m.d.piggott Website

 
 
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Location

 

4.82Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Funke:2017:10.1016/j.cma.2017.04.019,
author = {Funke, SW and Farrell, PE and Piggott, MD},
doi = {10.1016/j.cma.2017.04.019},
journal = {COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING},
pages = {167--186},
title = {Reconstructing wave profiles from inundation data},
url = {http://dx.doi.org/10.1016/j.cma.2017.04.019},
volume = {322},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper applies variational data assimilation to inundation problems governed by the shallow water equations with wetting and drying. The objective of the assimilation is to recover an unknown time-varying wave profile at an open ocean boundary from inundation observations. This problem is solved with derivative-based optimisation and an adjoint wetting and drying scheme to efficiently compute sensitivity information. The capabilities of this approach are demonstrated on an idealised sloping beach setup in which the profile of an incoming wave is reconstructed from wet/dry interface observations. The method is robust to noise in the observations if a regularisation term is added to the optimisation objective. Finally, the method is applied to a laboratory experiment of the Hokkaido-Nansei-Oki tsunami, where the wave profile is reconstructed with a relative L∞ error of less than 1%.
AU  - Funke,SW
AU  - Farrell,PE
AU  - Piggott,MD
DO  - 10.1016/j.cma.2017.04.019
EP  - 186
PY  - 2017///
SN  - 0045-7825
SP  - 167
TI  - Reconstructing wave profiles from inundation data
T2  - COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
UR  - http://dx.doi.org/10.1016/j.cma.2017.04.019
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000404823300009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/51993
VL  - 322
ER  -
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