Imperial College London
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ProfessorDavidHam

Faculty of Natural Sciences, Department of Mathematics

Professor of Computational Mathematics
 
 
 
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Contact

 

+44 (0)20 7594 5003david.ham Website CV

 
 
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Location

 

753Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Wallwork:2020:10.1007/s42452-020-2745-9,
author = {Wallwork, JG and Barral, N and Kramer, SC and Ham, DA and Piggott, MD},
doi = {10.1007/s42452-020-2745-9},
journal = {SN Applied Sciences},
pages = {1--11},
title = {Goal-oriented error estimation and mesh adaptation for shallow water modelling},
url = {http://dx.doi.org/10.1007/s42452-020-2745-9},
volume = {2},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This study presents a novel goal-oriented error estimate for the nonlinear shallow water equations solved using a mixed discontinuous/continuous Galerkin approach. This error estimator takes account of the discontinuities in the discrete solution and is used to drive two metric-based mesh adaptation algorithms: one which yields isotropic meshes and another which yields anisotropic meshes. An implementation of these goal-oriented mesh adaptation algorithms is described, including a method for approximating the adjoint error term which arises in the error estimate. Results are presented for simulations of two model tidal farm configurations computed using the Thetis coastal ocean model (Kärnä et al. in Geosci Model Dev 11(11):4359–4382, 2018). Convergence analysis indicates that meshes resulting from the goal-oriented adaptation strategies permit accurate QoI estimation using fewer computational resources than uniform refinement.
AU  - Wallwork,JG
AU  - Barral,N
AU  - Kramer,SC
AU  - Ham,DA
AU  - Piggott,MD
DO  - 10.1007/s42452-020-2745-9
EP  - 11
PY  - 2020///
SN  - 2523-3971
SP  - 1
TI  - Goal-oriented error estimation and mesh adaptation for shallow water modelling
T2  - SN Applied Sciences
UR  - http://dx.doi.org/10.1007/s42452-020-2745-9
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000538087000057&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://link.springer.com/article/10.1007%2Fs42452-020-2745-9
UR  - http://hdl.handle.net/10044/1/86816
VL  - 2
ER  -
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