dc.contributor.author | Turner, M | |
dc.contributor.author | Peiró, J | |
dc.contributor.author | Moxey, D | |
dc.date.accessioned | 2017-12-15T09:22:43Z | |
dc.date.issued | 2016-11-23 | |
dc.description.abstract | The generation of sufficiently high quality unstructured high-order meshes remains a significant obstacle in the adoption of high-order methods. However, there is little consensus on which approach is the most robust, fastest and produces the ‘best’ meshes. We aim to provide a route to investigate this question, by examining popular high-order mesh generation methods in the context of an efficient variational framework for the generation of curvilinear meshes. By considering previous works in a variational form, we are able to compare their characteristics and study their robustness. Alongside a description of the theory and practical implementation details, including an efficient multi-threading parallelisation strategy, we demonstrate the effectiveness of the framework, showing how it can be used for both mesh quality optimisation and untangling of invalid meshes. | en_GB |
dc.identifier.citation | Vol. 163, pp. 340 - 352 | en_GB |
dc.identifier.doi | 10.1016/j.proeng.2016.11.069 | |
dc.identifier.uri | http://hdl.handle.net/10871/30683 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.rights | © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license | en_GB |
dc.subject | high-order mesh generation | en_GB |
dc.subject | variational mesh generation | en_GB |
dc.subject | energy functional | en_GB |
dc.subject | numerical optimization | en_GB |
dc.title | A Variational Framework for High-order Mesh Generation | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2017-12-15T09:22:43Z | |
dc.identifier.issn | 1877-7058 | |
exeter.article-number | C | en_GB |
dc.description | This is the final version of the article. Available from Elsevier via the DOI in this record. | en_GB |
dc.identifier.journal | Procedia Engineering | en_GB |