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Cheng Endowment"],"award-info":[{"award-number":["Richard T. Cheng Endowment"]}],"id":[{"id":"10.13039\/100023092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100023092","name":"Old Dominion University - College of Sciences","doi-asserted-by":"publisher","award":["Richard T. Cheng Endowment"],"award-info":[{"award-number":["Richard T. Cheng Endowment"]}],"id":[{"id":"10.13039\/100023092","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Engineering with Computers"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Efficient and robust anisotropic mesh adaptation is crucial for Computational Fluid Dynamics (CFD) simulations. The CFD Vision 2030 Study highlights the pressing need for this technology, particularly for simulations targeting supercomputers. This work applies a fine-grained speculative approach to anisotropic mesh operations. Our implementation exhibits more than 90% parallel efficiency on a multi-core node. Additionally, we evaluate our method within an adaptive pipeline for a spectrum of publicly available test-cases that includes both analytically derived and error-based fields. For all test-cases, our results are in accordance with published results in the literature. Support for CAD-based data is introduced, and its effectiveness is demonstrated on one of NASA\u2019s High-Lift prediction workshop cases.<\/jats:p>","DOI":"10.1007\/s00366-024-01994-0","type":"journal-article","created":{"date-parts":[[2024,5,25]],"date-time":"2024-05-25T14:02:06Z","timestamp":1716645726000},"page":"3801-3827","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Speculative anisotropic mesh adaptation on shared memory for CFD applications"],"prefix":"10.1007","volume":"40","author":[{"given":"Christos","family":"Tsolakis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikos","family":"Chrisochoides","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,25]]},"reference":[{"key":"1994_CR1","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1016\/j.jcp.2012.12.035","volume":"242","author":"MA Goffin","year":"2013","unstructured":"Goffin MA, Baker CMJ, Buchan AG, Pain CC, Eaton MD, Smith PN (2013) Minimising the error in eigenvalue calculations involving the Boltzmann transport equation using goal-based adaptivity on unstructured meshes. 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