Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Freddie D. Witherden"'
Publikováno v:
AIAA Journal. 60:1032-1051
An extended version of the synthetic eddy method for generation of synthetic turbulence has been developed via a source term formulation and implemented in the open-source cross-platform solver PyFR. The method caters for the full space-dependent ani
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::102aaa667c44d4e4f3541d4a2653ca7d
https://doi.org/10.2514/1.j061046
https://doi.org/10.2514/1.j061046
Publikováno v:
New Journal of Physics, Vol 22, Iss 9, p 093023 (2020)
A recent thrust in turbulence closure modeling research is to incorporate machine learning (ML) elements, such as neural networks, for the purpose of enhancing the predictive capability to cover a broader class of flows. For generalizability to unsee
Externí odkaz:
https://doaj.org/article/df2d7e34c9bd4abbbb27b46c6e0f349c
Autor:
Freddie D. Witherden
Publikováno v:
Computing in Science & Engineering. 23:29-37
In this work, we make the case for Python as a first-class language for high-performance computing (HPC) applications. Our rationale is based on three trends: an increasing desire for applications to be user friendly; the shift toward such applicatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::93b3d632eb4afb0b62613ba589e01a7b
https://doi.org/10.1109/mcse.2021.3080126
https://doi.org/10.1109/mcse.2021.3080126
Publikováno v:
AIAA Journal. 59:825-841
The computational cost associated with simulating fluid flows can make it infeasible to run many simulations across multiple flow conditions. Building upon concepts from generative modeling, we introduce a new method for learning neural network model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b563a28e5324c3115174779cc81bc062
https://doi.org/10.2514/1.j059315
https://doi.org/10.2514/1.j059315
Autor:
Freddie D. Witherden, Antony Jameson
Publikováno v:
AIAA Journal. 58:184-197
High-order numerical methods for unstructured grids combine the superior accuracy of high-order spectral or finite difference methods with the geometric flexibility of low-order finite volume or fi...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c4ecb6d64bd00590ef3a58ae0eae40e
https://doi.org/10.2514/1.j058434
https://doi.org/10.2514/1.j058434
Novel methods are presented in this initial study for the fusion of GPU kernels in the artificial compressibility method (ACM), using tensor product elements with constant Jacobians and flux reconstruction. This is made possible through the hyperboli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72d9dcc669c08c98bc2be644caa1d476
http://arxiv.org/abs/2107.14027
http://arxiv.org/abs/2107.14027
Publikováno v:
Journal of Fluid Mechanics. 875:758-780
Eigenmodes of averaged small-amplitude perturbations to a turbulent channel flow – which is one of the most fundamental canonical flows – are identified for the first time via an extensive set of high-fidelity graphics processing unit accelerated
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35866411d1511b8ebca0d71afea5dad1
https://doi.org/10.1017/jfm.2019.520
https://doi.org/10.1017/jfm.2019.520
Publikováno v:
Journal of Computational Physics. 374:692-723
Overset methods are commonly employed to enable the effective simulation of problems involving complex geometries and moving objects such as rotorcraft. This paper presents a novel overset domain connectivity algorithm based upon the direct cut appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7abbfb9f171ce4967d1f58f63bb26d4e
https://doi.org/10.1016/j.jcp.2018.05.036
https://doi.org/10.1016/j.jcp.2018.05.036
Publikováno v:
Computer Physics Communications. 233:193-205
Modern hardware architectures such as GPUs and manycore processors are characterised by an abundance of compute capability relative to memory bandwidth. This makes them well-suited to solving temporally explicit and spatially compact discretisations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbe02cfb3286d477b2de51734807a533
https://doi.org/10.1016/j.cpc.2018.06.016
https://doi.org/10.1016/j.cpc.2018.06.016