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Items where Greenwich Author is "Soar, Dr Peter"

Items where Greenwich Author is "Soar, Dr Peter"

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Jump to: Engineering and Physical Sciences Research Council (Grant No. EP/W032147/1; EP/W031167/1) | Marie Skłodowska-Curie Individual Fellowship (MetaSpine, MSCA-IF-EF-ST, 832430/2018) | School of Engineering and the School of Computing and Mathematical Sciences within the Faculty of Engineering and Science at the University of Greenwich
Number of items: 3.

Engineering and Physical Sciences Research Council (Grant No. EP/W032147/1; EP/W031167/1)

Kao, A ORCID logoORCID: https://orcid.org/0000-0002-6430-2134, Tonry, C ORCID logoORCID: https://orcid.org/0000-0002-8214-0845, Soar, P ORCID logoORCID: https://orcid.org/0000-0003-1745-9443, Krastins, I, Fan, X, Lee, PD and Pericleous, K ORCID logoORCID: https://orcid.org/0000-0002-7426-9999 (2023) Modulating meltpool dynamics and microstructure using thermoelectric magnetohydrodynamics in additive manufacturing. In: IOP Conference Series: Materials Science and Engineering. IOP Conference Series: Materials Science and Engineering, 1281 . IOP Publishing Ltd, 012022. ISSN 1757-8981 (Print), 1757-899X (Online) (doi:10.1088/1757-899X/1281/1/012022)

Marie Skłodowska-Curie Individual Fellowship (MetaSpine, MSCA-IF-EF-ST, 832430/2018)

Soar, Peter ORCID logoORCID: https://orcid.org/0000-0003-1745-9443, Dall’Ara, Enrico, Palanca, Marco and Tozzi, Gianluca (2024) Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics. Extreme Mechanics Letters, 71:102202. pp. 1-14. ISSN 2352-4316 (Online) (doi:10.1016/j.eml.2024.102202)

School of Engineering and the School of Computing and Mathematical Sciences within the Faculty of Engineering and Science at the University of Greenwich

Soar, Peter ORCID logoORCID: https://orcid.org/0000-0003-1745-9443, Dall’Ara, Enrico, Palanca, Marco and Tozzi, Gianluca (2024) Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics. Extreme Mechanics Letters, 71:102202. pp. 1-14. ISSN 2352-4316 (Online) (doi:10.1016/j.eml.2024.102202)

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