R
R. A. McD. Galbraith
Researcher at University of Glasgow
Publications - 44
Citations - 782
R. A. McD. Galbraith is an academic researcher from University of Glasgow. The author has contributed to research in topics: Vortex & Airfoil. The author has an hindex of 16, co-authored 44 publications receiving 740 citations.
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A New Stall-Onset Criterion for Low Speed Dynamic-Stall
TL;DR: In this paper, a new stall criterion is proposed and developed in the best traditions of the Beddoes/Leishman dynamic-stall model, which is shown to be very capable of reconstructing the Glasgow's data for stall onset both the ramp-up and oscillatory tests.
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Examination of vortex deformation during blade-vortex interaction
TL;DR: The results of a blade-vortex interaction (BVI) study incorporating particle image velocimetry (PIV) are presented in this article, where the deformation and division of the interaction vortex during head-on interactions are documented.
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An experimental study of dynamic stall on a finite wing
TL;DR: In this article, the authors examined the dynamic stalling of a finite wing of aspect ratio 3·0 when subject to constant pitch motions up to and beyond stall and found that the wing loading distribution was consistent with conventional understanding of steady wing loading up to the incidence at which the dynamic stall vortex was initiated.
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Computational Fluid Dynamics Study of Three-Dimensional Dynamic Stall of Various Planform Shapes
Agis Spentzos,George N. Barakos,Ken Badcock,Bryan E. Richards,Frank N. Coton,R. A. McD. Galbraith,Eric Berton,Daniel Favier +7 more
TL;DR: The calculations revealed the detailed structure of the 3-D dynamic stall vortex and its interaction with the tip vortex, and strong similarities in the flow topology were identified for wings of very different planforms.
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Modelling dynamic stall vortex inception at low Mach numbers
A. J. Niven,R. A. McD. Galbraith +1 more
TL;DR: In this paper, a comparison of dynamic stall onset from low Mach number windtunnel data contained in the University of Glasgow's database and that from the well established Beddoes' model is presented.