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World class computing and information science research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

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Number of items: 5.

Morar, Nicolau and Roy, Rajkumar and Mehnen, Jorn and Nicholls, J.R. and Gray, Simon (2017) The effect of trepanning speed of laser drilled acute angled cooling holes on the high temperature low cycle corrosion fatigue performance of CMSX-4 at 850 °C. International Journal of Fatigue. 112–120. ISSN 0142-1123

Marsh, Gabriel and Wignall, Colin and Thies, Philipp R. and Barltrop, Nigel and Incecik, Atilla and Venugopal, Vengatesan and Johanning, Lars (2016) Review and application of Rainflow residue processing techniques for accurate fatigue damage estimation. International Journal of Fatigue, 82. pp. 757-765. ISSN 0142-1123

Polezhayeva, Helena and Toumpis, Athanasios and Galloway, Alexander and Molter, Lars and Ahmad, Bilal and Fitzpatrick, Michael E. (2015) Fatigue performance of friction stir welded marine grade steel. International Journal of Fatigue, 81. pp. 162-170. ISSN 0142-1123

Gorash, Yevgen and Chen, Haofeng (2013) A parametric study on creep-fatigue strength of welded joints using the linear matching method. International Journal of Fatigue, 55. pp. 112-125. ISSN 0142-1123

Bezazi, A. and Pierce, S.G. and Worden, K. and Harkati, E. (2007) Fatigue life prediction of sandwich composite materials under flexural tests using a Bayesian trained artificial neural network. International Journal of Fatigue, 29 (4). pp. 738-747. ISSN 0142-1123

This list was generated on Wed Sep 20 01:29:41 2017 BST.