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The University of Southampton
Engineering

Accurate and precise digital image correlation: impact on material identification Seminar

Time:
16:00 - 17:00
Date:
5 February 2014
Venue:
Seminar room 3011, Building 19. Tea, coffee and refreshments will be available

For more information regarding this seminar, please telephone Dr Yeping Xiong on +44 (0)23 8059 6619 or email Y.Xiong@soton.ac.uk .

Event details

An FSI group seminar

Abstract:

Digital image correlation (DIC) is an optical-numerical measurement technique that not only allows to reconstruct the shape of objects, but more importantly determines the displacement and stain fields at the surface of this object under any kind of loading. Thanks to its full-field character it is a technique often applied to identify  mechanical material parameters for a widespread range of different materials. Indeed, in contrast to standard testing with stringent conditions on the preparation of the specimens one now can get access to these parameters in a single test setup.

In this presentation the basic fundamentals underlying the technique will be reviewed with specific focus of some error sources that might harm both the accuracy and precision of the technique. Moreover, the impact of these error sources on the final determined material parameters will be studied via a numerical simulator that includes DIC and the Virtual Fields Method (VFM) for material identification.

Speaker information

Dr Pascal Lava , Department of Mechanical Engineering and Applied Material Sciences, Leuven University. Pascal Lava acquired a Master degree in mathematics at Ghent University in June 2002. On May 16th 2006, he acquired a PhD in sciences – nuclear physics at Ghent University. Since January 1st 2008, he works as an associate professor at the department Metallurgy and Materials engineering (MTM) at Leuven University. Research topics of Lava Pascal include: Digital Image Correlation (DIC) and material identification via virtual fields and finite element updating. Pascal Lava is author of more than 25 peer-reviewed articles and the founder and main developer of the DIC platform MatchID.

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