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Shock and Vibration
Volume 19 (2012), Issue 5, Pages 765-785
http://dx.doi.org/10.3233/SAV-2012-0686

Prediction of Full Field Dynamic Strain from Limited Sets of Measured Data

Peter Avitabile and Pawan Pingle

Structural Dynamics and Acoustic Systems Laboratory, University of Massachusetts Lowell, MA, USA

Received 25 April 2012; Accepted 25 April 2012

Copyright © 2012 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Dynamic response is an important consideration for design of structures due to operating or occasional loadings. The resulting dynamic stress strain is also of concern for fatigue and structural health monitoring. Typically, the actual loading and structural condition (boundary conditions, environmental condition, geometry, mechanical properties, etc.) are not necessarily known. Much effort is expended in attempting to identify the loads and appropriate model for prediction of these types of events. At best, the forces and actual boundary conditions are approximate and have an effect on the overall predicted response and resulting stress-strain that is identified for subsequent evaluation.

Experimental data can only be obtained from limited sets of points, such as those typically collected with accelerometers. These are normally used in the evaluation the state of a structure in service condition. More recently, Digital Image Correlation (DIC) and Dynamic Photogrammetry (DP) have become very important techniques to measure the surface response. These are non-contact and full-field techniques, which allow that much more simultaneous data to be measure. The sets of limited surface data that are collected can be used in conjunction with an expansion algorithm to obtain full field information. The finite element model mass and stiffness matrices are used to obtain the normal constitutive relations as well as the modal characteristics. This information is used to develop the expansion algorithm and for the stress recovery during the back substitution process typically employed.