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Residual stress and quantitative phase mapping on complex geometries

Published online by Cambridge University Press:  07 May 2014

Masoud Allahkarami
Affiliation:
School of Mechanical and Aerospace Engineering, Oklahoma State University, Tulsa, Oklahoma 74106
Jay C. Hanan*
Affiliation:
School of Mechanical and Aerospace Engineering, Oklahoma State University, Tulsa, Oklahoma 74106
*
a)Author to whom correspondence should be addressed. Electronic mail: [email protected]

Abstract

As a consequence of substantial advances in computer-aided design and manufacturing technology, engineering parts are no longer restricted to combination of simple geometrical shapes. Implementing complex curved surfaces in engineering components in combination with finite-element geometry optimization has become a prevalent means of designing a part. Measuring residual stresses using X-ray diffraction (XRD) on complex curved surfaces requires further development of current measurement methods. Here we investigate how a laboratory XRD system equipped with a five-axis stage and two-dimensional detector can execute sin2ψ residual stress measurements on curved surfaces. Shadowing that blocks the diffracted beam to reach the detector was avoided using proper rotations and tilting of the sample. A standard video-laser alignment system commonly used to manually place the sample in the center of diffraction was used to also generate virtual maps of the sample's curved surfaces on a fine mesh grid. The geometry was then used for setting the required rotations and tilt angles. A set of diffraction frames collected using this method on a model zirconia dental ceramic, afforded the opportunity to superimpose phase and stresses on a complex geometry. This is a step forward for the XRD technology, and its usefulness applies to many different industries.

Type
Technical Articles
Copyright
Copyright © International Centre for Diffraction Data 2014 

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References

Allahkarami, M. and Hanan, J. C. (2011a). “Mapping the tetragonal to monoclinic phase transformation in zirconia core dental crowns,” Dent. Mater. 27(12), 12791284.CrossRefGoogle ScholarPubMed
Allahkarami, M. and Hanan, J. C. (2011b). “X-ray diffraction mapping on a curved surface,” J. Appl. Crystallogr. 44(6), 12111216.CrossRefGoogle Scholar
Allahkarami, M. and Hanan, J. C. (2012a). “Residual stress and phase transformation in Zirconia restoration ceramics,” in Advances in Bioceramics and Porous Ceramics V: Ceramic Engineering and Science Proceedings, edited by Narayan, R. and Colombo, P., (Wiley–American Ceramic Society), pp. 3747.Google Scholar
Allahkarami, M. and Hanan, J. C. (2012b). “Residual stress delaying phase transformation in Y-TZP bio-restorations,” Phase Transit. 85(1–2), 169178.Google Scholar
Arora, J. (2004). Introduction to Optimum Design (Academic Press), 2nd ed.Google Scholar
Bale, H. A., Tamura, N., and Hanan, J. C. (2010). “Cyclic impact fatigue and macroscopic failure considering grain-to-grain residual stress in ceramic dental restorations”. SEM 2010 Annual Conference & Exposition on Experimental and Applied Mechanics.Google Scholar
BrukerAXS Inc. (2005). M86-EXX007 GADDS User Manual, Chapter 12, Madison, Wisconsin, USA.Google Scholar
Chatillon, S., Cattiaux, G., Serre, M., and Roy, O. (2000). “Ultrasonic non-destructive testing of pieces of complex geometry with a flexible phased array transducer,” Ultrasonics 38, 131134.Google Scholar
Coelho, A. A. (2007). TOPAS-Academic, version 4.1 (Computer Software), Coelho Software, Brisbane.Google Scholar
Dickinson, M. H. (1999). “Bionics: biological insight into mechanical design,” Proc. Natl. Acad. Sci. USA 96(25), 1420814209.Google Scholar
Forest, J. and Salvi, J. (2002). A review of laser scanning three-dimensional digitizers. Proceedings of the 2002 IEE/RSJ Intl. Conference on Intelligent Robots and Systems EPFL, Lausanne, Switzerland.Google Scholar
Hagan, M., Demuth, H., and Beale, M. (2002). Neural Network Design.Google Scholar
He, B. (2011). Two-Dimensional X-ray Diffraction (John Wiley & Sons, Hoboken, New Jersey).Google Scholar
He, B., Jin, F., Preckwinkel, U., and Smith, K. (2004). “Retractable knife-edge for XRD combinatorial screening,” Int. Centr. Diffr. Data Adv. X-ray Anal. 47, 194199.Google Scholar
Janushevskis, A., Auzins, J., Melnikovs, A., and Ancane, A. G. (2012). “Shape Optimization of Mechanical Components for Measurement Systems,” Advanced Topics in Measurements, Prof. Zahurul Haq (Ed.), chapter 12, 243–264.Google Scholar
Krawitz, A. D. (2001). Introduction to Diffraction in Materials, Science and Engineering (Wiley-Interscience).Google Scholar
Magne, P. (2007). “Efficient 3D finite element analysis of dental restorative procedures using micro-CT data,” Dent. Mater. 23(5), 539548.Google Scholar
Verdonschot, N., Fennis, W. M. M., Kuijs, R. H., Stolk, J., Kreulen, C. M., and Creugers, N. H. J. (2001). “Generation of 3-D finite element models of restored human teeth using micro-CT techniques,” Int. J. Prosthodont. 14(4), 310315.Google Scholar
Wirza, R., Bloor, M. S., and Fisher, J. (2002). “Inspection strategies for complex curved surfaces using CMM,” in Computational Science_ICCS 2002 LNCS 2331, edited by Sloot Peter, M. A., Hoekstra, A. G., Kenneth Tan, C. J., Dongarra, J. J. (Springer-Verlag, Berlin, Heidelberg), pp. 184193.Google Scholar