Confidence Assessment in Fatigue Damage Prognosis

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Shankar Sankararaman You Ling Sankaran Mahadevan

Abstract

This paper presents a methodology for assessing the confidence and the predictive capability of prognosis models, using the application of fatigue crack growth analysis. Structures with complicated geometry and multi-axial variable amplitude loading conditions are considered. Several models –finite element model, crack growth model, retardation model, surrogate model, etc. – are efficiently connected through a Bayes network and the parameters of these models are calibrated after collecting inspection data. The results of the calibration are then used to develop a Bayesian confidence metric to assess the confidence of the models used in fatigue crack growth analysis. Three types of uncertainty are included in analysis: (1) natural variability in loading and material properties; (2) data uncertainty, due to crack detection uncertainty, measurement errors, and sparse data; (3) modeling uncertainty and errors in crack growth analysis, and finite element analysis. The proposed methodology is illustrated using a numerical example of surface cracking in a cylindrical structure.

How to Cite

Sankararaman, S., Ling, Y., & Mahadevan, S. . (2010). Confidence Assessment in Fatigue Damage Prognosis. Annual Conference of the PHM Society, 2(1). https://doi.org/10.36001/phmconf.2010.v2i1.1894
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Keywords

fatigue crack growth, Uncertainty Quantification, confidence assessment, Bayes factor, Bayes network

References
(Paris et al., 1961) P.C.Paris, M.P.Gomez, and W.E. Anderson. A rational analytic theory of fatigue. The Trend in Engineering (1961). 13, 9-14.

(Liu and Mahadevan, 2008) Y. Liu and S. Mahadevan. Probabilistic fatigue life prediction using an equivalent initial flaw size distribution. 2008. Int J Fatigue, doi:10.1016/j.ijfatigue.2008.06.005.

(Urbina, 2009) A. Urbina. Uncertainty Quantification and Decision Making in Hierarchical Development of Computational Models. 2009. Doctoral Thesis Dissertation. Vanderbilt University, Nashville, TN.

(Sankararaman et al., 2009) S. Sankararaman, Y. Ling, C. Shantz, and S. Mahadevan. 2009. Uncertainty Quantification in Fatigue Damage Prognosis. In the Proceedings of the 1st Annual Conference of the Prognostics and Health Management Society, San Diego, CA. Sept 27 – Oct 1, 2009.

(Saxena et al., 2009) A. Saxena, J. Celaya, B. Saha, S. Saha, and K. Goebel, "Evaluating Algorithmi Performance Metrics Tailored for Prognostics", In the Proceedings of IEEE Aerospace Conference, Big Sky, MO, 2009.

(Rebba and Mahadevan, 2006) R. Rebba and S. Mahadevan. Model Predictive Capability Assessment Under Uncertainty. 2006. AIAA Journal. Vol 44, No. 10. Oct. 2006.

(Makeev et al., 2006) A. Makeev, Y. Nikishkov, E. Armanios. A concept for quantifying equivalent initial flaw size distribution in fracture mechanics based life prediction models, Int J Fatigue (2006),Vol. 29, No. 1, Jan. 2007.

(Cross et al., 2007) R. Cross, A. Makeev, E. Armanios.
Simultaneous uncertainty quantification of fracture mechanics based life prediction model parameters, Int J Fatigue, Vol. 29, No. 8, Aug. 2007.

(Doebling and Hemez, 2001) S.W. Doebling and F.M. Hemez. Overview of Uncertainty Assessment for Structural Health Monitoring. In the Proceedings of the 3rd International Workshop on Structural Health Monitoring, September 17-19, 2001, Stanford University, Stanford, California.

(Hemez et al., 2003) F.M. Hemez, A.N. Roberson, and A.C. Rutherford. Uncertainty Quantification and Model Validation for Damage Prognosis. In the Proceedings of the 4th International Workshop on Structural Health Monitoring, Stanford University, Stanford, California, September 15-17, 2003.

(Farrar et al., 2004) C.R. Farrar, G. Park. F.M. Hemez, T.B. Tippetts, H. Sohn, J. Wait, D.W. Allen, and B.R. Nadler. Damage Detection and Prediction for Composite Plates. J. of The Minerals, Metals and Materials Society, November 2004.

(Farrar and Lieven, 2006). C.R. Farrar and N.A.J. Lieven. Damage Prognosis: The Future of Structural Health Monitoring. Phil. Trans. R. Soc. A (2007) 365, 623–632 doi:10.1098/rsta.2006.1927. Published online 12 December 2006.

(Besterfield et al., 1991) G.H. Besterfield, W.K. Liu, A.M. Lawrence, and T. Belytschko. Fatigue crack growth reliability by probabilistic finite elements, Computer Methods in Applied Mechanics and Engineering, Volume 86, Issue 3. 1991.

(Patrick et al., 2007) R. Patrick, M.E. Orchard, B. Zhang, M.D. Koelemay, G.J. Kacprzynski, A.A. Ferri, and G.J. Vachtsevanos. An integrated approach to helicopter planetary gear fault diagnosis and failure prognosis. Autotestcon, 2007 IEEE , vol., no., pp.547-552, 17-20 Sept. 2007.

(Gupta and Ray, 2007) S. Gupta, and A. Ray. Real-time fatigue life estimation in mechanical structures. Meas. Sci. Technol. 18 (2007) 1947–1957. doi:10.1088/0957-0233/18/7/022.

(Pierce et al., 2008) S.G. Pierce, K. Worden, and A. Bezazi. Uncertainty analysis of a neural network used for fatigue lifetime prediction. Mechanical Systems and Signal Processing, Volume 22, Issue 6, Special Issue: Mechatronics, August 2008, Pages 1395-1411, ISSN 0888-3270, DOI: 10.1016/j.ymssp.2007.12.004.

(Orchard et al., 2008) M. Orchard, G. Kacprzynski, K. Goebel, B. Saha, and G. Vachtsevanos. Advances in Uncertainty Representation and Management for Particle Filtering Applied to Prognostics. In the Proceedings of the 1st Prognostics and Health Management (PHM) Conference, Denver, CO. Oct 6-9, 2008.

(Papazian et al., 2009) J.M. Papazian, E.L. Anagnostou, S.J. Engel, D. Hoitsma, J. Madsen, R.P. Silberstein, G. Welsh, and J.B. Whiteside. A structural integrity prognosis system. Engineering Fracture Mechanics, Volume 76, Issue 5, Material Damage Prognosis and Life-Cycle Engineering, March 2009, Pages 620-632, ISSN 0013-7944, DOI: 10.1016/j.engfracmech.2008.09.007.

(Yuen et al., 2006)B.K.C. Yuen, and F. Taheri. Proposed modifications to the Wheeler retardation model for multiple overloading fatigue life prediction. International Journal of Fatigue, Volume 28, Issue 12, December 2006, Pages 1803-1819, ISSN 0142-1123, DOI: 10.1016/j.ijfatigue.2005.12.007.

(Schjive, 1976) J. Schijve. Observations on the Predictions of Fatigue Crack Growth Prediction under Variable Amplitude loading. ASTM STP 595, 1976, pp. 3-23.

(Noroozi et al., 2008) A.H. Noroozi, G. Glinka, S. Lambert, Prediction of fatigue crack growth under constant amplitude loading and a single overload based on elasto-plastic crack tip stresses and strains, Engineering Fracture Mechanics, Volume 75, Issue 2, January 2008, Pages 188-206.

(Sheu et al., 1995) B.C. Sheu, P.S. Song, and S. Hwang. Shaping exponent in wheeler model under a single overload. Eng Fract Mech 1995;51(1): 135– 43.

(Song et al., 2001) P.S. Song, B.C. Sheu, and L. Chang. A modified wheeler model to improve predictions of crack growth following a single overload. JSME Int J Series A 2001;44(1):117–22.

(Liu and Mahadevan, 2005) Y. Liu, and S. Mahadevan. 2005. Multiaxial high-cycle fatigue criterion and life prediction for metals. International Journal of Fatigue, 2005. 27(7): p. 790-80.

(Sankararaman et al., 2010) S. Sankararaman, Y. Ling, and S. Mahadevan. Statistical Inference of Equivalent Initial Flaw Size with Complicated Structural Geometry and Multi-axial Variable Amplitude Conditions. Int J. Fatigue. Available Online 2010. doi:10.1016/j.ijfatigue.2010.03.012.

(McFarland, 2008) J. McFarland. Uncertainty analysis for computer simulations through validation and calibration. Ph D. Dissertation, Vanderbilt University, 2008.

(Zhang and Mahadevan, 2001) R. Zhang and S. Mahadevan. Fatigue reliability analysis using nondestructive inspection, J. Struct Engrg 127 (2001) 957-965.

(Zhang and Mahadevan, 2003) R. Zhang, and S. Mahadevan. Bayesian methodology for reliability model acceptance. Reliability Engineering & System Safety, Volume 80, Issue 1, April 2003, Pages 95-103.

(Jiang and Mahadevan, 2006) X. Jiang, and S. Mahadevan. Bayesian risk-based decision method for model validation under uncertainty. Reliability Engineering & System Safety, Volume 92, Issue 6, June 2007, Pages 707-718.

(ANSYS, 2007) ANSYS. ANSYS theory reference, release 11.0. ANSYS Inc., 2007.
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Technical Papers

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