Abstract
The aeronautics industry has benefited from the use of numerical models to supplement or replace the costly design-build-test paradigm. These models are often calibrated using experimental data to obtain optimal fidelity-to-data but compensating effects between calibration parameters can complicate the model selection process due to the non-uniqueness of the solution. One way to reduce this ambiguity is to include a robustness requirement to the selection criteria. In this study, the info-gap decision theory is used to represent the lack of knowledge resulting from compensating effects and a robustness analysis is performed to investigate the impact of uncertainty on both deterministic and stochastic fidelity metrics. The proposed methodology is illustrated on an academic example representing the dynamic response of a composite turbine blade.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
SNECMA and HERAKLES: Aube de Turbomachine en Matériau Composite et Procédé pour sa Fabrication - Brevet. WO 2011/080443 A1 (2011)
Berman, A.: Multiple acceptable solutions in structural model improvement. AIAA J. 33 (5), 924–927 (1995)
Atamturktur, S., Liu, Z., Cogan, S., Juang, H.: Calibration of imprecise and inaccurate numerical models considering fidelity and robustness: a multi-objective optimization-based approach. Struct. Multidiscip. Optim. 51, 659–671 (2014)
Govers, Y., Link, M.: Stochastic model updating - Covariance matrix adjustment from uncertain experimental modal data. Mech. Syst. Signal Process. 24 (3), 696–706 (2010)
Smith, A.F.M., Roberts, G.O.: Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods. J. R. Stat. Soc. 55 (1), 3–23 (1993)
Chib, S., Greenberg, E.: Understanding the Metropolis-Hastings algorithm. Am. Stat. 49 (4), 327–335 (1995)
Aherne, F.J., Thacker, N.A., Rockett, P.I.: The Bhattacharyya metric as an absolute similarity measure for frequency coded data. Kybernetika 34 (4), 363–368 (1998)
Ben-Haim, Y.: Info-Gap Decision Theory: Decisions Under Severe Uncertainty. Academic, New York (2006). [ISBN: 978-0-12-373552-2]
Hall, J.W., Lempert, R.J., Keller, K., Hackbarth, A., Mijere, C., McInerney, D.J.: Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods. Risk Anal. 32 (10), 1657–1672 (2012)
Ben-Haim, Y., Zacksenhouse, M., Keren, C., Dacso, C.C.: Do we know how to set decision thresholds for diabetes? Med. Hypotheses 73 (2), 189–193 (2009)
Kuczkowiak, A.: Modèle hybride incertain pour le calcul de réponse en fonctionnement d’un alternateur. PhD thesis, Université de Franche-Comté (2014)
Naouar, N., Vidal-Sallé, E., Schneider, J., Maire, E., Boisse, P.: Meso-scale FE analyses of textile composite reinforcement deformation based on X-ray computed tomography. Compos. Struct. 116, 165–176 (2014)
Couégnat, G.: Approche multiéchelle du comportement mécanique de matériaux composites à renfort tissé. PhD thesis, Université Sciences et Technologies-Bordeaux I (2008)
Dupin, C.: Etude du comportement mécanique des matériaux composites à matrice céramique de faible épaisseur. PhD thesis, Bordeaux 1 (2013)
Naouar, N., Vidal-Salle, E., Schneider, J., Maire, E., Boisse, P.: 3d composite reinforcement meso F.E. analyses based on X-ray computed tomography. Compos. Struct. 132, 1094–1104 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 The Society for Experimental Mechanics, Inc.
About this paper
Cite this paper
Lépine, P., Cogan, S., Foltête, E., Parent, MO. (2016). Robust Model Calibration Using Determinist and Stochastic Performance Metrics. In: Atamturktur, S., Schoenherr, T., Moaveni, B., Papadimitriou, C. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-29754-5_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-29754-5_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29753-8
Online ISBN: 978-3-319-29754-5
eBook Packages: EngineeringEngineering (R0)