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A unified method and its application to brake instability analysis involving different types of epistemic uncertainties. (English) Zbl 1480.74096

Summary: The key idea of the proposed method is the use of the equivalent variables named as evidence-based fuzzy variables, which are special evidence variables with fuzzy focal elements. On the basis of the equivalent variables, an uncertainty quantification model is established, in which the unified probabilistic information related to the uncertain responses of engineering systems can be computed with the aid of the fuzziness discretization and reconstruction, the belief and plausibility measures analysis, and the interval response analysis. Monte Carlo simulation is presented as a reference method to validate the accuracy of the proposed method. The proposed method then is extended to perform squeal instability analysis involving different types of epistemic uncertainties. To illustrate the feasibility and effectiveness of the proposed method, seven numerical examples of disc brake instability analysis involving different epistemic uncertainties are provided and analyzed. By conducting appropriate comparisons with reference results, the high accuracy and efficiency of the proposed method on quantifying the effects of different epistemic uncertainties on brake instability are demonstrated.

MSC:

74H10 Analytic approximation of solutions (perturbation methods, asymptotic methods, series, etc.) of dynamical problems in solid mechanics
74K99 Thin bodies, structures
03E72 Theory of fuzzy sets, etc.
Full Text: DOI

References:

[1] Papinniemi, A.; Lai, J. C.S.; Zhao, J.; Loader, L., Brake squeal: a literature review, Appl. Acoust., 63, 4, 391-400 (2002)
[2] Júnior, M. T.; Gerges, S. N.Y.; Jordan, R., Analysis of brake squeal noise using the finite‐element method: a parametric study, Appl. Acoust., 69, 2, 147-162 (2006)
[3] Oberkampf, W. L.; Helton, J. C.; Joslyn, C. A.; Wojtkiewicz, S. F.; Ferson, S., Challenge problems: uncertainty in system response given uncertain parameters, Reliab. Eng. Syst. Safe., 85, 1-3, 11-19 (2004)
[4] Sarrouy, E.; Dessombz, O.; Sinou, J. J., Piecewise polynomial chaos expansion with an application to brake squeal of a linear brake system, J. Sound Vib., 332, 3, 577-594 (2013)
[5] Nechak, L.; Gillot, F.; Besset, S.; Sinou, J. J., Sensitivity analysis and Kriging based models for robust stability analysis of brake systems, Mech. Res. Commun., 69, 136-145 (2015)
[6] Nobari, A.; Ouyang, H.; Bannister, P., Uncertainty quantification of squeal instability via surrogate modelling, Mech. Syst. Signal Process., 60-61, 887-908 (2015)
[7] Nobari, A.; Ouyang, H.; Bannister, P., Statistics of complex eigenvalues in friction-induced vibration, J. Sound Vib., 338, 169-183 (2015)
[8] Moore, R. E., Interval Analysis (1966), Prentice-Hall: Prentice-Hall Englewood Cliffs · Zbl 0176.13301
[9] Zadeh, L. A., Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets Syst., 1, 1, 3-28 (1978) · Zbl 0377.04002
[10] Shafer, G., A Mathematical Theory of Evidence (1976), Princeton University Press: Princeton University Press Princeton · Zbl 0359.62002
[11] Beer, M.; Ferson, S.; Kreinovich, V., Imprecise probabilities in engineering analyses, Mech. Syst. Signal Process., 37, 1-2, 4-29 (2013)
[12] Xia, B.; Yu, D., Interval analysis of acoustic field with uncertain-but-bounded parameters, Comput. Struct., 112-113, 12, 235-244 (2012)
[13] Wang, C.; Qiu, Z., Uncertain temperature field prediction of heat conduction problem with fuzzy parameters, Int. J. Heat Mass Transf., 91, 725-733 (2015)
[14] Zhang, Z.; Jiang, C.; Wang, G. G.; Han, X., First and second order approximate reliability analysis methods using evidence theory, Reliab. Eng. Syst. Safe., 137, 40-49 (2015)
[15] Wu, D.; Gao, W.; Wang, C.; Tangaramvong, S.; Tin-Loi, F., Robust fuzzy structural safety assessment using mathematical programming approach, Fuzzy Sets Syst., 293, 30-49 (2016) · Zbl 1378.90094
[16] Lü, H.; Yu, D., Brake squeal reduction of vehicle disc brake system with interval parameters by uncertain optimization, J. Sound Vib., 333, 26, 7313-7325 (2014)
[17] Gauger, U.; Hanss, M.; Gaul, L., On the inclusion of uncertain parameters in brake squeal analysis, (Proceedings of the IMAC-XXIV: Conference and Exposition on Structural Dynamics (2006))
[18] Giannini, O., Fuzzy model for the prediction of brake squeal noise, (Proceedings of the IMAC-XXIII: Conference and Exposition on Structural Dynamics (2005))
[19] Massa, F.; Do, H. Q.; Tison, T.; Cazier, O., Uncertain friction induced vibration study: coupling of fuzzy logic, fuzzy sets and interval theories, ASME J. Risk Uncertain. Part B, 2, 1, Article 011008-1-12 (2016)
[20] Lü, H.; Shangguan, W. B.; Yu, D., An imprecise probability approach for squeal instability analysis based on evidence theory, J. Sound Vib., 387, 96-113 (2016)
[21] Sofi, A.; Romeo, E., A unified response surface framework for the interval and stochastic finite element analysis of structures with uncertain parameters, Probab. Eng. Mech. (2017)
[22] Qiu, Z.; Xia, Y.; Yang, J., The static displacement and the stress analysis of structures with bounded uncertainties using the vertex solution theorem, Comput. Method Appl. Mech. Eng., 196, 49-52, 4965-4984 (2007) · Zbl 1173.74355
[23] Qiu, Z.; Wang, X., Parameter perturbation method for dynamic responses of structures with uncertain-but-bounded parameters based on interval analysis, Int. J. Solids Struct., 42, 18, 4958-4970 (2005) · Zbl 1119.74410
[24] Kaufmann, A.; Gupta, M. M., Introduction to Fuzzy Arithmetic (1985), Van Nostrand Reinhold: Van Nostrand Reinhold New York · Zbl 0588.94023
[25] Gauger, U.; Turrin, S.; Hanss, M.; Gaul, L., A new uncertainty analysis for the transformation method, Fuzzy Sets Syst., 159, 11, 1273-1291 (2008) · Zbl 1170.93337
[26] Wang, C.; Qiu, Z.; Xu, M.; Qiu, H., Novel fuzzy reliability analysis for heat transfer system based on interval ranking method, Int. J. Therm. Sci., 116, 234-241 (2017)
[27] Zhou, M. J., A design optimization method using evidence theory, J. Mech. Des., 128, 4, 1153-1161 (2006)
[28] Jiang, C.; Zhang, W.; Wang, B.; Han, X., Structural reliability analysis using a copula-function-based evidence theory model, Comput. Struct., 143, 19-31 (2014)
[29] Nie, X. H.; Huang, G. H.; Li, Y. P.; Liu, L., IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty, J. Environ. Manage., 84, 1, 1-11 (2007)
[30] Wang, C.; Qiu, Z.; He, Y., Fuzzy interval perturbation method for uncertain heat conduction problem with interval and fuzzy parameters, Int. J. Numer. Meth. Eng., 104, 5, 330-346 (2015) · Zbl 1352.80011
[31] Straszecka, E., An interpretation of focal elements as fuzzy sets, Int. J. Intell. Syst., 18, 7, 821-835 (2003) · Zbl 1018.68511
[32] Zhou, Y. T.; Jiang, C.; Han, X., Interval and subinterval analysis methods of the structural analysis and their error estimations, Int. J. Comp. Meth., 3, 229-244 (2006) · Zbl 1198.65088
[33] S. Ferson, V. Kreinovich, L. Ginzburg, D.S. Myers, K. Sentz, Constructing Probability Boxes and Dempster-Shafer Structures, Technical Report SAND2003-4015, Sandia National Laboratories, Albuquerque, NM, 2003.; S. Ferson, V. Kreinovich, L. Ginzburg, D.S. Myers, K. Sentz, Constructing Probability Boxes and Dempster-Shafer Structures, Technical Report SAND2003-4015, Sandia National Laboratories, Albuquerque, NM, 2003.
[34] Baudrit, C.; Dubois, D.; Guyonnet, D., Joint propagation and exploitation of probabilistic and possibilistic information in risk assessment, IEEE Trans. Fuzzy Syst., 14, 5, 593-608 (2006)
[35] Pedroni, N.; Zio, E.; Ferrario, E.; Pasanisi, A.; Couplet, M., Hierarchical propagation of probabilistic and non-probabilistic uncertainty in the parameters of a risk model, Comput. Struct., 126, 2, 199-213 (2013)
[36] Gil, M. A., Special issue on fuzzy random variables, Inform. Sci., 133, 1-2 (2001) · Zbl 0982.00024
[37] Baudrit, C.; Couso, I.; Dubois, D., Joint propagation of probability and possibility in risk analysis: towards a formal framework, Int. J. Approx. Reason., 45, 1, 82-105 (2007) · Zbl 1123.68123
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