Sensitivity analysis and propagation of uncertainty for the simulation of vehicle pass-by noise

United Nations Economic Commission for Europe, Addendum 50: Regulation No. 51 Revision 3. Uniform provisions concerning the approval of motor vehicles having at least four wheels with regard to their sound emissions; 2016. United Nations Economic Commission for Europe, Addendum 50: Regulation No. 51 Revision 2. Uniform provisions concerning the approval of motor vehicles having at least four wheels with regard to their sound emissions; 2011. Locqueteau, 2012, Point of view of automotive OEM for new passby noise regulation R51– 03: challenges and new deployment Pardo, 2012, Exterior pass-by noise regulation – monitoring database and impact assessment International Organization for Standardization, ISO 362-1: Measurement of noise emitted by accelerating road vehicles – Engineering method – Part 1: M and N categories; 2015. International Organization for Standardization, ISO 362: Acoustics – Measurement of noise emitted by accelerating road vehicles – Engineering method; 1998. International Organization for Standardization, ISO 10844: Acoustique - Spécification des surfaces d’essai pour le mesurage du bruit émis par les véhicules routiers et leurs pneumatiques; 2014. Huijssen, 2013, A synthesis procedure for pass-by noise of automotive vehicles employing numerically evaluated source-receiver transfer functions, J Sound Vib, 332, 3790, 10.1016/j.jsv.2013.01.042 Braun, 2013, Noise source characteristics in the ISO 362 vehicle pass-by noise test: literature review, Appl Acoust, 74, 1241, 10.1016/j.apacoust.2013.04.005 Braun, 2014 Van de Ponseele, 2012, Source-Transfer-Receiver approaches: a review of methods Janssens, 2014, Pass-by noise engineering: a review of different transfer path analysis techniques Sandberg, 2002, Tyre/road noise reference book, Informex de Recquigny, 2008 Jaynes, 1957, Information theory and statistical mechanics, Phys. Rev., 106, 620, 10.1103/PhysRev.106.620 Kapur, 1992 C. Shannon, A mathematical theory of communication 27 (1948) 379–423, 623–656. Saltelli, 2008 Hammersley, 1964 Robert, 1999 Hellekalek, 1998 Bratley, 1988, Algorithm 659: implementing sobol’s quasirandom sequence generator, ACM Trans. Math. Softw., 14, 88, 10.1145/42288.214372 Halton, 1960, On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals, Numer. Math., 2, 84, 10.1007/BF01386213 Iooss, 2015, A review on global sensitivity analysis methods Jacques, 2005, Contributions á l’analyse de sensibilité et á l’analyse discriminante généralisée, Université Joseph-Fourier - Grenoble, I Iooss, 2011, Revue sur l’analyse de sensibilité globale de modèles numériques, Journal de la Societe Française de Statistique, 152, 1 Saltelli, 2000 Saltelli, 2004 Saltelli A, TS. On the relative importance of input factors in mathematical models : Safety assessment for nuclear waste disposal 97 (2002) 702–709. Mara, 2012, Variance-based sensitivity indices for models with dependent inputs, Reliab Eng Syst Saf, 107, 115, 10.1016/j.ress.2011.08.008 McKay, 1997, Nonparametric variance-based methods of assessing uncertainty importance, Reliab Eng Syst Saf, 57, 267, 10.1016/S0951-8320(97)00039-2 Sobol IM. Sensitivity estimates for nonlinear mathematical models 1 (1993) 407–414. Burnham, 2004, Multimodel inference: understanding AIC and BIC in model selection, Sociol Methods Res, 33, 261, 10.1177/0049124104268644 Burnham, 2002 MacKay, 1991, Bayesian interpolation, Neural Comput, 4, 415, 10.1162/neco.1992.4.3.415