Probabilistic Analysis of Brake Noise : A Hierarchical Multi-fidelity Statistical Approach

Abstract: Computer Aided Engineering driven analysis is gaining grounds in automotive industry. Prediction of brake noise using CAE techniques has become populardue to its overall low cost as compared to physical testing. However, the presence of several uncertain parameters which affect brake noise and also the lack of basic understanding about brake noise, makes it difficult to make reliable decisions based on CAE analysis. Therefore, the confidence level in CAE techniques has to be increased to ensure reliability and robustness in the CAE solutions which support design work. One such way to achieve reliability in the CAE analysis isinvestigated in this thesis by incorporating the effects of different sources of uncertainty and variability in the analysis and estimating the probability of designfailure (probability of brake noise above a certain threshold). While incorporating the uncertainties in the CAE analysis ensures robustness, it is computationally intensive. This thesis work aims to gain an understanding about a brakenoise - creep groan, and to bring robustness into the CAE analysis along with reduction in computational time. A probabilistic analysis technique called hierarchical multi-fidelity statistical approachis explored in this thesis work, to estimate the probability of design failure or design robustness at a faster rate. It incorporates the stochasticity in the input parameters while running simulations. The method involves application of a hierarchy of approximations to the system response computed with variations in mesh resolution or variations in number of modes or changing solver time step,etc. And finally it uses the probability theory, to relate the information provided by approximate solutions to get the target failure estimation.Through this method, reliable data regarding the probability of design failure was approximated for every simulation and at a reduced computational time.Additionally, it provided information about critical parameters that influenced brake noise which was meritorious for design management. Estimation of probability of design failure by this method has been proved to be reliable in the case of brake noise according to the simulation results and the method can be considered robust.