Uncertainty quantification in chemical systems

We demonstrate the use of multiwavelet spectral polynomial chaos techniques for uncertainty quantification in non-isothermal ignition of a methane-air system We employ Bayesian inference for identifying the probabilistic representation of the uncertain parameters and propagate tills uncertainty through the ignition process We analyze the time evolution of moments and probability density functions of the, solution We also examine the role and significance of dependence among the uncertain parameters We finish with a discussion of the role of non-linearity and the performance of the algorithm. Copyright 0 2009 John Wiley & Sons, Ltd