Executive Summary : | Uncertainty Quantification is an emerging area of research for variability analysis of the systems with random variables. There are several methodologies available in the literature which can be used to quantify uncertainty in the systems in which the design variables have the physical inaccuracies. Out of the available methods, two widely used methods- Polynomial Chaos Expansion (PCE) and Orthogonal Experiments (OE) are used for stochastic and statistical analysis, respectively. The orthogonal experiments method is a subset of Design of Experiments (DOE) technique where the experiments are designed in an orthogonal manner and using Statistical Inference the variability in system response is observed. On the other hand, the PCE techniques model the system as a black box where the system response is a polynomial function of several random variables.This project aims to investigate correlation between the theories of Polynomial Chaos Expansion and Orthogonal Experiments through their origins. The former one is a stochastic approach while the later one is a statistical technique. However, both of them are widely used in many applications and one of such applications is variability analysis of systems having process variations. Both the techniques are proven to be effective in uncertainty quantification in the literature. The objective of this project is to correlate their theoretical foundations which could be helpful for many applications. |