Uncertainty Quantification in Temperature Distribution for Annular Fins

ABSTRACT

Quantification of uncertainty in prediction of temperature distribution in annular fins has been investigated in the present paper by applying the Non Intrusive Spectral Projection (NISP) method. The fin parameter and the ambient temperature have been considered to be the uncertain inputs, described by either the Gaussian, or, the LogNormal probability distribution functions. The stochastic and the deterministic mean solutions have been compared and the respective confidence intervals have been obtained. It has been observed that for higher values of standard deviations, particularly with LogNormal probability distribution of the uncertain variables, the mean solutions considerably differ, although the confidence intervals could be reasonably predicted using the deterministic solution and the limiting values of the uncertain parameters. In this respect, three different methods have been employed in the present study and it has been observed that the combined bound method performs the best.

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