The Application of the Norton-Bailey Law for Creep Prediction Through Power Law Regression

Accurate determination of constitutive modeling constants used in high value components, especially in electric power generation equipment, is vital for related design activities. Parts under creep are replaced after extensive deformation is reached, so models, such as the Norton-Bailey power law, support service life prediction and repair/replacement decisions. For high fidelity calculations, experimentally acquired creep data must be accurately regressed over a variety of temperature, stress, and time combinations. If these constants are not precise, then engineers could be potentially replacing components with lives that have been fractionally exhausted, or conversely, allowing components to operate that have already been exhausted. By manipulating the Norton-Bailey law and utilizing bivariate power-law statistical regression, a novel method is introduced to precisely calculate creep constants over a variety of sets of data. The limits of the approach are explored numerically and analytically.Copyright © 2013 by ASME