Abstract:
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Additively manufactured metals are widely used in everything from jet engines to medical implants. When subjected to repeated, low-intensity stresses the microstructure (including porosity) plays a key role in the initiation, growth, and eventual unstable propagation of cracks. Estimating the slope and endpoints of the stable crack growth region for moderate stress levels is critical in determining safe working conditions for a given material and application, as well as for comparing new alloys or heat treatments. Current estimation methods operate on noisy, numerically differentiated data which may also be smoothed. We show first that the slope and endpoints can be estimated using nonlinear least squares, and differences between model parameter estimates from various data sets can be tested using a bootstrap resampling scheme. Secondly, we explore a procedure to directly use the measured data to incorporate the uncertainty from the numerical differentiation into the parameter estimates. This work has the potential to impact measurement standards and support statistically sound evaluation of new materials and heat treatment methods.
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