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Publication Citation: Uncertainty Estimate of Charpy Data Using a 5-factor 8-run Design of Experiments

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Author(s): Charles G. Interrante; Jeffrey T. Fong; James J. Filliben; Nathanael A. Heckert;
Title: Uncertainty Estimate of Charpy Data Using a 5-factor 8-run Design of Experiments
Published: July 27, 2008
Abstract: Scatter in laboratory data with duplicates on Charpy impact tests is analyzed by identifying several sources of variability such as temperature, manganese sulfide, initial strain, mis-orientation, and notch radius in order to estimate the predictive 95% confidence intervals of the mean energy of absorption for each specific test temperature.  Using a combination of real and virtual data on a high-strength pressure vessel grade steel (ASTM A517) over a range of temperatures from -40 C (-40 F) to 182 C (360 F), and the concept of a statistical design of experiments, we present an uncertainty estimation methodology using a public-domain statistical analysis software named DATAPLOT.  A numerical example for estimating the mean, standard deviation, and predictive intervals of the Charpy energy at 48.9 C (120 F) is included.  To illustrate the application potential of this methodology, we enhance it with formulas of  error propagation  to estimate  the  mean,  standard deviation, and predictive intervals of the associated static crack initiation toughness,  KIc .  A discussion of the significance and limitations of the proposed methodology, and a concluding remark are given at the end of this paper.
Proceedings: Proceedings of 2008 ASME Pressure Vessels and Piping Division Conference July 27-31, 2008, Chicago, Illinois, USA
Pages: pp. 1 - 27
Location: Chicago, IL
Dates: July 27-31, 2008
Keywords: Applied mechanics; Charpy energy; Charpy V-notch impact test; design of experiments; engineering safety;error propagation; fracture mechanics; fracture toughness; impact resistance; mathematical modeling; materials science; mechanical properties; mechanical testing; metallurgical engineering; pressure vessels and piping; pressure vessel steels; sensitivity analysis; statistical data analysis; structural integrity; uncertainty analysis; virtual experiments.
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