Oxidation and the Effects of High Temperature Exposures on Notched Fatigue Life of an Advanced Powder Metallurgy Disk Superalloy
Oxidation and the effects of high temperature exposures on notched fatigue life were considered for a powder metallurgy processed supersolvus heat-treated ME3 disk superalloy. The isothermal static oxidation response at 704 C, 760 C, and 815 C was consistent with other chromia forming nickel-based superalloys: a TiO2-Cr2O3 external oxide formed with a branched Al2O3 internal subscale that extended into a recrystallized - dissolution layer. These surface changes can potentially impact disk durability, making layer growth rates important. Growth of the external scales and dissolution layers followed a cubic rate law, while Al2O3 subscales followed a parabolic rate law. Cr- rich M23C6 carbides at the grain boundaries dissolved to help sustain Cr2O3 growth to depths about 12 times thicker than the scale. The effect of prior exposures was examined through notched low cycle fatigue tests performed to failure in air at 704 C. Prior exposures led to pronounced debits of up to 99 % in fatigue life, where fatigue life decreased inversely with exposure time. Exposures that produced roughly equivalent 1 m thick external scales at the various isotherms showed statistically equivalent fatigue lives, establishing that surface damage drives fatigue debit, not exposure temperature. Fractographic evaluation indicated the failure mode for the pre-exposed specimens involved surface crack initiations that shifted with exposure from predominately single intergranular initiations with transgranular propagation to multi-initiations from the cracked external oxide with intergranular propagation. Weakened grain boundaries at the surface resulting from the M23C6 carbide dissolution are partially responsible for the intergranular cracking. Removing the scale and subscale while leaving a layer where M23C6 carbides were dissolved did not lead to a significant fatigue life improvement, however, also removing the M23C6 carbide dissolution layer led to nearly full recovery of life, with a transgranular initiation typical to that observed in unexposed specimens.
Low cycle fatigue of René 80 as affected by prior exposure
Low cycle fatigue of the Ni base alloy René 80 was studied at 871°C. Prior to testing, specimens were exposed for 100 h at 982°C either stress-free or at 97 MPa (1/3 the yield). The LCF studies were supplemented by tensile and creep tests. The prior exposure caused significant microstructural changes and life reductions which were most pronounced for stress exposed specimens tested at high rates. Dislocation substructures were extensively studied. The deformation mode was constant for all smooth bar fatigue tests and the dislocation arrangements resembled those seen in creep far more closely than those characteristic of tensile deformation. The observed behavior was attributed to time-dependent changes and environmental interactions. The presence of classical creep/fatigue interactions was considered to be of only minor importance in these experiments.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.