A Study of the Growth of Small Fatigue Cracks in a High Strength Steel Using a Surface Acoustic Wave Technique

Abstract

An ultrasonic surface acoustic wave technique for studying the growth behaviour of small fatigue cracks is described. The technique allows crack depth and opening stress to be monitored continuously during the course of a fatigue test. Results are given for a 1740 MPa yield strength, silicon-modified, AISI 4340 steel tested under zero-to-tension cyclic loading. Good agreement is shown between acoustically determined crack depth and that measured by post-fracture optical microscopy. The monitoring of changing crack depth-to-surface length ratios during tests is also demonstrated. Acoustically determined crack opening stresses were found to be about 10% higher than values determined by measurements of crack tip opening displacements by scanning electron microscopy. Effects on crack growth of two different specimen surface preparations, electropolishing and diamond paste polishing, are also reported. Growth rates in electropolished specimens were as much as an order of magnitude higher than in diamond paste polished specimens which had a shallow but significant layer of compressive residual stress. NOMENCLATURE u/c = ratio of crack depth to half surface crack length C = crack front E = modulus of elasticity AK, A& = range of K , and of effective K , CTOD = crack tip opening displacement K , = mode I stress intensity factor N = number of cycles P = power input to acoustic transducer rb = reversed crack tip plastic zone size R = stress ratio = urn in/^,,, wb = beam width at transmitting transducer = crack reflection coefficient K = wave number (2n/I) J. = acoustic wavelength v = Poisson's ratio p = distance between origin of surface crack and tangent line to crack front u* = acoustic stress uOp = opening stress usat = saturation stress urnin, u,,, = minimum and maximum applied stress uCTOD = opening stress based on CTOD measurements Aueff = range of effective stress u; = cyclic yield strength @ = elliptic integral of second kind o : angular frequency of surface acoustic wave

The use of nondestructive evaluation methods in fatigue: A review

“…Such thermal energy release is possible to be detected by infrared (IR) imaging. Its detection during fatigue loading on metallic specimens at the laboratory scale has been used to correlate temperature changes with the fatigue response . Related experimental investigations have been performed using both active, ie, in cases in which an external heat source is used, and passive, ie, when energy release from damage naturally produces heat changes.…”

“…The procedure for applying both techniques in the context of laboratory‐scale materials testing relies on the placement of appropriate sensors in a number of locations to ensure that signals resulting from damage will be detectable . The most common type of sensors used in acoustic NDE methods are piezoelectric transducers which vary in terms of size and detectable frequency range . After the acoustic waves are detected and converted to an electric signal, the signals are amplified and filtered before being stored.…”

“…Its detection during fatigue loading on metallic specimens at the laboratory scale 16,78,79,82 has been used to correlate temperature changes with the fatigue response. 18,41,83,84 Related experimental investigations have been performed using both active, 85 ie, in cases in which an external heat source is used, and passive, [77][78][79] ie, when energy release from damage naturally produces heat changes. The release of thermal energy has been investigated qualitatively by using uncalibrated systems with the NDE objective being to detect the existence of damage or by using calibrated systems which allow the quantification of actual temperature changes which are then processed to provide damage sizing and source identification.…”

“…4,90,92,93 The most common type of sensors used in acoustic NDE methods are piezoelectric transducers which vary in terms of size and detectable frequency range. 82,83,94,95 After the acoustic waves are detected and converted to an electric signal, the signals are amplified and filtered before being stored. These signals are then analyzed and postprocessed to relate extracted features (eg, amplitude, duration, peak frequency, and attenuation) to potential damage sources.…”