Measurements of the stress-induced changes in ultrasonic wave speeds in steels typically used in railroad rails are presented. All of the five possible relative changes in wave speeds for a uniaxial state of stress have been determined and agree, to within the limits of accuracy of the measurement, with the second-order theory of Hughes and Kelly. The third-order elastic constants are calculated from the acoustoelastic data. Subject Classification: [43]85.20, [43]85.22, [43]35.26.

Measurements of the stress-induced changes in ultrasonic wave speeds in several samples of steels typically used in railroad rails are presented. All of the five possible relative changes in wave speeds for an initially isotropic material subjected to a uniaxial state of stress have been determined and agree to within the limits of accuracy of the measurement with the second-order theory of Hughes and Kelly. The third-order elastic constants are calculated from the acoustoelastic data.

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Most of the methods for determining residual stresses inside metallic solids are destructive, which is undesirable. The ultrasonic technique provides a useful nondestructive tool in the evaluation of stresses. This work presents the application of shear and longitudinal waves in the determination of stress state in a steel bar. A bar stressed by a hydraulic system is used to simulate the effect of the tensile stress. The stresses are recorded and compared with the real value calculated using the force and the bar cross-sectional area. The comparison between the theoretical and experimental results shows that it is possible to correlate tensile stresses and velocity with both methods, although the longitudinal critically refracted LCR waves have greater sensitivity to the stress.

High precision, fast ultrasonic thermometer based on measurement of the speed of sound in air Rev. Sci. Instrum. 73, 4022 (2002); 10.1063/1.1510576 Study of circumferential waves and their interaction with defects on cylindrical shells using line-source laser ultrasonicsThe determination of the stress field inside metallic parts is one of the most important challenges to the designer. Although the prediction of the stress distribution can be done by several numerical and empirical methods, the real stress value is almost always unknown. Several destructive and nondestructive techniques have been tested to accomplish this task, including the application of x rays, saw cut, neutron diffraction and so on, but none of them seems to have a suitable correlation between cost and applicability. Ultrasonic techniques have been used for flaw detection since the 1950s. The main application was in the identification of cracks and voids. In this work we present the application of ultrasound in the evaluation of a one-dimensional stress field using the longitudinal critically refracted waves (L CR ). A new ultrasonic L CR probe is presented and its performance is evaluated using PC based instrumentation. Also, the L CR waves' sensitivity is verified using a low cost commercial flaw detector. The results show that the technique can be applied to quantify the magnitude of the stresses in bars, using either the PC based or the commercial flaw detector system, as long as the high sensitivity longitudinal critically refracted waves are used.

Frequency analysis of Fourier spectra from ultrasonic signals was used for predicting intramuscular fat content of beef tissue. The most significant parameter in the frequency domain for predicting intramuscular fat concentration in beef was the number of local maxima. It represents the discontinuity of the Fourier spectrum caused by inhomogeneous fat concentrations in the longissimus muscle, which had the correlation coefficient .89 (P < .05) when a 2.25-MHz shear probe was used. The optimum frequency for predicting the amount of intramuscular fat content in the longissimus muscle was found to be 1.92 MHz. A multivariate regression model was developed using parameters in the frequency domain as follows: percentage of fat concentration = 1.790 - 2.373x (lower frequency) + .049x (bandwidth) + 1.178x (local maxima) (R2 = .82). Validation demonstrated that the multivariate model in the frequency domain was capable of predicting intramuscular fat concentration with an average of 1.17 percentage of fat error (P < .05). The multivariate model was most appropriate for predicting intramuscular fat below 4%. The mean accuracy of the model in the frequency domain was approximately 79%.