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Mechanical Engineering Commons

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1993

Semiconductor and Optical Materials

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Articles 1 - 8 of 8

Full-Text Articles in Mechanical Engineering

Effects Of Acoustic Scattering At Rough Surfaces On The Sensitivity Of Ultrasonic Inspection, Peter B. Nagy, Laszlo Adler, James H. Rose Jan 1993

Effects Of Acoustic Scattering At Rough Surfaces On The Sensitivity Of Ultrasonic Inspection, Peter B. Nagy, Laszlo Adler, James H. Rose

Review of Progress in Quantitative Nondestructive Evaluation

Ultrasonic inspection of ordinary samples with more or less rough surfaces is an everyday problem in industrial NDE. Contact techniques require flat or other regular (e. g., cylindrical) surfaces of negligible roughness with respect to the acoustic wavelength. Immersion techniques are less susceptible to surface topography, but they still require that the surface radius be larger than the beam diameter and the surface roughness be comparable or less than the wavelength in the immersion fluid. This difference is due to the fact that in immersion inspection surface irregularities do not significantly reduce the energy transmission into the specimen but rather ...


Acoustic Microscopy Measurements To Correlate Surface Wave Velocity And Surface Roughness, Y. C. Lee, Jan D. Achenbach, Jin O. Kim Jan 1993

Acoustic Microscopy Measurements To Correlate Surface Wave Velocity And Surface Roughness, Y. C. Lee, Jan D. Achenbach, Jin O. Kim

Review of Progress in Quantitative Nondestructive Evaluation

Acoustic microscopy can be used for very localized measurements of the velocity and attenuation of surface waves, and hence is a possible technique for nondestructive evaluation of near surface damage due to fatigue, machining, friction, wear, etc. Because the frequency of operation of an acoustic microscope is high, usually above 100 MHz, the wavelength of the surface wave is relatively small, and thus the roughness of the specimen may affect the wave velocity. In most cases the specimens must be polished to a metallurgical level to ensure that the true Rayleigh wave velocity, i.e., the one for a smooth ...


Ultrasonic Sensing Simulation Of Cdte Single Crystal Growth, Yichi Lu, Haydn N. G. Wadley Jan 1993

Ultrasonic Sensing Simulation Of Cdte Single Crystal Growth, Yichi Lu, Haydn N. G. Wadley

Review of Progress in Quantitative Nondestructive Evaluation

Today’s infrared detector arrays consist of Hg1-xCdxTe deposited upon lattice matched Cd1-xZnxTe substrate wafers. Very high quality Cd1-xZnxTe crystals must be grown so that substrate wafer defects do not degrade the detector’s performance. Usually, the Cd1-xZnxTe crystals are grown by a Bridgman technique in which a charge is melted in a cylindrical quartz ampoule and slowly withdrawn from the hot zone (at ~ 1100°C) of a furnace.1 The best quality crystal is obtained from material solidified under plane front conditions.2 This is difficult to achieve, and a need has arisen for insitu sensing of the growth ...


Monte-Carlo Simulation Of Ultrasonic Grain Noise, I. Yalda-Mooshabad, Frank J. Margetan, R. Bruce Thompson Jan 1993

Monte-Carlo Simulation Of Ultrasonic Grain Noise, I. Yalda-Mooshabad, Frank J. Margetan, R. Bruce Thompson

Review of Progress in Quantitative Nondestructive Evaluation

In ultrasonic inspections for small or subtle defects in metals, defect signals may be obscured by grain noise echoes which arise from the scattering of sound by the microstructure of the metal. Models for predicting microstructural noise levels are consequently essential for accurately assessing the reliability of the ultrasonic inspections. Existing noise models, like the independent scatterer model (ISM) [1], are capable of predicting only average noise characteristics, such as the root-mean-square (rms) noise level. Average noise levels, although useful, are not sufficient for assessing detection reliability. One needs to know the manner in which noise signals are distributed about ...


Modeling Ultrasonic Microstructural Noise In Titanium Alloys, Frank J. Margetan, R. Bruce Thompson, I. Yalda-Mooshabad Jan 1993

Modeling Ultrasonic Microstructural Noise In Titanium Alloys, Frank J. Margetan, R. Bruce Thompson, I. Yalda-Mooshabad

Review of Progress in Quantitative Nondestructive Evaluation

Ultrasonic echoes from small or subtle defects in metals may be masked by competing “noise” echoes which arise from the scattering of sound by grains or other microstructural elements. Algorithms for estimating the detectability of such defects consequently require quantitative models for microstructural noise. In previous work [1,2] we introduced an approximate noise model for normal-incidence immersion inspections using tone-burst pulses, and we used the model to estimate signal/noise ratios for brittle (hard-alpha) inclusions in titanium alloys. In the present work we consider an extension of that noise model to inspections using broadband incident pulses. Like its predecessor ...


Relationships Between Ultrasonic Noise And Macrostructure Of Titanium Alloys, K. Y. Han, R. Bruce Thompson, Frank J. Margetan, James H. Rose Jan 1993

Relationships Between Ultrasonic Noise And Macrostructure Of Titanium Alloys, K. Y. Han, R. Bruce Thompson, Frank J. Margetan, James H. Rose

Review of Progress in Quantitative Nondestructive Evaluation

The complex microstructure of two-phase titanium alloys can produce considerable ultrasonic backscattering noise. The noise introduces problems in detecting small flaws, such as hard-alpha inclusions, by forming a background which can mask the flaw signals. Therefore better understanding of grain noise is required to quantify and increase the detectability of the small flaws. As an aid to understanding the grain noise, an independent scattering model was constructed and studied during last two years by Margetan and Thompson. In that model for the backscattered noise generated by a tone burst, the grain noise is described by following equation (1) N(t ...


Ultrasonic Inspection, Material Noise And Surface Roughness, Mehmet Bilgen, James H. Rose, Peter B. Nagy Jan 1993

Ultrasonic Inspection, Material Noise And Surface Roughness, Mehmet Bilgen, James H. Rose, Peter B. Nagy

Review of Progress in Quantitative Nondestructive Evaluation

The ultrasonic detection of subsurface flaws, such as cracks or voids, may be greatly degraded by the presence of rough surfaces [1,2]. The loss of signal-to-noise arises for three reasons. First, the randomization of the phase of the wave by the roughness may reduce the phase coherent signal from the flaw. Second, additional noise is generated directly by the reflection of the incident beam by the rough surface. Finally, the material noise is modified.


Theory Of Ultrasonic Backscatter From Multiphase Polycrystalline Solids, James H. Rose Jan 1993

Theory Of Ultrasonic Backscatter From Multiphase Polycrystalline Solids, James H. Rose

Review of Progress in Quantitative Nondestructive Evaluation

Ultrasound scatters from the microscopic single crystals that constitute polycrystalline solids. The scattering originates from crystallite-crystallite variations in the density and elastic constants. For single-phase materials, each crystallite has the same density and the same crystalline symmetry. Hence, in single-phase materials scattering arises from the variation in velocity, which in turn is due to the anisotropy of the elastic constants and the more or less random orientation of the crystallites [1,2]. The situation is considerably more complicated in multiphase alloys where the density, the crystal symmetry and the elastic constants vary from crystallite to crystallite.