Evaluating grain size in polycrystals with rough surfaces by corrected ultrasonic attenuation

Ultrasonic attenuation is commonly used to estimate grain size in polycrystalline materials. However, surface roughness can distort the measurements, leading to inaccuracies. Prior research has shown that rough surfaces affect wave propagation and scattering patterns. It was already known that surface irregularities influence the transmission and reflection of ultrasonic waves. No prior work had resolved how to correct for these effects in grain size evaluation. This gap motivated the development of a correction scheme for ultrasonic attenuation. Existing methods struggle to account for surface roughness in nondestructive testing. That uncertainty drove the need for a more accurate grain size evaluation technique.

The study aimed to address the challenge of ultrasonic grain size evaluation in samples with rough surfaces. The goal was to develop a correction method that accounts for surface roughness effects. The researchers sought to improve the accuracy of grain size measurements in polycrystalline metals. They focused on refining ultrasonic attenuation calculations for nondestructive testing. The motivation came from the limitations of current methods in handling rough surfaces. The study aimed to reduce measurement fluctuations caused by surface irregularities. The researchers wanted to ensure consistent results across varying surface conditions. Their objective was to provide a reliable tool for industrial and scientific applications.

The researchers combined modified transmission and reflection coefficients with a Multi-Gaussian beam model. They used Weaver's diffuse scattering theory to establish an inverse model for attenuation. The transducer model accounted for wave propagation in rough interfaces. Experimental validation involved samples with different surface roughness and microstructures. The method incorporated a correction scheme for the attenuation coefficient. They tested polished and unpolished samples to assess accuracy. The Multi-Gaussian beam model simulated wave behavior at rough surfaces. The inverse model allowed for grain size evaluation from corrected attenuation data.

The corrected method reduced grain size fluctuations to ±1.17μm for samples with varying surface roughness. For polished samples, the relative error compared to optical microscopy was no more than ±3.61%. The inverse model based on Weaver's theory provided consistent grain size estimates. The fluctuation range was significantly lower than uncorrected measurements. The method demonstrated high accuracy across different surface conditions. The results showed improved reliability in ultrasonic grain size evaluation. The correction scheme effectively minimized surface roughness effects. The method proved effective for nondestructive testing in industrial settings.

The study demonstrated that accounting for surface roughness improves ultrasonic grain size evaluation. The correction scheme reduced measurement fluctuations in samples with rough surfaces. The inverse model based on Weaver's theory provided accurate grain size estimates. The method showed high consistency across varying surface conditions. The relative error compared to optical microscopy was within acceptable limits. The results suggest that the correction method enhances the reliability of ultrasonic testing. The presented approach offers a nondestructive tool for industrial applications. The findings support the use of corrected attenuation for grain size evaluation.