Metallic material grain structure characterization using ultrasonic arrays

Abstract

Ultrasound backscattering signals from material microstructures can be used to evaluate the
material microstructure grain size. This typically involves making pulse-echo immersion measurements at multiple locations using a focused ultrasonic transducer in order to obtain an
accurate estimate of the root-mean-square amplitude of the back-scattered signal at a specified
focal position. However, this restricts some practical applications of using such techniques in, for
example, on-line measurements in high-value manufacturing and in-service inspections where
multiple immersion measurements are not feasible to use. The main benefit of using ultrasonic
phased arrays is that one array probe at one position can focus ultrasound beams at multiple
points using different focal laws either physically or in data postprocessing. Potentially this means
that accurate grain size measurements can be obtained from a single array measurement. In this
thesis, the classic backscattering method for conventional transducers is adapted to be used for
full matrix capture datasets from an ultrasonic array. Three-dimensional ultrasonic models are
developed in the proposed inverse process to measure material microstructure grain size. Both
three-dimensional and two-dimensional forward wave scattering models are employed to simulate
full matrix capture data, depending on the complexity and computational efficiency required. In
scenarios where computational resources are limited, three-dimensional models are selectively
replaced with two-dimensional models approximations to enhance efficiency. Statistical analysis
techniques are used to quantify uncertainty and evaluate the robustness of the proposed method.
Experimental validations were conducted on two metallic materials and one industrial casting
specimen: copper (EN1652), bright mild steel (BS970), and Inconel 600 casting (EDF reference
1591-B359-D3). A good agreement is shown between the experimentally measured grain sizes
from array data and metallography measurements. Additionally, a parametric study is presented
to investigate the influence of various factors on the accuracy of grain size estimation, including ultrasound frequency, the number of array elements, and image pixel resolution. Compared to
the classic pulse-echo immersion back-scattering measurements, the proposed method enables
accurate measurement of grain size in a direct contact configuration at fewer locations. This has
potential to make on-line grain size measurements possible.

Date of Award	30 Sept 2025
Original language	English
Awarding Institution	University of Bristol
Supervisor	Paul D Wilcox (Supervisor) & Jie Zhang (Supervisor)