Cohort 4

Bond Lau

University: University of Bristol

Supervisors: Prof Anthony Croxford and Dr Alexander Velichko

PhD Project: Quantitative characterisation of metals using multiple scattering of ultrasonic waves

This project revolves around the exploitation of the multiple scattering phenomenon with respect to ultrasonic waves to quantitatively characterise microstructural properties of metallic materials. These include but are not limited to material grain size, shape, and the orientation of anisotropic crystals found in micro-textured regions.
There are several major advantages compared to traditional measurements using a single transducer. Firstly, the approach is based entirely on post-processing of the transmitter-receiver backscattered array data, and does not require any changes in array hardware or specific requirements regarding specimen geometry. Secondly, it is possible to extract data for desired local areas within the material, which implies the possibility of microstructural characterisation of each local material region. Finally, the method can also be used for detection and localisation of weak local material inhomogeneities, which are undetectable using conventional imaging (microtextured regions, creep damage etc.)

Qiming Kong

University: University of Bristol

Supervisors: Prof Bruce Drinkwater and Dr Alexander Velichko

PhD Project: Defect characterization of ultrasound images using image processing technology

With the gradual maturity of ultrasonic imaging technology, the characterization of defects through ultrasonic images has gradually emerged. However, the development of ultrasound image processing has been restricted due to the scattering problem of ultrasound and the lack of good imaging data. The aim of this project is to devise a more automated method for characterizing defects. By improving the existing imaging algorithms to reduce the interference caused by scattering, and designing a sufficient amount of simulated data for image processing and machine learning experiments. And through the above method to design a better ultrasonic image processing algorithm.

Brandon Mills

University: University of Strathclyde

Supervisor: Dr Yashar Javadi

PhD Project: Non-destructive evaluation of residual stress using the collaborative robot

The basis of this project is to non-destructively evaluate the residual stress induced by welding, and then to integrate this method using the collaborative robot to allow for automated and possibly in process testing.

Atul Sharma

University: University of Bristol 

Supervisors: Dr Robert Hughes (Bristol) and Prof Anthony Peyton (Manchester) Sponsor: Ether NDE

EngD Project: Eddy-Current inspection of complex geometries in carbon fibre composites

Carbon fibre composites are used in many engineering industries, including aerospace, automotive, and the energy sector. Non-contact inductive (eddy-current) sensors have been shown to detect damage and manufacturing flaws in carbon fibre structures, however, the complex electromagnetic interaction with these multi-layered anisotropic fibrous structures is poorly understood, preventing accurate characterisation of critical mechanical properties such as fibre volume fraction. This research aims to develop finite element COMSOL models based on detailed multi-scale experimental characterisation (employing, micro-CT imaging and conductivity coupon testing) of the statistical variation in electro-structural properties of carbon fibre composite materials to more accurately model the eddy-current measurement of composite structures. The results of the study will be used to aid in the inversion of critical material and structural properties of industrial components, as well as to optimise probe designs and establish a database of highly-characterised material properties to assist in training future machine-learning inversion algorithms.

James An 

University: University of Bristol

Supervisors: Dr Jie Zhang, Dr Alexander Velichko and Dr Nicolas Larrosa

PhD Project: Defect characterisation using ultrasonic arrays

Over the last decades, there has been a rapid increase of using ultrasound arrays to detect and characterize defects. Particularly, post-processing imaging algorithms such as Total Focusing Method (TFM) can be used on a full set of captured matrix data (FMC) to perform high-resolution imaging. However, due to the diffraction of waves, the imaging resolution of ultrasound array is limited to around a wavelength of the ultrasound in use, and this leaves high uncertainty to small defect characterization from its ultrasound image. The scattering behavior from small defects can be extracted (scattering matrix) and used to characterise it. However, the accuracy of characterising procedure is affected by surrounding noise and defect surface condition such as roughness and asperities. This limits the real application of defect characterization using ultrasonic arrays in practice (within 0.1 wavelength accuracy). This project will look to develop a method to characterise defects more accurately by suppressing the effect from surrounding noise and defect surface condition.

Will Punter

University: Bristol

Supervisors: Dr Rob Hughes and Prof Bruce Drinkwater

PhD Project: ​Automated analysis approaches for structural health monitoring on aerospace primary structure with ultrasonic and electromagnetic sensor arrays​ 

The aim of the project is to develop permanently installed sensors for monitoring structural hotspots, exploring approaches based on ultrasonic and eddy current arrays. The hotspot of interest are defects initiating from bolt-holes in multi-layered aircraft wing skins. The objective is to detect these defects as early as possible in the defects-growth cycle. A particular aspect of interest is how data fusion is performed between the two sensing modalities to enhance detection and characterisation of damage. 

Currently, research is being carried out to evaluate the suitability of a variety of sensing methodologies, using finite-element analysis and experimentation to establish which techniques to carry forward in the data fusion and analysis stage.

Rylan Gomes

University: Strathclyde

Sponsor: Spirit Aerosystems

Supervisor: Dr Ehsan Mohseni and Prof Gareth Pierce

PhD Project: Non-Destructive Evaluation of Aerospace Composites at the Manufacturing Stage

Peng Jin

University: Nottingham

Supervisors: Prof Richard Smith and Prof Matt Clark

PhD Project: Smart metallurgy

Zhenshan Wang

University: Bristol

Supervisors: Dr Alexander Velichko and Dr Jie Zhang

PhD Project: Super-resolution 3D ultrasound tomography for material microstructure characterisation

This project introduces a cutting-edge super-resolution 3D ultrasound tomography method for in-depth material microstructure characterization. Conventional non-destructive material analysis methods often struggle to provide comprehensive volumetric data, particularly for large samples. This project addresses this challenge by leveraging advanced ultrasonic techniques.

Analyzing local scattering patterns from ultrasonic measurements, this project’s proposed method offers unprecedented insights into material microstructures. This breakthrough has profound implications for understanding material behavior. By precisely characterizing material microstructures, this project promises to enhance the reliability and efficiency of safety-critical components in various industries.

The project entails implementing a sophisticated measurement setup with robotic arm scanning systems to capture ultrasonic data from various incident and scattered angles. Advanced signal processing tools developed in this project will extract local scattering patterns, enabling precise quantitative characterization of microstructural parameters. Through rigorous validation and analysis, this research aims to unveil the strengths and limitations of the developed technique, ultimately advancing material science and non-destructive evaluation.

Amine Hifi

University: Strathclyde

Supervisor: Prof Gareth Pierce and Prof Charles MacLeod

PhD Project: Collaborative mobile robotics for high-value manufacturing

Keiran Agnew

University: Strathclyde

Supervisor: Prof Gareth Pierce and Prof Charles MacLeod

PhD Project: Robotic enabled sensing/welding

Yuankai Ren

University: Imperial

Supervisors: Dr Bo Lan and Dr Fred Cegla

PhD Project: Ultrasonic evaluation of Li-ion batteries

Matthew Shields

University: Strathclyde

Supervisors: Prof Gareth Pierce and Dr Randika Vithanage

PhD Project: Collaborative and hybrid robotic techniques for NDT measurements

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