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Damage detection in reinforced concrete and self-healing concrete structures using non-destructive testing techniques

Wang, Yu 2020. Damage detection in reinforced concrete and self-healing concrete structures using non-destructive testing techniques. PhD Thesis, Cardiff University.
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Abstract

This thesis mainly contains the investigation of the role of Acoustic Emission (AE) and Acousto-Ultrasonics (AU) as the Non-Destructive Testing (NDT) techniques for concrete structure. Further the techniques applied in this work explored the application and feasibility of AE to monitor and characterise the behaviour of the recently developed self-healing concrete structure. Experimental studies were conducted on a range of specimen in different scale, focusing on the development and application of experimental techniques and data analysis methods for source characterisation, damage detection, location and assessment of AE. The four main topics and findings are as follows: 1. Characterisation of basic failure mode on concrete member Considering the complexity of AE signals of concrete structure, a fundamental study on the source characterisation of two basic failure mode of concrete is conducted using a combined method of parametric analysis and waveform analysis. The maximum amplitude and corresponding characteristic instantaneous frequency are extracted as two indicators of basic failure mode to characterise the complex damage source in concrete. 2. Characterisation of AE source using Moment Tensor Analysis (MTA) A detailed experimental investigation of Moment Tensor Analysis (MTA) is conducted on a concrete cube to elucidate the SiGMA procedure performed by the H-N source. Then the MTA results obtained from a bending testing on a RC beam shows a promising agreement with results obtained via the conventional parameter-based method. Comparison between different methods is discussed and concluded. 3. Laboratory investigations on AE monitoring of self-healing behaviours The applicability of AE techniques to monitor the whole damage and healing process of the vascular-network based self-healing system is evaluated and was found that the Kaiser effect and Felicity ratio could be applied as an indicator to assess the healing efficiency. Principal Component Analysis and unsupervised pattern recognition techniques are adopted to differentiate between concrete fracture signals and other sources. 4. Crack size monitoring and measurement using ultrasonic testing method Experimental studies are conducted using Acousto-Ultrasonics on a range of different size specimen to monitor and measure the crack development. The prospect and potential application of the AU technique investigating impact of healing agent of vascular network-based system were explored.

Item Type: Thesis (PhD)
Date Type: Completion
Status: Unpublished
Schools: Engineering
Uncontrolled Keywords: Acoustic Emission, Damage Detection, Self-healing, Concrete, Reinforced Concrete, Moment Tensor Analysis, Acousto-Ultrasonics _______________________________________
Date of First Compliant Deposit: 24 September 2021
Last Modified: 24 Sep 2021 15:33
URI: http://orca.cardiff.ac.uk/id/eprint/144442

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