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Development of non‐destructive methodology for detection of arc strike, spatter and fusion type of welding defects which may form on steam generator (SG) tubes that are in close proximity to the circumferential shell welds. Such defects, especially fusion‐type defects, are detrimental to the structural integrity of the SG. This paper aims to focus on this problem.

This paper presents a new methodology for non‐destructive detection of arc strike, spatter and fusion type of welding defects. This methodology uses remote field eddy current (RFEC) ultrasonic non‐destructive techniques and K‐means clustering.

Distinctly different RFEC signals have been observed for the three types of defects and this information has been effectively utilized for automated identification of weld fusion which produces two back‐wall echoes in ultrasonic A‐scan signals. The methodology can readily distinguish fusion‐type defect from arc strike and spatter type of defects.

The methodology is unique as there is no standard guideline for non‐destructive evaluation of peripheral tubes after shell welding to detect arc strike, spatter and fusion type of welding defects.

Lorentz force evaluation is a non-destructive evaluation method for conducting specimens. The movement of a specimen relative to a permanent magnet leads to Lorentz forces that are perturbed in the presence of a defect. This defect response signal (DRS) is used for defect reconstruction. To solve a linear inverse problem for defect reconstruction, an accurate and fast forward computation method is required. As existing forward methods are either too slow or too inaccurate, the purpose of this paper is to propose the single voxel approach (SVA) as a novel method.

In SVA, the DRS is computed as a superposition of DRSs from single defect voxels, which are calculated in advance, by applying the boundary element source method. This research uses a setup of an isotropic conducting specimen, a spherical permanent magnet and defects of different shapes at different depths. With the help of simulations, this study compares the SVA to the previously proposed approximate forward solution (AFS) and the extended area approach (EAA) using the normalized root mean square error (NRMSE). Simulated data using the finite element method serve as the reference solution.

SVA shows across all simulations NRMSE values <2.5 per cent compared to <8 per cent for EAA and <12 per cent for AFS.

The superposition principle of SVA allows for the application of linear inverse methods for defect reconstruction while providing sufficient accuracy of the forward method.

The quality of components under fused filament fabrication (FFF) is related to the correct filament spacing and bonding of successively deposited layers and is evaluated mainly by scanning electron microscopy (SEM). However, it is a destructive technique and real-time evaluation is not possible. Optical coherence tomography (OCT), on the other hand, is an optical method that acquires cross-sectional images non-invasively and in real-time. Therefore, this paper aims to propose and validate the use of OCT as a non-destructive quality evaluation tool for FFF using Polylactic Acid (PLA) filaments.

PLA three-dimensional (3D) printed samples were made in a variety of nozzle temperatures and mesh spacing. These samples were fractured in liquid nitrogen and inspected using SEM (as a gold standard) to evaluate dimensions and morphology, then the samples were evaluated by OCT in the same area, allowing the results confrontation.

Our results indicate a good correlation between OCT and SEM for the dimensional assessment of layers. When the filament was extruded in lower temperatures, the OCT images presented sharply defined interfaces between layers, in contrary to higher nozzle temperatures, denoting better fusion between them. However, higher extruding temperatures are incurred in greater deviations from nominal dimensions of the mesh. Finally, we demonstrate the advantage of a full 3D tomographic reconstruction to inspect within a FFF sample, which enabled the inspection of “hidden” information, not visible on a single cross-sectional cut.

This paper proposes OCT as a novel and nondestructive evaluation tool for FFF.

Parachutes are equipment that is repeatedly used as and when needed. Some of them are used for as many as 60 jumps. The property of the canopy fabric gets deteriorated with use. It is evaluated by destructive tensile and bursting strength. This study aims to focus on the nondestructive evaluation of the canopy fabric's fitness by testing air permeability and relating it with bursting strength. Predictor equations were developed to determine bursting strength from air permeability values.

ANOVA techniques and statistical regression equations were formed.

A series of samples containing five parachutes fabrics was used seven times, and their air permeability and bursting strength were determined to find the extent to the effect of reuse of parachute fabrics on their bursting strength and air permeability determination. It was found that there was a progressive drop in bursting strength and an increase in air permeability. An investigation of the extent of determination in terms of bursting strength and an increase in air permeability following the sense of five different types of parachute fabrics is reported.

The work focuses on the prediction of bursting strength to textile materials only and may not apply to other materials like membranes and sheets. The process of determining air permeability is relatively simpler and faster.

The bursting strength can be predicted for used parachutes, which are otherwise subjected to destructive testing.

The men using the parachutes can be assured of the superior flawless performance of the parachute as equipment and also contribute to the saving of resources due to nondestructive testing, 100% evaluation of all parachutes is possible.

This article describes the nature of the test procedure and discusses the means of introducing it to users of parachutes. It is accepted that the method must undergo field evaluation and possible modification before it can become a routine tool of parachute using organizations.

The purpose of this paper is to describe the full‐wave modelling of pulsed terahertz systems utilized in non‐destructive testing.

At the outset, some basic information on the terahertz NDT are outlined and then, general remarks on its numerical modelling are presented. Frequency domain FEM and time domain FDTD analysis is carried out. Finally comparison of computed and measured signals is shown in order to prove numerical analysis correctness.

It is possible to model in a relatively simple way a terahertz system for nondestructive evaluation of dielectric materials. In contrast to other published work, the entire measuring setup is modelled, including photoconductive antenna with hemispherical lens, focusing lens and evaluated material with exemplary defect.

This paper gives a description of the terahertz non‐destructive testing system with comparison of simulated and measured results.

In eddy current nondestructive testing, a probe with a ferrite core such as an E-core coil is usually used to detect and locate defects such as cracks and corrosion in conductive material. However, the E-core coil has some disadvantages, such as large volume and difficulty in the process of winding the coils. This paper aims to present a novel T-core probe and its analytical model used for evaluating hidden holes in a multi- layer conductor.

By using a cylindrical coordinate system, the solution domain is truncated in the radial direction. The magnetic vector potential of each region excited by a filamentary coil is derived, and the expansion coefficients of the solutions are obtained by matching the boundary and interface conditions between the regions. By using the truncated region eigenfunction expansion method, the final expression in closed form for the impedance of the multi-turn coil is worked out, and the impedance calculation is performed in Mathematica. For frequencies ranging from 100 Hz to 100 kHz, both the impedance changes of the T-core coil above the multi-layer conductor without a hidden hole and in the absence of the layered conductor were calculated, and the influence of a hidden hole in the multi-layer conducting structure on the impedance change was investigated.

The correctness of the analytical model of the T-core coil was verified by the finite element method and experiments. The proposed T-core coil has higher sensitivity than an air-core coil, and similar sensitivity and smaller size than an E-core coil.

A new T-core coil probe and its accurate theoretical model for defect evaluation of conductor were presented; probe and analytical model can be used in probe design, detection process simulation or can be directly used in defect evaluation of multi-layer conductor.

This paper aims to present a methodology for the detection and categorisation of metal powder particles that are partially attached to additively manufactured lattice structures. It proposes a software algorithm to process micro computed tomography (µCT) image data, thereby providing a systematic and formal basis for the design and certification of powder bed fusion lattice structures, as is required for the certification of medical implants.

This paper details the design and development of a software algorithm for the analysis of µCT image data. The algorithm was designed to allow statistical probability of results based on key independent variables. Three data sets with a single unique parameter were input through the algorithm to allow for characterisation and analysis of like data sets.

This paper demonstrates the application of the proposed algorithm with three data sets, presenting a detailed visual rendering derived from the input image data, with the partially attached particles highlighted. Histograms for various geometric attributes are output, and a continuous trend between the three different data sets is highlighted based on the single unique parameter.

This paper presents a novel methodology for non-destructive algorithmic detection and categorisation of partially attached metal powder particles, of which no formal methods exist. This material is available to download as a part of a provided GitHub repository.

A building deteriorates over time due to aging, wear and tear, and inadequate maintenance. Building diagnosis requires a sound knowledge of engineering, building defects, and detection tools to assess the condition of a building. The physical deterioration of a building reduces its ability to perform its intended function, while environmental deterioration influences the comfort and health of building occupants. This study presents a multi-tiered framework for the inspection of building elements and the environmental conditions of a building.

A three-tiered building inspection framework is proposed in this study, which consists of the following: Tier-I—a preliminary inspection, Tier-II—a detailed inspection, and Tier-III—an expert investigation. Each tier of inspection assesses the severity of building defects using different technologies for different levels of inspection.

Proposed multi-tier inspection framework is tested and implemented on a case study. Results were promising, with organized data management on a common platform for both physical and environmental condition inspection having the potential to save time.

The application program developed for the implementation of structured multi-tiered building inspection provides better documentation and data management for building inspection data that can save time involved in manual data operations in traditional paper-based processes.

This paper aims to present a data-processing methodology combining kernel change detection (KCD) and efficient global optimization algorithms for solving inverse problem in eddy current non-destructive testing. The main purpose is to reduce the computation cost of eddy current data inversion, which is essentially because of the heavy forward modelling with finite element method and the non-linearity of the parameter estimation problem.

The KCD algorithm is adapted and applied to detect damaged parts in an inspected conductive tube using probe impedance signal. The localization step allows in reducing the number of measurement data that will be processed for estimating the flaw characteristics using a global optimization algorithm (efficient global optimization). Actually, the minimized objective function is calculated from data related to defect detection indexes provided by KCD.

Simulation results show the efficiency of the proposed methodology in terms of defect detection and localization; a significant reduction of computing time is obtained in the step of defect characterization.

This study is the first of its kind that combines a change detection method (KCD) with a global optimization algorithm (efficient global optimization) for defect detection and characterization. To show that such approach allows to reduce the numerical cost of ECT data inversion.