X-ray computed tomography (CT) is an increasingly versatile tool in non-destructive evaluation (NDE), with applications that have rapidly expanded beyond traditional defect detection to include dimensional measurement and emerging areas such as material characterization. We propose a framework for introducing test objects to the NDE workflow to achieve more robust and quantitative X-ray CT analysis in NDE applications.
Case study is conducted on a challenging imaging scenario with low-attenuating granular material packed in high-attenuating structures. The study focus on the segmentation of materials within the CT volume, aiming to extract information about the packed grains. A mock assembly was designed to replicate real-world packing behaviors, incorporating a range of particle sizes that reflect typical distributions. This setup guides the parameterization of volumetric analyses for complex particle assemblies. We compare the results from X-ray CT with complementary techniques, such as dynamic light scattering, to validate and enhance the characterization results. Additionally, we leverage X-ray CT simulation tool, such as Livermore Tomography Tools (LTT), to extend the test object concept into the digital domain. This digital twin approach enables optimization of imaging techniques, reconstruction parameters, and analysis routines offline.

The increasing demand for 100% inspection in aerospace and defense manufacturing has exposed a critical bottleneck: the speed limitations of conventional industrial Computed Tomography (CT). For complex geometries like turbine blades, traditional methods that rely on heavy physical source filtration to achieve necessary image quality inherently reduce signal strength, forcing a trade-off between scan speed and accuracy. This creates a barrier to effective inline quality control.

This presentation directly addresses this challenge by demonstrating a transformative and immediately applicable solution using photon counting (PC) detectors with kV thresholding. Attendees will first learn the practical downsides of the source filter method, illustrated with clear data showing the significant loss of useful high-energy photons. We will then introduce, by principle of problem-centered comparison, the technique of kV thresholding. This technique electronically removes low-energy noise without attenuating the high-energy signal essential for penetrating dense materials.

Through a detailed case study, we will provide a step-by-step walkthrough of how this technology was used to reduce a complete turbine blade scan from the 10-minute industry standard to an actual 1-minute CT. The session will feature a direct comparative analysis of results from the THOR 10G PC detector versus best-in-class flat panel detectors, providing attendees with tangible evidence and performance benchmarks they can apply to their own equipment evaluations. Participants will leave with actionable insights into optimizing their CT processes, enabling them to evaluate and implement this next-generation technology to drastically increase throughput and achieve true inline metrology.

The advances of computing power and the characteristic of Computer Tomography (CT) scans, provides the NDT industry now with the capabilities to export digital volumes or "digital twins"; including the shape, features and defects of the scanned samples, into Finite Elements Analysis (FEA) simulation models.

Such capabilities allows the product development, damage tolerance analysis and the re-engineering of products to be accelerated thanks to the collaboration between NDT and design departments.

The technical presentation will describe the process and the steps taken to transfer CT scans voxels volumes to FEA analysis using applicable examples and describing successful trials.

High Energy X-ray Computed tomography (HEXCT) is gravitating towards standard nondestructive testing (NDT) for the assessment of large (>1m2), dense (>steel), components and assemblies. However, understanding and optimising configurations, assessing different systems and underwriting production systems requires significant development work. This paper discusses AWE Nuclear Security Technologies activities to support its interests in HEXCT including, Image Quality Indicators (IQI), scintillator and camera development.
The evolution of AWE’s high energy imaging development (incorporating both X-rays and neutrons) required the parallel design, manufacture, metrology and scanning of representative IQI’s. Initial IQI’s were a series of - off axis concentric rotors manufactured from aluminum, bronze and steel. Designed to be interchangeable with specific engineered features embedded in them these IQIs were first imaged on the IMAT and LANCE neutron facilities as well as conventional XCT. Following this, a larger dedicated fast neutron tungsten based IQI was developed and imaged on a dedicated fast neutron facility in Wisconsen. From the learning curves of these IQI, more intricate IQI designs were conceived and manufactured, the latest iteration of which is the ‘Flowerpot’ and ‘Minion’. The design, manufacture and initial result of these will be presented.
Scintillators are essential for conversion of X-rays to visible light. The efficiency of which is closely related to the elemental composition. Typically, lanthanides are of significant interest due to their naturally high X-ray stopping power, however, the development of efficient lanthanide oxide-based scintillators derived from powder form is relatively immature relative to single crystals derived from the melt phase. We give a brief introduction to recent progress in the UK regarding techniques for modelling, powder manufacture and high throughput screening using conventional X-rays for a number of different candidate scintillator formulations.
Finally, we discuss the pros and cons of cameras vs panel for image detection. Recent advances in CMOS chips have had a significant impact on the affordability and efficiency of cameras making them much more attractive as potential alternatives to panel detectors in the field of HEXCT.