With the rise of additive manufacturing (AM), nondestructive evaluation (NDE) of complex AM parts is becoming essential. This study combines resonant ultrasound spectroscopy (RUS), finite element (FE) simulations, and machine learning to classify ceramic samples with complex geometries. Because variability among nominally identical samples renders traditional RUS analysis ineffective, a random forest (RF) model is trained predominantly on FE simulation data, supplemented by varying amounts of experimental data. Accuracy improves with more experimental training data, but exceeds 70% even when trained with less than 25% of the experimental data. The best results are achieved by selecting a narrow frequency range, guided by simulation results and RF feature importance. This method—training primarily on FE simulations and testing on experimental data—offers a practical way to interpret complex RUS data and could be applied to other data-scarce NDE scenarios.
Bond testing is a relatively less well-known nondestructive testing (NDT) technique. This practical guide provides an overview of existing dedicated bond testing techniques, including pitch-catch, mechanical impedance analysis (MIA), and resonance, and explains how they apply to various material systems, such as honeycomb sandwich panels, composite laminates, and metal-to-metal bonds. The strengths, limitations, and optimal use cases of each technique are presented to help NDT inspectors make informed decisions in real-world applications. By linking material characteristics to inspection physics, this tutorial explains how to select the most effective bond testing approach for reliable defect detection across different composite materials and bonded structures.
Digital twins (DTs) are increasingly seen as a promising tool for bridge management, yet bridge owners hold diverging views on bridge digital twin (BDT) requirements, benefits, and feasibility. The International Association for Bridge Maintenance and Safety (IABMAS) Working Group on Digital Twins conducted an international survey of bridge owners and reviewed current developments in DT and case studies. The survey covered owners’ management needs, DT definitions, input/output expectations, and perceived potential. Owners see promise in DTs but want clearer guidance on minimum requirements, practical benefits, and scalable implementation strategies. Case studies illustrate their strengths in lifecycle decision-making and weaknesses tied to data fragmentation. Coherent data standards, platform interoperability, and integration with existing asset management workflows are essential. This work outlines a roadmap toward a harmonized, owner-centered BDT framework grounded in coherent standards, scalable implementation paths, and cross-sectoral collaboration.
This study presents the newly developed “Antriebsbatterie-Inspektion mittels Röntgen” (AIR) system, a 2D X-ray imaging technology designed for radiation-safe scanning of entire vehicles. Utilizing a 360 kV X-ray source, AIR acquires high-resolution images from a bird’s-eye view, allowing for comprehensive inspection of battery packs, including their modules and cells. The aim of this study is to evaluate the mechanical integrity of various battery types, including prismatic, cylindrical, and pouch cells, by examining the visibility of cell and gap deformations. For this purpose, radiographic X-ray images of electric vehicles (EVs) with their built-in traction batteries are examined manually for the visibility and separability of individual cells and intercell gaps. Complementary measurements on reference cells with defined defects demonstrate that AIR can reveal typical mechanical anomalies such as layer misalignment, local deformations, and swelling based on cell and gap visibility.
To address high system complexity and missed detection of orientation-specific discontinuities in existing eddy current inspection methods for tubes, this paper proposes a magnetic polarity–controlled eddy current testing approach for inspecting the inner surfaces of tubes, focusing on notch-like discontinuities with rectangular cross sections. Two series-connected excitation coils wound in opposite directions generate a radially polarized magnetic field, inducing eddy currents that couple effectively with discontinuities at various orientations for multidirectional detection. The detection principle is explained based on the directional characteristics of the electromagnetic field, validated through finite element simulation, and confirmed experimentally on steel tube specimens with machined rectangular discontinuities. Results demonstrate that the proposed method can effectively detect artificial discontinuities measuring 12 mm × 0.5 mm × 0.5 mm at different orientations while maintaining low system complexity and reduced signal processing difficulty. This work presents a new approach to eddy current detection of multidirectional discontinuities within tubes.
