Epoxy polymer-based materials are widely used in structural assemblies due to their efficient and robust bonding capabilities. Nondestructive testing tools are needed to assess joint quality, and ideally strength, as contaminants, and some other defects, introduced during the manufacturing process can potentially cause material softening of the epoxy, leading to the degradation of the structural integrity of the bonded components. The application of the nonlinear response with ultrasonic methods used to characterize the epoxy material itself has been underexplored. This study investigates the use of an ultrasonic second-harmonic generation (SHG) method to characterize contaminant-induced material softening in epoxy polymers, with the contaminant being a release agent. The nonlinearity parameter associated with SHG was measured with varying contamination levels. To validate the effectiveness of the SHG method, nonlinear resonant ultrasonic spectroscopy (NRUS) was employed to independently assess the variation in material softening with the increase of contamination levels. Additionally, tensile testing was conducted on contaminated samples to establish a correlation between mechanical strength and the nonlinear parameter related to the degradation due to the material softening. This study demonstrated that the SHG technique is a promising nondestructive evaluation method for detecting contaminant-induced degradation in epoxy materials.

This article reports the findings of a numerical study of mode conversion between fundamental Lamb and Rayleigh waves and vice versa in quarter and half spaces. Fundamental Lamb wave (A0 and S0) propagation in a plate attached to a quarter space and the subsequent mode conversion to a Rayleigh wave was studied using finite element analysis. B-Scans show that a beat-like phenomenon can be observed for the R → L conversion and a generation length can be observed for the L → R conversion. The quarter-space model was also used to study the Rayleigh to Lamb mode conversion. Two hypotheses were developed based on the observed mode conversion efficiencies: (a) the main driving factor of mode conversion between Lamb and Rayleigh waves is the grazing incidence of bulk modes and (b) due to scattering and diffraction, the modes will require a generation length to stabilize in amplitude. Both hypotheses were tested and confirmed using numerical models, including a half-space model to study the diffraction of bulk waves from an incident Lamb wave. The results are of significance for nondestructive evaluation of complex structures where such structural discontinuities exist and it becomes important to understand the fundamental mode conversion phenomenon.

Many ultrasonic non-destructive evaluation measurement models use a composite technique in which processes such as transduction, beam propagation, scattering etc. are described separately using sub-models. The output response in these composite models is then obtained by combining the outputs of sub-models using analytical techniques. The Kirchhoff approximation (KA) has typically been a preferred approach for modeling the scattering of ultrasonic waves from defects because it is less resource-intensive than full-wave scattering (FWS) models. In this paper, we study the validity (accuracy) of the KA in modeling various benchmark measurements. We describe a composite model and apply it to simulate benchmark tests. We obtain two sets of results separately with the KA and the boundary element method (BEM), without changing any of the other sub-models used in the composite model. We compare model predictions with measurement data to study the validity of KA under different test scenarios as well as to identify the use-cases for FWS models such as the BEM.

Excessive quantities of samarium-cobalt (Sm-Co) magnet material are being scrapped needlessly due to a lack of understanding of inhomogeneity distribution and unacceptable internal defects. If there is a way to identify, locate, characterize and when needed separate the defective portions of magnet material, utilization can be increased and product quality improved. Further, the magnets' magnetic and mechanical performance can be improved by reducing the occurrence of internal defects. This paper reports on a cost-effective and efficient nondestructive evaluation method based on an ultrasonic testing (UT) technique applied for detecting and characterizing internal defects in Sm-Co sintered magnets. Applying the UT technique will allow users to comprehensively analyze internal defects, such as inclusions, porosity, microcracks, and other structural irreg-ularities, check for homogeneity and anomalous regions and give the locations of these internal anomalies and defects within the Sm-Co sintered magnets. The UT technique can also be applied to other rare-earth permanent magnets, such as sintered or die-upset neodymium-iron-boron (Nd-Fe-B) magnets. The UT technique can effectively guide quality control and acceptable product selection, in addition to optimizing the magnet alloy design and production processes. Thus, it can facilitate the improvement of magnet manufacturing efficiency and machinability, reduce scrap, prolong service life, increase the use of what would be post-production waste, and enhance product reuse and recycling at end-of-life disposition.

Structural health monitoring (SHM) is the automation of the condition assessment process of an engineered system. When applied to geometrically large components or structures, such as those found in civil and aerospace infrastructure and systems, a critical challenge is in designing the sensing solution that could yield actionable information. This is a difficult task to conduct cost-effectively, because of the large surfaces under consideration and the localized nature of typical defects and damages. There have been significant research efforts in empowering conventional measurement technologies for applications to SHM in order to improve performance of the condition assessment process. Yet, the field implementation of these SHM solutions is still in its infancy, attributable to various economic and technical challenges. The objective of this Roadmap publication is to discuss modern measurement technologies that were developed for SHM purposes, along with their associated challenges and opportunities, and to provide a path to research and development efforts that could yield impactful field applications. The Roadmap is organized into four sections: distributed embedded sensing systems, distributed surface sensing systems, multifunctional materials, and remote sensing. Recognizing that many measurement technologies may overlap between sections, we define distributed sensing solutions as those that involve or imply the utilization of numbers of sensors geometrically organized within (embedded) or over (surface) the monitored component or system. Multi-functional materials are sensing solutions that combine multiple capabilities, for example those also serving structural functions. Remote sensing are solutions that are contactless, for example cell phones, drones, and satellites. It also includes the notion of remotely controlled robots.

Excessive Sm-Co magnet material is being scrapped needlessly due to a lack of understanding of inhomogeneity distribution and unacceptable internal defects. If there is a way to identify, locate, and separate the defective portions of a magnet material, utilization can be increased and quality improved. Further, the magnets’ magnetic and mechanical performance can be improved by reducing the occurrence of internal defects. This paper reports on a cost-effective and efficient nondestructive evaluation method based on an ultrasonic testing (UT) technique applied for detecting and characterizing internal defects in Sm-Co sintered magnets. Applying the UT technique will allow users to comprehensively analyze internal defects, such as inclusions, porosity, microcracks, and other structural irregularities, check for homogeneity and anomalous regions, and give the location of these internal anomalies and defects within the Sm-Co sintered magnets. The UT technique can also be applied to other rare-earth permanent magnets, such as sintered or die-upset Nd-Fe-B magnets. The UT technique can effectively guide quality control and product selection, in addition to optimizing the magnet alloy design and production processes. Thus, it can facilitate the improvement of magnet manufacturing efficiency and machinability, reduce scrap, prolong service life, increase the use of what would be post-production waste, and enhance product reuse and recycling at end-of-life disposition.

Longitudinal critically refracted (LCR) waves have already been widely applied for residual stress characterization. Such waves are usually generated using mode-conversion at the first critical angle of the incident longitudinal wave, which gives waves that then propagate at a dip-angle, and this places energy close to the surface of the specimen. The dip-angle needs to be minimized to improve both velocity measurement and residual stress characterization sensitivity. This paper reports a novel double-fold coil phased EMAT that can decrease the dip-angle. The performance of this new EMAT was investigated using both a COMSOL model and experiments. Initial model validation was provided through a comparison with experimental data. The EMAT design also enables scanning of samples, and operation in harsh environments where use of a PZT based transducer and couplants can complicate and limit inspection. The use of the EMAT has the potential to give more accurate time of flight (TOF) data and enhances the reliability and accuracy for residual stress measurement.

Adhesive joints have been an effective alternative to conventional mechanical fasteners for joining similar and dissimilar materials in the aerospace industry. Adhesive joints have various advantages, including uniform stress distribution, lower weight, and design flexibility, but quality issues and possible defects in these joints have limited wider use. In this study, contaminants mixed into the epoxy-adhesive, which cause cohesive failure, were investigated. In the manufacturing process there can be various contaminants, such as release agents, oils, and moisture. Since release agents are essential materials during the manufacturing process, these were used in this study. A nonlinear ultrasonic technique was employed to evaluate the micro-scale defects in the adhesive due to contaminants. The experiments measured the nonlinearity parameter, with varying the contamination level, at 0, 0.5, 1.0, and 1.5% of the total weight of the epoxy mixture. The nonlinearity parameter exhibited higher sensitivity than the sound velocity, which is a conventional linear ultrasonic parameter, for the differentiation of the contamination levels in the adhesive. Furthermore, differential scanning calorimetry (DSC) and Rockwell hardness testing were conducted to monitor changes in chemical and mechanical properties respectively, with varying degrees of the contamination. It is shown that using the correlation between the nonlinearity parameter and chemical, and mechanical properties of the adhesive, there is the basis for an advanced inspection system, which has potential to improve the detectability of micro-scale defects in adhesively jointed structures.

Due to their superior strength and shock resistance, lattice core sandwich panels (LCSPs) have potential applications in many fields. In this work, acoustic emission (AE) technology was adopted to monitor three-point bending tests of titanium alloy pyramidal LCSPs. Simultaneously, AE signals which were collected during the bending process were post-processed by cluster analysis. The AE signals can be divided into three classes which correspond to three damage modes, specifically face-sheet wrinkling, core member buckling and face-sheet crushing. These results offer guidance for deploying AE technology for structural health monitoring of titanium alloy pyramidal LCSP components during active service.

Adhesive joints have been an effective alternative to conventional mechanical fasteners for joining materials in the aerospace and automotive industries. Although adhesive joints have various advantages, including uniform stress distribution, lower weight, improved corrosion tolerance, and design flexibility, there can be various defects in adhesive joints, which have limited wider application. This paper investigates the effect of a contaminant on the chemical and mechanical properties of the epoxy-adhesive and seeks to determine if a second harmonic generation method can reliably detect and characterize the degree of contamination in the epoxy-adhesive. A contact based ultrasonic through-transmission method was used to measure nonlinearity and then the nonlinearity parameter was calculated using the measured fundamental and second harmonic frequency components in the signals. It was found that there is higher sensitivity to contaminant concentration, up to 1.5%, of the nonlinearity parameter than that for the sound velocity. These data were also found to correlate with changes in the mechanical hardness, which was measured by the Rockwell hardness testing, with different four levels of contamination. Differential scanning calorimetry (DSC) and the thermogravimetric analysis (TGA) were also conducted to assess the effect of the contaminant on thermal properties of the epoxy-adhesive. The DSC and TGA techniques were used to evaluate the curing reaction and the thermal stability of the epoxy-adhesive respectively.

The potential to provide improved performance for advanced composites through the addition of multi-walled carbon nanotubes (MWCNTs) to carbon fiber composites is of interest in several applications. To investigate performance four types of composite specimens with different off-axis angles were subjected to progressive tensile loading. The results show that MWCNTs can improve the bearing capacity of the composite and the off-axis orientation angle can enhance the toughness of the composite. During loading acoustic emission (AE) signals were collected and they were post-processed using cluster analysis based on a Fuzzy C-Means algorithm. The analysis of the AE signals shows that data can be divided into categories which correlate with three damage modes: matrix cracking, fiber debonding and fiber breakage. The AE peak frequency characteristics of each damage mode were identified. Additional characterization was provided by using micro-computed tomography (Micro-CT) during the progressive tensile loading process. The CT images visualize damage location and evolution in the composites and data exhibit good correlations with the AE data for defects predication. The combination of AE and micro-CT technology were shown to effectively characterize damage evolution of the composites, and such data can potentially serve as a reference for the structural health monitoring of these composites when used in structures.

The use of ultrasonic longitudinal critically refracted (LCR) waves is one approach used for near surface material characterization. It has been shown to be sensitive to stress and, in general, less sensitive to the effects of the texture of the material. Although the LCR wave is increasingly widely applied, in experiments the factors that influence the formation of the LCR beam are seldom discussed. This paper reports a new numerical model used to investigate the transducers' parameters that can contribute to the directionality of the LCR wave and hence enable performance optimization when used for industrial applications. An orthogonal experimental method is used to study the sensitivity to the transducer parameters which influence the LCR wave beam characteristics. This method provides a design tool used to study and optimize multiple parameter experiments and it can identify which parameter or parameters are of most significance. The effects of incident angle, the aperture and the center frequency of the transducer were all studied. It is shown that the aperture of the transducer, the center frequency and the incident angle are the most important factors in controlling the directivity of the resulting LCR wave fields. The model was validated by comparision of data to those obtained with a finite element model. Experiments were also performed to confirm the numerical results. The model and experimental data provided improve understanding of the transducer selection and positioning in the optimization of LCR wave fields in experiments, which can be used to give signals which exhibit higher sensitivity for near-surface stress characterization.

Progressive tensile damage for carbon fiber composites both containing and without multi-walled carbon nanotubes (MWCNTs) is discussed and this work is an extension of a previously published study. The composite specimens were subjected to progressive tensile experiments, and AE signals were collected during loading. The signals were post-processed using cluster analysis based on the Fuzzy C-Means algorithm. The results show that AE signals can be divided into three classes, corresponding to three damage modes: matrix cracking, fiber debonding, and fiber breakage. The AE peak frequency characteristics of each damage mode were found. Samples were also characterized using micro-computed tomography (Micro-CT) imaging and the observed damage shows good correlation with AE signal characterization for defect class prediction. Analyzing the data clusters it can be found that MWCNTs can delay and in some cases prevent both matrix cracking and fiber debonding in laminate composites. It was found that matrix cracking, debonding and fiber break AE signals for composites with CNTs correspond to a higher frequency range than that without CNTs. The results give guidance for composite design when considering MWCNTs and structure health monitoring of these composite materials.

Nondestructive evaluation (NDE) is seen as families of mature inspection methodologies which have benefited from major advances in technology, sensor manipulation, and data analysis in the past 20 years, including new types and materials for sensors, and most importantly, leveraging advances in computers for data capture, processing, and modeling. Life management approaches which use such data have also evolved and condition based maintenance (CBM) is now routinely applied to many active components (e.g., pumps, valves, and rotating machines), with in some cases the use of algorithms (prognostics) that estimate remaining useful life (URL). The same period has seen deployment of structural health monitoring (SHM) but, at a slower rate of development, when applied to passive components in high-tech industries including aerospace, wind turbines, and nuclear (e.g., airframe, blades, pressure vessels, and concrete). New approaches to prognostics are now offering emerging opportunities for deployment, bring together more traditional NDE data and that given by SHM, for passive structures, using a common metrics concept, integrated with using technology that utilize new sensors, wireless data transmission, robotic deployments, and advanced data processing, including artificial intelligence (AI). As new approaches to RUL determination, including more big data, become available for prognostic analysis, there are potentially opportunities to operate within the framework of the internet of things (IoT) and what is becoming known as NDE 4.0.

Electronics operating at cryogenic temperatures play a critical role in future science experiments and space exploration programs. The Deep Underground Neutrino Experiment (DUNE) uses a cold electronics system for data taking. Specifically, it utilizes custom-designed Application Specific Integrated Circuits (ASICs). The main challenge is that these circuits will be immersed in liquid Argon and that they need to function for 20+ years without any access. Ensuring quality is critical, and issues may arise due to thermal stress, packaging, and manufacturing-related defects: if undetected, these could lead to long-term reliability and performance problems. This paper reports an investigation into non-destructive evaluation techniques to assess their potential use in a comprehensive quality control process during prototyping, testing, and commissioning of the DUNE cold electronics system. Scanning acoustic microscopy (SAM) was used to investigate permanent structural changes in the ASICs associated with thermal cycling between room and cryogenic temperatures. Data are assessed using a correlation analysis, which can detect even minimal changes happening inside the ASICs.