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Metal injection molding (MIM) processes are generally more cost-effective for the generation of metallic AM components. However, the thermal processing required to remove the polymer and sinter the metal powder is not well understood in terms of resulting mechanical response and damage evolution, especially in ambient atmospheres where contamination is present. This study aims to provide a range of achievable mechanical properties of copper produced using a MIM-based method called fused filament fabrication (FFF) that is post-processed in a nonideal environment. These results showed direct correlations between sintering temperature to multiple aspects of material behavior. In addition, Nondestructive Evaluation (NDE) methods are leveraged to understand the variation in damage evolution that results from the processing, and it is shown that the higher sintering temperatures provided more desirable tensile properties for strength-based applications. Moreover, these results demonstrate a potential to tailor mechanical properties of FFF manufactured copper for a specific application. [ABSTRACT FROM AUTHOR]

The system presented in this paper enables automatization of the two-dimensional calibration process (determination of Barkhausen noise (BN) intensity dependence on in-plane components of strain). Then, using dedicated software created by the authors in LabVIEW environment, and with the help of two dimensional calibration data one can effectively determine strain and stress distribution i.e. magnitude and orientation of main strain/stress components relative to measurement direction. BN signal measurements are performed using an advanced, multidirectional Barkhausen noise (BN) measuring sensor and a measurement system dedicated for cooperation with it. The system uses a robust algorithm for the strain components determination based on calibration surfaces, instead of usually applied curves, thus taking the influence of normal strain component directly into account instead of treating it as a correction factor (if not completely neglecting). The originality of the system arises also from the fact that this is the first BN measurement system that is self-calibrating (i.e. automatically loads the calibration sample in a pre-programmed way, performs BN signal measurements and calculates calibration planes), provided that the user possesses enough of the investigated material for calibration sample preparation. [ABSTRACT FROM AUTHOR]

Thermal embrittlement is a key concern for the structural integrity of engineering components. Monitoring thermal embrittlement may indicate susceptibility to crack initiation and growth and therefore act as a damage precursor. In this study the correlation between thermoelectric power (also known as the Seebeck Coefficient) and the hardness of thermally aged 2507 super duplex stainless steel was demonstrated, showing the suitability of using thermoelectric power as a proxy measurement for embrittlement. This article presents a continuous high-temperature thermoelectric power monitoring system that is suitable for installation on large engineering assets. Using temperature gradients in the sample of < 6.5 °C a measurement standard deviation of 5.8 nV/°C was possible, which was sufficient to monitor the ~ 850 nV/°C increase in thermoelectric power that occurred in this study. [ABSTRACT FROM AUTHOR]

The lack of real defect data samples has become a challenging problem for the effective application of deep learning networks in ultrasound target detection. This paper proposes a data augmented generative adversarial network (DCSGAN) aimed at overcoming the scarcity of welding ultrasonic defect data in training target detection networks. This network utilizes bilinear interpolation to expand the real data sample space, facilitating the extraction of high-dimensional defect spatial features through deeper networks. By obtaining a mixed dataset of generative data and real data, training and testing experiments are conducted on the object detection network. The experimental results demonstrate that the data augmentation method proposed in this paper effectively enhances the detection rate of ultrasonic welding defects in the target detection network, which has reference significance for similar application scenarios of ultrasonic defect detection. [ABSTRACT FROM AUTHOR]

Conformal coatings are used to protect microelectronic circuitry and increasingly optoelectronics and photonics from detrimental effects of the environment, such as moisture, dust, gasses, and mechanical abrasion. The conventional approach to determine the mean time to failure of conformally coated microelectronic components is usually labor-intensive and time-consuming. We recently showed (Shi et al., 2024) that the quasi-optical approach terahertz (THz) time-of-flight tomography (TOFT) could in principle be used to map conformal-coating thickness over a sample of dimensions on the scale of square centimeters. In this study, we employ THz TOFT to characterize several conformal-coating types on microelectronic test samples in a nondestructive and noncontact manner. This study extends previous work on acrylic conformal coatings. THz TOFT is shown to be effective in the thickness characterization of silicone and acrylic conformal coatings, but not nanometric atomic-layer-deposition metal-oxide coating, which is too thin for the technique. [ABSTRACT FROM AUTHOR]

Resin canals produce and transport oleoresins that are important for tree defenses within the Pinaceae family. Rapid measurement techniques are needed to better understand how resin canal characteristics vary due to genetic and environmental effects. Here we describe a semi-automated microscopy imaging system that was built for quantifying longitudinal resin canals. Tree increment cores from 210 loblolly pine (Pinus taeda L.) trees were prepared into radial strips and the transverse surface of the samples polished with 400 and then 600 grit sandpaper. Each sample was imaged along its entire length (pith to bark) with the images collected from a monochrome camera connected to a Plan Fluorite 4× objective lens. The samples were imaged on the transverse surface via transmitted 850 nm near-infrared light directed at the radial surfaces of the samples. A total of 24 153 images were collected and then processed offline in Python using the Open Computer Vision Library (OpenCV) using a series of algorithms including contrast correction, noise removal, thresholding, contour identification, erosion, and dilation. A total of 24 491 resin canals were identified and their size quantified. The resin canals were assigned into annual rings and positioned within the earlywood or latewood of a ring using cross-correlation whereby a pseudo-density value was derived from the images and matched with density values measured by X-ray densitometry. Of the total resin canals identified, 51.5% were in the earlywood and 48.5% in the latewood, with the majority being detected in the earlywood in the first six years and the latewood in years 7 and above. This study represents the most information collected on the resin canals of loblolly pine. The detailed description of the hardware and image analysis methods should serve as a useful guide to others interested in imaging resin canals as well as other anatomical features. [ABSTRACT FROM AUTHOR]

Rail breakage can cause train derailment that leads to catastrophic consequences, prevention of which is worthy of a significant amount of investment in finance and time. Non-destructive evaluation can provide qualitative and quantitative inspection of rail tracks in-situ to detect dangerous faults, even though these defects are primarily invisible or hardly noticed from the surface of the rail. To make it efficient and convenient, infrared thermography technique offers a remote operation without interfering with rail transportation. The image processing for edge detection can further quantify the defect deterioration by depicting the contour of the defect. Moreover, the optimal parameters for various edge operators provide reliable detection for natural fracture defects. [ABSTRACT FROM AUTHOR]

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Abstract The management of unknown weapons obtained from warfare, military operations, and terrorist situations requires a series of nondestructive testing processes. This management process, which is aimed at collecting information on the nature of the weapons, encompasses identification, processing, transportation, and storage of the obtained weapons. A lack of identification marks in acquired ammunition may indicate the potential presence of a chemical weapon. Therefore, nondestructive evaluation methods have been employed to identify unknown weapons. However, these methods rely on neutron- and radiation-based analyses, which require radiation-handling experts and specific protective facilities. Consequently, their application in this field is challenging. Herein, a nondestructive ultrasonic testing method, which can identify substances inside unknown weapons and optimize the verifiability of the state of the ammunition, was employed as an alternative method to overcome these limitations. The experimental system enabled quantitative and qualitative analyses of the internal chemicals by analyzing the time difference in acquiring the signals, particularly when the results indicate that the internal substance is a liquid. The results of this study can serve as a basis for advancing the application of ultrasonic testing as a viable and efficient approach for managing unknown weapons.

The effects of salt water exposure at deep ocean depth pressures when coupled with low temperatures on the material characteristics of three unique additively manufactured polymers has been investigated through a detailed experimental approach. The polymers in the study were manufactured utilizing both Vat Photopolymerization and Material Extrusion printing techniques. The Material Extrusion process was utilized to produce material specimens of Stratasys ULTEM 9085 and Markforged Onyx while the Vat Photopolymerization process was used to produce specimens of Accura ClearVue. The ULTEM 9085 and Markforged Onyx are filament based polymers and the ClearVue is a liquid based resin. The specimens were first submerged in a high pressure, salt water bath of 3.5% NaCl solution at 34.5 MPa (5000 lb/in2) for a total exposure time of 60 days to determine the water absorption characteristics. Subsequent to the salt water exposure at high pressure, the specimens were evaluated to determine changes in tension, compression, flexure, and in-plane fracture properties. To determine the effects of water saturation and low temperature coupling, the mechanical testing was performed at temperatures of 20 °C, 0 °C and −20 °C in both dry and saturated conditions. Additionally, non-destructive testing in the form of TeraHertz and FIRT imaging was conducted to analyze the physical material changes through the thickness of the material due to the saline water absorption. To quantify the change in material storage and loss moduli properties, Dynamic Mechanical Analysis (DMA) characterization was performed on each of the AM polymers in dry and saturated states. The DMA testing also quantified changes in the Glass Transition Temperature because of salt water exposure. In summary, The current study investigates the effects of coupled long term/high pressure salt water exposure with low temperatures on the mechanical and material characteristics of three unique AM polymers by: (1) immersing the materials in a salt water solution at 34.5 MPa for 60 days, (2) Conducting post exposure mechanical testing on the materials at 0 °C and −20 °C with comparisons to 20 °C testing on dry specimens, and quantifies changes in material properties through DMA experiments. The results from all testing in the study show that high pressure salt water exposure when coupled with low temperatures has unique effects on each of the materials considered in the study and careful consideration to each parameter must be given based on the material type when components will be employed in marine operations.

The management of unknown weapons obtained from warfare, military operations, and terrorist situations requires a series of nondestructive testing processes. This management process, which is aimed at collecting information on the nature of the weapons, encompasses identification, processing, transportation, and storage of the obtained weapons. A lack of identification marks in acquired ammunition may indicate the potential presence of a chemical weapon. Therefore, nondestructive evaluation methods have been employed to identify unknown weapons. However, these methods rely on neutron- and radiation-based analyses, which require radiation-handling experts and specific protective facilities. Consequently, their application in this field is challenging. Herein, a nondestructive ultrasonic testing method, which can identify substances inside unknown weapons and optimize the verifiability of the state of the ammunition, was employed as an alternative method to overcome these limitations. The experimental system enabled quantitative and qualitative analyses of the internal chemicals by analyzing the time difference in acquiring the signals, particularly when the results indicate that the internal substance is a liquid. The results of this study can serve as a basis for advancing the application of ultrasonic testing as a viable and efficient approach for managing unknown weapons. [ABSTRACT FROM AUTHOR]

Some metal structures in the aerospace and nuclear industries are subjected to repeated impact loads that accumulate microcracks until fracture, called impact fatigue damage, which will compromise the metal structure’s overall strength and fatigue life. The microcracks generated by impact fatigue damage on metal materials are so small that, at present, only some microscopic characterization methods have been used to evaluate its damage level, such as scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), energy X-ray dispersive spectroscopy (EDS), and X-ray Photoelectron Spectroscopy (XPS). There is a lack of more convenient and effective non-destructive testing methods. In this paper, the combination of nonlinear acoustic modulation and coda wave interferometry is used to detect impact fatigue damage on 40Cr steel specimens. The simulation discusses the observability of local elastic modulus reduction caused by impact fatigue damage in nonlinear coda wave interferometry (NCWI). Finally, NCWI experiments were carried out on six 40Cr steel specimens with different impact times. Results show that the proposed method can effectively detect and quantify the metal impact fatigue damage. [ABSTRACT FROM AUTHOR]

Composite materials/structures are rapidly advancing, offering improved product efficiency, cost-effectiveness, and superior specific properties. These materials find increasing applications in corrosion resistance and load-carrying structures across industries such as aerospace, wind turbines, transportation, and medical equipment. Therefore, ensuring reliable non-destructive evaluation of composites is crucial to address safety concerns and minimise maintenance expenses. The microwave non-destructive evaluation (NDE) method is particularly well-suited for characterising the material properties of composites. In our study, we utilise a large flange open-ended rectangular waveguide (OERW) probe, measuring 152 mm x 152 mm, to assess the complex reflection coefficient of dielectric materials. This measurement enables the extraction of essential material parameters using a forward electromagnetic model combined with an optimised method. To enhance accuracy, we introduce an iterative conjugate gradient descent (CGD) optimiser with adaptive segmentation. This approach effectively avoids local minima and reduces disparities in integrand values, resulting in precise measurements of material properties. Our proposed method provides estimations of the dielectric constant within a range of 1 to 10 and accurately determines sample thickness with a controlled limit of 3% error across all samples. Furthermore, we observe that as the loss-factor value decreases, the error in calculating the loss-factor of samples increases, which is supported by numerical analysis. [ABSTRACT FROM AUTHOR]

Borehole pulsed eddy-current (PEC) systems based on uniform linear multicoil arrays (ULMAs) perform efficient nondestructive evaluations (NDEs) of metal casings. However, the limited physical space of the borehole restricts the degrees of freedom (DoFs) of ULMAs to be less than the number of constraints, which leads to the difficulty of compensating for the differences in signals acquired by different receivers with different transmitting-to-receiving distances (TRDs), and thus limits the effectiveness of the ULMA system. To solve this problem, this paper proposes sparse linear constraint minimum variance (S-LCMV) for NDEs of downhole casings employing ULMAs. By transforming and characterizing the original PEC signal, it was observed that the signal power dramatically decreased with increasing Legendre polynomial stage, confirming that the signal was sparsely distributed over the Gauss–Legendre stages. Using this property, the S-LCMV cost function with reduced constraints was constructed to provide enough DoFs to accurately calculate the weight coefficients, thus improving the detection performance. The effectiveness of the proposed method was verified through field experiments on an 8-element ULMA installed in a borehole PEC system for NDEs of oil-well casings. The results demonstrate that the proposed method could improve the weighting effect by reducing the number of constraints by 70% while ensuring the approximation accuracy, which effectively improved the signal-to-noise ratio of the measured signals and reduced the computational cost by about 87.9%. [ABSTRACT FROM AUTHOR]

The drilling of composite structure leads to its damage, near the peripheral areas of the drilled hole, due to the laminar structure of the composites. The goodness of a drilling process can be evaluated by measuring the extent of the damage caused by it. In the present study, lock-in thermography non-destructive inspection method is proposed to characterise the drilling damages in glass fiber–reinforced polymer panel. A semi-automated image processing methodology is proposed to calculate damage parameters, namely delamination area and size, and delamination factor. The effect of excitation frequency on the damage characterisation is studied to decide the optimum frequency range to measure the damage parameters through signal-to-noise ratio and damage visibility. The damage parameters are measured at optimum frequency. The study showed that the lock-in thermography technique has the potential to characterise drilling damage. [ABSTRACT FROM AUTHOR]

The effects of salt water exposure at deep ocean depth pressures when coupled with low temperatures on the material characteristics of three unique additively manufactured polymers has been investigated through a detailed experimental approach. The polymers in the study were manufactured utilizing both Vat Photopolymerization and Material Extrusion printing techniques. The Material Extrusion process was utilized to produce material specimens of Stratasys ULTEM 9085 and Markforged Onyx while the Vat Photopolymerization process was used to produce specimens of Accura ClearVue. The ULTEM 9085 and Markforged Onyx are filament based polymers and the ClearVue is a liquid based resin. The specimens were first submerged in a high pressure, salt water bath of 3.5% NaCl solution at 34.5 MPa (5000 lb/in²) for a total exposure time of 60 days to determine the water absorption characteristics. Subsequent to the salt water exposure at high pressure, the specimens were evaluated to determine changes in tension, compression, flexure, and in-plane fracture properties. To determine the effects of water saturation and low temperature coupling, the mechanical testing was performed at temperatures of 20 °C, 0 °C and -20 °C in both dry and saturated conditions. Additionally, non-destructive testing in the form of TeraHertz and FIRT imaging was conducted to analyze the physical material changes through the thickness of the material due to the saline water absorption. To quantify the change in material storage and loss moduli properties, Dynamic Mechanical Analysis (DMA) characterization was performed on each of the AM polymers in dry and saturated states. The DMA testing also quantified changes in the Glass Transition Temperature because of salt water exposure. In summary, The current study investigates the effects of coupled long term/high pressure salt water exposure with low temperatures on the mechanical and material characteristics of three unique AM polymers by: (1) immersing the materials in a salt water solution at 34.5 MPa for 60 days, (2) Conducting post exposure mechanical testing on the materials at 0 °C and -20 °C with comparisons to 20 °C testing on dry specimens, and quantifies changes in material properties through DMA experiments. The results from all testing in the study show that high pressure salt water exposure when coupled with low temperatures has unique effects on each of the materials considered in the study and careful consideration to each parameter must be given based on the material type when components will be employed in marine operations. [ABSTRACT FROM AUTHOR]

This work applies high-frequency rotational Eddy Current Testing (ECT) to characterize various material and manufacturing properties of fiber-filled fused filament fabrication (FFF) components. Using the FFF process, multilayer coupons were produced with varying filament feedstock materials, extrusion multipliers, and raster orientation patterns. With extrusion multiplier being used to adjust interlayer void content, these manufacturing variables were investigated given their significant influence on the mechanical performance of FFF samples. A custom 15 MHz transmit-receive (TR) ECT probe demonstrated sufficient sensitivity to visualize the phenomena of the swept variables. Furthermore, the extraction of simple features from the rotational ECT scans produced clustering and trendlines consistent with observations from X-Ray computed tomography (CT). Thus, this novel approach to nondestructive evaluation (NDE) of fiber filled FFF components is effective for detection and characterization of impactful AM material properties. [ABSTRACT FROM AUTHOR]

A new algorithm is developed to automatically detect rebar locations and diameters of reinforced concrete structures using the ground penetrating radar technique. The study uses two-way travel time and biquadratic equations to formulate electromagnetic wave speed in reinforced concrete structures where hyperbolic signatures are approximated. Leveraging an established algorithm, a computer code has been developed to offer automated analysis of ground-penetrating radar data obtained from survey grids. Four reinforced concrete slabs were designed, fabricated, and tested to validate the developed evaluation approach. The proposed methodology demonstrates outstanding signal processing proficiency and reliably and effectively identifies rebar information. [ABSTRACT FROM AUTHOR]

The aim of this article is to determine a similar point to the Lift-Off intersection point (LOI) obtained from a geometric configuration of a Pulsed Eddy Current (PEC) sensor. This configuration enables easy determination of the LOI point through a single measurement, thus avoiding measurement noise. The sensor consists of an external excitation coil and two internal probes that overlap and have similar characteristics for reception. The similar point LOI is determined by the intersection of the signals from the transient response of the sensor's internal probes. Importantly, this point is independent of lift-off variation. Moreover, the amplitude and time measurement of this point vary with the variation of the physical and geometric properties of the sample. To assess the effectiveness of this similar point, a numerical code based on electromagnetic phenomena was developed. This code investigates the impact of thickness and electrical conductivity of metal sheets on the response of the PEC sensor, both with and without a ferrite core at this point. Additionally, a practical sensor prototype was constructed to validate the results obtained from the numerical model. The obtained results demonstrated a strong correlation between the numerical and experimental outcomes, thus confirming the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

This study conducted a systematic analysis and investigation of near-infrared (NIR) spectroscopy for assessing tomato fruits' quality. This was combined with the integration of multivariate techniques for analysis to improve existing methods for nondestructive quality assessment of tomato fruits. Variations in tomato characteristics were revealed by selecting spectral indices, leading to changes in reflection spectra at different wavelengths. To achieve more accurate predictions, the use of vectors containing various spectral indices became necessary. This study found that predicting key tomato characteristics relies more on the informativeness and predictive ability of vectors derived from spectral indices than on the method used to reduce data volume. Regression models were developed to automate the prediction of six tomato characteristics based on the spectral data. The developed models for vitamin C content, titratable organic acids, and lycopene showed the highest predictive efficiency (over 90%) among the investigated features. These results highlight the potential of regression models to be integrated into automated systems for assessing the quality of tomato fruits, providing sufficiently accurate information to enhance quality control processes. [ABSTRACT FROM AUTHOR]

An automated method for nondestructively characterizing the layer-by-layer raster orientation of additively manufactured components fabricated via the fused filament fabrication (FFF) process is presented, which utilizes full waveform capture of the ultrasonic signal paired with two-dimensional fast Fourier transform analysis. The proposed method extracts internal features of the fabricated component at various depths and then applies the two-dimensional Fourier transformation in the spatial domain to analyze the raster path and extract the orientation. Three material systems are studied: a standard polymer (Poly cyclohexylenedimethylene terephthalate glycol, PCTG), an engineered polymer (high-temperature nylon, HTN) and a carbon fiber-filled polymer (polyethylene terephthalate, PET-CF). Samples were fabricated using an industrial-grade FFF system and scanned using a high-resolution custom immersion ultrasonic platform. Studies were performed using both a 10 MHz and a 15 MHz spherically focused transducer, with the 10 MHz transducer yielding more accurate and more consistent results for the investigated material systems. The analyzed results show that the presented automated method can accurately identify the direction of the raster path with an error within 1°–2° in each of the first 9~10 deposited layers of the investigated PCTG and the PET-CF samples, and the first 14 layers of the HTN samples. This study provides an approach for the automated analysis of the internal features of FFF components using ultrasonic testing, which can further inform the quality control process, in turn increasing reliability and enabling acceptance of AM parts in various industries. [ABSTRACT FROM AUTHOR]

The service life and structural safety of components are affected by the thermal ageing of materials; therefore, a non-destructive evaluation of materials is extremely essential and crucial. In this work, heat-resistant steel Cr12MoV was selected as a specimen, and the embrittlement period of heat-resistant steel Cr12MoV was obtained by accelerated thermal ageing experiments. The effects of service temperature and service time on the mechanical properties of heat-resistant steel were analysed. The non-destructive testing of heat-resistant steel was carried out by using magneto-acoustic compound detection techniques based on electromagnetic acoustic transducers. In the process, magneto-acoustic compound detection signals were decoupled. The electromagnetic characteristic parameters and ultrasonic characteristic parameters of the detection signals were extracted to evaluate the mechanical properties and thermal ageing of heat-resistant steel. The quantitative evaluation ability of thermal ageing brittleness of heat-resistant steel was improved by using the magneto-acoustic compound detection techniques compared with single eddy current detection method or single ultrasonic detection method. [ABSTRACT FROM AUTHOR]

Thermal barrier coatings (TBCs) in gas turbine engines are used in expressly harsh environments; thus, assessing TBC integrity status is critical for safety and reliability. However, traditional periodic maintenance involves visual inspections of the TBCs, requiring the gas turbine to be decommissioned and partially dismantled. Most importantly, tiny defects or internal damages that easily cause coating failure cannot be identified. In this work, a new nondestructive evaluation (NDE) technique of TBCs based on quantum dot (QD) anion exchange is first explored internationally. By exchanging anions between the Cl ions and the CsPbBr3 QDs, the degrees of salt corrosion of the TBCs are evaluated. The resultant NDE technique shows that the colour of the TBCs obviously changes from green to blue, accompanied by a large blueshift (∼ 100 nm) of the photoluminescence (PL) peak position. In addition, the relationship between the PL peak position and coating thermophysical properties indicates that the precision of this NDE technique may easily identify the µm-level of the thermal growth oxide (TGO) changes inside the TBCs. [ABSTRACT FROM AUTHOR]

X-ray computed tomography (XCT) is a widely adopted nondestructive technique for characterizing internal porosity in additive manufactured (AM) components. However, the accuracy and precision of porosity characterization using XCT can be affected by factors, such as XCT system configuration and post-processing methodologies. This study investigates the influence of these variables on porosity characterization by comparing results obtained from four different XCT systems and two distinct analysis workflows applied to a single metallic AM sample. A benchmark is also established for the XCT performance by using a high-resolution reference dataset generated through mechanical polishing serial sectioning (MPSS). Porosity metrics, including volume fraction, pore count, size distribution, and equivalent spherical diameter (ESD), were computed for large pores ( $\ge 84~\mu $ m) within the XCT and MPSS datasets. By comparing these metrics across XCT systems and workflows, this research aims to demonstrate the variability introduced by different XCT configurations and analysis procedures, providing insights into the potential limitations and uncertainty considerations needed while carrying out XCT-based porosity characterization of AM components.

The field of plant phenotype is used to analyze the shape and physiological characteristics of crops in multiple dimensions. Imaging, using non-destructive optical characteristics of plants, analyzes growth characteristics through spectral data. Among these, fluorescence imaging technology is a method of evaluating the physiological characteristics of crops by inducing plant excitation using a specific light source. Through this, we investigate how fluorescence imaging responds sensitively to environmental stress in garlic and can provide important information on future stress management. In this study, near UV LED (405 nm) was used to induce the fluorescence phenomenon of garlic, and fluorescence images were obtained to classify and evaluate crops exposed to abiotic environmental stress. Physiological characteristics related to environmental stress were developed from fluorescence sample images using the Chlorophyll ratio method, and classification performance was evaluated by developing a classification model based on partial least squares discrimination analysis from the image spectrum for stress identification. The environmental stress classification performance identified from the Chlorophyll ratio was 14.9% in F673/F717, 25.6% in F685/F730, and 0.209% in F690/F735. The spectrum-developed PLS-DA showed classification accuracy of 39.6%, 56.2% and 70.7% in Smoothing, MSV, and SNV, respectively. Spectrum pretreatment-based PLS-DA showed higher discrimination performance than the existing image-based Chlorophyll ratio. [ABSTRACT FROM AUTHOR]

EIT was found recently that it can also be applied to dielectrics under a high-frequency AC voltage. However, the EIT evaluation method for dielectrics has not been established sufficiently; in particular, there are no example studies of the drawing of impedance plane diagrams, which is widely used as an evaluation method for eddy current testing (ECT). Therefore, we have attempted to draw an impedance plane diagram based on the Ampère-Maxwell equation and a simple electrical circuit, as performed in ECT. First, a theoretical solution for the impedance based on the Ampère-Maxwell equation that considers eddy and displacement currents was derived, and impedance plane diagrams were then drawn. From the impedance plane diagrams obtained, it was shown that the same trends can be drawn for the diagrams for both conductors and dielectrics. Next, an electrical circuit model for EIT was proposed that takes into account both the conductivity and the permittivity. Using this model, impedance plane diagrams for conductors and dielectrics were drawn, and for dielectrics in particular, it was shown that the diagrams can be drawn by considering the conductivity. In addition, similar to the impedance plane diagrams drawn from the electrical circuit model and derived from the Ampère-Maxwell equation, the change behavior in the diagrams clearly differs between the cases where the conductivity and permittivity change and the case where the lift-off changes. This demonstrates the effectiveness of the electrical circuit model in providing a qualitative understanding of the effects of the dielectric conditions and measurement conditions on EIT. [ABSTRACT FROM AUTHOR]

C/SiC composites are high-temperature structural materials with excellent properties, such as high-temperature resistance and light weight, and are widely used in aerospace fields as advanced materials. Pores are common and unavoidable defects inside composite components, especially affecting mechanical properties and further affecting the safety and life of the components during the service stage. Conventional methods for pore characterization in regular-shaped composites are not suitable for special-shaped C/SiC composite components. To accurately evaluate the effect of pore defects on component properties, in this paper, an effective method is proposed to characterize the spatial distribution state of isolated pores in a special-shaped C/SiC composite component. The isolated pores in the C/SiC composites are identified and localized based on the fractal dimension of local fine characterization of X-ray computed tomography (CT) images using fractal theory. A very strong correlation is found between the fractal dimension of the pore segmentation images and pore characteristics, which is used to identify the connected and isolated pores in C/SiC composites. According to the CT images and fractal dimension statistics analysis results, isolated pores were accurately identified and located. The nondestructive evaluation of isolated pore distribution state inside the studied component was achieved via three-dimensional visual characterization. The minimum volume of the isolated pores identified by the proposed method is 5832 μm3. The results provide a strong basis for further analyzing the effect of pore defect distributions on the mechanical properties of composite components. [ABSTRACT FROM AUTHOR]

This article presents a concept, materials, and methods to devise a Bond Quality Index (BQI) for assessing composite bond quality, approximately correlating to the respective bond strength. Interface bonding is the common mechanism to join two composite structural components. Ensuring the health and quality of the bond line between two load-bearing composite structures is crucial. The article presents the classification and data-driven distinction between two types of bond lines between similar structural components. The interface bonds in composite plates were prepared using polyester peel ply and TX-1040 nylon peel ply. For all the plates, ultrasonic inspection through scanning acoustic microscopy (SAM) (>10 MHz) was performed before and after localized failure of the plate by impinging energy. Energy was impinged 0–10 J/cm2 of in the 16-ply plates, and 0–25 J/cm2 were impinged in 40-ply plates. Followed by bond failure and SAM, a new parameter called the Bond Quality Index (BQI) was formulated using ultrasonic scan data and energy data. The BQI was found to be 0.55 and 0.45, respectively, in plates with polyester peel ply and TX-1040 nylon peel ply bonds. Further, in 40-ply plates with polyester peel ply resulted in a BQI equivalent to 3.49 compared to 0.75 in plates with a TX-1040 nylon peel ply bond. Currently, the BQI is not normalized; however, this study could be used for AI-driven normalized BQIs for all types of bonds in the future. [ABSTRACT FROM AUTHOR]

For CdZnTe crystals containing extended defects – coherent and incoherent twin boundaries, as well as lamellar systems of twins, we measure the propagation patterns of surface acoustic waves (SAW) in the gigahertz range excited by a sharply focused femtosecond laser pulse. Comparison of the calculated SAW radial velocities with experimental data allows us to determine the local crystallographic orientation of crystal regions with defects. We discover strong anisotropic scattering of SAW at twin boundaries and show that the structure of the twin boundary can be determined from the pattern of SAW scattering. Also, we demonstrate the non-reciprocal SAW propagation in lamellar twin systems, as well as quasi-waveguide SAW propagation along the lamellar twin layer. [ABSTRACT FROM AUTHOR]

With the growing interest in metal additive manufacturing using laser powder bed fusion (LPBF), there is a need for advanced in-situ nondestructive evaluation (NDE) methods that can dynamically monitor manufacturing process-related variations, that can be used as a feedback mechanism to further improve the manufacturing process, leading to parts with improved microstructural properties and mechanical properties. Current NDE techniques either lack sensitivity beyond build layer, are costly or time-consuming, or are not compatible for in-situ integration. In this research, we develop an electrical resistance diagnostic for in-situ monitoring of powder fused regions during laser powder bed fusion printing. The technique relies on injecting current into the build plate and detecting voltage differences from conductive variations during printing using a simple, cheap four-point electrode array directly connected to the build plate. A computational model will be utilized to determine sensitivities of the approach, and preliminary experiments will be performed during the printing process to test the overall approach. [ABSTRACT FROM AUTHOR]

Cellular lattice structures possess high strength-to-weight ratios suitable for advanced lightweight engineering applications. However, their quality and mechanical performance can degrade because of defects introduced during manufacturing or in-service. Their complexity and small length scale features make defects difficult to detect using conventional nondestructive evaluation methods. Here we propose a current injection-based method, electrical resistance tomography (ERT), that can be used to detect damaged struts in conductive cellular lattice structures with their intrinsic electromechanical properties. The reconstructed conductivity distributions from ERT can reveal the severity and location of damaged struts without having to probe each strut. However, the low central sensitivity of ERT may result in image artifacts and inaccurate localization of damaged struts. To address this issue, this study introduces an absolute, high throughput, conductivity reconstruction algorithm for 3D ERT. The algorithm incorporates a strut-based normalized sensitivity map to compensate for lower interior sensitivity and suppresses reconstruction artifacts. Numerical simulations and experiments on fabricated representative cellular lattice structures were performed to verify the ability of ERT to quantitatively identify single and multiple damaged struts. The improved performance of this method compared with classical ERT was observed, based on greatly decreased imaging and reconstructed value errors.

This study conducted a systematic analysis and investigation of near-infrared (NIR) spectroscopy for assessing tomato fruits’ quality. This was combined with the integration of multivariate techniques for analysis to improve existing methods for nondestructive quality assessment of tomato fruits. Variations in tomato characteristics were revealed by selecting spectral indices, leading to changes in reflection spectra at different wavelengths. To achieve more accurate predictions, the use of vectors containing various spectral indices became necessary. This study found that predicting key tomato characteristics relies more on the informativeness and predictive ability of vectors derived from spectral indices than on the method used to reduce data volume. Regression models were developed to automate the prediction of six tomato characteristics based on the spectral data. The developed models for vitamin C content, titratable organic acids, and lycopene showed the highest predictive efficiency (over 90%) among the investigated features. These results highlight the potential of regression models to be integrated into automated systems for assessing the quality of tomato fruits, providing sufficiently accurate information to enhance quality control processes.

Borehole pulsed eddy-current (PEC) systems based on uniform linear multicoil arrays (ULMAs) perform efficient nondestructive evaluations (NDEs) of metal casings. However, the limited physical space of the borehole restricts the degrees of freedom (DoFs) of ULMAs to be less than the number of constraints, which leads to the difficulty of compensating for the differences in signals acquired by different receivers with different transmitting-to-receiving distances (TRDs), and thus limits the effectiveness of the ULMA system. To solve this problem, this paper proposes sparse linear constraint minimum variance (S-LCMV) for NDEs of downhole casings employing ULMAs. By transforming and characterizing the original PEC signal, it was observed that the signal power dramatically decreased with increasing Legendre polynomial stage, confirming that the signal was sparsely distributed over the Gauss–Legendre stages. Using this property, the S-LCMV cost function with reduced constraints was constructed to provide enough DoFs to accurately calculate the weight coefficients, thus improving the detection performance. The effectiveness of the proposed method was verified through field experiments on an 8-element ULMA installed in a borehole PEC system for NDEs of oil-well casings. The results demonstrate that the proposed method could improve the weighting effect by reducing the number of constraints by 70% while ensuring the approximation accuracy, which effectively improved the signal-to-noise ratio of the measured signals and reduced the computational cost by about 87.9%.

A new algorithm is developed to automatically detect rebar locations and diameters of reinforced concrete structures using the ground penetrating radar technique. The study uses two-way travel time and biquadratic equations to formulate electromagnetic wave speed in reinforced concrete structures where hyperbolic signatures are approximated. Leveraging an established algorithm, a computer code has been developed to offer automated analysis of ground-penetrating radar data obtained from survey grids. Four reinforced concrete slabs were designed, fabricated, and tested to validate the developed evaluation approach. The proposed methodology demonstrates outstanding signal processing proficiency and reliably and effectively identifies rebar information.

This study aims to inspect grout defects in rock bolts using electromagnetic (EM) waves. The experiments are conducted using one intact rock bolt and eight defective rock bolts with defect ratios (DR) of 10–50%. A two-conductor transmission line is configured using a pair of rock bolts to transmit EM waves. The EM waves are generated and detected using a time-domain reflectometer. Consequently, the velocity of the EM waves increases with increasing DR. Additionally, almost identical velocities are observed at the same DR, regardless of the defect locations. Moreover, the EM wave reflections are observed at these defects. The defect locations are estimated using the velocity and reflection time of the defects. The estimated location is in good agreement with the actual location. This study demonstrates that EM waves can be an effective tool for evaluating grout defects in rock bolts.

We present a methodology to estimate quantitatively the area and depth of horizontal defects that generate heat in non-destructive tests such as burst vibrothermography or inductive thermography, without previous knowledge of the shape of the heat source. The method is based on extracting the temporal evolution of the temperature at the centre of the heated region, together with the thermogram obtained at the end of the excitation. The temperature displayed in this thermogram is averaged in circumferences concentric with the centre of the heated region to obtain an averaged radial profile which is fitted, together with the temporal evolution of the temperature, to a circular heat source model. By fitting synthetic data corresponding to rectangular heat sources with added noise, we analyse the accuracy of the method to retrieve the area and depth of the heat source for different depths and aspect ratios. Experimental results show that the method is able to estimate the area and depth of heat sources with aspect ratios below 1/1.5 with accuracy of about 10%. [ABSTRACT FROM AUTHOR]

The effect of misaligned mechanical stresses on the excitation of ultrasonic vibrations by focused laser radiation near a small-diameter hole in aluminum alloy is investigated. The analysis of the behavior of the signal at various mutual angles and values of two uniaxial stresses is carried out. It is shown that at certain angles under the action of mechanical stresses, not only the contrast of laser ultrasound images changes, but also their rotation as a whole relative to the center of the hole can occur. The possibility of disappearance of the linear component of laser ultrasonic signals at certain characteristics of stress and appearance of a nonlinear component is also demonstrated. [ABSTRACT FROM AUTHOR]

Steel structures are usually coated with anticorrosion coatings. Authors have developed a detection method of coating deterioration by infrared measurement. The mid-wavelength infrared camera captures both the reflection from the coating surface and the emission due to temperature rise of the coating. It is possible that the two components cancel each other out. We proposed a multi-wavelength lock-in infrared data processing that performs lock-in processing using time-series data of only the infrared reflection and emission components at different sensitivity wavelengths as reference signals. This method can separately detect the infrared reflection and emission components and quantitatively evaluate the coating thickness. [ABSTRACT FROM AUTHOR]

This study develops a framework for determining the material parameters of layered engineered wood in a nondestructive manner. The motivation lies in enhancing nondestructive evaluation (NDE) and quality assurance (QA) for engineered wood or mass timber, promising construction materials for sustainable and resilient civil structures. The study employs static compression tests, guided wave measurements, and a genetic algorithm (GA) to solve the inverse problem of determining the mechanical properties of a laminated veneer lumber (LVL) bar. Miniature LVL samples are subjected to compression tests to derive the elastic moduli and Poisson's ratios. Due to the intrinsic heterogeneity, the destructive compression tests yield large coefficients of variances ranging from 2.5 to 73.2%. Dispersion relations are obtained from spatial–temporal sampling of dynamic responses of the LVL bar. The GA pinpoints optimal mechanical properties by updating orthotropic elastic constants of the LVL material, and thereby dispersion curves, in a COMSOL simulation in accordance with experimental dispersion relations. The proposed framework can support estimation accuracy with errors less than 10% for most elastic constants. Focusing on vertical flexural modes, the estimated elastic constants generally resemble reference values from compression tests. This is the first study that evaluates the feasibility of using guided waves and multi-variable optimization to gauge the mechanical traits of LVL and establishes the foundation for further advances in the study of layered engineered wood structures. [ABSTRACT FROM AUTHOR]