SEARCH · Search NASA

Results for “nondestructive testing techniques”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

An Eddy Current Case Study using NASA’s Transfer Function and Limited-Sample Probability of Detection Guidebooks

Probability of detection (POD) requirements for NASA fracture-critical human-rated systems can be met by (1) claiming ‘similarity’ to NASA Standard Nondestructive Evaluation (NDE) flaw sizes or (2) by inspector-specific POD demonstration, known as NASA Special NDE. Standard NDE flaw sizes are intended to represent the detection capability of most qualified inspectors, and were primarily based on POD studies in the development of the Space Shuttle Program Orbiter fracture control plan. However, these Standard NDE flaw sizes were based on fatigue cracks in flat panels of one material alloy over a limited range of panel thicknesses. While the POD study was comprehensive, the inspection conditions are relatively narrow. An evaluation of similarity between the Standard NDE POD study and flight component conditions is required to apply Standard NDE to specific flight component inspections. A similarity evaluation may include differences in materials, surface finish, component geometry (e.g., curvature, corners, welds), and inspection access. Similarity is typically based on a qualitative engineering evaluation. Recently, NASA published a quantitative methodology to assess similarity. If similarity is not supported by test and analysis, then the methodology provides a transfer function of flaw size for Special NDE POD demonstration. NASA recommends that Special POD demonstrations use flaws that are flight-like or more difficult to detect than flight component flaws, which are commonly induced fatigue cracks. Often, it is not feasible to induce fatigue cracks in flight component geometry, and therefore, a simpler representative geometry is used, commonly a flat panel, for POD demonstration. Inducing cracks in simple geometry specimens can be time-consuming and expensive, and thus, minimizing the number of flawed specimens is desired. Traditionally, NASA Special NDE demonstration was limited to MIL-HDBK-1823A methods or the binomial point-estimate method (PEM), commonly known as 29/29. Recently, NASA published a limited-sample POD (LS-POD) methodology for signal-response NDE techniques (e.g., eddy current) that provides POD demonstration with fewer specimens than previous approaches. LS-POD suggests a minimum of 10 flawed specimens, compared to 29 in the PEM and the suggested minimum of 40 from MIL-HDBK-1823A. The methodology also includes new guidance on evaluating the probability of false calls. In this presentation, these new transfer function and LS-POD methodologies are described and illustrated through an eddy current detection capability of far-side flaws on thin welded panels. A geometry-based transfer function is developed using electro-discharge machined (EDM) notches in flight component and simple geometry to estimate the Special NDE flaw size that is representative of the critical initial flaw size required by the fracture analysis. Then, fatigue cracks are induced in simple flat panels of the transferred flaw size, and the LS-POD methodology is used for Special NDE demonstration.

P. A. Parker↗

DOE OSTI2015

Monitoring system for the quality assessment in additive manufacturing

Additive Manufacturing (AM) refers to a process by which a set of digital data -representing a certain complex 3dim design - is used to grow the respective 3dim real structure equal to the corresponding design. For the powder-based EOS manufacturing process a variety of plastic and metal materials can be used. Thereby, AM is in many aspects a very powerful tool as it can help to overcome particular limitations in conventional manufacturing. AM enables more freedom of design, complex, hollow and/or lightweight structures as well as product individualisation and functional integration. As such it is a promising approach with respect to the future design and manufacturing of complex 3dim structures. On the other hand, it certainly calls for new methods and standards in view of quality assessment. In particular, when utilizing AM for the design of complex parts used in aviation and aerospace technologies, appropriate monitoring systems are mandatory. In this respect, recently, sustainable progress has been accomplished by joining the common efforts and concerns of a manufacturer Additive Manufacturing systems and respective materials (EOS), along with those of an operator of such systems (MTU Aero Engines) and experienced application engineers (Carl Metrology), using decent know how in the field of optical and infrared methods regarding non-destructive-examination (NDE). The newly developed technology is best described by a high-resolution layer by layer inspection technique, which allows for a 3D tomography-analysis of the complex part at any time during the manufacturing process. Thereby, inspection costs are kept rather low by using smart image-processing methods as well as CMOS sensors instead of infrared detectors. Moreover, results from conventional physical metallurgy may easily be correlated with the predictive results of the monitoring system which not only allows for improvements of the AM monitoring system, but finally leads to an optimisation of the quality and insurance of material security of the complex structure being manufactured. Both, our poster and our oral presentation will explain the data flow between the above mentioned parties involved. A suitable monitoring system for Additive Manufacturing will be introduced, along with a presentation of the respective high resolution data acquisition, as well as the image processing and the data analysis allowing for a precise control of the 3dim growth-process.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R 2 ) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Integrated Nondestructive Assay Systems to Estimate Plutonium in Spent Fuel Assemblies

An integrated nondestructive assay (NDA) system combining active (neutron generator) and passive neutron detection and passive gamma (PG) detection is being analyzed in order to estimate the amount of plutonium, verify initial enrichment, burnup, and cooling time, and detect partial defects in a spent fuel assembly (SFA). Active signals are measured using the differential die-away (DDA), delayed neutron (DN), and delayed gamma (DG) techniques. Passive signals are measured using total neutron (TN) counts and both gross and spectral resolved gamma counts. To quantify how a system of several NDA techniques is expected to perform, all of the relevant NDA techniques listed above were simulated as a function of various reactor conditions such as initial enrichment, burnup, cooling time, assembly shuffling pattern, reactor operating conditions (including temperature, pressure, and the presence of burnable poisons) by simulating the NDA response for five sets of light water reactor assemblies. In this study, we compare the performance of several exploratory model-fitting options (including neural networks, adaptive regression with splines, iterative bias reduction smoothing, projection pursuit regression, and regression with quadratic terms and interaction terms) to relate data simulated with measurement and model error effects from various subsets of the NDA techniques to the total Pu mass. Isotope masses for SFAs and expected detector responses (DRs) for several NDA techniques are simulated using MCNP, and the DRs become inputs to the fitting process. Such responses include eight signals from DDA, one from DN, one from TN, and up to seven from PG; the DG signal will be examined separately. Results are summarized using the root-mean-squared estimation error for plutonium mass in held-out subsets of the data for a range of model and measurement error variances. Different simulation assumptions lead to different spent fuel libraries relating DRs to Pu mass. Some results for training with one library and testing with another library are also given.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRS2006

The Application of Principal Component Analysis Using Fixed Eigenvectors to the Infrared Thermographic Inspection of the Space Shuttle Thermal Protection System

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the good material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued when a fixed set of eigenvectors is used to process the thermal data from the RCC materials. These eigen vectors can be generated either from an analytic model of the thermal response of the material under examination, or from a large cross section of experimental data. This paper will provide the details of the analytic model; an overview of the PCA process; as well as a quantitative signal-to-noise comparison of the results of performing both embodiments of PCA on thermographic data from various RCC specimens. Details of a system that has been developed to allow insitu inspection of a majority of shuttle RCC components will be presented along with the acceptance test results for this system. Additionally, the results of applying this technology to the Space Shuttle Discovery after its return from flight will be presented.

Cramer, K. Elliott↗

NASA NTRS2004

Automated Guided-Wave Scanning Developed to Characterize Materials and Detect Defects

The Nondestructive Evaluation (NDE) Group of the Optical Instrumentation Technology Branch at the NASA Glenn Research Center has developed a scanning system that uses guided waves to characterize materials and detect defects. The technique uses two ultrasonic transducers to interrogate the condition of a material. The sending transducer introduces an ultrasonic pulse at a point on the surface of the specimen, and the receiving transducer detects the signal after it has passed through the material. The aim of the method is to correlate certain parameters in both the time and frequency domains of the detected waveform to characteristics of the material between the two transducers. The scanning system is shown. The waveform parameters of interest include the attenuation due to internal damping, waveform shape parameters, and frequency shifts due to material changes. For the most part, guided waves are used to gauge the damage state and defect growth of materials subjected to various mechanical or environmental loads. The technique has been applied to polymer matrix composites, ceramic matrix composites, and metal matrix composites as well as metallic alloys. Historically, guided wave analysis has been a point-by-point, manual technique with waveforms collected at discrete locations and postprocessed. Data collection and analysis of this type limits the amount of detail that can be obtained. Also, the manual movement of the sensors is prone to user error and is time consuming. The development of an automated guided-wave scanning system has allowed the method to be applied to a wide variety of materials in a consistent, repeatable manner. Experimental studies have been conducted to determine the repeatability of the system as well as compare the results obtained using more traditional NDE methods. The following screen capture shows guided-wave scan results for a ceramic matrix composite plate, including images for each of nine calculated parameters. The system can display up to 18 different wave parameters. Multiple scans of the test specimen demonstrated excellent repeatability in the measurement of all the guided-wave parameters, far exceeding the traditional point-by-point technique. In addition, the scan was able to detect a subsurface defect that was confirmed using flash thermography This technology is being further refined to provide a more robust and efficient software environment. Future hardware upgrades will allow for multiple receiving transducers and the ability to scan more complex surfaces. This work supports composite materials development and testing under the Ultra-Efficient Engine Technology (UEET) Project, but it also will be applied to other material systems under development for a wide range of applications.

Martin, Richard E.↗

DOE OSTI2015

Designing of sparse 2D arrays for Lamb wave imaging using coarray concept

2D ultrasonic arrays have considerable application potential in Lamb wave based SHM systems, since they enable equivocal damage imaging and even in some cases wave-mode selection. Recently, it has been shown that the 2D arrays can be used in SHM applications in a synthetic focusing (SF) mode, which is much more effective than the classical phase array mode commonly used in NDT. The SF mode assumes a single element excitation of subsequent transmitters and off-line processing the acquired data. In the simplest implementation of the technique, only single multiplexed input and output channels are required, which results in significant hardware simplification. Application of the SF mode for 2D arrays creates additional degrees of freedom during the design of the array topology, which complicates the array design process, however, it enables sparse array designs with performance similar to that of the fully populated dense arrays. In this paper we present the coarray concept to facilitate synthesis process of an array’s aperture used in the multistatic synthetic focusing approach in Lamb waves-based imaging systems. In the coherent imaging, performed in the transmit/receive mode, the sum coarray is a morphological convolution of the transmit/receive sub-arrays. It can be calculated as the set of sums of the individual sub-arrays’ elements locations. The coarray framework will be presented here using a an example of a star-shaped array. The approach will be discussed in terms of beampatterns of the resulting imaging systems. Both simulated and experimental results will be included.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Elastic moduli reduction in SiC-SiC tubular specimen after high heat flux neutron irradiation measured by resonant ultrasound spectroscopy

The initial results of a post-irradiation examination study conducted on a SiC-SiC tubular specimen irradiated under a high radial heat flux are presented herein. The elastic properties of the specimen were evaluated before and after the irradiation using the resonant ultrasound spectroscopy (RUS) technique. The composite tubular specimen was considered as an orthotropic elastic with nine elastic constants (Young's moduli, shear moduli and Poisson's ratios—three components of each) for representing its full elastic deformation behavior. All the elastic moduli decreased after irradiation; the reduction was as high as 35% in one of the moduli. The significant decrease in the moduli indicates the presence of microcracks. The results from a computational study show significant stress development in the specimen due to irradiation, primarily caused by differential swelling across the thickness of the specimen. The evaluated stresses exceed the proportional limit stress of the material, indicating the likelihood of matrix microcracking, and thus corroborating the results obtained from RUS. X-ray Computed Tomography (XCT) study confirmed the presence of cracks in the irradiated specimen. These cracks occurred at the inner region of the specimen and propagated in axial and hoop directions. Finally, these XCT results are in agreement with the RUS results and stress distribution results from the computational study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full Waveform Inversion

Concrete is a major construction material worldwide and plays a crucial role in the nuclear industry. The elastic properties of concrete are prone to change and degrade while in service, as it is often subjected to extreme operational and environmental conditions. An accurate evaluation of concrete's elastic properties is thus essential to ensure structural integrity and safety. This is especially true for concrete in nuclear power plants, where irradiation effects significantly impact concrete mechanical properties. There are various methods to assess these properties, with ultrasound-based techniques showing high potential due to their nondestructive nature, cost-effectiveness, and safety. While several nondestructive evaluation methods exist, most rely on idealizations such as assuming homogeneous material and plane wavefronts. In this work, we address these issues by introducing an ultrasound-based nondestructive method aimed at reconstructing spatially varying images of concrete mechanical properties. By accurately modeling wave physics, including scattering and reflection, we overcome several of the aforementioned idealizations and aim to utilize the full waveform for imaging material properties through depth, resulting in more reliable images. Full waveform inversion (FWI) was first introduced by geophysicists to reconstruct subsurface elastic property images. The goal is to minimize the difference between simulated and recorded wavefield signals, often through gradient-based optimization algorithms. While FWI is primarily conducted using the acoustic approximation of the wave equation, few works focus on elastic FWI, where the goal is to reconstruct images of not only the pressure wave speed but also the shear wave speed and density (or their equivalents). This work explores the potential of using elastic FWI to predict concrete mechanical properties as an initial effort for a more accurate monitoring of concrete conditions in service. Reconstructing images of different elastic parameters enables more specificity and accurate condition diagnosis. This paper will detail this approach and provide examples demonstrating the effectiveness of elastic FWI in reconstructing comprehensive maps of concrete mechanical properties.

42 - ENGINEERING↗

NASA NTRS2003

High-Performance Acousto-Ultrasonic Scan System Being Developed

Acousto-ultrasonic (AU) interrogation is a single-sided nondestructive evaluation (NDE) technique employing separated sending and receiving transducers. It is used for assessing the microstructural condition and distributed damage state of the material between the transducers. AU is complementary to more traditional NDE methods, such as ultrasonic cscan, x-ray radiography, and thermographic inspection, which tend to be used primarily for discrete flaw detection. Throughout its history, AU has been used to inspect polymer matrix composites, metal matrix composites, ceramic matrix composites, and even monolithic metallic materials. The development of a high-performance automated AU scan system for characterizing within-sample microstructural and property homogeneity is currently in a prototype stage at NASA. This year, essential AU technology was reviewed. In addition, the basic hardware and software configuration for the scanner was developed, and preliminary results with the system were described. Mechanical and environmental loads applied to composite materials can cause distributed damage (as well as discrete defects) that plays a significant role in the degradation of physical properties. Such damage includes fiber/matrix debonding (interface failure), matrix microcracking, and fiber fracture and buckling. Investigations at the NASA Glenn Research Center have shown that traditional NDE scan inspection methods such as ultrasonic c-scan, x-ray imaging, and thermographic imaging tend to be more suited to discrete defect detection rather than the characterization of accumulated distributed microdamage in composites. Since AU is focused on assessing the distributed microdamage state of the material in between the sending and receiving transducers, it has proven to be quite suitable for assessing the relative composite material state. One major success story at Glenn with AU measurements has been the correlation between the ultrasonic decay rate obtained during AU inspection and the mechanical modulus (stiffness) seen during fatigue experiments with silicon carbide/silicon carbide (SiC/SiC) ceramic matrix composite samples. As shown in the figure, ultrasonic decay increased as the modulus decreased for the ceramic matrix composite tensile fatigue samples. The likely microstructural reason for the decrease in modulus (and increase in ultrasonic decay) is the matrix microcracking that commonly occurs during fatigue testing of these materials. Ultrasonic decay has shown the capability to track the pattern of transverse cracking and fiber breakage in these composites.

Roth, Don J.↗

NASA NTRS2003

High-Performance Acousto-Ultrasonic Scan System Being Developed

Acousto-ultrasonic (AU) interrogation is a single-sided nondestructive evaluation (NDE) technique employing separated sending and receiving transducers. It is used for assessing the microstructural condition and distributed damage state of the material between the transducers. AU is complementary to more traditional NDE methods, such as ultrasonic cscan, x-ray radiography, and thermographic inspection, which tend to be used primarily for discrete flaw detection. Throughout its history, AU has been used to inspect polymer matrix composites, metal matrix composites, ceramic matrix composites, and even monolithic metallic materials. The development of a high-performance automated AU scan system for characterizing within-sample microstructural and property homogeneity is currently in a prototype stage at NASA. This year, essential AU technology was reviewed. In addition, the basic hardware and software configuration for the scanner was developed, and preliminary results with the system were described. Mechanical and environmental loads applied to composite materials can cause distributed damage (as well as discrete defects) that plays a significant role in the degradation of physical properties. Such damage includes fiber/matrix debonding (interface failure), matrix microcracking, and fiber fracture and buckling. Investigations at the NASA Glenn Research Center have shown that traditional NDE scan inspection methods such as ultrasonic c-scan, x-ray imaging, and thermographic imaging tend to be more suited to discrete defect detection rather than the characterization of accumulated distributed micro-damage in composites. Since AU is focused on assessing the distributed micro-damage state of the material in between the sending and receiving transducers, it has proven to be quite suitable for assessing the relative composite material state. One major success story at Glenn with AU measurements has been the correlation between the ultrasonic decay rate obtained during AU inspection and the mechanical modulus (stiffness) seen during fatigue experiments with silicon carbide/silicon carbide (SiC/SiC) ceramic matrix composite samples. As shown in the figure, ultrasonic decay increased as the modulus decreased for the ceramic matrix composite tensile fatigue samples. The likely microstructural reason for the decrease in modulus (and increase in ultrasonic decay) is the matrix microcracking that commonly occurs during fatigue testing of these materials. Ultrasonic decay has shown the capability to track the pattern of transverse cracking and fiber breakage in these composites.

Roth, Don J.↗

DOE OSTI2020

Integrating Predictions for Improving Defect Classification Accuracy in NDT-based Assessment of Concrete - 20229

There is an increasing need to create predictive models for defect classification in concrete using the output of non-destructive testing (NDT) techniques. Recent advancement of machine-learning algorithms has offered several techniques for developing classification models for different types of data sets. However, the performance of these algorithms is very uncertain, mainly when applied to small and noisy datasets. For example, when human access is limited (e.g., nuclear facility), robot-based NDT is preferred. But compared to manual tests with humans present on site, the data sets are small, and more noise can exist. Therefore, it is imperative to develop new approaches to ensure a consistently high classification accuracy for inadequate data sets. This study explores the classification performance on NDT dataset using classifiers from different machine-learning algorithms, namely k-Nearest Neighbor (kNN), Decision Tree, Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The authors further integrated the predictions from these classifiers using proposed methods. The integration strategy combines the output of the classifiers based on two different measures, accuracy, and performance (ACC and PERF), using equations such as sum, average, and square-root-of-sums-of-squares (SRSS). Our results reveal varying classification accuracies across individual classifiers with different misclassifications across the test data set. The integration strategy provided significant improvement in the classification accuracy compared to the individual classifiers. Furthermore, the results indicate minimal variation across the integration methods as compared to the variation across the individual classifiers. To conclude, prediction integration offers a unique approach for combining the output of multiple classifiers to create redundancies with the potential of achieving high classification performance and improved reliability in predictive models for defect detection in concrete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Requalification of historical intermediate level waste (ILW) for the repository KONRAD on basis of non destructive assay (NDA) and re-evaluated nuclide vectors - 15289

The storage facility for ILW of the HDB contains a large number of historical waste products in 200-l drum geometry, which were produced in the 1970's to the 1990's. In the next years more ILW will be treated and stored at HDB, exceeding the storage capacity of the ILW store. All waste products produced at HDB are treated according to the acceptance criteria of the repository KONRAD and are planned to final storage in this repository. In order to qualify the waste materials for final storage in KONRAD and to remove parts of the inventory from the storage chambers this project was started. The main issues of the project, which will be accompanied by the regulator, are product control measures like gas chromatographic analyses of remotely sampled gas syringes and non destructive assay techniques like?-spectrometry and neutron-analytics. The product control is followed by declaration on the basis of re-evaluated nuclide vectors and a repackaging of the drums in licensed containers. The packaging concept includes a 400-l drum as qualified over-pack, because several of the historical drums cannot be qualified as IP-II or type A package. The annual space between the two drums is filled with quartz sand for stability and additional shielding. The drum set is afterwards inserted into a qualified UBA-container provided by GNS. In the case that the product control measures and the reassessment of the declarations result in a violation of the activity limits of the relevant acceptance criteria for KONRAD, the respective drum has to be physically re-qualified after correspondence with the surveillance authorities. This program will be applied to a fraction of approx. 400 canisters, which were selected on the basis of several quality aspects like dose rate below 100 mSv/h, nuclide inventory below 100 A2 according to paragraph 201 of TS-R-1 and well-known waste composition. In the future more waste products will be treated in the same way, if approved containers exist for the inventory. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2001

Computed Tomography Support for Microgravity Materials Science Experiments

The accurate measurement of density in both liquid and solid samples is of considerable interest to Principal Investigators with materials science experiments slated for the ISS. The work to be described is an innovative application of a conventional industrial nondestructive evaluation instrument. Traditional applications of industrial computed tomography (CT) rely on reconstructing cross sections of large structures to provide two-dimensional planar views which can identify defects such as porosity, or other material anomalies. This has been done on microgravity materials science experiments to check the integrity of ampoule-cartridge assemblies for safety purposes. With a substantially monoenergetic flux, as can be obtained with a radioactive cobalt source, there will be a direct correlation between absorption and density. Under such conditions it then becomes possible to make accurate measurements of density throughout a sample, and even when the sample itself is enclosed within a furnace and a safety required cartridge. Such a system has been installed at Kennedy Space Center (KSC) and is available to PIs to examine samples before and after flight. The CT system is being used to provide density information for two purposes. Firstly, the determination of density changes from liquid to solid is vital information to the PI for purposes of modeling the solidification behavior of his sample, and to engineers who have to design containment ampoules and must allow for shrinkage and other volume changes that may occur during processing. While such information can be obtained by pycnometric measurements, the possibility of using a furnace installed on the CT system enables one to examine potentially dangerous materials having high vapor pressures, while not needing visible access to the material. In addition, uniform temperature can readily be obtained, and the system can be controlled to ramp up, hold, and ramp down while collecting data over a wide range of parameters automatically. Results of initial tests on low melting point elements such as gallium, indium and tin will be presented, and the intent is to proceed to compounds such as InSb, HgCdTe and CdTe. Alloys such as Pb-Sb (PI - Poirier, U AZ) and Cu-Al (PI - Trivedi, Ames Lab.), which are the subjects of flight experiments, will also be examined. The second application is the conversion of measured density values directly to composition. This was successfully done with the mercury cadmium telluride alloys grown on the second and fourth United States Microgravity Payload (USMP-2 and USMP-4) missions by Lehoczky. CdTe values along the length of the boules were obtained at KSC prior to cutting the sample, and could have been obtained prior to its removal from the cartridge and ampoule. Examples of the data obtained will be shown. It is anticipated that several of the materials science PIs will avail themselves of the technique described, initially for determining densities prior to flight, and then to acquire early quantitative data on the compositional variation within their samples.

Gillies, Donald C.↗

DOE OSTI2018

Assessing High-energy, Laser-driven, X-ray Sources as a Technique to Analyse ILW Containers - 18242

The principle concern regarding intermediate level waste (ILW) containers is the internal volumetric expansion due to the formation of corrosion products. To tackle this (via non-destructive testing) the development of a new technique to identify problematic containers was initiated by radiographic imaging and neutron assay of small scale, simulated, nuclear waste packages. This was achieved using a high-energy laser pulse to produce a bright burst of high-energy Bremsstrahlung radiation for imaging and a pulse of thermal energy neutrons for isotopic quantification. The small scale, simulated, nuclear waste packages (typically a quarter of a 28 mm natural uranium penny encased in grout) were produced with corrosion from oxygen and hydrogen rich environments to simulate the potential effects of long term storage. These samples were characterised using electron and ion beam techniques prior to encapsulation to establish the extent of corrosion and sample morphology. The small-scale samples were analysed using high-resolution x-ray tomography (XRT). These 3D pictures identified the corrosion state of the material and the effect on the surrounding grout matrix. These data sets were used as a baseline to compare with the 2D images obtained from the high-energy radiography to ascertain the imaging quality and potential capability of a laser driven inspection system. The study established the non-destructive imaging capability of a high-energy laser driven x-ray source for identifying fine features such as corrosion products on uranium samples encased in grout and cracks, and for penetrative imaging through large thicknesses of grout. In addition, generation of laser-driven neutrons of thermal energy required for active interrogation of uranium isotopes is demonstrated experimentally and simulations of the neutron inspection method are presented, thus paving the way for criticality testing of ILW containers. This current study is single pulse exposure acquisition, but the data can be used to predict the potential capability of a diode-pumped laser-driven system operating at, or above, 10 Hz by utilising, for example, the Dipole laser technology recently delivered by the STFC Central Laser Facility. Such a system will enable 3D tomography of nuclear waste containers and also greatly reduced signal to noise ratio via multiple acquisition and image stacking. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full-Waveform Inversion

Concrete is a vital material in construction—especially in the nuclear industry, where it is used in critical structures such as containment vessels. Over time, concrete can degrade due to harsh operational and environmental conditions, necessitating that its elastic properties be accurately evaluated to ensure structural integrity and safety. Traditional nondestructive evaluation methods such as ultrasound-based techniques often rely on simplifying assumptions that may not hold true for concrete. This paper presents an advanced ultrasound-based method that uses elastic full-waveform inversion (EFWI) to create detailed images of concrete’s mechanical properties. By accurately modeling wave behaviors such as scattering and reflection, we aim to overcome the limitations of conventional ultrasonic-based methods. In this work, the imaging problem involved reconstructing the various elastic properties of a heterogenous concrete block with three steel rebars embedded in it. The ultrasonic measurements were synthetically generated from multiple sources and receivers, and the reconstruction process was performed using a gradient-based optimization algorithm. Our approach leveraged EFWI to reconstruct high-resolution images of the pressure wave speed, shear wave speed, and density. Multiple misfit functions—including L2-norm, cross-correlation (CC), and L1-norm—combined with total variation (TV) regularization and parameter constraints using a Sigmoid function—were explored for the reconstruction. The results demonstrated that using the L1-norm misfit function in conjunction with TV regularization and Sigmoid constraints significantly improved the reconstruction quality in comparison to traditional methods. This approach provided clearer images with fewer artifacts and better captured background heterogeneity. Our findings highlight that, when properly designed, EFWI carries great potential for providing comprehensive, more accurate, and more reliable assessments of concrete conditions, as is crucial for the maintenance and safety of nuclear power plant structures.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2016

A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem, we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Investigation of dissimilar metal welds by energy-resolved neutron imaging

A nondestructive study of the internal structure and compositional gradient of dissimilar metal-alloy welds through energy-resolved neutron imaging is described in this paper. The ability of neutrons to penetrate thick metal objects (up to several cm) provides a unique possibility to examine samples which are opaque to other conventional techniques. The presence of Bragg edges in the measured neutron transmission spectra can be used to characterize the internal residual strain within the samples and some microstructural features, e.g. texture within the grains, while neutron resonance absorption provides the possibility to map the degree of uniformity in mixing of the participating alloys and intermetallic formation within the welds. In addition, voids and other defects can be revealed by the variation of neutron attenuation across the samples. This paper demonstrates the potential of neutron energy-resolved imaging to measure all these characteristics simultaneously in a single experiment with sub-mm spatial resolution. Two dissimilar alloy welds are used in this study: Al autogenously laser welded to steel, and Ti gas metal arc welded (GMAW) to stainless steel using Cu as a filler alloy. The cold metal transfer variant of the GMAW process was used in joining the Ti to the stainless steel in order to minimize the heat input. The distributions of the lattice parameter and texture variation in these welds as well as the presence of voids and defects in the melt region are mapped across the welds. The depth of the thermal front in the Al–steel weld is clearly resolved and could be used to optimize the welding process. As a result, a highly textured structure is revealed in the Ti to stainless steel joint where copper was used as a filler wire. The limited diffusion of Ti into the weld region is also verified by the resonance absorption.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗