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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Photovoltaic Cable Connectors: A Comparative Assessment of the Present State of the Industry

The consequences of failure for balance-of-systems components (such as photovoltaic (PV) cable connectors) include offline module string(s); low system voltage; arc, ground, insulation, and overtemperature faults; triggered fuse(s); system shutdown; and fire. The degradation modes for connectors are studied here through an industry survey and its subsequent examination, which are compared with field-degraded specimens. A total of 117 specimens were obtained from a variety of locations and climates or accelerated tests. A failure analysis for connectors from PV installations was developed (and applied to 54 specimens), including nondestructive examinations (photography, a custom resistance-current scan, and X-ray computed tomography) and destructive examinations (featuring milling of the external plastic, extraction of the internal convolute spring, and potting and polishing in cross section). Surface and through-thickness composition of the metal pins and springs was quantified using scanning electron microscopy with energy-dispersive X-ray spectroscopy. Fourier transform infrared spectroscopy was used to verify the base polymer materials and compare the chemical structure of the connector body, bushing, end nut, and o-ring. Thermogravimetric analysis and differential scanning calorimetry were used to further verify the degradation of the same polymeric components.

cable connectors↗
DOE OSTI2024

Photovoltaic Cable Connectors: A Comparative Assessment of the Present State of the Industry [Slides]

The consequences of failure for balance of systems (BoS) components (such as PV cable connectors) include offline module string(s); low system voltage; arc, ground, insulation, and over-temperature faults; triggered fuse(s); system shutdown; and fire. The degradation modes for connectors are studied here through an industry survey and its subsequent examination, which are compared to field-degraded specimens. 117 specimens were obtained from a variety of locations and climates or accelerated tests. A failure analysis for connectors from PV installations was developed (and applied to 54 specimens) including nondestructive examinations (photography, a custom resistance-current scan, and X-ray computed tomography) and destructive examinations (featuring milling of the external plastic, extraction of the internal convolute spring, and potting and polishing in cross-section). Surface and through-thickness composition of the metal pins and springs was quantified using scanning electron microscopy with energy-dispersive X-ray spectroscopy. Fourier-transform infrared spectroscopy was used to verify the base polymer materials and compare the chemical structure of the connector body, bushing, end nut, and o-ring. Thermogravimetric analysis and differential scanning calorimetry were used to further verify the degradation of the same polymeric components. Updated from 2023 NIST/UL Workshop on Photovoltaic Materials Durability (website: https://events.ul.com/WPMogn?rt=aAuoWsl4E0KaORLCMeOgfA) and 2024 PVRW workshop (https://pvrw.nrel.gov/past-proceedings).

14 SOLAR ENERGY↗
DOE OSTI2025

Evaluation and Development of Phase Array Ultrasonic Testing (PAUT) System for Additively Manufactured Parts

This research focuses on the application of advanced ultrasonic testing techniques developed by The Phased Array Company (TPAC) for inspecting defects in additive manufacturing (AM) parts. Traditionally, X-ray computed tomography is the standard for inspecting AM components. Although, the long inspection and analysis time, along with relatively high cost make implementation difficult. Thus, an alternative nondestructive evaluation (NDE) approach is necessary to support quality assurance efforts within the field of AM. TPAC is recognized as a leader in ultrasonic testing innovation, deploying sophisticated algorithms such as Total Focusing Method (TFM) and Phased Wave Imaging (PWI) for ultrasonic data processing and interpretation. This work will explore how the TFM and PWI algorithms can assist defect detection within polymer AM parts. The AM field is seeking novel NDE methods to provide support within quality control and assurance efforts. Advanced ultrasonics inspection have the potential to fulfill this need.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Evaluation and Development of Phase Array Ultrasonic Testing (PAUT) System for Additively Manufactured Parts

This research focuses on the application of advanced ultrasonic testing techniques developed by The Phased Array Company (TPAC) for inspecting defects in additive manufacturing (AM) parts. Traditionally, X-ray computed tomography is the standard for inspecting AM components. Although, the long inspection and analysis time, along with relatively high cost make implementation difficult. Thus, an alternative nondestructive evaluation (NDE) approach is necessary to support quality assurance efforts within the field of AM. TPAC is recognized as a leader in ultrasonic testing innovation, deploying sophisticated algorithms such as Total Focusing Method (TFM) and Phased Wave Imaging (PWI) for ultrasonic data processing and interpretation. This work will explore how the TFM and PWI algorithms can assist defect detection within polymer AM parts. The AM field is seeking novel NDE methods to provide support within quality control and assurance efforts. Advanced ultrasonics inspection have the potential to fulfill this need.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Radiative transition probabilities of neutral and singly ionized Europium estimated by laser-induced breakdown spectroscopy (LIBS)

Laser-induced breakdown spectroscopy (LIBS) is a versatile technique for compositional analysis for solids, liquids, or gasses. LIBS is an asset for the quantitative or qualitative analysis of resource limited materials like actinides and rare earths because it is quasi-nondestructive. Two Eu 2 O 3 pellets were synthesized to be a test and validation set, respectively. Spectral lines identified from the National Institute of Standards and Technology database with fundamental data reported were used to form Saha-Boltzmann plots. The Saha-Boltzmann plots were used to determine the plasma temperatures and electron densities of the laser-induced plasmas for both samples. These Saha-Boltzmann plots were then used to calculate previously unreported transition probabilities associated with identified peaks. Additionally, the transition probabilities presented in this paper provide the capability for calibration free LIBS to be performed more readily on europium samples and the spectroscopic analysis of stellar bodies. Eight previously unreported transition probabilities are presented in this paper; five for Eu I and three for Eu II. The transition probabilities for Eu I ranged from 0.172 to 7.38 × 10 7 s -1 and those for Eu II ranged from 1.56 to 6.75 × 10 7 s -1 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Neutron Total Scattering Analysis of Materials for the Nuclear Fuel Cycle

Here, this paper reviews recent experimental efforts at the University of Tennessee and Oak Ridge National Laboratory to comprehensively characterize the structural details of materials relevant for the nuclear fuel cycle by employing advanced neutron scattering techniques. For the study of nuclear ceramics, neutron scattering offers distinct advantages over traditional laboratory or synchrotron X-ray diffraction, including enhanced sensitivity to elements with a low atomic mass, such as oxygen, nitrogen, and carbon. The key to these efforts is the recent advancement in the neutron scattering infrastructure at the high-flux diffractometers at the Spallation Neutron Source. The high neutron flux at these instruments enables neutron total scattering, a nondestructive bulk technique that simultaneously captures both short-range structural effects through pair distribution function analysis and long-range order through diffraction pattern analysis. This approach is particularly important for a comprehensive description of defective, disordered, or amorphous nuclear materials. The case studies presented here include analyses of the local defect structure in hyperstoichiometric uranium oxides and short-range order of ion-irradiated ceramics. This advanced analytical methodology will improve our understanding of the behavior of materials in extreme environments and contribute to the development of more resilient nuclear materials.

Neutron scattering↗
DOE OSTI2025

Formation of Composite SiC/SiC Joints by Embedded Wire Chemical Vapor Deposition

The joining of ceramic monoliths or composites to date has primarily been limited to the formation of brittle monolithic joints using heterogeneous (dissimilar) materials, similar to brazing in metals. The development of a damage-tolerant joint layer by SiC fiber reinforcements is demonstrated here. Tube workpieces made of SiC fiber-SiC matrix composite are joined using a nonwoven SiC fiber mat densified by embedded wire chemical vapor deposition (EWCVD), creating a fiber-reinforced weld-like joint by homogeneous joining. EWCVD uses a localized heating method to target deposition and growth to the joint region specifically, while minimizing thermal damage to the surrounding composite tube material. X-ray computed tomography (XCT) is used to nondestructively characterize as-made joints for relative density, adhesion, and composition. In situ XCT analysis during mechanical testing revealed crack deflections in the bonding layer, which indicates a toughening mechanism typical of ceramic matrix composite phase. Gas permeation testing of these proof-of-concept composite joints identified relatively high leak rates in comparison to fully coated SiC/SiC composite tube workpieces. In conclusion, the novelty of the composite joining method and current technology challenges, including gas permeability, are discussed in comparison with traditional ceramic joints and materials.

SiC↗
DOE OSTI2022

Characterization of nonlinear ultrasonic waves behavior while interacting with poor interlayer bonds in large-scale additive manufactured materials

Over the past decades, researchers have developed several nonlinear ultrasonic techniques for quality control of materials commonly used in different applications. Owing to the superior sensitivity of nonlinear ultrasound waves to small defects such as micro-cracks, their applicability in different nondestructive testing (NDT) problems has been investigated in numerous studies. These studies utilize frequency domain analysis to detect the generation of higher harmonics because of the formation of defects in the inspected medium. Frequency domain analysis based on the Fourier transform is a significant approach used in linear systems; however, it may not perform adequately on nonlinear systems. Hence, studies on nonlinear dynamics and physics consider analyzing systems' behavior in the phase-space domain. In contrast to the frequency domain analysis, which can result in information loss, analysis in the phase-space domain retains all the information regarding a system's states. Here, we investigate the nonlinearities induced by poor interlayer bonding in polymer-based additive manufactured parts in the phase-space domain. It is convenient to characterize the nonlinearity in the phase-space domain because it provides a geometrical representation of a system's states. Two types of low quality interlayer bond are considered. The first type is simulated artificially while the second type is manufactured by reducing the bond quality during the printing process. The analysis verified that the received ultrasonic signals exhibit classical nonlinear behavior in the phase-space domain while interacting with simulated poor interlayer bonds. In addition, the results showed that the behavior of ultrasonic waves is amplitude-dependent and evolves into models that have not been previously reported. Furthermore, Largest Lyapunov Exponent (LLE) is used to quantify the behavior of nonlinear ultrasonic waves while interacting with poor interlayer bonds. Using LLE, it was observed that the divergence rate of the phase-space trajectories depends on the amplitude of the excitation. This observation quantitatively proves that nonlinear behavior of ultrasound while interacting with poor interlayer bonds can be amplitude-dependent. The results of both simulated and inherent poor interlayer bond cases showed that LLE can be used as a reliable quantitative damage-sensitive feature to detect and potentially characterize weak bonds, which are difficult to detect using conventional approaches. Additionally, the reported results in the phase-space domain provide a basis for proposing a new mathematical model for ultrasonic waves interacting with poor interlayer bonds.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Soft X-ray reflection ptychography

Scanning transmission X-ray microscopy and ptychography have become mature tools for high-resolution, element-specific imaging of nanoscale structures. However, transmission geometries impose stringent constraints on sample thickness and preparation, thereby limiting investigations of extended or bulk specimens, especially in the soft X-ray region. Here, we demonstrate reflection-geometry soft X-ray ptychography as a robust imaging mode. Instrumental feasibility and spatial resolution are established using a lithographically defined Siemens star and barcode test pattern on a multilayer substrate. We empirically demonstrate a full-pitch spatial resolution of ca. 45 nm from Fourier ring correlation analysis of the reconstructed object. The results highlight the potential of the reflection geometry for nondestructive X-ray studies of materials without the need for transmissive samples.

Guenzing, Damian [Lawrence Berkeley National Labor↗
DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of metallic contaminants on the electrochemical and thermal behavior of Li-ion electrodes

Emerging nondestructive (direct) recycling techniques for lithium-ion batteries may introduce metallic impurities into recycled electrodes. In the present work, the impact of such nonionic contaminants on the practical performance of both anode and cathode materials is evaluated using a synergistic combination of electrochemical and thermal analysis. The impurities under study have been selected through evaluation of industrially shredded batteries, and include Fe0, Al0, Mg0, Cu0, and Si0. The electrochemical behavior of materials containing each individual contaminant at either the anode or the cathode is evaluated in both half-cell and full-cell format. Further, the first-cycle thermal signatures of full cells are used to validate and complement electrochemical signatures, and the two techniques are used in conjunction to suggest distinct mechanisms of electrochemical reactivity for the various impurities. At the anode, metallic contaminants are found to disrupt performance through direct reaction with Li and may serve as weak catalysts to accelerate electrolyte degradation. At the cathode, metallic contaminants show evidence of crossover during formation cycling to disrupt SEI formation. We suggest that coupled electrochemical and thermal analysis may be used to both identify the presence of contaminants and to elucidate specific mechanisms of reactivity for metallic impurities under anodic and cathodic conditions.

Contaminant↗
DOE OSTI2022

Homomorphic Encryption for Machine Learning and Artificial Intelligence Applications

Third-party and expert analysis is a cost-effective solution for solving specialized problems or processing large datasets related to reactor structural health monitoring and nondestructive evaluation. However, when handling proprietary information, third-party and expert analysts pose a privacy risk. To address this challenge, Homomorphic Encryption (HE) permits arithmetic operations on encrypted data without exposing the underlying data. Implementations of Machine Learning (ML) and Artificial Intelligence (AI) algorithms using HE greatly enhances the capabilities of third-party analysts while maintaining a low security risk. This paper details current success in applying Principal Component Analysis (PCA) and Fully Connected Neural Networks (NN) using the Microsoft SEAL implementation of the popular CKKS Fully Homomorphic Encryption (FHE) algorithm. The MNIST Handwritten Dataset is analyzed as a proof-of-concept demonstration of the implementations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

3D Reconstruction of a High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning with High-Precision EBSD and Surface Profilometry

High-energy diffraction microscopy (HEDM) combined with in situ mechanical testing is a powerful nondestructive technique for tracking the evolving microstructure within polycrystalline materials during deformation. This technique relies on a sophisticated analysis of X-ray diffraction patterns to produce a three-dimensional reconstruction of grains and other microstructural features within the interrogated volume. However, it is known that HEDM can fail to identify certain microstructural features, particularly smaller grains or twinned regions. Characterization of the identical sample volume using high-resolution surface-specific techniques, particularly electron backscatter diffraction (EBSD), can not only provide additional microstructure information about the interrogated volume but also highlight opportunities for improvement of the HEDM reconstruction algorithms. In this study, a sample fabricated from undeformed “low solvus, high refractory” nickel-based superalloy was scanned using HEDM. The volume interrogated by HEDM was then carefully characterized using a combination of surface-specific techniques, including epi-illumination optical microscopy, zero-tilt secondary and backscattered electron imaging, scanning white light interferometry, and high-precision EBSD. Custom data fusion protocols were developed to integrate and align the microstructure maps captured by these surface-specific techniques and HEDM. The raw and processed data from HEDM and serial sectioning have been made available via the Materials Data Facility (MDF) at https://doi.org/10.18126/4y0p-v604 for further investigation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Monitoring accelerated alkali-silica reaction in concrete prisms with petrography and electrical conductivity measurements

We report deterioration of concrete due to alkali-silica reaction (ASR) involves a reaction between alkaline ions in the cement pore solution and non-crystalline silica found in many aggregates. Diagnosing and quantifying deterioration due to ASR in concrete currently requires destructive testing for microscopy examinations. In this paper, electrical conductivity is investigated qualitatively as an alternative non-destructive evaluation (NDE) method of ASR in hardened concrete. The study was performed using an unrestrained set of small concrete prism specimens made with highly reactive small aggregates, and kept in an environmental chamber according to ASTM C1293 standard. In a companion study, destructive petrography and damage rating index (DRI) assessment, and pore solution extraction and analysis were performed on the same set of accelerated ASR specimens. The results show that temporal evolution of nondestructive bulk resistivity is linearly correlated with destructive DRI score.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Coordinated neutron and X-ray computed tomography of meteorites: Detection and distribution of hydrogen-bearing materials

The presence and distribution of hydrogen-bearing materials in meteorites are important constraints on processes in the early solar system, and the delivery of volatile constituents to growing planets. Here, in this paper, we show that coordinated neutron and X-ray computed tomography, NXCT, can reveal the presence and distributions of hydrogen-bearing materials in meteorites, and thus help constrain the presence and actions of water in the early solar system. NXCT is nearly nondestructive of meteorite samples. Neutron fluence in NXCT is approximately seven orders of magnitude less than in typical instrumental neutron activation analysis, and so produces little residual radioactivity and currently undetectable changes in isotope ratios. Heating during NXCT is minimal, but NXCT will overprint the record of cosmic ray exposure held in natural thermoluminescence. Two meteorites were examined. EET 87503 is a howardite, a regolith breccia inferred to be from the asteroid 4 Vesta, and contains fragments of eucrite basalt, diogenite pyroxenite, and H-rich carbonaceous chondrites. With NXCT, the chondrite fragments within the meteorite piece can be clearly located and characterized, in preparation for possible extraction and detailed analyses. Graves Nunataks (GRA) 06100 is a CR2 chondrite meteorite that contains abundant iron metal and H-bearing silicates from aqueous alteration. In NXCT, H-bearing altered material is clearly distinguished from metal, and its distribution in three dimensions is revealed as a constraint on the processes of alteration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Status Report on Characterization of High Burnup Fuel with Advanced Nondestructive Pulsed Neutron PIE

Characterizing irradiated or spent nuclear fuels with pulsed neutron techniques provides microstructural data such as phase fractions as well as crystallographic data, e.g. lattice parameters, from diffraction analysis. Diffraction characterization is complemented by spatially resolved mapping of isotope densities from energy-resolved neutron imaging, in particular neutron absorption resonance imaging, and overall bulk isotope assay with better sensitivity for minority isotopes from neutron absorption resonance spectroscopy without spatial resolution. Furthermore, after characterization at ambient condition, heating of irradiated or spent fuel will allow to characterize differences of e.g. lattice thermal expansion or phase transition temperature and kinetics compared to fresh fuel as well as enable the study of disappearance of irradiation defects. This data enables benchmarking of predictions of properties of irradiated fuels for which otherwise experimental data is sparse. The effort described here strives to characterize a section cut from a high-burnup fuel. Volumes smaller than entire fuel pellets or rodlets as proposed here, e.g. sections cut from a fuel pellet, to pave the way to characterize entire pellets or rodlets in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Analysis of PNAR Spent Fuel Safeguards Measurements using the ORIGEN Data Analysis Module

This paper summarizes the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements using the ORIGEN data analysis module for 23 boiling water reactor spent fuel assemblies that were performed in Finland under an international collaboration on spent fuel safeguards verification methods. PNAR is part of the proposed integrated nondestructive system to be used for safeguards verifications at the planned Finnish encapsulation facility. Besides measuring passive neutron and gamma emission rates from an assembly like a Fork detector, PNAR also measures the PNAR ratio, which is expected to correlate with the fissile content in the assembly. The emission rates and PNAR ratio can be used to verify the operator declarations and the fissile content of an assembly, respectively. The analysis was performed using the ORIGEN Data Analysis Module, which was originally developed for predicting Fork detector neutron and gamma signals for spent fuel measurements and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the IAEA. The Module includes the ORIGEN burnup analysis code and integrates detector response functions pre-generated using MCNP to predict detector signals in several seconds per assembly. In this study, new response functions specific to PNAR measurements were generated for ORIGEN Module. The study also analyzes impacts of using detailed fuel design and operation information vs. standard safeguards information on results calculated by ORIGEN Module. Using detailed information reduced the standard deviation of relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. This paper describes how ORIGEN Module calculates the expected PNAR neutron and gamma signals and PNAR ratio and how they compare with corresponding measured values.

Ilas, Germina↗
DOE OSTI2020

Spent fuel nondestructive assay integrated characterization from active neutron, passive neutron, and passive gamma

Spent nuclear fuel comprises a wide range of irradiated isotopic material compositions, and characterization through nondestructive measurements is beneficial in verifying declared parameters before the fuel is placed in storage, final disposal, and/or reprocessed. This paper discusses results from three nondestructive assay instruments, including passive gamma, passive neutron, and active neutron methods, that measured fifty spent fuel assemblies at the Clab interim storage facility in Sweden. Here, integrated analysis of the measurements from the three different instruments allowed parametric assessments of cooling time, burnup, neutron multiplication, fissile mass, initial enrichment, and decay heat of each individual fuel assembly. Passive gamma measurements were found to be the most beneficial in predicting cooling time, passive neutron for determining burnup, active neutron in estimating initial enrichment, and both passive and total neutron for multiplication correlations. Fissile mass was best estimated using any combination of any two of the instruments such that corrections for isotopic changes in the fuel could be accounted for with the first set of measurements and multiplication of the assembly in the second. In conclusion, the nondestructive assay technologies demonstrated through this effort enhance the characterization of spent nuclear fuel assemblies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗