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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Scalable in situ non-destructive evaluation of additively manufactured components using process monitoring, sensor fusion, and machine learning

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. However, the current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques, which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. In this work, an in situ NDE (INDE) system was engineered to detect subsurface flaws detected in X-Ray Computed Tomography (XCT) directly from process monitoring data. A multilayer, multimodal data input allowed the INDE system to detect numerous subsurface flaws in the size range of 200–1000µm using a novel human-in-the-loop annotation procedure. Furthermore, a framework was established for generating probability-of-detection (POD) and probability-of-false-alarm (PFA) curves compliant with NDE standards by systematically comparing instances of detected subsurface flaws to post-build XCT data. Here, we also introduce for the first time in the AM in situ sensing literature the a 90/95 – the flaw size corresponding to a 90% detection rate on the lower 95% confidence interval of the POD curve. The INDE system successfully demonstrated POD capabilities commensurate with traditional NDE methods. Traditional ML performance metrics were also shown to be inadequate for assessing the ability of the INDE system’s flaw detection performance. It is the hope of the authors that future studies will adopt the POD and PFA approach outlined here to provide better insight into the utility of process monitoring for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A scoping review of non-destructive testing (NDT) techniques in building performance diagnostic inspections

Understanding building envelope thermodynamics is an essential foundation of building sciences, mainly due to the envelope’s role as a boundary layer for exterior environments, as well as a container and regulator of internal microclimates. This paper presents a scoping literature review of select Non-destructive Testing (NDT) techniques for building envelope scanning and surveying for thermodynamic diagnostics. The investigation focuses specifically on reviewing six NDT techniques: Ground Penetrating Radar (GPR), Light Detection and Ranging (LiDAR)/Laser Scanning, Thermography, Ultrasound, Close-Range Photogrammetry and Through Wall Imaging Radar (TWIR). The aim is to identify knowledge gaps in terms of their use in accurately characterizing envelope compositions for further integration in Building Energy Modeling (BEM). Each technique was evaluated according to set categories imbibed from the American Society of Heating, Refrigerating, and Air Conditioning Engineering (ASHRAE) Standard 211P that showcase the technique’s ability to extract various relevant information. A framework is then developed to inform users on how to use hybrid NDT-based workflows applied in building envelope energy audits. The study concludes by discussing possibilities of utilizing NDT in large-scale audit automation, BEM integration, and developing built environment policies focusing on increasing existing building performance through retrofitting design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Non-destructive evaluation and machine learning methods for inspection of spent nuclear fuel canisters: A state-of-the-art review

Nuclear energy is among the cleanest and most efficient energy sources currently available. The operation of nuclear power plants (NPPs) produces large amounts of high-level radioactive waste known as spent nuclear fuel (SNF). Currently, large amounts of SNF is stored in dry cask storage systems (DCSSs) for extended interim storage until a permanent disposal solution becomes available. During the extended interim storage, the DCSS, particularly the SNF canisters, may degrade and abnormal conditions may occur. Therefore, non-destructive evaluation (NDE) and machine learning (ML) approaches are necessary for inspection of SNF canisters. This paper presents a state-of-the-art review of literature by summarizing recent progress made on the applications of NDE and ML for inspection of SNF canisters. Sixteen NDE methods are examined and compared: visual inspection, ultrasonic guided waves (UGWs), laser-based approaches, acoustic emission (AE), eddy current testing (ECT), non-invasive acoustic sensing, dynamic modal testing, cosmic ray muons tomography, neutron imaging, gamma rays detection, fiber optical sensors, through-wall communications, X-ray computed tomography (CT), vibrothermography, monoenergetic photon sources, and surface acoustic wave (SAW) sensors. The technology readiness level (TRL) for each method is assessed and compared. Recent publications on ML-enhanced visual inspection, AE, non-invasive acoustic sensing, dynamic modal testing, and neutron imaging for SNF canisters are summarized and future research needs are identified. In conclusion, this review article provides a convenient reference on the state-of-the-art applications of NDE and ML methods for inspection of SNF canisters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Mixture-of-Experts for Multi-Domain Defect Identification in Non-Destructive Inspection

Composite materials are widely used in aircraft structures because of their superior mechanical properties. However, their complex failure modes require sophisticated inspection methods to ensure structural integrity. Ultrasonic testing (UT) is a common non-destructive inspection (NDI) technique for aircraft composites that can detect internal and external defects with high resolution and accuracy. Despite their effectiveness, traditional UT methods rely on the manual interpretation of ultrasonic signals, which is time-consuming, labor-intensive, and subjective. Furthermore, processing such large-scale data, particularly across materials of varying thicknesses, significantly increases the computational demands of deep learning model optimization. To overcome these challenges, we propose an efficient sparse mixture-of-experts (MoE) model with a multi-level loss function and introduce four novel training objectives to improve computational efficiency and accuracy in identifying surface defects in composite aircraft materials. Here, we evaluated our approach on material with multiple thicknesses or domains comprising various defects. Our experimental results demonstrate higher accuracy and F1-Score, with only 10% training epochs compared to baseline MoE.

composite materials↗
DOE OSTI2022

Understanding the Elastic, Plastic, and Damage Features in Fracturing of Self-reinforced Thermoplastic Composites via Non-destructive Digital Imaging Correlation

This work demonstrated the utilization of non-destructive Digital Imaging Correlation (DIC) method to characterize the elastic, plastic, and damage features during the Mode I intra-laminar fracturing process of self-reinforced thermoplastic composites by using a self-reinforced polypropylene (PP) composite as an example. The DIC results clearly showed the development of huge plastic zone (PZ) and non-negligible Fracture Process Zone (FPZ) in front of the notch tip during the fracturing process, and the geometries and sizes of the foregoing zones at the peak load were further quantified. Such an interesting fracturing behavior of self-reinforced thermoplastic composites is way different from brittle materials (e.g., glass, acrylic, etc.), ductile materials (e.g., aluminum, steel, etc.), and even quasi-brittle materials (e.g., concrete, nanoparticle-reinforced composites, tough ceramics, wood, cement, carbon/glass fiber-reinforced polymers, etc.). Thus, understanding the elastic, plastic, and damage features is the first step before better characterizing the material fracture properties of self-reinforced thermoplastic composites through new analytical methods and computational modeling. These efforts are of utmost importance for wide applications of self-reinforced thermoplastic composites in various engineering fields in the future.

Lightweight Composites, Self-reinforced Thermoplas↗
DOE OSTI2020

Modeling the Destruction of Glycolate in the Defense Waste Processing Facility (DWPF) Recycle Stream and Concentration Factors for Glycolate in the 2H Evaporator

Two models were developed to predict maximum glycolate concentrations in the Savannah River Site (SRS) Concentration, Storage, and Transfer Facility (CSTF) from implementation of the Nitric-Glycolic flowsheet at the Defense Waste Processing Facility (DWPF). One model describes the kinetics of glycolate destruction via chemical oxidation with sodium permanganate. This model conservatively predicts glycolate concentration delivered to the CSTF with a high probability the actual glycolate concentration is lower than predicted. The second model describes the potential concentration of said residual glycolate within the 242-16H (i.e., “2H”) Evaporator system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2017

Additive Manufacturing (AM) Activities and Non-Destructive Evaluation (NDE) at GSFC

NASA personnel will be meeting with a delegation from the Japan Aerospace Exploration Agency (JAXA) Office of Safety and Mission Assurance (OSMA) at Langley Research Center on 2217 through 3217. The purpose of the meeting is a technical interchange between NASA and JAXA to discuss Non-Destructive Evaluation (NDE) of Additive Manufacturing (AM) parts and the HALT process (relates to accelerated life testing). The visitors will be a small group of Japanese citizens. Goddard Space Flight Center (GSFC) has been asked to participate in the meeting, either in person or via teleconference. This presentation covers NDE efforts at GSFC and provides a cursory overview of AM and lab capabilities.

additive manufacturing↗
DOE OSTI2020

Non-Destructive Postirradiation Examination of the AFC-4C Capsule/Rodlet 5 Experiment

The AFC-4C irradiation test was irradiated at the Idaho National Laboratory Advanced Test Reactor to investigate several different fast reactor fuels that could be used to facilitate ultra-high burnup applications in sodium fast reactors. Several different alloys, fuel geometries, bonding materials, and coating/barrier were tested in ferritic-martensitic HT-9 cladding. The AFC-4C capsule 5 was removed from the reactor at around 8.7 at %HM burnup to begin postirradiation examination. This report presents and discusses the non-destructive PIE results of the AFC-4C-capsule / rodlet 5, a U-10Zr solid fuel, sodium bonded with HT9 with internal Cr-coating, and its performance is evaluated against the historical fuel performance of previously irradiated fuel from literature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Non-destructive, whole-plant phenotyping reveals dynamic changes in water use efficiency, photosynthesis, and rhizosphere acidification of sorghum accessions under osmotic stress

Noninvasive phenotyping can quantify dynamic plant growth processes at higher temporal resolution than destructive phenotyping and can reveal phenomena that would be missed by end-point analysis alone. Additionally, whole-plant phenotyping can identify growth conditions that are optimal for both above- and below-ground tissues. However, noninvasive, whole-plant phenotyping approaches available today are generally expensive, complex, and non-modular. We developed a low-cost and versatile approach to noninvasively measure whole-plant physiology over time by growing plants in isolated hydroponic chambers. We demonstrate the versatility of our approach by measuring whole-plant biomass accumulation, water use, and water use efficiency every two days on unstressed and osmotically stressed sorghum accessions. We identified relationships between root zone acidification and photosynthesis on whole-plant water use efficiency over time. Our system can be implemented using cheap, basic components, requires no specific technical expertise, and should be suitable for any non-aquatic vascular plant species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Winding θ and destructive interference of instantons

While the θ dependence of field theories is 2π periodic, the ground-state wavefunctions at θ and θ + 2π often belong to different classes of symmetry-protected topological states. When this is the case, a continuous change of the θ parameter can introduce an interface that supports a nontrivial field theory localized on the wall. We consider the 2d CP N-1 sigma model as an example and construct a weak-coupling setup of this interface theory by considering the small S1 compactification with nonzero winding θ parameter and a suitable symmetry-twisted boundary condition. This system has N classical vacua connected by fractional instantons, but the anomaly constraint tells us that the fractional-instanton amplitudes should vanish completely to have N-fold degeneracy at the quantum level. We show how this happens in this purely bosonic system, uncovering that the integration over the zero modes annihilates the fractional instanton amplitudes, in sharp contrast to what happens when the θ angle is constant. Moreover, we provide another explanation of this selection rule by showing that the N perturbative vacua acquire different charges under the global symmetry with the activation of the winding θ angle. We also demonstrate a similar destructive interference between instanton effects in the CP N-1 quantum mechanics with the Berry phase.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Fast and Non-Destructive Determination of Water Content in Ionic Liquids at Varying Temperatures by Raman Spectroscopy and Multivariate Regression Analysis

Imidazolium acetate ionic liquids (ILs) have been utilized as promising solvents in many applications that involve varying water content and temperature. These experimental variables affect the anion-cation intermolecular interactions, which in turn influence the performance of the ILs in these applications. Here, this paper shows Raman spectroscopy can be used as an operando method to measure water content in IL solvents when simultaneous temperature changes may occur. The Raman spectra of 1-alkyl-3-methylimidazolium acetate ILs (alkyl chain length n = 2, 4, 6, 8) with varying water content (from 0.028 to 0.899 water mole fraction) and temperature (from 78.1 K to 423.1 K) were measured. Increasing the water content or decreasing the temperature of the tested ILs weakens the anion-cation intermolecular interactions. The water content of these ILs can be quantified even in conditions when the temperature is changing using Raman spectroscopy combined with multivariate regression analysis, including principal component regression (PCR), partial-least-squares regression (PLSR), and artificial neural networks (ANNs). The ANN model combined with partial-least-squares (PLS) achieves the highest prediction accuracy of water content in ILs at varying temperatures (RMSECV = 0.017, R 2 CV = 99.1%, RMSEP = 0.019, R 2 P = 98.8%, RPD = 8.93). Raman spectroscopy provides a potential fast non-destructive operando method to monitor the water content of ILs even in applications when the temperature may be simultaneously altered; this information can lead to the optimized use of these ILs in many applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Non-destructive electrochemical diagnosis of failure mechanisms in aqueous zinc batteries

The early detection of secondary reactions that affect the life and performance of zinc manganese oxide batteries requires a shift from conventional time-consuming and often destructive procedures to rapid lifetime-predictive techniques. In this work, an electrochemical approach is employed to elucidate independent signatures for four common types of failure mechanisms in zinc manganese dioxide (Zn||MnO2) batteries—namely, the loss of zinc inventory, the loss of active material at the cathode, electrolyte depletion, and increased cell impedance. Our findings, specific to coin cell configurations, reveal that each induced failure mechanism can be distinctively modeled and identified based on responses from the rest voltage and columbic-efficiency data for prompt detection. For instance, electrolyte depletion response manifests a distinctive abrupt (>80 %) decrease in columbic efficiency (CE) and charge-rest voltage (Vc) while the discharge-rest voltage remained constant at ~1.3 V. Furthermore, electrolyte rejuvenation of the cell increased the CE to >95 % and restored Vc from ~0.3 to >1.7 V. Recovery experiments and reference performance tests demonstrated consistency between electrochemical descriptors and their associated failure mechanisms. Further, the outcomes of this work provide valuable insights and data models for some of the dominant failure mechanisms present in zinc manganese battery chemistries, which are beneficial to accelerated early-lifetime diagnosis and advancement of Zn batteries development.

25 ENERGY STORAGE↗
DOE OSTI2025

How non-ohmic contact-layer diodes in perovskite pinholes affect abrupt low-voltage reverse-bias breakdown and destruction of solar cells

Perovskite solar cells (PSCs) rapidly degrade under reverse bias, a condition that may occur during partial shading. Here, in this study, we use electrical measurements, electron microscopy, and optical and thermal imaging to investigate abrupt breakdown and hotspotting under low reverse potentials (<|-2| V). We show that microscopic pinholes in the perovskite layer cause rapid, destructive breakdown under reverse bias despite minimally reducing power conversion efficiencies. Measurements on miniature (200-micrometer diameter) PSCs and perovskite-free transport-layer diodes indicate that abrupt, low-voltage breakdown occurs in nanoscale to micrometer-scale defects and that metal migration and filamentation are unlikely causes. Reverse-bias stability substantially improves when pinholes in the perovskite and transport layers are eliminated. Atomic layer deposition of tin oxide prevents abrupt breakdown by ensuring physical separation between electrodes-not by blocking metal ion migration. Perovskite researchers should adopt cleaner, more uniform deposition techniques to enable robust PSCs for further research and commercial applications.

14 SOLAR ENERGY↗
DOE OSTI2020

Non-destructive spatial analysis of phosphatase activity and total protein distribution in the rhizosphere using a root blotting method

Phosphorus (P) is an essential macronutrient for plant growth, but bioavailable P in soils is often limited due to immobilization resulting from pH and geochemical interactions. Understanding the dynamics of P in soils and elucidating the mechanisms by which plants access P from their environment are critical to evaluating productivity, particularly in nutrient poor environments. Phosphorus from organic matter can act as a major source of P for organisms in soil systems. Phosphatases, enzymes that liberate inorganic P from organic sources, are produced by both plants and microbes and are considered one of the most active classes of enzymes in soil. In this work we developed a root blotting method to spatially image phosphatase activity in the rhizosphere. Proteins from the rhizosphere are transferred to a nitrocellulose membrane while retaining their enzymatic activity and two-dimensional spatial distribution. Subsequent application of a fluorogenic phosphatase indicator, DDAO phosphate, enables visualization of the distribution of phosphatase activity in the sample. The proteins can then be fixed to the membrane and treated with a SYPRO® Ruby gel stain, a fluorescent total protein stain, allowing for visualization of total protein distribution. Taken together, the images of phosphatase activity and total protein localization can be mapped back to the root architecture and provide insight into factors affecting the spatial distribution of enzymatic activity and protein accumulation in the rhizosphere. Notably, this method can be applied to plants growing in rhizoboxes containing soil or soilless growth mixtures (e.g., sand or various potting mixes) and, because of the non-destructive nature of this approach, be performed over time to track changes. We anticipate that this fluorescent indicator imaging technique on root blots can be used in diverse plant-microbe-soil systems to better understand the role of phosphatases in P acquisition and soil P cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Plant biochemistry influences tropospheric ozone formation, destruction, deposition, and response

Tropospheric ozone (O 3 ) is among the most damaging air pollutant to plants. Plants alter the atmospheric O 3 concentration in two distinct ways: (i) by the emission of volatile organic compounds (VOCs) that are precursors of O 3 ; and (ii) by dry deposition, which includes diffusion of O 3 into vegetation through stomata and destruction by nonstomatal pathways. Isoprene, monoterpenes, and higher terpenoids are emitted by plants in quantities that alter tropospheric O 3 . Deposition of O 3 into vegetation is related to stomatal conductance, leaf structural traits, and the detoxification capacity of the apoplast. The biochemical fate of O 3 once it enters leaves and reacts with aqueous surfaces is largely unknown, but new techniques for the tracking and identification of initial products have the potential to open the black box.

59 BASIC BIOLOGICAL SCIENCES↗