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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

In-Plane Liftout and Push-to-Pull for In Situ Mechanical Testing of Irradiated Inconel X-750

A streamlined sample preparation method for nanomechanical testing is needed to improve the quality of specimens, reduce the cost, and increase the versatility of specimen fabrication. This work outlines an in-plane liftout focused ion beam (FIB) fabrication procedure to prepare electron-transparent specimens for in situ transmission electron microscopy (TEM) nanomechanical testing. Ion etching and electron backscatter diffraction (EBSD) techniques were used to lift out a [110] oriented grain from a neutron-irradiated bulk X-750 alloy. Careful control of voltages and currents ensured precision. Top surface thinning sweeps prevented resurfacing and redeposition while dog-bone geometries were shaped with a 1:4 gauge width-to-milling pattern diameter ratio. Nanotensile testing in the TEM with a picoindenter allowed for the estimation of an ultimate tensile strength of 2.41 GPa, and inspection revealed a high density of bubbles in the X-750 matrix. The proposed fabrication procedure is significant for preparing samples from radioactive materials, studying complex structures that are orientation-dependent, and analyzing desired planar areas.

36 MATERIALS SCIENCE↗

In situ detection and characterization of alkali-silica reaction damage in concrete using contactless ultrasonic wavefield imaging

Here we present work to characterize cracking damage in concrete caused by alkali-silica reactivity distress. We apply contactless ultrasonic scan inspection, exploiting Rayleigh wave scattering from concrete inhomogeneities. The scanning system utilizes a multi-channel MEMS sensor array to collect ultrasonic wavefield data from concrete subjected to ASR-promoting environments. The location and extent of ASR damage are established by internal expansion measurements from embedded strain gauges, scanning electron microscope images of cored samples, and expansion measurements from companion samples. A wavefield data processing method extracts oscillatory fields from the ultrasonic wavefield data to detect distinct zones of ASR damage. A damage index is proposed to further characterize the extent of ASR damage. The results confirm the feasibility and accuracy of the approach to characterize ASR damage in concrete. The fully contactless ultrasonic scanning measurement system does not require separate material samples and enables in situ characterization of ASR damage within concrete structures.

36 MATERIALS SCIENCE↗

Evaluating the Lightning Strike Damage Tolerance for CFRP Composite Laminates Containing Conductive Nanofillers

Conductive nanofillers, such as carbon nanotube, graphene nanoplatelets, and carbon black particles (with diameters in nanometers) have been shown to enhance the electrical conductivity of fiber reinforced polymer matrix composites in many existing studies. The motivation is primarily for lightning strike protection, electromagnetic interference shielding, de-icing, and the manufacturing of lightweight electronic components. Here, we evaluate the lightning strike damage tolerance of carbon fiber reinforced polymer (CFRP) matrix composite laminates containing conductive nanofillers with varying weight fractions, including carbon black (CB), carbon nanotubes (CNT), and a mix of CB and CNT, through simulated lightning strike tests, followed by both non-destructive ultrasonic inspection and destructive sectioning to characterize the damage inflicted by the simulated lightning strike. Three-point flexural tests are performed to evaluate the residual strength retained by all CFRP specimens. Results show that lightning strike damage experienced varying levels of reduction for CFRP composite specimens containing conductive fillers in comparison to the baseline specimen without fillers. Notably, the delamination only penetrated to the interface between the 1st and 2nd layer for the specimen with 0.25 wt.% CNT in comparison to the baseline CFRP specimen for which the delamination penetrated to the interface between the 5th and 6th layer. Moreover, the retention of the flexural modulus increased from 26.5% to a maximum of 95.0% for the specimen with 0.25 wt.% hybrid CB and CNT. Yet, we show that using our chosen conductive fillers cannot fully eliminate lightning strike damage. Additionally, adding conductive fillers could compromise the flexural properties. We provide discussions on future recommendations on using conductive fillers for the lightning strike protection of CFRP composites.

36 MATERIALS SCIENCE↗

Core-Level Spectroscopy with Hard and Soft X-rays on Phosphorus-Containing Compounds for Energy Conversion and Storage

The electronic properties of nine solid phosphorus (P)-containing compounds with varying oxidation states and chemical environments, including GaP (–III) , InP (–III) , red-P (0) , H 3 P (III) O 3 , Na 2 H 2 P 2 (IV) O 6 , H 3 P (V) O 4 , KH 2 P (V) O 4 , Na 2 HP (V) O 4 , and InP (V) O 4 , are investigated using X-ray absorption near-edge structure (XANES) spectroscopy in the hard (P K-edge) and soft X-ray regime (P L 2,3 - edge). We find shifts in the absorption-edge positions and correlate them with the ligands surrounding the P atom, likely causing a different core–hole interaction screening for different compounds. Complementing the experimental analysis, ab initio many-body calculations of XANES spectra provide insights into the excitonic nature of the observed spectral features and their impact on the electronic structure of the materials. Furthermore, we report on P K-edge XANES measurements on aqueous phosphorus-containing acids, including H 3 PO 3 , H 3 PO 4 , and their mixtures. At first sight, the spectra of the aqueous acids are similar to those of their solid counterparts. However, close inspection reveals a slight red shift of the absorption edge and the presence of fewer spectral features compared with spectra of the respective solids. Mixtures of aqueous acids display spectral features corresponding to the individual components, indicating the potential for speciation and quantification through fingerprinting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.

Tabassum, Anika↗

Dynamic fracture of glass fiber-reinforced ductile polymer matrix composites and loading rate effect

Here, the dynamic fracture of S-2 glass fiber-reinforced polymer matrix composites (FRPMCs) was investigated in this study. The matrix ductility was improved by a recently developed network topology modification technique via mixing partially reacted substructures (mPRS). The composite material was manufactured and characterized by micro-CT scanning and scanning electron microscopy (SEM). Dynamic single-edge notched bending (d-SENB) experiments were performed on the composites by using a modified split-Hopkinson pressure bar. Each specimen’s fracture process was visualized by ultrafast X-ray imaging. Such in-situ radiography enabled identifying the damage initiation below 50-micron scale and inspecting its propagation through the internal structures of opaque composites, thereby accurately quantifying the composites’ mechanical properties. Furthermore, the identical d-SENB experiments were designed and the digital image correlation (DIC) was employed to monitor the stress wave propagation on the composite specimens. The force and deflection measurements were modified and correlated to the physical damage processes. Besides, quasi-static SENB experiments were conducted to identify the loading rate effects on the composites’ fracture behaviors. The force and deflection history, bending stiffness, energy dissipation, and fracture toughness at different loading rates were quantified and compared. Finally, post-fracture analysis by micro-CT scanning and SEM provided physical observations on the variation of the fracture morphology by different loading rates.

42 ENGINEERING↗

Comparative study of helium bubbles in a Ti-Ta alloy and a Ti/Ta nanocomposite

Here, we investigated the size, density, and distribution of helium (He) bubbles in a Ti-Ta single-phase alloy and a Ti/Ta dual-phase nanocomposite using transmission electron microscopy. The Ti/Ta nanocomposite was fabricated via phase separation during high-temperature annealing of the single-phase Ti-Ta alloy. He ion implantation in the Ti-Ta single-phase alloy leads to the formation of nano-scale He bubbles (~1.7 nm in size, ~2.6×10 5 /μm 3 in volumetric density). He bubbles were found to segregate to grain boundaries. Under identical implantation conditions, numerous He bubbles also formed in the Ti/Ta nanocomposite. Closer inspection revealed that He bubbles in the Ti-rich phase are smaller and of higher volumetric density (~1.2 nm, ~8.4×10 5 /μm 3 ) than those in the Tarich phase (~3 nm, ~1.8×10 5 /μm 3 ) and the single-phase alloy. He bubbles were also observed to decorate phase boundaries, but they were generally smaller than those on grain boundaries. These results suggest that Ti/Ta phase boundaries are less conducive to the growth of large He bubbles than grain boundaries in the Ti-Ta single phase alloy.

36 MATERIALS SCIENCE↗

Photoluminescence probing of light absorption centers at silica laser damage

We use photoluminescence (PL) imaging to study damage growth precursors within laser damage sites on the surface of silica. Damage site evolution is induced by multiple shots of UV nanosecond pulsed laser at various energy densities and monitored throughout the early stages of growth. Wide-field PL imaging rapidly locates microscopic light absorption centers within the silica damage site. Our quantitative analysis shows that damage sites with strong local PL intensity show a higher probability of growth upon subsequent laser pulses. Scanning electron microscopy (SEM) paired with a study of PL spectrum shows that the strong PL intensity appears from the subsurface fractures with high defect density, which provides a local light absorption center leading to significant damage growth. We believe that this result offers an efficient optical damage mitigation strategy by providing a rapid and non-destructive optical inspection approach.

36 MATERIALS SCIENCE↗

Spaceborne Accelerators Portfolio

MeV-range, satellite-mounted electron accelerators are needed for various space-related applications, such measuring the coupling between the magnetotail and ionosphere. The technologies and design approaches being developed for spaceborne accelerators emphasize high reliability, high average power, flexible operation, efficient power use, and operation from low-voltage DC power supplies. These same attributes are also relevant to industrial processing and inspection as well as medical applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Unsupervised anomaly detection in MeV ultrafast electron diffraction

MeV ultrafast electron diffraction (MUED) is a pump-probe technique used to study the dynamic structural evolution of materials. An ultrashort laser pulse triggers structural changes, which are then probed by an ultrashort relativistic electron beam. To overcome low signal-to-noise ratios, diffraction patterns are averaged over thousands of shots. However, shot-to-shot instabilities in the electron beam can distort individual patterns, introducing uncertainty. Improving MUED accuracy requires detecting and removing these anomalous patterns from large datasets. In this work, we developed a fully unsupervised methodology for the detection of anomalous diffraction patterns. Using a convolutional autoencoder, we calculate the reconstruction mean squared error of the diffraction patterns. Based on the statistical analysis of this error, we provide the user an estimation of the probability that the pattern is normal, which also allows a posterior visual inspection of the images that are difficult to classify. This method has been trained with only 100 diffraction patterns and tested on 1521 patterns, resulting in a false positive rate between 0.2% and 0.4%, with a training time of 10 s per image and a test time of about 1 s per image. Here, the proposed methodology can also be applied to other diffraction techniques in which large datasets are collected that include faulty images due to instrumental instabilities.

43 PARTICLE ACCELERATORS↗

Performance Evaluation of Comparative Vacuum Monitoring and Piezoelectric Sensors for Structural Health Monitoring of Rotorcraft Components

The costs associated with the increasing maintenance and surveillance needs of aging structures are rising at an unexpected rate. Multi-site fatigue damage, hidden cracks in hard-to-reach locations, disbonded joints, erosion, impact, and corrosion are among the major flaws encountered in today’s extensive fleet of aging aircraft and space vehicles. Aircraft maintenance and repairs represent about a quarter of a commercial fleet’s operating costs. The application of Structural Health Monitoring (SHM) systems using distributed sensor networks can reduce these costs by facilitating rapid and global assessments of structural integrity. The use of in-situ sensors for real-time health monitoring can overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring systems can automatically process data, assess structural condition, and signal the need for human intervention. The ease of monitoring an entire on-board network of distributed sensors means that structural health assessments can occur more often, allowing operators to be even more vigilant with respect to flaw onset. SHM systems also allow for condition-based maintenance practices to be substituted for the current time-based or cycle-based maintenance approach thus optimizing maintenance labor. The Federal Aviation Administration has conducted a series of SHM validation and certification programs intended to comprehensively support the evolution and adoption of SHM practices into routine aircraft maintenance practices. This report presents one of those programs involving a Sandia Labs-aviation industry effort to move SHM into routine use for aircraft maintenance. The Airworthiness Assurance NDI Validation Center (AANC) at Sandia Labs, in conjunction with Sikorsky, Structural Monitoring Systems Ltd., Anodyne Electronics Manufacturing Corp., Acellent Technologies Inc., and the Federal Aviation Administration (FAA) carried out a trial validation and certification program to evaluate Comparative Vacuum Monitoring (CVM) and Piezoelectric Transducers (PZT) as a structural health monitoring solution to specific rotorcraft applications. Validation tasks were designed to address the SHM equipment, the health monitoring task, the resolution required, the sensor interrogation procedures, the conditions under which the monitoring will occur, the potential inspector population, adoption of CVM and PZT systems into rotorcraft maintenance programs and the document revisions necessary to allow for their routine use as an alternate means of performing periodic structural inspections. This program addressed formal SHM technology validation and certification issues so that the full spectrum of concerns, including design, deployment, performance and certification were appropriately considered. Sandia Labs designed, implemented, and analyzed the results from a focused and statistically relevant experimental effort to quantify the reliability of a CVM system applied to Sikorsky S-92 fuselage frame application and a PZT system applied to an S-92 main gearbox mount beam application. The applications included both local and global damage detection assessments. All factors that affect SHM sensitivity were included in this program: flaw size, shape, orientation and location relative to the sensors, as well as operational and environmental variables. Statistical methods were applied to performance data to derive Probability of Detection (POD) values for SHM sensors in a manner that agrees with current nondestructive inspection (NDI) validation requirements and is acceptable to both the aviation industry and regulatory bodies. The validation work completed in this program demonstrated the ability of both CVM and PZT SHM systems to detect cracks in rotorcraft components. It proved the ability to use final system response parameters to provide a Green Light/Red Light (“GO” – “NO GO”) decision on the presence of damage. In additional to quantifying the performance of each SHM system for the trial applications on the S-92 platform, this study also identified specific methods that can be used to optimize damage detection, guidance on deployment scenarios that can affect performance and considerations that must be made to properly apply CVM and PZT sensors. These results support the main goal of safely integrating SHM sensors into rotorcraft maintenance programs. Additional benefits from deploying rotorcraft Health and Usage Monitoring Systems (HUMS) may be realized when structural assessment data, collected by an SHM system, is also used to detect structural damage to compliment the operational environment monitoring. The use of in-situ sensors for health monitoring of rotorcraft structures can be a viable option for both flaw detection and maintenance planning activities. This formal SHM validation will allow aircraft manufacturers and airlines to confidently make informed decisions about the proper utilization of CVM and PZT technology. It will also streamline future regulatory actions and formal certification measures needed to assure the safe application of SHM solutions.

42 ENGINEERING↗

Microscopic Measurement: Need for Nuclear Material Sample Specimen Characterization Capability

The Surveillance, Fabrication, and Off-Site Operations team at Lawrence Livermore National Laboratory is beginning an update to the nuclear material machining lab in Superblock. Plutonium and other nuclear materials tend to accelerate the aging process for equipment and machines that would otherwise be maintainable for long lives. They have their lifespans shortened from deteriorated seals, embrittled polymer components, accelerated corrosion, and damage to electronics from exposure to radioactive materials. The cost of installation of equipment into a glove box (GB) tends to outstrip the cost of the equipment itself. Due to the magnification of cost, the historical approach to equipment installs has been to purchase and install the highest-quality and most robust equipment available to maximize time between failures and updates. To make room for the installation of a new lathe, the inspection GB is being moved to a different location within the machining lab. As part of the overall effort, the equipment within the inspection GB is being revisited. Current measurement capabilities are antiquated and starting to become problematic due to age. Advances in metrology are sought for more comprehensive characterization of scientific samples. This document aims to identify several options for the replacement of current measurement equipment and identify a system for purchase and eventual installation. The intention is not to select the cheapest system, but rather to identify a system that best meets the needs of both the operators and principal investigators (PI). Following the convention of the SYSM-5620 Design Thinking and System Engineering, it was determined that a laser confocal measurement system from Keyence is the most suitable option for our programmatic need. Form factor, capability, and maintainability were considered. Along with stakeholder input, to ensure the best decision for the Nuclear Material Technology Program.

36 MATERIALS SCIENCE↗

CEBAF Accelerator Tunnel Robot Project

Advancements in the field of robotics allow for the use of remotely controlled robots to perform tasks that have typically required human intervention. Jefferson Lab has explored the possibilities of robots placed in the accelerator tunnel to perform remote inspections that would otherwise require powering down equipment and completing lengthy radiological surveys that impact beam operations. A robotic solution ? driven by a human operator ? could not only reduce accelerator down time but also support the Lab's radiation exposure policy (known as "ALARA" - As Low As Reasonably Acceptable) by handling routine tunnel and beamline investigations in place of a human being. However, operating a remote device in a radioactive, high electronic-noise area is not a trivial task and drop-in solutions are rarely as simple as they seem. We will present the past prototypes that were tested as well follow-on technology developed from the project. We will also briefly survey current applications of robots at accelerator facilities with an eye toward future applications.

McGuckin, Theodore↗

Analysis of Dust Samples Collected from an Inland ISFSI Site (Site A)

In September of 2020, dust samples were collected from the surface of spent nuclear fuel (SNF) dry storage canisters during an inspection at an inland Independent Spent Fuel Storage Installation. The purpose of the sampling was to assess the composition and abundance of the soluble salts present on the canister surface, information which provides a metric for potential corrosion risks. The samples were delivered to Sandia National laboratories for analysis. At Sandia, the soluble salts were leached from the dust and quantified by ion chromatography. In addition, subsamples of the dust were taken for scanning electron microscope analysis to determine the texture and mineralogy of the dust and salts. The results of those analyses are presented in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of origin. This information is subsequently utilized to identify failure trends and to implement corrective measures on the offending cavity. Manual inspection of large-scale, time-series data, generated by frequent system failures is tedious and time consuming, and thereby motivates the use of machine learning (ML) to automate the task. This study extends work on a previously developed system based on traditional ML methods (Tennant and Carpenter and Powers and Shabalina Solopova and Vidyaratne and Iftekharuddin, Phys. Rev. Accel. Beams, 2020, 23, 114601), and investigates the effectiveness of deep learning approaches. The transition to a DL model is driven by the goal of developing a system with sufficiently fast inference that it could be used to predict a fault event and take actionable information before the onset (on the order of a few hundred milliseconds). Because features are learned, rather than explicitly computed, DL offers a potential advantage over traditional ML. Specifically, two seminal DL architecture types are explored: deep recurrent neural networks (RNN) and deep convolutional neural networks (CNN). We provide a detailed analysis on the performance of individual models using an RF waveform dataset built from past operational runs of CEBAF. In particular, the performance of RNN models incorporating long short-term memory (LSTM) are analyzed along with the CNN performance. Furthermore, comparing these DL models with a state-of-the-art fault ML model shows that DL architectures obtain similar performance for cavity identification, do not perform quite as well for fault classification, but provide an advantage in inference speed.

97 MATHEMATICS AND COMPUTING↗

Local structure elucidation of tungsten-substituted vanadium dioxide (V$$_{1-x}$$W$$_x$$O$$_2$$)

Abstract Initially, vanadium dioxide seems to be an ideal first-order phase transition case study due to its deceptively simple structure and composition, but upon closer inspection there are nuances to the driving mechanism of the metal-insulator transition (MIT) that are still unexplained. In this study, a local structure analysis across a bulk powder tungsten-substitution series is utilized to tease out the nuances of this first-order phase transition. A comparison of the average structure to the local structure using synchrotron x-ray diffraction and total scattering pair-distribution function methods, respectively, is discussed as well as comparison to bright field transmission electron microscopy imaging through a similar temperature-series as the local structure characterization. Extended x-ray absorption fine structure fitting of thin film data across the substitution-series is also presented and compared to bulk. Machine learning technique, non-negative matrix factorization, is applied to analyze the total scattering data. The bulk MIT is probed through magnetic susceptibility as well as differential scanning calorimetry. The findings indicate the local transition temperature ( $$T_c$$ T c ) is less than the average $$T_c$$ T c supporting the Peierls-Mott MIT mechanism, and demonstrate that in bulk powder and thin-films, increasing tungsten-substitution instigates local V-oxidation through the phase pathway VO $$_2\, \rightarrow$$ 2 → V $$_6$$ 6 O $$_{13} \, \rightarrow$$ 13 → V $$_2$$ 2 O $$_5$$ 5 .

Wilson, Catrina E. (ORCID:0000000173397318)↗

Analysis of Dust Samples Collected from an Inland ISFSI Site (''Site B'').

In October of 2020, dust samples were collected from the surface of spent nuclear fuel (SNF) dry storage canisters during an inspection at an inland Independent Spent Fuel Storage Installation, the second inland site at which surface deposits have been sampled. The purpose of the sampling was to assess the composition and abundance of the soluble salts present on the canister surface, information which provides a metric for potential corrosion risks. The samples were delivered to Sandia National laboratories for analysis. At Sandia, the soluble salts were leached from the dust and quantified by ion chromatography. In addition, subsamples of the dust were taken for scanning electron microscopy to determine the texture and mineralogy of the dust and salts. The results of those analyses are presented in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Electrochemical Imaging of Interfaces in Energy Storage via Scanning Probe Methods: Techniques, Applications, and Prospects

Developing a deeper understanding of dynamic chemical, electronic, and morphological changes at interfaces is key to solving practical issues in electrochemical energy storage systems (EESSs). To unravel this complexity, an assortment of tools with distinct capabilities and spatiotemporal resolutions have been used to creatively visualize interfacial processes as they occur. This review highlights how electrochemical scanning probe techniques (ESPTs) such as electrochemical atomic force microscopy, scanning electrochemical microscopy, scanning ion conductance microscopy, and scanning electrochemical cell microscopy are uniquely positioned to address these challenges in EESSs. We describe the operating principles of ESPTs, focusing on the inspection of interfacial structure and chemical processes involved in Li-ion batteries and beyond. We discuss current examples, performance limitations, and complementary ESPTs. Finally, we discuss prospects for imaging improvements and deep learning for automation. We foresee that ESPTs will play an enabling role in advancing EESSs as we transition to renewable energies.

25 ENERGY STORAGE↗