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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Label-free functional analysis of root-associated microbes with dynamic quantitative oblique back-illumination microscopy

The increasing global demand for food, coupled with concerns about the environmental impact of synthetic fertilizers, underscores the urgency of developing sustainable agricultural practices. Nitrogen-fixing bacteria, known as diazotrophs, offer a potential solution by converting atmospheric nitrogen into bioavailable forms, reducing the reliance on synthetic fertilizers. However, a deeper understanding of their interactions with plants and other microbes is needed. In this study, we introduce a recently developed label-free 3D quantitative phase imaging technology called dynamic quantitative oblique back-illumination microscopy (DqOBM) to assess the functional dynamic activity of diazotrophs in vitro and in situ. Our experiments involved three different diazotrophs (Sinorhizobium meliloti, Azotobacter vinelandii, and Rahnella aquatilis) cultured on media with amendments of carbon and nitrogen sources. Over 5 days, we observed increased dynamics in nutrient-amended media. These results suggest that the observed bacterial dynamics correlate with their metabolic activity. Furthermore, we applied qOBM to visualize microbial dynamics within the root cap and elongation zone of Arabidopsis thaliana primary roots. This allowed us to identify distinct areas of microbial infiltration in plant roots without the need for fluorescent markers. Our findings demonstrate that DqOBM can effectively characterize microbial dynamics and provide insights into plant-microbe interactions in situ, offering a valuable tool for advancing our understanding of sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Using geodetic data in geothermal areas

Geodetic observations, often in conjunction with other data, provide a cost-effective means for identifying and characterizing geothermal resources. Here, a review of the various methods reveals how the technology for measuring deformation has advanced considerably in the past few decades. Currently, interferometric synthetic aperture radar is the method of choice for monitoring deformation at a geothermal field. A discussion of geodetic monitoring at The Geysers geothermal field, California, illustrates some of the progress made and the challenges that remain.

58 GEOSCIENCES↗
DOE OSTI2021

Nanoparticle Mediated Delivery of Therapeutic mRNA for Protection Against Lung Damage

Medical countermeasures (MCMs) based on messenger ribonucleic acid (mRNA) are promising due to their programmability, targeting precision and specificity, predictable physicochemical properties, and amenability to scalable manufacture. However, safe and effective delivery vehicles are needed, especially for targeting the lung. We developed a generalized approach to nanoparticle-mediated mRNA delivery to lung, and used it to evaluate candidate therapies. In initial studies, reporter mRNA was delivered using lipid-coated mesoporous silica nanoparticles (LC-MSNs) and lipid nanoparticles (LNPs), the latter with greater consistency. Then, mRNA encoding known protein therapies were delivered using LNPs. These formulations showed some toxicity in mice with lung damage, but those with IL-1RA, sACE2-Ig, and ANGPT1 mRNA were modestly therapeutic on balance. Our work advances the state of the art for mRNA delivery to lung, and provides a foundation for evaluating and characterizing mRNA-based lung therapies, including three that appear to be exceptionally promising.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

BLADE: An Automated Framework for Classifying Light Curves from the Center for Near-Earth Object Studies Fireball Database

Fireballs (bolides) are high-energy luminous phenomena produced when meteoroids and small asteroids enter Earth’s atmosphere at hypersonic speeds, often resulting in fragmentation or complete disintegration accompanied by significant energy release. The resulting bolide light curves capture temporal brightness variations as these objects traverse increasingly dense atmospheric layers, providing essential information on meteoroid entry dynamics, fragmentation behavior, and atmospheric energy deposition processes. The Center for Near-Earth Object Studies’ (CNEOS) continuously expanding fireball database offers a globally comprehensive archive of bolide events, including light curves and associated metadata. Events associated with infrasound detections allow direct correlations between acoustic signatures and light curve features, therefore enabling detailed analyses of fragmentation dynamics and energy deposition. Here, we introduce Bolide Light-curve Analysis and Discrimination Explorer (BLADE), a robust and high-fidelity framework specifically designed to analyze bolide light curves for objects detected from space. BLADE incorporates a processing pipeline integrating Savitzky–Golay filtering, prominence-based peak detection, and gradient analysis, enabling systematic identification and classification of fragmentation events and their associated energy release characteristics. Preliminary results demonstrate that BLADE reliably distinguishes distinct bolide behaviors, providing an objective, scalable methodology for characterization and analysis of large bolide light curve data sets. This foundational work establishes a novel pathway for advanced bolide research, with promising applications in planetary defense and global atmospheric monitoring. Future research should adopt an integrative approach combining CNEOS optical data with complementary infrasound measurements, further clarifying relationships between bolide energy deposition and acoustic signatures, thus refining our understanding of meteoroid and asteroid atmospheric entry processes.

Asteroids↗
DOE OSTI2020

Full characterization of ultrathin 5-nm low-k dielectric bilayers: Influence of dopants and surfaces on the mechanical properties

Ultrathin films and multilayers, with controlled thickness down to single atomic layers, are critical for advanced technologies ranging from nanoelectronics to spintronics to quantum devices. However, for thicknesses less than 10 nm, surfaces and dopants contribute significantly to the film properties, which can differ dramatically from that of bulk materials. Therefore, for amorphous films being developed as low dielectric constant interfaces for nanoelectronics, the presence of surfaces or dopants can soften films and degrade their mechanical performance. Here we use coherent short-wavelength light to fully and nondestructively characterize the mechanical properties of individual films as thin as 5 nm within a bilayer. In general, we find that the mechanical properties depend both on the amount of doping and the presence of surfaces. In very thin (5-nm) silicon carbide bilayers with low hydrogen doping, surface effects induce a substantial softening - by almost an order of magnitude - compared with the same doping in thicker (46-nm) bilayers. These findings are important for informed design of ultrathin films for a host of nano- and quantum technologies, and for improving the switching speed and efficiency of next-generation electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impedance‐matching model‐in‐the‐loop simulation

Abstract Impedance matching is a novel approach to executing model‐in‐the‐loop (MIL) simulations. The concept, key features, and sample applications of this approach have been described in a series of publications. This paper advances theory and implementation for impedance‐matching MIL by: (1) developing a feedback linearization technique for implementing MIL for nonlinear virtual systems, (2) systematically characterizing MIL performance‐stability tradeoffs using three design‐oriented criteria—performance: defined as closeness of the controlled‐actuator impedance to the virtual‐boundary impedance;control effort: low controller response at high frequencies to reduce sensitivity to measurement noise and uncertainties in the actuator model; andstability: pursued using passivity of the controlled actuator system, and (3) assessing, through experimentation, the robustness of two ways to estimate feedback reaction force from the test article. These fundamental advancements to MIL are described using a one‐dimensional configuration consisting of a fluid‐filled cylindrical vessel as the physical test article and a uniaxial hydraulic shake table controlled to imitate different seismic isolation systems at the base of the vessel.

Engineering↗
DOE OSTI2023

Characterization of the In Vivo Deuteration of Native Phospholipids by Mass Spectrometry Yields Guidelines for Their Regiospecific Customization

Customization of deuterated biomolecules is vital for many advanced biological experiments including neutron scattering. However, because it is challenging to control the proportion and regiospecificity of deuterium incorporation in live systems, often only two or three synthetic lipids are mixed together to form simplistic model membranes. This limits the applicability and biological accuracy of the results generated with these synthetic membranes. Despite some limited prior examination of deuterating Escherichia coli lipids in vivo, this approach has not been widely implemented. In this report an extensive mass spectrometry-based profiling of E. coli phospholipid deuteration states with several different growth media was performed, and a computational method to describe deuterium distributions with a one-number summary is introduced. The deuteration states of 36 lipid species were quantitatively profiled in 15 different growth conditions, and tandem mass spectrometry was used to reveal deuterium localization. Regressions were employed to enable the prediction of lipid deuteration for untested conditions. Small-angle neutron scattering was performed on select deuterated lipid samples, which validated the deuteration states calculated from the mass spectral data. Based on these experiments, guidelines for the design of specifically deuterated phospholipids are described. This unlocks even greater capabilities from neutron-based techniques, enabling experiments that were formerly impossible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Advanced data analysis in inertial confinement fusion and high energy density physics

Bayesian analysis enables flexible and rigorous definition of statistical model assumptions with well-characterized propagation of uncertainties and resulting inferences for single-shot, repeated, or even cross-platform data. This approach has a strong history of application to a variety of problems in physical sciences ranging from inference of particle mass from multi-source high-energy particle data to analysis of black-hole characteristics from gravitational wave observations. The recent adoption of Bayesian statistics for analysis and design of high-energy density physics (HEDP) and inertial confinement fusion (ICF) experiments has provided invaluable gains in expert understanding and experiment performance. In this Review, we discuss the basic theory and practical application of the Bayesian statistics framework. We highlight a variety of studies from the HEDP and ICF literature, demonstrating the power of this technique. Due to the computational complexity of multi-physics models needed to analyze HEDP and ICF experiments, Bayesian inference is often not computationally tractable. Two sections are devoted to a review of statistical approximations, efficient inference algorithms, and data-driven methods, such as deep-learning and dimensionality reduction, which play a significant role in enabling use of the Bayesian framework. We provide additional discussion of various applications of Bayesian and machine learning methods that appear to be sparse in the HEDP and ICF literature constituting possible next steps for the community. We conclude by highlighting community needs, the resolution of which will improve trust in data-driven methods that have proven critical for accelerating the design and discovery cycle in many application areas.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Advancements in Multiphysics Microdepletion Analysis of an eVinci TM -like Microreactor Leveraging OpenMC-CRAB Workflow

Nuclear microreactors (MRs) are a class of nuclear reactor technology, characterized by reduced dimensions, modular design, and reduced power output in contrast to conventional Light Water Reactors (LWRs). MRs are proposed for supplying electricity and eventual process heat to remote locations, such as military installations and disaster-affected areas. Current research work sponsored by the US Department of Energy Microreactor Program (MRP) is devoted to the development of novel modeling and simulation tools to better support MR vendors and regulatory bodies. Notably, the NRC is projected to utilize the CRAB multiphysics software driver for executing both design and beyond-design-basis accident analyses. Furthermore, the NRC has been utilizing the MELCOR code to calculate mechanistic source terms during accidents. Since MELCOR relies on isotopic inventory and reactor temperature/power profiles under accident conditions, which theoretically can be derived from CRAB, the goal is to establish a comprehensive CRAB-MELCOR computational framework. Past work was focused on testing and demonstrating CRAB's capability to generate results that can be used to inform mechanistic source term calculations in MELCOR. In particular, a computational workflow leveraging OpenMC-generated microscopic cross sections and CRAB was first applied to perform multiphysics microscopic depletion calculation followed by an accident scenario for a stylized microreactor problem. In fiscal year 2024, the research work has been focused on applying the OpenMC-CRAB workflow, which was first tested in fiscal year 2023, to a realistic 3D heat-pipe cooled MR problem representative of the eVinci TM design. The latter computational problem was developed with inputs from WEC to conserve selected neutronic and thermal characteristics of the eVinci TM design without releasing proprietary data. The results of this simulation, encompassing isotopic inventory, power density distribution, and kinetic parameters, will inform both MELCOR and the WEC-developed FATE code for mechanistic source terms calculations. The results from the two codes will then be compared for code verification purposes. This report contains the design characteristics of the realist heat pipe cooled microreactor developed as a use-case for the verification exercise, and the current results for the multiphysics microscopic depletion performed with the OpenMC-CRAB workflow. The results include eigenvalue as a function of time, power distribution at EOL, in addition to nuclides inventory's time evolution and spatial distribution. Finally, we report improvements to the workflow efficiency achieved through a collaboration with the NEAMS programs. Through this collaborative effort, we were able to strongly decrease the computational time for the multiphysics microdepletion calculation (i.e., from 17.4 hours to 5.7 hours on 280 processors) in addition to simplifying the interface to generate isotopics spatial distribution utilizable by FATE and MELCOR. Future work, including the improvement of the current microscopic cross-sections' library and the simulation of an accident scenario at EOL, is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Microanalytical Approaches to Characterizing REE in Appalachian Basin Underclays

The search for a reliable U.S. domestic source of rare earth elements (REE) is necessary to support the demand of advanced energy applications (e.g., catalysts, electronics, magnets). Sedimentary deposits may be sources for selectively recovering REE and critical metals—specifically the interbedded seat rock, or underclay, that underlies or forms the floor of a coal seam. This material is often a major component of coal waste fines and refuse and thus readily available. This study examines several Appalachian Basin underclays associated with actively mined coal seams as potential feedstocks for the REE. Multimodal microanalytical electron microscopy (SEM, FIB-SEM, EMPA) synchrotron-based µXRF, and image processing techniques are coupled with detailed elemental and mineral data to classify the 2D and 3D petrophysical properties of the materials. The REE contents of Appalachian Basin underclays were measured from 235–399 ppm and predominantly observed as discrete REE-bearing minerals such as monazite and xenotime on the order of 10–100 µm in size. These REE-bearing minerals typically accounted for less than 1% of the scanned areas and volumes under SEM and FIB-SEM analysis, with the exception of regions enriched in crandallite. Synchrotron-based µXRF elemental maps further identified several REE deposition environments in different underclays, including micro-scale (10–100 µm) light REEs co-localizing with Ca and P, micro-scale heavy REEs with Fe, and large-scale light REEs (>200 µm) co-localizing with Sr, Ba, Ca and P.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterization of build parameters and microstructure in low heat input WAAM of Ni-based superalloy Haynes 282

Conference paper for 2024 10th International Conference on Advances in Materials, Manufacturing & Repair for Power Plants. Ni-based superalloy Haynes 282 is a prime candidate for advanced power generation systems due to its superior fabricability, weldability, and high-temperature performance. Additive manufacturing offers potential cost and time savings for gas turbine components. Wire-arc direct energy deposition can create large components but often requires post-processing treatments, such as hot isostatic pressing (HIP), to address porosity. This study explores a low heat-input, high deposition rate GMAW process to achieve fully dense Haynes 282 without HIP. Twenty-one blocks were deposited, varying travel and wire feed speeds. Initial analysis (visual inspection, microstructural examination, and CT) revealed the impact of build parameters on internal porosity and defects. Scanning electron microscopy provided insights into structural heterogeneity and microstructural properties. Related journal article can be found at https://doi.org/10.31399/asm.cp.am-epri-2024p0001.

Adam, Benjamin↗
DOE OSTI2022

Editorial: Nanotechnology for natural products

Humans around the globe have lived through an unprecedented time. The emergence and rapid spread of coronavirus disease 2019 (COVID-19) have resulted in the loss of millions of lives, and this number is still climbing every day and hour. As a consequence, there have been drastic changes over the past two years in how we live, communicate, and work, some of which may have changed forever: remote conferencing has become a new norm for businesses, schools, and academia; work-from-home and hybrid working is now more than just acceptable in many industries; most importantly, COVID-19 has raised global awareness of infectious diseases and pandemic responses to an exceptional level. Certainly, COVID-19 is not the only disease that is causing human suffering at this moment. Other highly contagious and lethal viruses, such as the human immunodeficiency virus (HIV), Ebola, and the recent addition to the list, Monkeypox, pose extraordinary challenges to modern civilizations. On the other hand, non-communicable diseases, such as heart disease, stroke, and cancer, are still claiming the majority of deaths on a global level (World Health Organization, 2020). Before the availability of synthetic drugs, civilizations worldwide relied on natural products extracted from the environment and various organisms for healthcare. Natural products and their derivatives continue to be critical components in the drug library available today. Indeed, almost a quarter of the new drugs approved by the US Food and Drug Administration (FDA) since 1981 are natural products, botanical mixtures, or their derivatives (Newman and Cragg, 2020). Recent developments in analytical characterization, genome mining, and engineering have further increased interest in drug discovery from the pool of natural products (Atanasov et al., 2021). This Research Topic celebrates a collection of studies at the intersection of natural product research and nanotechnological advances. As a successor and extension of the Research Topic in “Nanotechnology in Traditional Medicines and Natural Products” published last year (Zhang et al., 2021), the present collection focused more on recent developments in employing the synthesis and characterization of nanostructures for the delivery of functional natural products. Specifically, the use of carrier nanostructures to conjugate or encapsulate therapeutically active natural products with carrier nanostructures could enable their robust, targeted delivery tailored to either tackle a specific disease or unlock a drug administration pathway. Over the last decade, nanostructures such as liposomes (Pattni et al., 2015) and lipid nanoparticles (Hou et al., 2021) have been developed as versatile platforms for the inclusion and delivery of a wide range of therapeutical compounds; a significant advance in this aspect is the stabilization of mRNA strands for COVID-19 vaccination recently produced by Pfizer/BioNTech and Moderna (Tenchov et al., 2021). Such engineered nanomaterials are now widely used in the development of new drugs, while regulatory forces, such as the US FDA, remain cautious with the evaluation of each product on a case-by-case basis (Wang and Grainger, 2022). In this collection, Zeng et al. provided a timely review of natural products conjugated to and contained within nanomaterials for the ongoing COVID-19 pandemic. Natural products that are potentially useful in the mitigation of this disease, such as chloroquine and curcumin, supported in nanocarrier systems, have been discussed in detail. More broadly, Cheng et al. comprehensively reviewed the use of liposomes as a nanocarrier for natural products. This article provides a summary of natural product compounds and extracts used to form liposomal structures. Readers can further enjoy the practical aspects of these engineered drugs for the treatment of specific diseases as well as insights into future directions in this field.

peptides↗
DOE OSTI2021

Advancing Pressure Gain Combustion for Terrestrial Turbine Systems

The principal objectives of this project were to demonstrate the operability of a natural gas - air RDE at gas turbine engine cycle conditions. To achieve these goals, our specific tasks were to 1) characterize the dynamic injection and mixing performance of candidate injectors, 2) assess the engine operability via interrogation of spatio-temporal dynamics of combustor inlet and exit flows, 3) measure the engine emissions, and 4) complete an overall assessment of the pressure gain potential of the device. In order to advance RDE technology to the greatest extent possible, the reactants and experimental conditions were chosen to replicate combustor and injector conditions in a terrestrial power generation system. This path was taken because the scaling of combustion devices is, in general, an immature area given the challenges of interrelated mixing and chemical kinetics processes both of which scale with operating conditions.

03 NATURAL GAS↗
DOE OSTI2020

Initial Temperature Testing of Advanced Manufactured Melt Wire Package

As a part of the In-Pile Instrumentation Program, The Idaho National Laboratory (INL) has recently established in-house capabilities to fabricate and test new advanced manufactured sensors for measuring the peak irradiation temperature inside a nuclear test reactor. Although nuclear test reactors can use standard methods of real-time temperature monitoring, such as thermocouples, the complexity of feedthroughs and attachment complications to collect real-time measurements greatly increases the cost of the experiment. Passive monitoring techniques may be utilized that exploit the melting point of well characterized material (standard melt wires), however, the limited space available for instrumentation during experiments is also a challenge. To accommodate the challenge, INL has expanded its temperature detection instrumentation capabilities paired with the advancement of in-house advanced manufacturing options to include printed melt wires for peak irradiation temperature measurement. The advanced manufactured melt wire package can determine peak temperatures in experiments that can fit the challenging space available during irradiation. Recent results and knowledge from this ongoing work have made it possible to develop unique temperature sensors that can accomplish user specific temperature ranges inside the harsh environments experienced during radiation testing. This report summarizes the initial temperature testing using fabricated melt wires with two different melting temperatures, silver (melting temperature of ~960 °C) and solder (melting temperature of ~160 °C), that were initially tested for their relative melting points using non-standard method of furnace and hot plate testing under normal air conditions. Future work will include more controlled way of testing printed melt wires under inert gas with multiple temperature measurements followed by comparison of standard melt wire package performance for baseline characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Measurements of source emittance and beam coherence properties of the upgraded Advanced Photon Source

The Advanced Photon Source (APS) has been upgraded with a multi-bend achromat lattice, achieving significantly reduced electron beam emittance and enhanced X-ray coherence. Precise characterization of these properties is essential for optimizing beamline performance and enabling new experiments that take full advantage of the upgraded source. We report on measurements of source size and transverse coherence properties using grating interferometry at two beamlines: the APS 3-ID-B undulator beamline and the 1-BM-B bending magnet beamline. The results confirm the world-record horizontal emittance of the upgraded APS below 30 pm rad and validate the theoretical design parameters. We further investigate the impact of optical aberrations and mechanical vibrations at the 12-ID-C beamline on coherence preservation. These measurements establish a benchmark for future beamline enhancements and demonstrate the effectiveness of grating interferometry for high-precision beam characterization. Our findings provide critical insights into synchrotron beam dynamics, coherence degradation mechanisms, and strategies for optimizing beamline X-ray optics at next-generation light sources.

Advanced Photon Source↗
DOE OSTI2026

Native Architecture of Wheat Straw Cell Walls: A Unified Model from X-ray Scattering and Solid-State NMR

Plant secondary cell walls constitute the dominant reservoir of renewable biomass, comprising tightly packed cellulose, hemicellulose, and lignin at the nanoscale. Recent advances in solid-state NMR spectroscopy and the availability of small-angle X-ray scattering for biomass characterization have led to an accumulation of experimental data on cell wall organization, yet no explicit structure model has simultaneously satisfied both Xray and NMR observations. Using wheat straw as a model system, we propose a structural framework consistent with current knowledge of cellulose biosynthesis, X-ray scattering data, and one- and two-dimensional 13 C solid-state NMR spectra. In this model, 18-chain elementary fibrils align in parallel and populate the cross-section at random. Arabinose-substituted xylan shows no conformational dependence for cellulose-binding in wheat, and only a minor fraction of 2-fold xylan appears in close proximity to cellulose, unlike in Arabidopsis, where xylan is more tightly attached to the cellulose surface. While NMR data cannot unambiguously resolve the internal arrangement of the 18 glucan chains, X-ray scattering profiles uniquely constrain the fibril size and exclude the possibility of tight bundling in the intact walls. The specific interaction between the matrix polymers and the cellulose elementary fibrils must be reconsidered in light of the small interfibril spaces, which bring the matrix components into spatial proximity with cellulose even in the absence of attractive interactions. These findings provide fundamental molecular-level insight into cellulose fibril architecture and matrix−polymer interactions, resolving longstanding discrepancies between spectroscopic and scattering data and advancing our understanding of biopolymer assembly into structurally and functionally versatile lignocellulosic biomaterials.

Carbohydrates↗
DOE OSTI2026

Probing Dynamic Phase Changes in Electrochemical Systems with Cryogenic and in Situ Analytical Electron Microscopy (Final Technical Report)

In this project, we focus on the advancement of our newly developed, unique in situ and cryogenic analytical electron microscopy (AEM) techniques and the development of additional high-end capabilities to quantitatively elucidate the mechanisms of resistive state changes in solid-state electrochemical materials for non-volatile, neuromorphic memory. The objectives of the proposed research are (1) to characterize and elucidate the mechanisms by which electronic state changes occur in various solid-state devices to build guiding principles for electrochemically activated smart materials; (2) to advance our understanding of such mechanisms by coupling cryogenic and in situ techniques to control kinetics of the observed mechanisms while mitigating probe-induced damage; and (3) to utilize additional advanced techniques including electron-beam induced current and quantum mechanical simulations in order to identify the underlying fundamental science of such processes, including roles of defect formation and its effect on phase nucleation, as well as dynamics of these processes in the electrochemical systems at the nanometer scale.

25 ENERGY STORAGE↗
DOE OSTI2025

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗