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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Thermal and electric properties of Nd(1.85)Ce(0.15)CuO(4-y) and Pr(1.85)Ce(0.15)CuO(4-y)

Electric resistivity, magnetic susceptibility, thermoelectric power, and Hall coefficient of Nd(1.85)Ce(0.15)CuO(4-y) and Pr(1.85)Ce(0.15)CuO(4-y) whose onset temperature of the superconductivity are 24 and 23 K were measured. Experimental results show many interesting features. In particular, the Hall coefficients are negative and relatively flat as a function of temperature. However, the temperature dependence of the thermoelectric power (TEP) for these two samples shows the positive sign for both samples in contrast to the previous results. Moreover, TEP for both samples remains flat in the normal state below 250 K, but decreases rapidly above 250 K. TEP of only Pr(1.85)Ce(0.15)CuO(4-y) shows a peak near 50 K. Finally, onset temperatures of sudden drop of TEP are higher than those of resistance drop. The physical properties of these samples produced at different conditions such as different heat treatment temperatures, atmospheres were also measured. TEP and resistance measurement show that oxygen deficiency is essential to produce better superconducting samples. Correlation between TEP and superconductivity for these different samples are discussed.

Lim, Z. S.↗
DOE OSTI2023

Tailoring material microstructure and property in wire-laser directed energy deposition through a wiggle deposition strategy

Developing effective strategies to directly control material microstructure, property, and anisotropy is an active research area in metal additive manufacturing. This work develops a wiggle deposition pattern for wire-laser directed energy deposition (DED) of 316L stainless steel (SS) to modify the solidification texture, particularly in the building direction, in as-deposited samples. Through multi-physics simulation, operando near-infrared imaging, and synchrotron x-ray characterization, it is found that the wiggle deposition strategy induces highly dynamic melt flow and oscillating thermal gradient in the melt pool, which is responsible for the variation of preferable grain growth direction and crystallographic texture in the sample. The specific texture reduces the anisotropy in the tensile strength of as-printed 316L SS samples cut along different directions. Also, it largely increases the ductility along the build direction. Crystal plasticity simulation is performed to correlate the sample texture with mechanical property. In conclusion, this work offers a unique approach for tailoring local properties through the control of melt pool instability by applying different tool paths.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Frictional Behavior Downdip Along the Subduction Megathrust: Insights From Laboratory Experiments on Exhumed Samples at In Situ Conditions

Subduction megathrusts exhibit a spectrum of slip modes, including catastrophic earthquakes. Although the mechanical and frictional properties of materials sampled from subduction zones have been studied extensively, few datasets have been collected for compositions and at pressure and temperature conditions representative of those in situ. The Nankai subduction zone in southwest Japan is a well-studied margin, and abundant data provide an opportunity to advance our understanding of fault and earthquake physics. Here, we use samples exhumed in the Shimanto and Sanbagawa Belts on Shikoku Island of southwest Japan that represent analogs for materials along the present-day megathrust at depths of ~5–>25 km, and we shear these at their peak in situ pressure-temperature (P-T) conditions. Effective normal stresses range from 28 to 192 MPa, and temperatures from 105°C to 470°C. We used pore fluid pressures of 45–240 MPa, corresponding to fluid overpressure ratios λ of 0.65 and 0.90. Slip velocities of 0.1–100 μm/s were used, in order to focus on the nucleation of instability and earthquakes. We found predominantly velocity-strengthening (inherently stable) behavior under all conditions for λ = 0.65. For λ = 0.90, velocity-weakening behavior was observed at 350°C, with velocity-strengthening behavior at lower and higher temperatures. The rate/state frictional stability parameter (a-b) increases with slip velocity at temperatures up to ~200°C and remains constant or decreases with slip velocity at higher temperatures. Altogether, our results demonstrate the potentially important roles of both temperature and slip velocity in controlling the distribution of stress and frictional rheology along subduction thrusts.

58 GEOSCIENCES↗
NASA NTRS1988

Interactions of light with rough dielectric surfaces - Spectral reflectance and polarimetric properties

The nature of the interactions of visible and NIR radiation with the surfaces of rock and mineral samples was investigated by measuring the reflectance and the polarization properties of scattered and reflected light for slab samples of obsidian and fine-grained basalt, prepared to controlled surface roughness. It is shown that the degree to which radiation can penetrate a surface and then scatter back out, an essential criterion for mineralogic determinations based on reflectance spectra, depends not only upon the composition of the material, but also on its physical condition such as sample grain size and surface roughness. Comparison of the experimentally measured reflectance and polarization from smooth and rough slab materials with the predicted models indicates that single Fresnel reflections are responsible for the largest part of the reflected intensity resulting from interactions with the surfaces of dielectric materials; multiple Fresnel reflections are much less important for such surfaces.

Yon, S. A.↗
DOE OSTI2025

A tale of two planets: Disparate evolutionary models for Mars inferred from radiogenic isotope compositions of Martian meteorites

The radiogenic isotopic compositions of basaltic Martian meteorites (shergottites) and clinopyroxene/olivine cumulate meteorites (nakhlite/chassignites) are used to define the global evolution of Mars. However, the two main groups of meteorites demonstrate that their sources underwent divergent styles of magmatic evolution. The shergottites portray a planet that differentiated ~4.52 billion years ago via solidification of a magma ocean, producing incompatible element-depleted and -enriched reservoirs that remained isolated until melt production. In contrast, the reservoir from which the nakhlite/chassignites derive may have formed earlier, produced melts that fractionated Sm/Nd and Hf/W differently, was compositionally less variable, and experienced a significantly more complex history following primordial differentiation than the shergottite sources. The disparate histories recorded by these two groups of meteorites elucidate important questions that could be addressed by acquiring additional samples. Obtaining samples that shared the isotopic systematics of the shergottites would provide confidence that extrapolating the primordial differentiation history of Mars from shergottite radiogenic isotope systematics is reasonable. Returned samples from Mars will also constrain the physical locations of the meteorite source regions, providing insights into the general structure of the Martian mantle. In addition, they will help constrain the phases present in the martian mantle during melting and the conditions under which they are stable. Finally, identifying an evolved lithology that satisfies the geochemical and isotopic constraints placed on the incompatible element-enriched endmember observed in the shergottites would define the nature of magmatic evolution on Mars and whether it is more akin to processes on the Earth or the Moon.

Mars↗
DOE OSTI2026

Joint Sample Analyses of Nuclear Forensic Materials Provided by the Republic of Kazakhstan: U. S. Laboratory Results

This document serves as an interim report to summarize sample analyses performed by Lawrence Livermore National Laboratory (LLNL) and Los Alamos National Laboratory (LANL) on a series of five nuclear forensics samples provided by the Institute of Nuclear Physics (INP) in the Republic of Kazakhstan. The sample set contains four uranium oxide powders and one low-enriched uranium fuel pellet. The samples were provided as part of a broader collaboration that involved a set of joint sample analyses conducted by INP and the US National Laboratories. The joint analyses are being conducted using well-developed analytical plans. These activities are designed to support the advancement of nuclear forensic science and capacity building in all three institutes in both countries. This report builds upon an earlier preliminary summary of the joint interactions and will be augmented by a final report. The final report will summarize the results and value of all sample analyses performed at the three institutes (INP, LLNL, and LANL). The final report will also provide an intercomparison of the results, analytical methods and best practices employed, as well as outline future collaborative nuclear forensics activities that are being developed in the Kazakhstan region.

and nuclear chemistry↗
NASA NTRS2016

Curating NASA's Past, Present, and Future Astromaterial Sample Collections

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (hereafter JSC curation) is responsible for curating all of NASA's extraterrestrial samples. JSC presently curates 9 different astromaterials collections in seven different clean-room suites: (1) Apollo Samples (ISO (International Standards Organization) class 6 + 7); (2) Antarctic Meteorites (ISO 6 + 7); (3) Cosmic Dust Particles (ISO 5); (4) Microparticle Impact Collection (ISO 7; formerly called Space-Exposed Hardware); (5) Genesis Solar Wind Atoms (ISO 4); (6) Stardust Comet Particles (ISO 5); (7) Stardust Interstellar Particles (ISO 5); (8) Hayabusa Asteroid Particles (ISO 5); (9) OSIRIS-REx Spacecraft Coupons and Witness Plates (ISO 7). Additional cleanrooms are currently being planned to house samples from two new collections, Hayabusa 2 (2021) and OSIRIS-REx (2023). In addition to the labs that house the samples, we maintain a wide variety of infra-structure facilities required to support the clean rooms: HEPA-filtered air-handling systems, ultrapure dry gaseous nitrogen systems, an ultrapure water system, and cleaning facilities to provide clean tools and equipment for the labs. We also have sample preparation facilities for making thin sections, microtome sections, and even focused ion-beam sections. We routinely monitor the cleanliness of our clean rooms and infrastructure systems, including measurements of inorganic or organic contamination, weekly airborne particle counts, compositional and isotopic monitoring of liquid N2 deliveries, and daily UPW system monitoring. In addition to the physical maintenance of the samples, we track within our databases the current and ever changing characteristics (weight, location, etc.) of more than 250,000 individually numbered samples across our various collections, as well as more than 100,000 images, and countless "analog" records that record the sample processing records of each individual sample. JSC Curation is co-located with JSC's Astromaterials Research Office, which houses a world-class suite of analytical instrumentation and scientists. We leverage these labs and personnel to better curate the samples. Part of the cu-ration process is planning for the future, and we refer to these planning efforts as "advanced curation". Advanced Curation is tasked with developing procedures, technology, and data sets necessary for curating new types of collections as envi-sioned by NASA exploration goals. We are (and have been) planning for future cu-ration, including cold curation, extended curation of ices and volatiles, curation of samples with special chemical considerations such as perchlorate-rich samples, and curation of organically- and biologically-sensitive samples.

Zeigler, R. A.↗
DOE OSTI2026

Construction of generalized quasilinear diffusion coefficient using neural networks with physical restrictions

The quasilinear diffusion coefficient (D QL ) derived from our machine learning framework shows comparable trends with the ground truth D QL obtained from GENRAY-CQL3D simulations. Additionally, for the strong absorption cases, the radial current drive profiles generated using the D QL from our model exhibit consistent behavior with those obtained from the original simulation. These findings indicate the potential of our surrogate modeling approach with physical restrictions to replicate key wave–plasma interaction characteristics while reducing computational costs. Traditionally, calculating D QL for wave–particle interactions relies on computationally intensive wave simulations coupled with Fokker–Planck solvers. To address this challenge, we developed a machine learning-based surrogate model with physical restrictions derived from cold plasma theory and bounce-averaged damping effects. First, we establish the propagation domain of Lower Hybrid Waves in the (N∥, ρ) space by identifying the accessibility limit and determining the upper and lower bounds of N∥ using the Potential Power Deposition (PPD) method. Subsequently, leveraging a database constructed using Latin hypercube sampling alongside the underlying physical restrictions (e.g. PPD), machine learning methods including U-Net and Recurrent Neural Networks are employed to design a physics-restricted machine learning framework capable of reconstructing D QL .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Plasma heating for containerless and microgravity materials processing

A method for plasma heating of levitated samples to be used in containerless microgravity processing is disclosed. A sample is levitated by electrostatic, electromagnetic, aerodynamic, or acoustic systems, as is appropriate for the physical properties of the particular sample. The sample is heated by a plasma torch at atmospheric pressure. A ground plate is provided to help direct the plasma towards the sample. In addition, Helmholtz coils are provided to produce a magnetic field that can be used to spiral the plasma around the sample. The plasma heating system is oriented such that it does not interfere with the levitation system.

Leung, Emily W.↗
DOE OSTI2020

Pool boiling critical heat flux studies of accident tolerant fuel cladding materials

Pool boiling experiments have been performed at atmospheric pressure on potential accident tolerant fuel (ATF) cladding materials (Zirlo®, Cr coated Zirlo®, FeCrAl coated Zirlo®, and monolithic SiC) to evaluate the Critical Heat Flux (CHF) points. Corrosion resistant coatings of Cr and FeCrAl alloy were deposited on flat Zirlo® samples using cold spray technology. The as-prepared samples after uniform surface polishing were subjected to autoclave tests at 360 °C water and 18.6 MPa for 360 h to simulate prototypic corrosion of the ATF cladding materials in LWR normal operation. Surface characteristics potentially influencing CHF such as surface morphology, roughness, static contact angle, and surface chemistry were characterized using a suite of characterization methods including scanning electron microscopy, 3D optical profilometry, optical contact angle measurements, and x-ray photoelectron spectroscopy (XPS). Thermo-physical properties of the samples such as density, thermal conductivity, and heat capacity were measured by differential scanning calorimetry and laser flash thermal diffusivity measurement. FeCrAl coatings showed CHF values comparable to bare Zirlo® samples, while slightly lower CHF values were observed for Cr coated samples and bulk SiC flats (produced by chemical vapor deposition, CVD). As-deposited Cr coatings showed 67% higher CHF than the as-polished Cr coatings due to its higher surface roughness level. The autoclave testing for the prepared samples generally increased the CHF except for the surface polished Cr coatings. Similar CHF values of bare Zirlo®, FeCrAl coating, and CVD SiC samples were observed after autoclave test but there were negligible change CHF of Cr coatings. XPS studies indicated that the formation or deposition of a few monolayers of hydrophobic carbonaceous species on surface can affect CHF values. The trends in CHF data are discussed in terms of evolution of the surface characteristics of the ATF materials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Overview of high-density QCD studies with the CMS experiment at the LHC

We review key measurements performed by CMS in the context of its heavy ion physics program, using event samples collected in 2010-2018 with several collision systems and energies. These studies provide detailed macroscopic and microscopic probes of the quark-gluon plasma (QGP) created at the LHC energies, a medium characterized by the highest temperature and smallest baryon-chemical potential ever reached in the laboratory. Numerous observables related to high-density quantum chromodynamics (QCD) were studied, leading to some of the most impactful and qualitatively novel results in the 40-year history of the field. Using a dedicated high-multiplicity trigger in the first pp run, CMS discovered that small collision systems can exhibit signs of collectivity, a generic phenomenon with significant implications and presently understood to affect essentially all soft physics processes. This observation opened new paths to understand how fluidity and plasma properties emerge in QCD matter as a function of system size. Measurements of jet quenching have reached a completely new level of detail by directly assessing, for the first time, the medium modification of parton showers, as opposed to simply observing leading hadrons or di-hadrons. The first fully reconstructed beauty hadron and heavy-flavor jet nuclear modifications were also measured. The large size of the event samples, the precision of the measurements, and the extension of the probed kinematical phase space, allowed many other hard probes of the QGP medium to be explored in detail, leading to multiple groundbreaking findings. In particular, the seminal measurements of bottomonium suppression patterns answer fundamental questions that have been actively pursued, both theoretically and experimentally, by the community since the mid-1980s. We conclude by outlining the opportunities offered by the continuation of this physics program at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2018

Applying Modern Analytical Techniques to the Apollo Samples: A Potential Model for Future Sample Return Missions

From 1969-1972 the Apollo missions collected 382 kg of lunar samples from six distinct locations on the Moon. Studies of the Apollo sample suite have shaped our understanding of the formation and early evolution of the Earth-Moon system, and have had important implications for studies of the other terrestrial planets (e.g., through the calibration of the crater counting record). Despite nearly 50 years of research on Apollo samples, scientists are still developing new theories about the origin and evolution of the Moon. In order to resolve these questions, scientists need access to new lunar samples, particularly new plutonic samples. Although no new large plutonic samples (i.e., hand-samples) remain to be discovered in the Apollo sample collection, there are many large polymict breccias in the Apollo collection containing relatively large (1 cm or larger) previously identified plutonic clasts, as well as a large number of unclassified lithic clasts. In addition, new, previously unidentified plutonic clasts are potentially discoverable within these breccias. The question becomes how to non-destructively locate and identify new lithic clasts of interest while minimizing the contamination and physical degradation of the samples.

Zeigler, Ryan A.↗
NASA NTRS2015

Using Technology to Better Characterize the Apollo Sample Suite: A Retroactive PET Analysis and Potential Model for Future Sample Return Missions

From 1969-1972 the Apollo missions collected 382 kg of lunar samples from six distinct locations on the Moon. Studies of the Apollo sample suite have shaped our understanding of the formation and early evolution of the Earth-Moon system, and have had important implications for studies of the other terrestrial planets (e.g., through the calibration of the crater counting record) and even the outer planets (e.g., the Nice model of the dynamical evolution of the Solar System). Despite nearly 50 years of detailed research on Apollo samples, scientists are still developing new theories about the origin and evolution of the Moon. Three areas of active research are: (1) the abundance of water (and other volatiles) in the lunar mantle, (2) the timing of the formation of the Moon and the duration of lunar magma ocean crystallization, (3) the formation of evolved lunar lithologies (e.g., granites) and implications for tertiary crustal processes on the Moon. In order to fully understand these (and many other) theories about the Moon, scientists need access to "new" lunar samples, particularly new plutonic samples. Over 100 lunar meteorites have been identified over the past 30 years, and the study of these samples has greatly aided in our understanding of the Moon. However, terrestrial alteration and the lack of geologic context limit what can be learned from the lunar meteorites. Although no "new" large plutonic samples (i.e., hand-samples) remain to be discovered in the Apollo sample collection, there are many large polymict breccias in the Apollo collection containing relatively large (approximately 1 cm or larger) previously identified plutonic clasts, as well as a large number of unclassified lithic clasts. In addition, new, previously unidentified plutonic clasts are potentially discoverable within these breccias. The question becomes how to non-destructively locate and identify new lithic clasts of interest while minimizing the contamination and physical degradation of the samples.

Zeigler, R. A.↗
DOE OSTI2023

Simulating lossy Gaussian boson sampling with matrix-product operators

Gaussian boson sampling, a computational model that is widely believed to admit quantum supremacy, has already been experimentally demonstrated and is claimed to surpass the classical simulation capabilities of even the most powerful supercomputers today. However, whether the current approach limited by photon loss and noise in such experiments prescribes a scalable path to quantum advantage is an open question. Here, to understand the effect of photon loss on the scalability of Gaussian boson sampling, we analytically derive the asymptotic operator entanglement entropy scaling, which relates to the simulation complexity. As a result, we observe that efficient tensor network simulations are likely possible under the N out ∝ √N scaling of the number of surviving photons N out in the number of input photons N. We numerically verify this result using a tensor network algorithm with U⁡(1) symmetry, and we overcome previous challenges due to the large local Hilbert-space dimensions in Gaussian boson sampling with hardware acceleration. Additionally, we observe that increasing the photon number through larger squeezing does not increase the entanglement entropy significantly. Finally, we numerically find the bond dimension necessary for fixed accuracy simulations, providing more direct evidence for the complexity of tensor networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1981

A complete X-ray sample of the high latitude sky from HEAO-1 A-2: log N lo S and luminosity functions

An experiment was performed in which a complete X-ray survey of the 8.2 steradians of the sky at galactic latitudes where the absolute value of b is 20 deg down to a limiting sensitivity of 3.1 x ten to the minus 11th power ergs/sq cm sec in the 2-10 keV band. Of the 85 detected sources 17 were identified with galactic objects, 61 were identified with extragalactic objects, and 7 remain unidentified. The log N - log S relation for the non-galactic objects is well fit by the Euclidean relationship. The X-ray spectra of these objects were used to construct log N - log S in physical units. The complete sample of identified sources was used to construct X-ray luminosity functions, using the absolute maximum likelihood method, for clusters galaxies and active galactic nuclei.

Piccinotti, G.↗
DOE OSTI2021

Collective Summary of sCO2 Materials Development (Supercritical Transformational Electric Power Generation (STEP) Level 2 Milestone Report) (Parts I - II)

Polymers such as PTFE (polytetrafluorethylene or Teflon), EPDM (ethylene propylene diene monomer) rubber, FKM fluoroelastomer (Viton), Nylon 11, Nitrile butadiene (NBR) rubber, hydrogenated nitrile rubber (HNBR) and perfluoroelastomers (FF_202) are commonly employed in super critical CO 2 (sCO2) energy conversion systems. O-rings and gaskets made from these polymers face stringent performance conditions such as elevated temperatures, high pressures, pollutants, and corrosive humid environments. In FY 2019, we conducted experiments at high temperatures (100°C and 120°C) under isobaric conditions (20 MPa). Findings showed that elevated temperatures accelerated degradation of polymers in sCO2, and that certain polymer microstructures are more susceptible to degradation over others. In FY 2020, the focus was to understand the effect of sCO2 on polymers at low (10 MPa) and high pressures (40 MPa) under isothermal conditions (100°C). It was clear that the same selectivity was observed in these experiments wherein certain polymeric functionalities showed more propensity to failure over others. Fast diffusion, supported by higher pressures and long exposure times (1000 hours) at the test temperature, caused increased damage in sCO2 environments to even the most robust polymers. We also looked at polymers under compression in sCO2 at 100°C and 20 MPa pressure to imitate actual sealing performance required of these materials in sCO2 systems. Compression worsened the physical damage that resulted from chemical attack of the polymers under these test conditions. In FY 2021, the effect of cycling temperature (from 50°C to 150°C to 50°C) for polymers under a steady sCO2 pressure of 20 MPa was studied. The aim was to understand the influence of cycling temperatures of sCO2 for typical polymers under isobaric (20 MPa) conditions. Thermoplastic polymers (Nylon, and PTFE) and elastomers (EPDM, Viton, Buna N, Neoprene, FF202, and HNBR) were subjected to 20 MPa sCO2 pressure for 50 cycles and 100 cycles in separate experiments. Samples were extracted for ex-situ characterization at 50 cycles and upon the completion of 100 cycles. Each cycle constituted of 175 minutes of cycling from 50°C to 150°C. The polymer samples were examined for physical and chemical changes by Dynamic Mechanical and Thermal Analysis (DMTA), Fourier Transform Infrared (FTIR) spectroscopy, and compression set. Density and mass changes immediately after removal from test were measured for degree of swell comparisons. Optical microscopy techniques and micro computer tomography (micro CT) images were collected on select specimens. Evaluations conducted showed that exposures to super-critical CO2 environments resulted in combinations of physical and/or chemical changes. For each polymer, the dominance of cycling temperatures under sCO2 pressures, were evaluated. Attempts were made to qualitatively link the permanent sCO2 effects to polymer micro- structure, free volume, backbone substitutions, presence of polar groups, and degree of crystallinity differences. This study has established that soft polymeric materials are conducive to failure in sCO2 through mechanisms of failure that are dependent on polymer microstructure and chemistry. Polar pendant groups, large atom substitutions on the backbone are some of the factors that are influential structural factors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗