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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

COMET-AR User's Manual: COmputational MEchanics Testbed with Adaptive Refinement

The COMET-AR User's Manual provides a reference manual for the Computational Structural Mechanics Testbed with Adaptive Refinement (COMET-AR), a software system developed jointly by Lockheed Palo Alto Research Laboratory and NASA Langley Research Center under contract NAS1-18444. The COMET-AR system is an extended version of an earlier finite element based structural analysis system called COMET, also developed by Lockheed and NASA. The primary extensions are the adaptive mesh refinement capabilities and a new "object-like" database interface that makes COMET-AR easier to extend further. This User's Manual provides a detailed description of the user interface to COMET-AR from the viewpoint of a structural analyst.

Moas, E.↗
NASA NTRS1999

Acoustic Studies of the Large Scale Ocean Circulation

Detailed knowledge of ocean circulation and its transport properties is prerequisite to an understanding of the earth's climate and of important biological and chemical cycles. Results from two recent experiments, THETIS-2 in the Western Mediterranean and ATOC in the North Pacific, illustrate the use of ocean acoustic tomography for studies of the large scale circulation. The attraction of acoustic tomography is its ability to sample and average the large-scale oceanic thermal structure, synoptically, along several sections, and at regular intervals. In both studies, the acoustic data are compared to, and then combined with, general circulation models, meteorological analyses, satellite altimetry, and direct measurements from ships. Both studies provide complete regional descriptions of the time-evolving, three-dimensional, large scale circulation, albeit with large uncertainties. The studies raise serious issues about existing ocean observing capability and provide guidelines for future efforts.

Menemenlis, Dimitris↗
NASA NTRS2013

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Figueroa-Vinas, Adolfo↗
NASA NTRS2016

NEEMO 20: Science Training, Operations, and Tool Development

The 20th mission of the National Aeronautics and Space Administration (NASA) Extreme Environment Mission Operations (NEEMO) was a highly integrated evaluation of operational protocols and tools designed to enable future exploration beyond low-Earth orbit. NEEMO 20 was conducted from the Aquarius habitat off the coast of Key Largo, FL in July 2015. The habitat and its surroundings provide a convincing analog for space exploration. A crew of six (comprised of astronauts, engineers, and habitat technicians) lived and worked in and around the unique underwater laboratory over a mission duration of 14-days. Incorporated into NEEMO 20 was a diverse Science Team (ST) comprised of geoscientists from the Astromaterials Research and Exploration Science (ARES/XI) Division from the Johnson Space Center (JSC), as well as marine scientists from the Department of Biological Sciences at Florida International University (FIU). This team trained the crew on the science to be conducted, defined sampling techniques and operational procedures, and planned and coordinated the science focused Extra Vehicular Activities (EVAs). The primary science objectives of NEEMO 20 was to study planetary sampling techniques and tools in partial gravity environments under realistic mission communication time delays and operational pressures. To facilitate these objectives two types of science sites were employed 1) geoscience sites with available rocks and regolith for testing sampling procedures and tools and, 2) marine science sites dedicated to specific research focused on assessing the photosynthetic capability of corals and their genetic connectivity between deep and shallow reefs. These marine sites and associated research objectives included deployment of handheld instrumentation, context descriptions, imaging, and sampling; thus acted as a suitable proxy for planetary surface exploration activities. This abstract briefly summarizes the scientific training, scientific operations, and tool development conducted during NEEMO 20 with an emphasis on the primary lessons learned.

Graff, T.↗
DOE OSTI2024

Seismic Resilience of Large Power Transformer Bushings & Non-SF6 Industrial Base Scan Review

Large (high voltage) power transformers (LPT), and more specifically, their bushings, are known to be susceptible to seismic failure. With bushing failure, a transformer will have to be replaced, which has a considerable lead time, adding to the power outage duration. Cost-efficient, proven solutions are not currently available to mitigate this risk, which can persist for the more than 30-year life of a particular transformer. This work will focus on developing and demonstrating a hardware solution to address seismic vulnerabilities and reduce outage risks from LPT failure. Sulfur Hexafluoride (SF6) is a specialty gas with excellent electrical insulation properties which has been used extensively in the power industry. This gas is unfortunately also one of the most potent greenhouse gases known to humanity. A 2014 report by the Intergovernmental Panel on Climate Change found that SF6 has a global warming potential (GWP) 23,000 times higher than Carbon Dioxide, and has the highest GWP of all gases assessed (Myhre 2013). SF6 is almost exclusively man-made and is produced for use as an insulator in high voltage electrical equipment. This makes the production and use of SF6 one of the leading sources of anthropogenic climate change. To fully eliminate the environmental impacts of SF6, alternative technology is needed. The ideal replacement would be a technology that can fulfil the same role as SF6, at the same cost or cheaper, but without adverse environmental effects. Currently, no technology fits this description, however several promising technologies have begun to enter the market. An industry scan was performed to assess the state of industry adoption and manufacturing capability for SF6-free alternative technologies for use at the high-voltage level, and the primary barriers to broader adoption.

10 SYNTHETIC FUELS↗
DOE OSTI2026

Halo Nuclei from Ab Initio Nuclear Theory

A realistic description of halo nuclei, characterized by low-lying breakup thresholds, requires a proper treatment of continuum effects. We have developed an ab initio approach, the No-Core Shell Model with Continuum (NCSMC), capable of describing both bound and unbound states in light nuclei in a unified way. With chiral two- and three-nucleon interactions as the only input, we can predict the structure and dynamics of halo and other light nuclei and, by comparing to available experimental data, test the quality of chiral nuclear forces. We review NCSMC calculations of weakly bound states and resonances of the exotic halo nuclei 6He, 8B, 11Be, and 15C. For the latter, we discuss its production in the capture reaction 14C(n,𝛾 )15C. We highlight the challenges of a description of 6He as a Borromean n-n-4He system. Finally, we present our calculations of excited states in 10Be exhibiting a one-neutron halo structure and a large scale No-Core Shell Model investigation of 11Li as a precursor of a full n-n-9Li NCSMC study.

Navrátil, Petr↗
NASA NTRS1991

Reusable Reentry Satellite (RRS): Telemetry, Tracking, and Command (TT/C) Coverage Tradeoff Study

The Reusable Reentry Satellite (RRS) Telemetry, Tracking & Command (TT&C) Coverage Tradeoff Study described herein was performed during Part 1 of the RRS Phase B contract. This report is one of several that describes the results of various trade studies performed to arrive at a recommended design for the RRS satellite system. The overall RRS Phase B Study objective is to design a relatively inexpensive satellite to access space for extended periods of time, with eventual recovery of experiments on Earth. The RRS will be capable of: (1) being launched by a variety of expendable launch vehicles; (2) operating in low earth orbit as a free flying unmanned laboratory; and (3) executing an independent atmospheric reentry and soft landing. The RRS will be designed to be refurbished and reused up to three times a year for a period of 10 years. The expected principal use for such a system is research on the effects of variable gravity (0 to 1.5 g) and radiation on small animals, plants, lower life forms, tissue samples, and materials processes. This Summary Report provides a description of the RRS Telemetry, Tracking & Command Analysis performed to study the ground station coverage available to meet RRS requirements. Concepts were considered that used off-the-shelf technology, had generous margins of capability, and high reliability, were easily maintained, cost effective, and were compatible with existing support networks. From this study, a recommended RRS TT&C configuration will be developed.

Source record↗
NASA NTRS2016

X-ray Cryogenic Facility (XRCF) Handbook

The X-ray & Cryogenic Facility (XRCF) Handbook is a guide for planning operations at the facility. A summary of the capabilities, policies, and procedures is provided to enhance project coordination between the facility user and XRCF personnel. This handbook includes basic information that will enable the XRCF to effectively plan and support test activities. In addition, this handbook describes the facilities and systems available at the XRCF for supporting test operations. 1.2 General Facility Description The XRCF was built in 1989 to meet the stringent requirements associated with calibration of X-ray optics, instruments, and telescopes and was subsequently modified in 1999 & 2005 to perform the challenging cryogenic verification of Ultraviolet, Optical, and Infrared mirrors. These unique and premier specialty capabilities, coupled with its ability to meet multiple generic thermal vacuum test requirements for large payloads, make the XRCF the most versatile and adaptable space environmental test facility in the Agency. XRCF is also recognized as the newest, most cost effective, most highly utilized facility in the portfolio and as one of only five NASA facilities having unique capabilities. The XRCF is capable of supporting and has supported missions during all phases from technology development to flight verification. Programs/projects that have benefited from XRCF include Chandra, Solar X-ray Imager, Hinode, and James Webb Space Telescope. All test programs have been completed on-schedule and within budget and have experienced no delays due to facility readiness or failures. XRCF is currently supporting Strategic Astrophysics Technology Development for Cosmic Origins. Throughout the years, XRCF has partnered with and continues to maintain positive working relationships with organizations such as ATK, Ball Aerospace, Northrop Grumman Aerospace, Excelis (formerly Kodak/ITT), Smithsonian Astrophysical Observatory, Goddard Space Flight Center, University of Alabama Huntsville, and more.

XRCF↗
NASA NTRS1972

Synchronous meteorological satellite system description document, volume 4

The command and data acquisition (CDA) station for the Synchronous Meteorological Satellite (SMS) program, located on the Eastern shore of Virginia, is described in terms of facility layout, ground support instrumentation, and capabilities. Data systems and equipment are described in detailed block diagrams. The major subsystems are identified and information on equipment specifications, frequency ranges, and data processing format is given. Automatic picture transmission, data utilization stations, data collection platforms, and the various communication links from the CDA station to the SMS spacecraft are discussed.

Lahzun, J.↗
NASA NTRS1983

Future Imaging Sensor Capabilities

Advanced imaging sensor technologies that are being developed for future NASA earth observation missions are discussed. These include the multilinear array, the Shuttle imaging spectrometer, and the Shuttle imaging radar. The principal specifications and functional descriptions of the instruments are presented, and it is shown that the advanced technologies will enable a synergistic approach to the use of VIS/IR and microwave imaging sensors for remote sensing research and applications. The key problems posed by these future imaging sensor technologies are discussed, with particular attention given to data rates, power consumption, and data processing.

Carver, K. R.↗
NASA NTRS2017

Modeling Microgravity Induced Fluid Redistribution Autoregulatory and Hydrostatic Enhancements

Space flight induces a marked cephalad (headward) redistribution of blood and interstitial fluid potentially resulting in a loss of venous tone and reduction in heart muscle efficiency upon introduction into the microgravity environment. Using various types of computational models, we are investigating how this fluid redistribution may induce intracranial pressure changes, relevant to reported reductions in astronaut visual acuity, part of the Visual Impairment and Intracranial Pressure (VIIP) syndrome. Methods: We utilize a lumped parameter cardiovascular system (CVS) model, augmented by compartments comprising the cerebral spinal fluid (CSF) space, as the primary tool to describe how microgravity, and the associated lack of hydrostatic gradient, impacts fluid redistribution. Models of ocular fluid pressures and biomechanics then accept the output of the above model as boundary condition input to allow more detailed, local analysis (see IWS Abstract by Ethier et al.). Recently, we enhanced the capabilities our previously reported CVS model through the implementation of robust autoregulatory mechanisms and a more fundamental approach to the implementation of hydrostatic mechanisms. Modifying the approach of Blanco et al., we implemented auto-regulation in a quasi-static manner, as an averaged effect across the span of one heartbeat. This approach reduced the higher frequency perturbations from the regulatory mechanism and was intended to allow longer simulation times (days) than models that implement within-beat regulatory mechanisms (minutes). A more fundamental approach to hydrostatics was implemented by a quasi-1D approach, in which compartment descriptions include compartment length, orientation and relative position, allowed for modeling of body orientation, relative body positioning and, in the future, alternative gravity environments. At this time the inclusion of hydrostatic mechanisms supplies additional capabilities to train and validate the CVS model with terrestrial data. Results and Conclusions: With the implementation of auto-regulation and hydrostatic modeling capabilities, the model performs as expected in the maintaining the CA (Central Artery) compartment pressure when simulating orientations ranging from supine to standing. The model appears to generally overpredict heart rate and thus cardiac output, possibly indicating sensitivity to the nominal heart rate, which is used as an initial set point of the regulation mechanisms. Despite this sensitivity, the model performs consistently for many hours of simulation time, indicating the success of our quasi-static implementation approach.

biomechanics↗
NASA NTRS2008

Cammp Team

The International Space Station (ISS) Configuration Analysis Modeling and Mass Properties (CAMMP) Team is presenting a demo of certain CAMMP capabilities at a Booz Allen Hamilton conference in San Antonio. The team will be showing pictures of low fidelity, simplified ISS models, but no dimensions or technical data. The presentation will include a brief description of the contract and task, description and picture of the Topology, description of Generic Ground Rules and Constraints (GGR&C), description of Stage Analysis with constraints applied, and wrap up with description of other tasks such as Special Studies, Cable Routing, etc. The models include conceptual Crew Exploration Vehicle (CEV) and Lunar Lander images and animations created for promotional purposes, which are based entirely on public domain conceptual images from public NASA web sites and publicly available magazine articles and are not based on any actual designs, measurements, or 3D models. Conceptual Mars rover and lander are completely conceptual and are not based on any NASA designs or data. The demonstration includes High Fidelity Computer Aided Design (CAD) models of ISS provided by the ISS 3D CAD Team which will be used in a visual display to demonstrate the capabilities of the Teamcenter Visualization software. The demonstration will include 3D views of the CAD models including random measurements that will be taken to demonstrate the measurement tool. A 3D PDF file will be demonstrated of the Blue Book fidelity assembly complete model with no vehicles attached. The 3D zoom and rotation will be displayed as well as random measurements from the measurement tool. The External Configuration Analysis and Tracking Tool (ExCATT) Microsoft Access Database will be demonstrated to show its capabilities to organize and track hardware on ISS. The data included will be part numbers, serial numbers, historical, current, and future locations, of external hardware components on station. It includes dates of all external ISS events and flights and the associated hardware changes for each event. The hardware location information does not always reveal the exact location of the hardware, only the general location. In some cases the location is a module or carrier, in other cases it is a WIF socket, handrail, or attach point. Only small portions of the data will be displayed for demonstration purposes.

Evertt, Shonn F.↗
NASA NTRS1973

SIRU development. Volume 3: Software description and program documentation

The development and initial evaluation of a strapdown inertial reference unit (SIRU) system are discussed. The SIRU configuration is a modular inertial subsystem with hardware and software features that achieve fault tolerant operational capabilities. The SIRU redundant hardware design is formulated about a six gyro and six accelerometer instrument module package. The six axes array provides redundant independent sensing and the symmetry enables the formulation of an optimal software redundant data processing structure with self-contained fault detection and isolation (FDI) capabilities. The basic SIRU software coding system used in the DDP-516 computer is documented.

Oehrle, J.↗
NASA NTRS1994

Principal Investigator in a Box Technical Description Document

This document provides a brief overview of the PI-in-a-Box system, which can be used for automatic real-time reaction to incoming data. We will therefore outline the current system's capabilities and limitations, and hint at how best to think about PI-in-a-Box as a tool for real-time analysis and reaction in section two, below. We also believe that the solution to many commercial real-time process problems requires data acquisition and analysis combined with rule-based reasoning and/or an intuitive user interface. We will develop the technology reuse potential in section three. Currently, the system runs only on Apple Computer's Macintosh series.

Groleau, Nick↗
DOE OSTI2024

Neural network emulation of spontaneous fission

Large-scale computations of fission properties are an important ingredient for nuclear reaction network calculations simulating rapid neutron-capture process (the 𝑟 process) nucleosynthesis. Due to the large number of fissioning nuclei potentially contributing to the 𝑟 process, a microscopic description of fission based on nuclear density functional theory (DFT) is computationally challenging. Here, we explore the use of neural networks (NNs) to construct DFT emulators capable of predicting potential energy surfaces and collective inertia tensors across the whole nuclear chart, starting from a minimal set of DFT calculations. We use constrained Hartree-Fock-Bogoliubov (HFB) calculations to predict the potential energy and collective inertia tensor in the axial quadrupole and octupole collective coordinates, for a set of nuclei in the 𝑟-process region. We then employ NNs to emulate the HFB energy and collective inertia tensor across the considered region of the nuclear chart. Least-action pathways characterizing spontaneous fission half-lives and fragment yields are then obtained by means of the nudged elastic band method. The potential energy predicted by NNs agrees with the DFT value to within a root-mean-square error of 500 keV, and the collective inertia components agree to within an order of magnitude. These results are largely independent of the NN architecture. The exit points on the outer turning line are found to be well emulated. For the spontaneous fission half-lives the NN emulation provides values that are found to agree with the DFT predictions within a factor of 10 3 across more than 70 orders of magnitude. Neural networks are able to emulate the potential energy and collective inertia well enough to reasonably predict physical observables. Future directions of study, such as the inclusion of additional collective degrees of freedom and active learning, will improve the predictive power of microscopic theory and further enable large-scale fission studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Modeling Codes Used for LAMP

LAMP team is planning on using multiple computer codes as tools for modeling beam dynamics, electromagnetics, and plasma environment in ion sources. Below is a description of the computer tools we have been using or planning to use in the future. Most of the codes chosen for the LAMP project are capable to model most of the beam dynamics in LAMP. A judicious choice of the appropriate code to use will be based on speed and fidelity of the modeling with faster calculations produced by simplifying some features.

43 PARTICLE ACCELERATORS↗
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↗
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↗