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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 919 records · Page 51

Crack Growth Rate and Fracture Toughness Tests on Irradiated Ex-Plant Materials

The performance of structural materials is critical for the safe and economic operation of light water reactors. Exposed to neutron irradiation during service, the reactor core internal materials can undergo significant microstructural and microchemical changes, leading to irradiation hardening and embrittlement. To ensure the structural integrity and functionality of nuclear reactor components during long-term operation, material degradation and damage mechanisms must be understood and managed adequately. In this work, irradiated materials harvested from the decommissioned Zorita reactor were studied for their cracking susceptibility and fracture resistance as a function of irradiation dose up to 47 displacement per atom (dpa). The material is a Type 304 stainless steel sectioned from the baffle plates of this pressurized water reactor with 38 years of service. Crack growth rate and fracture toughness J-resistance (J-R) curve tests were performed in low-corrosion-potential environments at ~315°C. All samples behaved similarly under cyclic loading, and no deteriorated corrosion-fatigue behavior was observed in the test environments. Under constant stress intensity factors, most samples did not show elevated crack growth rates, suggesting an adequate stress corrosion cracking resistance in the test environments. However, an unstable cracking behavior was observed in a 47-dpa sample, resulting in significantly higher crack growth rates than expected at high stress intensity factors. Crack instability was also observed in a 0.06-dpa sample but did not lead to a sustained high crack growth rate. The impact of neutron irradiation was more evident in the fracture toughness J-R curve tests. As the dose increased, the J-R curve declined considerably and became very shallow at high doses. A fully intergranular fracture morphology was also observed among the high-dose samples ruptured in an air atmosphere at room temperature. This brittle fracture mode in the absence of high temperature water environment confirmed a high degree of embrittlement of this material resulting from its service exposure to neutron irradiation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Mooring Lines for Marine Energy Workshop – Summary Report

This report summarizes the outcomes of the virtual Advanced Mooring Lines for Marine Energy Workshop. The workshop convened experts from industry, academia, and national laboratories to identify key challenges associated with the deployment of synthetic mooring lines for marine energy applications. Discussions focused on four technical areas—materials, failure and degradation, testing, and modeling. Despite the significant promise of leveraging synthetic mooring systems for marine energy applications, discussion highlighted broader research and development needed to address the lack of validated long-term performance data, insufficient structural health monitoring frameworks, limited large-scale testing capabilities, and gaps in predictive modeling. Overall, the workshop emphasized the importance of coordinated research and development efforts to advance reliable, durable, and cost-effective synthetic mooring solutions for marine energy applications.

16 TIDAL AND WAVE POWER↗

Evaluation of Optical Fiber Bragg Gratings in a Nuclear Reactor

Optical fiber-based sensors are capable of distributed temperature and/or strain measurements with high accuracy and sub-cm spatial resolution. Optical fibers have a small diameter ({approx}100 {mu}m), a small mass (and therefore fast response time), and are fabricated from high temperature-tolerant, radiation-hard materials. These qualities make optical fiber-based instrumentation a promising candidate for in-pile sensing applications, monitoring fuel performance during irradiation in test reactors, or embedding fibers in other commercial reactor components or structures. The Department of Energy and Idaho National Laboratory are restarting the TREAT reactor (Transient Reactor Test facility) and are interested in updating the reactor's instrumentation regarding the analysis of the test fuel. The ability of optical fibers to make distributed temperature measurements coupled with its small footprint makes optical fiber a viable candidate to monitor fuel performance in the TREAT reactor. The work presented in this paper focuses on the radiation hardness of various types of optical fiber Bragg gratings. Previous experiments have shown that the inscription of Bragg gratings into optical fiber can extend the radiation survivability of distributed sensing in optical fibers, and so the goal is to determine which types of Bragg gratings survive the best in a reactor environment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of a Miniature Small Punch Creep Test for Post Surveillance Test Specimens

Summary: This poster outlines a new small punch creep test (SPCT) for examining the mechanical properties of post surveillance test specimens. A surveillance test article was previously designed to study the effects of Molten-Salt conditions on the structural materials in the reactor. To better understand the post-test mechanical properties of the specimen, a miniature SPCT is proposed. The principle, testing standards and challenges of the method is introduced in the poster. An initial design of the testing apparatus is shown, and an experiment plan is outlined.

36 MATERIALS SCIENCE↗

Structure-property relationships and recyclability of natural fiber insulation

Thermal insulation can significantly decrease the energy required to maintain internal temperatures within buildings, saving money and decreasing environmental impacts. Many industrially available insulation options utilize petroleum-derived materials, such as polyurethane, fiberglass, and polystyrene, which can be detrimental to the environment by emitting greenhouse gases during production. A sustainable alternative to these synthetic insulations is the use of renewable feedstocks to produce comparable insulation products. In this work, natural fibers such as flax and banana were bound with an epoxy system to produce natural-fiber insulation. Key experimental parameters for this study included evaluating the fiber lengths and processing methods while varying the viscosity of the epoxy binder solvent dissolution. Insulation performance was determined by comparing density, thermal conductivity, resilience, and compressive strength; these parameters were tested to further understand and investigate the structure- property relationships within the system and to understand how these composites compare to current commercial materials. Furthermore, from this characterization and optimization, a natural fiber sample with an R/in. >5 was achieved, making these materials competitive with commercial alternatives.

Compressive strength↗

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with information on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.

97 MATHEMATICS AND COMPUTING↗

Divergence in land surface modeling: linking spread to structure

Divergence in land carbon cycle simulation is persistent and widespread. Regardless of model intercomparison project, results from individual models diverge significantly from each other and, in consequence, from reference datasets. Here we link model spread to structure using a 15-member ensemble of land surface models from the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as a test case. Our analysis uses functional benchmarks and model structure as predicted by model skill in a machine learning framework to isolate discrete aspects of model structure associated with divergence. We also quantify how initial conditions prejudice present-day model outcomes after centennial-scale transient simulations. Overall, the functional benchmark and machine learning exercises emphasize the importance of ecosystem structure in correctly simulating carbon and water cycling, highlight uncertainties in the structure of carbon pools, and advise against hard parametric limits on ecosystem function. We also find that initial conditions explain 90% of variation in global satellite-era values—initial conditions largely predetermine transient endpoints, historical environmental change notwithstanding. As MsTMIP prescribes forcing data and spin-up protocol, the range in initial conditions and high levels of predetermination are also structural. Our results suggest that methodological tools linking divergence to discrete aspects of model structure would complement current community best practices in model development.

58 GEOSCIENCES↗

Physics with CEBAF at 12 GeV and future opportunities

Here, we summarize the ongoing scientific program of the 12 GeV Continuous Electron Beam Accelerator Facility (CEBAF) and give an outlook into future opportunities. The program addresses important topics in nuclear, hadronic, and electroweak physics, including nuclear femtography, meson and baryon spectroscopy, quarks and gluons in nuclei, precision tests of the standard model and dark sector searches. Potential upgrades of CEBAF and their impact on scientific reach are discussed, such as higher luminosity, the addition of polarized and unpolarized positron beams, and doubling the beam energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modal Analysis and Testing of a Cantilever Beam: Results and Guide

This report discusses modal analysis and testing of a cantilever beam including an introduction to modal testing, simulation, analysis, and a comparison of results. An accompanying presentation can be found from the LLNL CASIS website. Modal testing and analysis are essential for characterizing the response of a structure during vibration environments. Determining natural frequencies and mode shapes helps determine whether resonances will be reached during operations and if so, how the structure will respond and how the response can be tuned. The goal of this work is to convey the basics of modal testing and analysis through a simple project. This can be applied later to more complex, applicable structures. This includes a variety of work including data collection, finite element analysis and data processing. For this project a cantilever beam was chosen because it is a simple, well-characterized structure.

42 ENGINEERING↗

Deep convolutional autoencoders as generic feature extractors in seismological applications

The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for different seismological applications, such as event discrimination (i.e., earthquake vs. noise waveforms, earthquake vs. explosion waveforms), and phase picking. These tests involve training an autoencoder, either undercomplete or overcomplete, on a large amount of earthquake waveforms, and then using the trained encoder as a feature extractor with subsequent application layers (either a fully connected layer, or a convolutional layer plus a fully connected layer) to make the decision. By comparing the performance of these newly designed models against the baseline models trained from scratch, we conclude that the autoencoder feature extractor approach may only outperform the baseline under certain conditions, such as when the target problems require features that are similar to the autoencoder encoded features, when a relatively small amount of training data is available, and when certain model structures and training strategies are utilized. The model structure that works best in all these tests is an overcomplete autoencoder with a convolutional layer and a fully connected layer to make the estimation.

58 GEOSCIENCES↗

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 3f Raw Data

XPS of Si/GaN photocathode after 10 hour chronoamperometry (CA) testing. Surface chemical composition and valence band structure of GaN were obtained by X-ray photoemission spectroscopy (XPS) on a Kratos Axis Ultra DLD system at a takeoff angle of 0° relative to the surface normal. An Al Kα source (hν = 1486.6 eV) was used to excite the core level electrons. Pass energy of 20 eV was used for the narrow scan of core levels and valence band spectra, and step size of 0.05 eV and 0.025 eV, respectively. The Spectral fitting was conducted using CasaXPS analysis software. The binding energy scales of all core levels were corrected to the N 1s of Ga – N bond at 397.8 eV. XPS O1s core level spectra from 10 hours CA tested Si/GaN sample, and deconvolution shows O - Ga bond, O - N - Ga bond and OH - H2O bond.

photocathode↗

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 3e Raw Data

XPS of Si/GaN photocathode after 4 hour chronoamperometry (CA) testing. Surface chemical composition and valence band structure of GaN were obtained by X-ray photoemission spectroscopy (XPS) on a Kratos Axis Ultra DLD system at a takeoff angle of 0° relative to the surface normal. An Al Kα source (hν = 1486.6 eV) was used to excite the core level electrons. Pass energy of 20 eV was used for the narrow scan of core levels and valence band spectra, and step size of 0.05 eV and 0.025 eV, respectively. The Spectral fitting was conducted using CasaXPS analysis software. The binding energy scales of all core levels were corrected to the N 1s of Ga – N bond at 397.8 eV. XPS O1s core level spectra from 4 hour CA tested Si/GaN sample, and deconvolution shows O - Ga bond, O - N - Ga bond and OH - H2O bond.

photocathode↗

Long-Term Stability of Ferri-/Ferrocyanide as an Electroactive Component for Redox Flow Battery Applications: On the Origin of Apparent Capacity Fade

We assess the suitability of potassium ferri-/ferrocyanide as an electroactive species for long-term utilization in aqueous organic redox flow batteries. A series of electrochemical and chemical characterization experiments was performed to distinguish between structural decomposition and apparent capacity fade of ferri-/ferrocyanide solutions used in the capacity-limiting side of a flow battery. Our results indicate that, in contrast with previous reports, no structural decomposition of ferri-/ferrocyanide occurs at tested pH values as high as 14 in the dark or in diffuse indoor light. Instead, an apparent capacity fade takes place due to a chemical reduction of ferricyanide to ferrocyanide, via chemical oxygen evolution reaction. We find that this parasitic process can be further exacerbated by carbon electrodes, with apparent capacity fade rates at pH 14 increasing with an increased ratio of carbon electrode surface area to ferricyanide in solution. Based on these results, we report a set of operating conditions that enables the long-duration cycling of alkaline ferri-/ferrocyanide electrolytes and demonstrate how apparent capacity fade rates can be engineered by the initial system setup. If protected from direct exposure to light, the structural stability of ferri-/ferrocyanide anions allows for their practical deployment as electroactive species in long duration energy storage applications.

25 ENERGY STORAGE↗

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 3d Raw Data

XPS of Si/GaN photocathode after 1 hour chronoamperometry (CA) testing. Surface chemical composition and valence band structure of GaN were obtained by X-ray photoemission spectroscopy (XPS) on a Kratos Axis Ultra DLD system at a takeoff angle of 0° relative to the surface normal. An Al Kα source (hν = 1486.6 eV) was used to excite the core level electrons. Pass energy of 20 eV was used for the narrow scan of core levels and valence band spectra, and step size of 0.05 eV and 0.025 eV, respectively. The Spectral fitting was conducted using CasaXPS analysis software. The binding energy scales of all core levels were corrected to the N 1s of Ga – N bond at 397.8 eV. X-ray photoemission spectroscopy (XPS) O1s core level spectra from 1 hour chronoamperometry (CA) tested Si/GaN sample, and deconvolution shows O - Ga bond, O - N - Ga bond, and OH - H2O bond.

photocathode↗

Macroscale structural changes of thylakoid architecture during high light acclimation in Chlamydomonas reinhardtii

Abstract Photoprotection mechanisms are ubiquitous among photosynthetic organisms. The photoprotection capacity of the green alga Chlamydomonas reinhardtii is correlated with protein levels of stress-related light-harvesting complex (LHCSR) proteins, which are strongly induced by high light (HL). However, the dynamic response of overall thylakoid structure during acclimation to growth in HL has not been fully understood. Here, we combined live-cell super-resolution microscopy and analytical membrane subfractionation to investigate macroscale structural changes of thylakoid membranes during HL acclimation in Chlamydomonas . Subdiffraction-resolution live-cell imaging revealed that the overall thylakoid structures became thinned and shrunken during HL acclimation. The stromal space around the pyrenoid also became enlarged. Analytical density-dependent membrane fractionation indicated that the structural changes were partly a consequence of membrane unstacking. The analysis of both an LHCSR loss-of-function mutant , npq4 lhcsr1 , and a regulatory mutant that over-expresses LHCSR, spa1-1 , showed that structural changes occurred independently of LHCSR protein levels, demonstrating that LHCSR was neither necessary nor sufficient to induce the thylakoid structural changes associated with HL acclimation. In contrast, stt7-9 , a mutant lacking a kinase of major light-harvesting antenna proteins, had a slower thylakoid structural response to HL relative to all other lines tested but still showed membrane unstacking. These results indicate that neither LHCSR- nor antenna-phosphorylation-dependent HL acclimation are required for the observed macroscale structural changes of thylakoid membranes in HL conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Detecting isolated resonance curves using fixed frequency voltage control tests

Isolated resonance curves, or isolas, are resonance branches of the harmonically forced system that exist separately from the main nonlinear forced response curve, leading to excessive vibrations. Traditional stepped or swept sine simulations and tests rely on continuation along the frequency parameter, typically resulting in a jump phenomenon along the primary resonance branch, prior to the disconnected isola. The main objective of this research is to propose an approach to identify isolated resonance curves by performing continuation along the input amplitude that initializes the response from a low-amplitude solution in the linear regime. Furthermore, this is achieved with the open-loop fixed frequency voltage control method that continues along the shaker voltage parameter and measures the so-called S-curves, which are theoretically a continuous solution branch that connect to the isola. The methodology is demonstrated on a fixture-wing-pylon assembly with a vibro-impact nonlinearity localized in a pylon subcomponent attachment. Multi-harmonic balance simulations are deployed to compute both the nonlinear forced response curves and S-curves to demonstrate the isola detection strategy on a reduced-order finite element model of the nonlinear system. Swept sine and fixed frequency voltage control tests are then conducted on the physical structure to demonstrate the isola detection experimentally, revealing the existence of the large amplitude vibrations that are undetected in the forces levels and frequencies measured with traditional frequency sweeping.

Characterization and Analytical Technique↗

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↗

Novel angular velocity estimation technique for plasma filaments

Magnetic field aligned filaments such as blobs and edge localized mode filaments carry significant amounts of heat and particles to the plasma facing components and they decrease their lifetime. The dynamics of these filaments determine at least a part of the heat and particle loads. These dynamics can be characterized by their translation and rotation. In this paper, we present an analysis method novel for fusion plasmas, which can estimate the angular velocity of the filaments on frame-by-frame time resolution. After pre-processing, the frames are two-dimensional (2D) Fourier-transformed, then the resulting 2D Fourier magnitude spectra are transformed to log-polar coordinates, and finally the 2D cross-correlation coefficient function (CCCF) is calculated between the consecutive frames. The displacement of the CCCF’s peak along the angular coordinate estimates the angle of rotation of the most intense structure in the frame. Further, the proposed angular velocity estimation method is tested and validated for its accuracy and robustness by applying it to rotating Gaussian-structures. The method is also applied to gas-puff imaging measurements of filaments in National Spherical Torus Experiment plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗