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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Triso Analysis Tool For Predictive Source Terms

Source term modeling for TRi-structural ISOtropic (TRISO) fuel has been performed for previous reactor designs, but few are available in the open literature. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that can be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. To meet this need, the TRISO Analysis Tool for Predictive Source terms (TRISO-ATOPS) was developed. This model calculates the release of the key safety-important fission products by diffusion through the kernel, silicon carbide and graphite based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system for removing fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. From this initial condition, the model calculates the fission product release for any transient temperature profile, and the fission product releases can then be used to assess radiological dose to the workers and the public using conventional radiological dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy Advanced Gas Reactor TRISO fuel development program. The example cases in this work demonstrate the flexibility of the model

Stoyer, Benjamin [Idaho National Laboratory (INL),↗
NASA NTRS1975

Fundamental analysis of the failure of polymer-based fiber reinforced composites

A mathematical model predicting the strength of unidirectional fiber reinforced composites containing known flaws and with linear elastic-brittle material behavior was developed. The approach was to imbed a local heterogeneous region surrounding the crack tip into an anisotropic elastic continuum. This (1) permits an explicit analysis of the micromechanical processes involved in the fracture, and (2) remains simple enough to be useful in practical computations. Computations for arbitrary flaw size and orientation under arbitrary applied loads were performed. The mechanical properties were those of graphite epoxy. With the rupture properties arbitrarily varied to test the capabilities of the model to reflect real fracture modes, it was shown that fiber breakage, matrix crazing, crack bridging, matrix-fiber debonding, and axial splitting can all occur during a period of (gradually) increasing load prior to catastrophic failure. The calculations also reveal the sequential nature of the stable crack growth process proceding fracture.

Kanninen, M. F.↗
NASA NTRS1977

Shuttle Experimental Radar for Geological Exploration (SERGE); antenna and integration concept definition study

The baseline configuration defined has the SERGE antenna panel array mounted on the OFT-2 pallet sufficiently high in the bay that negligible amounts of radiation from the beam are reflected from orbiter surfaces into the shuttle payload bay. The array is symmetrically mounted to the pallet along the array long dimension with the pallet at the center. It utilizes a graphite epoxy trusswork support structure. The antenna panels are of SEASAT engineering model design and construction. The antenna array has 7 panels and a 7-way naturally tapered coax corporate feed system. The performance of the system is predicted to exceed 33 db gain, have -15 db sidelobes in the E-plane and even lower in the H-plane, and have and E-plane beamwidth less than 2.2 deg, all within performance specification. The primary support structure is predicted to exceed the specified greater than 25 hertz fundamental frequency, although individual panels will have hertz fundamental frequency.

Kierein, J. W.↗
NASA NTRS1995

Operating capability and current status of the reactivated NASA Lewis Research Center Hypersonic Tunnel Facility

The NASA Lewis Research Center's Hypersonic Tunnel Facility (HTF) is a free-jet, blowdown propulsion test facility that can simulate up to Mach-7 flight conditions with true air composition. Mach-5, -6, and -7 nozzles, each with a 42 inch exit diameter, are available. Previously obtained calibration data indicate that the test flow uniformity of the HTF is good. The facility, without modifications, can accommodate models approximately 10 feet long. The test gas is heated using a graphite core induction heater that generates a nonvitiated flow. The combination of clean-air, large-scale, and Mach-7 capabilities is unique to the HTF and enables an accurate propulsion performance determination. The reactivation of the HTF, in progress since 1990, includes refurbishing the graphite heater, the steam generation plant, the gaseous oxygen system, and all control systems. All systems were checked out and recertified, and environmental systems were upgraded to meet current standards. The data systems were also upgraded to current standards and a communication link with NASA-wide computers was added. In May 1994, the reactivation was complete, and an integrated systems test was conducted to verify facility operability. This paper describes the reactivation, the facility status, the operating capabilities, and specific applications of the HTF.

Thomas, Scott R.↗
NASA NTRS1995

Operating capability and current status of the reactivated NASA Lewis Research Center hypersonic tunnel facility

The NASA Lewis Research Center's Hypersonic Tunnel Facility (HTF) is a free-jet, blowdown propulsion test facility that can simulate up to Mach-7 flight conditions with true air composition. Mach-5, -6, and -7 nozzles, each with a 42-in. exit diameter, are available. Previously obtained calibration data indicate that the test flow uniformity of the HTF is good. The facility, without modifications, can accomodate models approximately 10 ft long. The test gas is heated using a graphite core induction heater that generates a nonvitiated flow. The combination of clean-air, large-scale, and Mach-7 capabilities is unique to the HTF and enables an accurate propulsion performance determination. The reactivation of the HTF, in progress since 1990, includes refurbishing the graphite heater, the steam generation plant, the gaseous oxygen system, and all control systems. All systems were checked out and recertified, and environmental systems were upgraded to meet current standards. The data systems were also upgraded to current standards and a communication link with NASA-wide computers was added. In May 1994, the reactivation was complete, and an integrated systems test was conducted to verify facility operability. This paper describes the reactivation activities, the facility status, the operating capabilities, and specific applications of the HTF.

Thomas, S.↗
NASA NTRS2021

Specific Heat of Epoxies and Mixtures Containing Silica, Carbon Lamp Black, and Graphite

We present specific heat measurements in the 2 – 20 K range of several commercially available epoxies (Stycast 1266, Stycast 2850FT, EPO-TEK 377, and EPO-TEK 377H) and mixtures of one of these epoxy binders and fillers such as silica, carbon lamp black, and graphite. The results are briefly described in the context of the Debye model.

Thermosetting polymers↗
DOE OSTI2020

Impact of Grain Size on Performance Degradation of TREAT LEU

We argue that radiation damage induced degradation of thermal conductivity does not set a lower limit on fuel grain sizes for the low enriched uranium fuel design of the Transient Reactor Test Facility (TREAT). Earlier work reports that smaller grains cause a larger degradation of thermal conductivity than larger grains constraining the smallest feasible size of fuel grains. This work assesses TREAT’s transient performance in the presence of radiation damage. The difference between the two studies is in treating damaged and fresh graphite as serial (this work) or parallel (previous) heat resistors. We use a multiphysics model of TREAT fuel grains to compute the reduction in transient capability measured by the total deposited energy as a function of irradiation dose. We find that radiation damage has a negligible effect on energy deposition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Lithium-ion battery physics and statistics-based state of health model

A pseudo-2d model using COMSOL Multiphysics® software is developed to simulate performance and performance degradation of Li-ion batteries consisting of layered and olivine cathodes with graphite anode when subjected to peak shaving grid service. Multiple degradation pathways are considered, including solid electrolyte interphase (SEI) formation and breakdown at the anode, cathode dissolution and its synergistic effect on SEI formation at the anode. The model is validated by simulating commercial cylindrical cell performance. A global model is developed to simulate performance across all chemistries, along with individual chemistry models using global model parameters as initial values. There is good agreement between these models for various optimization parameters such as SEI equilibrium potential, cathode dissolution exchange current density, solvent diffusivity in the SEI and SEI ionic conductivity. To circumvent time constraints related to the COMSOL model, a 0d global model is developed which fits data well and provides more clarity on differences in cathode dissolution exchange current density. Again, good agreement for various optimization parameters is obtained among the COMSOL global & individual chemistry models and the 0-d model. The lessons learned from the physics-based model is used to develop a top down statistics-based model using current, voltage and anode volumetric change per mole lithium intercalated, along with their interactions as degradation predictors. This model predicts out of sample degradation for multiple grid services and electric vehicle drive cycle with high accuracy and provides the pathway to develop an efficient battery management system combining machine learning and findings from physics-based computationally intensive algorithms.

Crawford, Aladsair J.↗
DOE OSTI2023

Lithium-Ion Battery Diagnostics Using Electrochemical Impedance via Machine-Learning

Diagnosing battery states such as health, state-of-charge, or temperature is crucial for ensuring the safety and reliability of electrochemical energy storage systems. While some states, such as temperature, may be measured using cheap sensors, accurate diagnosis of battery health metrics usually requires time-consuming performance measurements, making them infeasible for use in real-world operation. These health metrics can be measured during lab-testing and then estimated on-line using predictive life models or via state observer algorithms such as Kalman filters, but these predictive methods should be supplemented by actual measurement of battery health whenever possible to ensure reliability. Rapid measurement of battery health may be done by various types of fast diagnostic techniques such as electrochemical impedance spectroscopy (EIS), which can be performed in only a few minutes and require only a fraction of the energy and power needed for a full charge and discharge measurement. But there is a substantial challenge for estimating battery health using EIS data, as EIS is sensitive to cell temperature, state-of-charge, current, and resting time in addition to health. Thus, utilizing EIS data to predict battery capacity requires correcting for all these additional variables, a task that is extremely difficult to handle analytically. This talk utilizes machine-learning methods to estimate the effectiveness of battery capacity prediction from EIS data, leveraging a data set of hundreds of EIS measurements recorded at varying temperature and state-of-charge throughout a 500-day aging study of 32 commercial, large-format NMC-Graphite lithium-ion batteries. Using EIS as input to machine-learning models is complicated by the nonlinear response of impedance to battery health, temperature, and state-of-charge, as well as the collinearity between the impedance response at neighboring frequencies, which can easily lead to overfit models. To train robust models, features from EIS data need to be extracted from the data or some subset of critical frequencies selected. Many approaches for extracting and selecting features from EIS data from electrochemical analysis and machine-learning fields were identified for analysis: using the entire raw spectra; selection of one, two, or many frequencies from the entire spectra; selecting interesting points from the EIS measurement using domain knowledge; fitting EIS with an equivalent-circuit model; calculating statistics on the raw impedance values; and reducing the dimensionality of the data using unsupervised linear (principal component analysis) and non-linear (uniform manifold approximation and projection) methods. These approaches were rigorously compared using a machine-learning pipeline approach, training linear, Gaussian process, and random forest regression models and quantifying performance using cross-validation as well as a held-out test set. An artificial neural network model trained on the raw spectra was also tested. Promising pipelines were fine-tuned via Bayesian hyperparameter optimization using cross-validation loss and training with class-specific weights to counter data set imbalance. The most reliable method for utilizing impedance in this work was the selection of two optimal frequencies through an exhaustive search, resulting in about 2% mean absolute error on test data for both Gaussian process and random forest model architectures. Interrogation of a variety of models reveals critical frequencies of 100 Hz and 103 Hz for this data set, though the optimal set of frequencies is not necessarily intuitive, i.e., the best performing models are not simply those that use impedance at frequencies that have the highest correlation to the relative discharge capacity. The best performing model is an ensemble model, which is able to predict battery capacity with 1.9% mean absolute error for unseen cells using impedance recorded at a variety of temperatures and states-of-charge.

battery↗
DOE OSTI2023

X-ray Absorption Spectroscopy Studies of a Molecular CO 2 -Reduction Catalyst Deposited on Graphitic Carbon Nitride

Metal-ligand complexes have been extensively explored as well-defined molecular catalysts in small molecule activation reactions such as carbon dioxide (CO 2 ) reduction. Many hybrid photocatalysts have been prepared by coupling such complexes with photoactive surfaces for use in solar CO 2 reduction. In this work, we employ X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopies, density functional theory (DFT) and computational XANES modeling to interrogate the structure of a hybrid photocatalyst consisting of a macrocyclic cobalt complex deposited on graphitic carbon nitride (C 3 N 4 ). Results show that the cobalt complex binds on C 3 N 4 through surface OH or NH 2 groups. By refining the local geometry and binding sites of this well-defined molecular cobalt complex on C 3 N 4 , here we established an important benchmark for modeling a large class of molecular catalysts that can be adapted to in situ/operando studies and further enhanced by applying chemometrics-based approaches and machine learning methods of XANES data analysis.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Next-Generation MKIII Lightweight HUT/Hatch Assembly

The MK III (H-1) carbon-graphite/ epoxy Hard Upper Torso (HUT)/Hatch assembly was designed, fabricated, and tested in the early 1990s. The spacesuit represented an 8.3 psi (≈58 kPa) technology demonstrator model of a zero prebreathe suit. The basic torso shell, brief, and hip areas of the suit were composed of a carbon-graphite/epoxy composite lay-up. In its current configuration, the suit weighs approximately 120 lb (≈54 kg). However, since future planetary suits will be designed to operate at 0.26 bar (≈26 kPa), it was felt that the suit's re-designed weight could be reduced to 79 lb (≈35 kg) with the incorporation of lightweight structural materials. Many robust, lightweight structures based on the technologies of advanced honeycomb materials, revolutionary new composite laminates, metal matrix composites, and recent breakthroughs in fullerene fillers and nanotechnology lend themselves well to applications requiring materials that are both light and strong. The major problem involves the reduction in weight of the HUT/ Hatch assembly for use in lunar and/or planetary applications, while at the same time maintaining a robust structural design. The technical objective is to research, design, and develop manufacturing methods that support fa b rica - tion of a lightweight HUT/Hatch assembly using advanced material and geometric redesign as necessary. Additionally, the lightweight HUT/Hatch assembly will interface directly with current MK III hardware. Using the new operating pressure and current MK III (H-1) interfaces as a starting block, it is planned to maximize HUT/Hatch assembly weight reduction through material selection and geometric redesign. A hard upper torso shell structure with rear-entry closure and corresponding hatch will be fabricated. The lightweight HUT/Hatch assembly will retrofit and interface with existing MK III (H-1) hardware elements, providing NASA with immediate "plug-andplay" capability. NASA crewmembers will have a lightweight, robust, life-support system that will minimize fatigue during extraterrestrial surface sojourns. Its unique feature is the utilization of a new and innovative family of materials used by the aerospace industry, which at the time of this reporting has not been used for the proposed application.

McCarthy, Mike↗
DOE OSTI2020

Quantification of Inactive Lithium and Solid–Electrolyte Interphase Species on Graphite Electrodes after Fast Charging

Rapid charging of Li-ion batteries is limited by lithium plating on graphite anodes, whereby Li+ ions are reduced to Li metal on the graphite particle surface instead of inserting between graphitic layers, which directly contributes to cell capacity loss because of the low reversibility of the Li plating/stripping process. Furthermore, precisely identifying the onset and amount of Li plating is therefore vital in order to remedy these issues. We demonstrate a titration technique with a detection limit of 20 nmol (5 × 10 –4 mAh) of Li that can be used to quantify inactive Li that remains on the graphite electrode after fast charging. The titration is extended to quantify the total amount of solid carbonate species and lithium acetylide (Li 2 C 2 ) within the solid–electrolyte interphase (SEI), and electrochemical modeling is used to determine the Li plating exchange current density (10 A/m 2 ) and stripping efficiency (65%) of plated Li metal on graphite. These techniques provide a highly accurate measure of the onset of Li plating and quantitative insight into graphite SEI evolution during fast charging.

25 ENERGY STORAGE↗
DOE OSTI2021

Predictive Battery Lifetime Modeling at NREL [Slides]

Battery lifetime models are used to extrapolate data from accelerated aging tests to simulate degradation in real-world applications such as electric vehicles and battery energy storage systems. Methods developed at NREL utilize both expert domain-knowledge and machine-learning to identify models, using statistical methods such as cross-validation and bootstrap resampling to interrogate model performance and quantify uncertainty. These models can be utilized in systems level simulations to predict battery performance or technoeconomic models to estimate the lifetime cost of battery systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

This report documents the benchmarks being developed and simulations performed using tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, utilizing MSRE experimental data. In FY23, three main work scopes were investigated under the NEAMS MSR work package at ANL. The first scope investigated the Griffin-SAM coupling model for simulating the pump startup transient experiment of MSRE. The analyses start with a simple model (single-channel, single-lattice), gradually adding more details (multi-channel, full-core) into the model. The results show that the reactivity loss curve is very sensitive to the axial boundary conditions and the radial core discretization. The simple model can predict a similar reactivity trend as that of the more sophisticated model, which is likely due to error cancellation. Accurately modeling the axial boundary condition may further improve the reactivity trend but would require significant efforts to generate the mesh of the MSRE inlet and upper plenum. The core channel radial discretization for the Griffin-SAM coupled model also depends on the flow distribution. Given the complex geometry in the inlet plenum, the flow distribution needed to be calculated from CFD analysis, which was performed using the NekRS code. This analysis employed a MSRE CAD model developed by Copenhagen Atomics. The CAD model was disassembled to keep the inlet plenum region only, which was subsequently cleaned and modified so that the mesh generated is under the memory limit. The results are merged to a few radial regions to show that the flow rate is highest in the central region. This would be useful for future improvement of the Griffin-SAM coupling model of the MSRE core. The last task investigated is tritium transport modeling using the standalone SAM code. This task aimed to initiate the effort to demonstrate and validate the tritium transport model implemented in SAM. The preliminary investigation employed an MSRE model consisting of the primary loop. Three tritium transport pathways were examined including the retention in the graphite, the permeation through the HX tube wall, and the removal from the off-gas system. The results compare well with the MSRE data, but improvements are still needed on the initial conditions (i.e., the present state may not have reached equilibrium), the boundary conditions, the off-gas system modeling, and a better numerical strategy to reach the equilibrium state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Reaction path model of the formation of abiotic immiscible hydrocarbon fluids in subducted carbonated serpentinites, Lanzo Massif (Western Italian Alps)

Fluids generated from subducted slabs participate in the cycling of deep carbon in the crust and upper mantle. In these fluids, aqueous carbon species vary in oxidation state between +IV and -IV depending on whether the fluids are oxidizing or reducing, respectively. Most studies of subduction-zone fluids have focused on oxidized carbon species. However, recent studies of natural samples have demonstrated the occurrence of deep, reducing fluids, generated in both subducted oceanic upper mantle and crustal rocks. CH 4 -H 2 -rich fluid inclusions in subducted carbonated serpentinites have demonstrated the existence of abiotic, immiscible, hydrocarbon fluids at upper mantle conditions. To investigate the formation of such immiscible hydrocarbon fluids during the evolution of subducted carbonated serpentinites, we used equilibrium constants from the Deep Earth Water model to carry out predictive chemical mass transfer modeling to simulate the alteration reactions. A novel feature of the models was the inclusion of an immiscible hydrocarbon fluid containing six components (CH 4,f , C 2 H 6,f , C 3 H 8,f , isoC 4 H 10,f , CO 2,f , H 2,f ). This feature enabled prediction of the formation of a separate immiscible fluid in equilibrium with aqueous species and minerals. We developed a predictive reaction path model of invasive H 2,f reacting with carbonated serpentinites and interstitial aqueous fluids for comparison with the natural samples from the Lanzo Massif, western Italian Alps. Over a range of temperatures and pressures, immiscible hydrocarbon fluids formed in association with altered mineral assemblages. Reaction progress caused the transformation of carbonated serpentinites and the formation of clinopyroxene, brucite, graphite, and hydrocarbon fluids, along with changes of pH, logfO 2 , and aqueous species. CH 4,f was the most abundant hydrocarbon species in all the models. The overall results at 2.0 GPa and 400 to 450 °C were consistent with the natural samples from the Lanzo Massif. Interestingly, large amounts of H 2 O formed due to oxidation of H 2 . More hydrocarbons and H 2 O formed in models with lower fluid/rock mass ratios or with more reactant H 2 . Models at different pressure and temperature conditions showed similar results with some variation in the relative stabilities of aragonite, graphite and olivine solid solution, and associated differences in mineral sequences, hydrocarbon fluids, values of aqueous species, and the final log fO 2 and pH. As a result, our models strongly support the laboratory and field evidence that reduction of carbonated serpentinites by infiltrating H 2 fluids can cause the formation of immiscible, abiotic hydrocarbon fluids in subduction zones.

58 GEOSCIENCES↗
DOE OSTI2025

Cavity electrodynamics of van der Waals heterostructures

Van der Waals heterostructures host many-body quantum phenomena that are tunable in situ using electrostatic gates. Their constituent two-dimensional materials and gates can naturally form plasmonic self-cavities, confining light in standing waves of current density due to finite-size effects. The plasmonic resonances of typical graphite gates fall in the gigahertz to terahertz range, corresponding to the same microelectronvolt to millielectronvolt energy scale as the phenomena in van der Waals heterostructures that they electrically control. This raises the possibility that the built-in cavity modes of graphite gates are relevant for shaping the low-energy physics of these heterostructures. However, probing these cavity-coupled electrodynamics is challenging as devices are notably smaller than the diffraction limit at the relevant wavelengths. Here we report on the intrinsic cavity conductivity of gate-tunable graphene heterostructures. As the carrier density is tuned, we observe coupling and spectral weight transfer between graphene and graphite plasmonic cavity modes in the ultrastrong coupling regime. We present an analytical model to describe the results and provide general principles for cavity design. Our findings show that intrinsic cavity effects are important for understanding the low-energy electrodynamics of van der Waals heterostructures and open a pathway for useful functionality through cavity control.

Electronic properties and materials↗