Search NASA⌕ Search

SEARCH · Search NASA

Results for “Metallic Fuel Database”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

101 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Results from the last DD and DT JET campaigns in the framework of the EUROfusion Tokamak Exploitation Work Package activity

JET, the only tokamak capable of operating with deuterium–tritium (D–T) fuel (since TFTR was shutdown in 1999), has provided essential experimental data to support ITER and DEMO design and operation. Within the EUROfusion Tokamak Exploitation Work Package, JET completed its final campaigns (2022–2023), culminating in the third D–T campaign (DTE3). These experiments addressed key challenges in plasma scenarios, exhaust control, and tritium management under reactor-relevant conditions. Significant progress was achieved in demonstrating ITER-like integrated scenarios with impurity seeding, achieving partial divertor detachment and high confinement ($H_{98}(y,2)$ ≈ 0.85) at 3 MA in D–T plasmas. Advanced exhaust regimes such as quasi-continuous exhaust (QCE) and X-point radiator (XPR) were successfully achieved first in D–D and then extended to D–T operation, confirming their relevance for mixed isotope operation. Operational milestones included a new world record of 69 MJ fusion energy in tritium-rich hybrid plasmas and long-pulse H-mode operation up to 60 s, contributing with unique data to the CICLOP database. Physics studies focused on peeling-limited pedestals in support of ITER and improved understanding of edge stability and impurity screening in metallic environments. Extensive usage of the shattered pellet injector (SPI) on JET provided critical information for the design of the ITER disruption mitigation system (DMS). Real-time control systems for D/T ratio control and plasma exhaust were deployed and demonstrated in D–D and D–T, while energetic particle physics investigations unfolded the role of fast ions in turbulence suppression mechanisms. Comprehensive tritium retention studies using gas balance method, post-mortem analysis, and ITER-relevant laser induced desorption spectroscopy (LIDS) diagnostics provided essential input for tritium accountancy strategies. These results are validating the ITER operational concepts, inform DEMO design, and deliver critical experience in nuclear operation and scenario integration.

disruptions↗
DOE OSTI2022

Accelerating the discovery of battery electrode materials through data mining and deep learning models

The availability of crystalline materials databases allows for building accurate machine learning (ML) models that can accelerate the exploration of materials chemical space for energy storage applications. In this work, we screen all inorganic materials included in the Materials Project and AFLOW databases as potential metal-ion battery electrodes. We develop an efficient protocol to mine and screen raw data in current databases and provide a new database of electrode materials by considering pairs of charged and discharged electrodes. This effort leads to a new database with over 190,000 instances, in contrast to the original battery database which contains about 5000. The expanded battery data set is then used to build regression-based deep neural network models for predicting average voltages and percentage volume changes upon charging and discharging, which present improvements of at least 28% for target properties with respect to previous models, and are now able to predict anode electrodes (low voltage region) as well as electrodes that will not work in electrochemical cells (negative voltages), overcoming the challenges identified in previous ML models for battery electrodes. Additionally, a further screening of the expanded database itself allowed us to identify 35 novel electrode candidates with excellent battery performance metrics.

25 ENERGY STORAGE↗
NASA NTRS2026

Polymer Composite Material Testing for a Cryotank Application

Composite cryotanks will play a key role in enabling the next generation of efficient aircraft. Carbon fiber reinforced polymer (CFRP) composites have the benefits of reduced weight and potentially higher structural strength compared to traditional metallic fuel tanks. A material screening study was conducted to inform material selection for liquid hydrogen (LH2) fuel storage. Three composite materials were considered because of their aerospace grade toughness, strength, and existing data to compare against. These materials were a thermoplastic low-melt polyaryletherketone (LM-PAEK)/carbon fiber (CF), thermoset/CF, and hybrid thermoset/thermoplastic polyurethane (TPU) veil/CF composite. Mechanical screening tests included tension, compression, in-plane shear (IPS), and tensile-tensile fatigue (TTF). Each material was tested at both a baseline (no liquid nitrogen/LN2 cycling) and 100 LN2-cycled conditions to determine the knockdown factor, if any, of each material when exposed to environmental loading effects in a cryotank. Results show minimal effects of the LN2-cycling compared against baseline values. The three materials behaved similarly in tension; however, the thermoplastic/CF had the highest IPS toughness. The hybrid thermoset/TPU/CF composite had the lowest IPS strength, compressive strength, and toughness. LN2-cycling had minimal effects on tensile-tensile fatigue performance of the thermoplastic/CF material. Mechanical data was captured to guide material down selection for future commercially viable hydrogen aircraft design. In its current state, there does not exist a consolidated, publicly available database for CFRP composite material performance data at cryogenic temperatures. The next step in this work is to test the thermoplastic and thermoset CFRP composites, as well as the neat resins, at LH2 relevant temperature (20 K) to capture this crucial material property data. These results are essential to inform cryotank design and modeling efforts. The process to start this next round of testing has begun. Planned mechanical tests include toughness (single-edge notched beam), tension (unidirectional and quasi-isotropic), thermal expansion, and thermal conductivity. Some tests will also be conducted at an intermediate temperature of 111 K relevant to liquid natural gas (LNG), another attractive fuel choice. The ultimate goal is to manufacture a sub-scale cryotank part that can pass relevant burst, fatigue, permeation, and thermal cycling tests. This work is a part of NASA’s Commercially viable Hydrogen Aircraft for Robust Growth in Efficiency (CHARGE) Project under the larger NASA Subsonic Vehicle Technologies and Tools (SVTT) Project.

composites↗
DOE OSTI2019

Hydrogen Adsorbents with High Volumetric Density: New Materials and System Projections

A high-capacity, low-cost method for storing hydrogen remains one of the primary barriers to the widespread commercialization of fuel cell vehicles. Storage via adsorption is a promising approach due to its fast kinetics, reversibility, and high gravimetric densities. An unfortunate characteristic of adsorptive storage is that high gravimetric densities typically come at the expense of volumetric density (total basis). The goal of this project is to demonstrate best-in-class adsorbents based on metal-organic frameworks (MOFs) that achieve high volumetric and gravimetric H 2 densities simultaneously, while maintaining reversibility and fast kinetics. This is accomplished using a combination ion of high-throughput computational screening and experimental synthesis and characterization. The performance of the most promising materials are projected to the system level by parameterizing system models developed by the Hydrogen Storage Engineering Center of Excellence (HSECoE).

08 HYDROGEN↗
DOE OSTI2022

Machine learning for design principles for single atom catalysts towards electrochemical reactions

Machine learning (ML) integrated density functional theory (DFT) calculations have recently been used to accelerate the design and discovery of heterogeneous catalysts such as single atom catalysts (SACs) through the establishment of deep structure–activity relationships. Here, this review provides recent progress in the ML-aided rational design of heterogeneous catalysts with the focus on SACs in terms of structure–activity relationships, feature importance analysis, high-throughput screening, stability, and metal–support interactions for electrochemistry. Support vector machine (SVM), random forest regression (RFR), and deep neural networks (DNN) along with atomic properties are mainly used for the design of SACs. The ML results have shown that the number of electrons in the d orbital, oxide formation enthalpy, ionization energy, Bader charge, d-band center, and enthalpy of vaporization are mainly the most important parameters for the defining of the structure–activity relationships for electrochemistry. However, the black-box nature of ML techniques occasionally makes a physical interpretation of descriptors, such as the Bader charge, d-band center, and enthalpy of vaporization, non-trivial. At the current stage, ML application is limited by the lack of a large and high-quality database. Future prospects for the development of a large database and a generalized ML algorithm for SAC design are discussed to give insights for further studies in this field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

High-Throughput Equilibrium Analysis of Active Materials for Solar Thermochemical Ammonia Synthesis

Solar thermochemical ammonia (NH 3 ) synthesis (STAS) is a potential route to produce NH 3 from air, water, and concentrated sunlight. This process involves the chemical looping of an active redox pair that cycles between a metal nitride and its complementary metal oxide to yield NH 3 . To identify promising candidates for STAS cycles, we performed a high-throughput thermodynamic screening of 1,148 metal nitride/metal oxide pairs. This data-driven screening was based on Gibbs energies of crystalline metal oxides and nitrides at elevated temperatures, G(T), calculated using a recently introduced statistically learned descriptor and 0 K DFT formation energies tabulated in the Materials Project database. Using these predicted G(T) values, we assessed the viability of each of the STAS reactions - hydrolysis of the metal nitride, reduction of the metal oxide, and nitrogen fixation to reform the metal nitride - and analyzed a revised cycle that directly converts between metal oxides and nitrides, which alters the thermodynamics of the STAS cycle. For all 1148 redox pairs analyzed and each of the STAS-relevant reactions, we implemented a Gibbs energy minimization scheme to predict the equilibrium composition and yields of the STAS cycle, which reveals new active materials based on B, V, Fe, and Ce that warrant further investigation for their potential to mediate the STAS cycle. This work details a high-throughput approach to assessing the relevant temperature-dependent thermodynamics of thermochemical redox processes that leverages the wealth of publicly available temperature-independent thermodynamic data calculated using DFT. This approach is readily adaptable to discovering optimal materials for targeted thermochemical applications and enabling the predictive synthesis of new compounds using thermally controlled solid-state reactions.

14 SOLAR ENERGY↗
NASA NTRS2022

Flow Testing of Corrugated Metal Flexhoses to Evaluate Flow-Induced Vibration and Stiffness

Corrugated metal flexhoses are used to supply fluid routing where straight rigid pipes cannot meet the design requirements due to vibrations, thermal expansion, or motion. These types of hoses are found in a wide range of applications at KSC (Exploration Ground Systems Program in particular) with various fluid commodities such as fuel, oxidizers, coolant, and cryogenics. However, flexibility of design comes at a price: due to increased levels of turbulence generated by the hose geometry, the necessary supply pressure must increase to achieve the same flow rate. Furthermore, the convolutes of the flexhoses interact with the flow field to generate areas of flow separation which leads to a phenomenon known as vortex shedding. When the frequency of vortex shedding couples with the natural frequency of the hose, this can be detrimental and cause premature failure. There are a limited amount of software that can correctly model the coupled fluid structure interactions(FSI) between the solid and fluid physics. This project aims to develop a computer model that can predict Flow-Induced Vibration (FIV) on flexhoses in one of the atypical configurations found in the State-of-the-Art (SOTA) standard for hoses in an angulated state. Our research seeks to extend the literature and expand NASA’s FIV standard. The computational rigor and resources available in the Apollo Era did not allow for flow coupling between fluids and structure interfaces to evaluate FIV of the flexhose. Our team believes that modern techniques and methods of evaluation should be used to reevaluate and extend the database of FIV and stiffness properties of flexhoses to assess the risk of failure. The core performance criteria is a computer model that is able to predict the FIV frequency within 10%.

Jared F. Congiardo↗
DOE OSTI2019

Identification and Characterization of Five Cold Stress-Related Rhododendron Dehydrin Genes: Spotlight on a FSK-Type Dehydrin With Multiple F-Segments

Dehydrins are a family of plant proteins that accumulate in response to dehydration stresses, such as low temperature, drought, high salinity, or during seed maturation. We have previously constructed cDNA libraries from Rhododendron catawbiense leaves of naturally non-acclimated (NA; leaf LT 50 , temperature that results in 50% injury of maximum, approximately -7 degrees C) and cold-acclimated (CA; leaf LT 50 approximately -50 degrees C) plants and analyzed expressed sequence tags (ESTs). Five ESTs were identified as dehydrin genes. Their full-length cDNA sequences were obtained and designated as RcDhn 1-5. To explore their functionality vis-a-vis winter hardiness, their seasonal expression kinetics was studied at two levels. Firstly, in leaves of R. catawbiense collected from the NA, CA, and de-acclimated (DA) plants corresponding to summer, winter and spring, respectively. Secondly, in leaves collected monthly from August through February, which progressively increased freezing tolerance from summer through mid-winter. The expression pattern data indicated that RcDhn 1-5 had 6- to 15-fold up-regulation during the cold acclimation process, followed by substantial down-regulation during deacclimation (even back to NA levels for some). Interestingly, our data shows RcDhn 5 contains a histidine-rich motif near N-terminus, a characteristic of metal-binding dehydrins. Equally important, RcDhn 2 contains a consensus 18 amino acid sequence (i.e., ETKDRGLFDFLGKKEEEE) near the N-terminus, with two additional copies upstream, and it is the most acidic (pI of 4.8) among the five RcDhns found. The core of this consensus 18 amino acid sequence is a 11-residue amino acid sequence (DRGLFDFLGKK), recently designated in the literature as the F-segment (based on the pair of hydrophobic F residues it contains). Furthermore, the 208 orthologs of F-segment-containing RcDhn 2 were identified across a broad range of species in GenBank database. This study expands our knowledge about the types of F-segment from the literature-reported single F-segment dehydrins (FSKn) to two or three F-segment dehydrins: Camelina sativa dehydrin ERD14 as F 2 S 2 K n type; and RcDhn 2 as F 3 SK n type identified here. Our results also indicate some consensus amino acid sequences flanking the core F-segment in dehydrins. Implications for these cold-responsive RcDhn genes in future genetic engineering efforts to improve plant cold hardiness are discussed.

09 BIOMASS FUELS↗
DOE OSTI2025

Charpy Impact Characterization of Surveillance Specimens Harvested from Palisades High Fluence A-60 Capsule

Located on the shores of Lake Michigan, the Palisades Nuclear Generating Station (PNGS) was a nuclear power plant that operated in Covert Township, Michigan. The plant had a single pressurized water reactor that produced electricity for the region. The PNGS was shut down in 2022 after more than four decades of service. The PNGS included in its surveillance program a surveillance capsule, designated A-60, containing specimens of a weld metal with nickel content of about 1.36 wt% and copper content of about 0.25 wt%. The capsule was removed from its surveillance position in early 1995 and has been resident in the spent fuel pool since that time. This capsule was irradiated to a fluence of 1.96×10 20 n/cm 2 (E>1MeV) that is equivalent for more than 150 effective full power years (EFPYs) for the US reactor pressure vessel (RPV) fleet. The material is also of special interest because of its very high nickel content and potential for development of NiMnSi (nickel-manganese-silicon) precipitates. Combination of very high fluence and very high Ni and Cu content makes the material in this capsule of great interest as benchmark for currently developing embrittlement trend curves (ETC) aiming to predict embrittlement at high fluences. Multi-year efforts by the Light Water Reactor Sustainability (LWRS) Program personnel from the Materials Research Pathway (MRP) to harvest this capsule finally succeeded in 2023. As a result, the Westinghouse Electric Company (WEC) through contract with Oak Ridge National Laboratory (ORNL) came to PNGS site, retrieved the A-60 capsule, brought it to WEC Churchill hot cell facility, opened the capsule and sent all surveillance specimens in the capsule to ORNL for future characterization by July 2023. Total of 9 tensile and 48 Charpy specimens were inventoried in the ORNL hot cells. Testing plan has been developed based on available specimens. It includes hardness, tensile, Charpy impact, Mini-CT fracture toughness testing, in-situ thermal annealing, and microstructural characterization, including Atom Probe Tomography (APT). Charpy impact testing has been completed and results are presented in this report. Moreover, negotiations with Pressurized Water Reactors Owners Group (PWROG) and Westinghouse resulted in Westinghouse donating to ORNL a piece of archive weld and base metal such that unirradiated characterization of these materials can be performed as part of this project. Comparison of measured hardening and embrittlement has been performed and data are compared to available large database.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

BISON fuel performance modeling optimization for experiment X447 and X447A using axial swelling and cladding strain measurements

With the recent need to qualify new reactor designs such as the Versatile Test Reactor (VTR), fuel performance calculations need to be performed to determine safety criteria of the proposed designs. In order to validate the fuel performance results obtained by a fuel performance code, BISON, for new reactor designs, legacy fuel from EBR-II and FFTF MFF with Post -Irradiation Examination (PIE) data need to be used as validation cases to benchmark models. Here in this work, BISON has been paired with the Fuels Irradiation & Physics Database (FIPD) and IFR Materials Information System (IMIS) to supply PIE data for comparison with simulations of EBR-II experiments X447/X447A. X447/X447A were assessed by implementing models for Fuel Cladding Chemical Interaction (FCCI) within BISON and optimizing the friction coefficient between the fuel surface and the cladding, the anisotropic swelling factor, and the HT9 first thermal creep scalar (which scales the first term in the HT9 creep equation) to best match the PIE axial fuel swelling height and cladding profilometry for all pins in X447/X447A. The optimal values were found using a generic algorithm developed to select different values for the three parameters until end criteria was met and error couldn’t be reduced further. The BISON-simulated cladding profilometry was evaluated using Standard Error of the Estimate (SEE) to account for the profile shape of the cladding profilometry. Optimal values for the friction coefficient, anisotropic fuel swelling factor, and HT9 first thermal creep scalar were found to best fit the BISON simulation results to the PIE measurements found in IMIS and FIPD. Improvements to current models are suggested to account for the underprediction of fuel swelling at low burnups and the overprediction of fuel swelling at higher burnups observed for the axial fuel swelling height. Although two pins in EBR-II X447/X447A (DP70 and DP75) were known to fail due to FCCI, none of the pins simulated in BISON reached a cumulative damage fraction (CDF) above 0.008 with FCCI correlations coupled in the BISON simulations. The error estimate generated for all pins in X447/X447A using optimal values was 209 µm, which is deemed acceptable.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗