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At least 919 records · Page 51

Data on erosion and hydrogen fuel retention in Beryllium plasma-facing materials

ITER will use beryllium as a plasma-facing material in the main chamber, covering a total surface area of about 620 m 2 . Given the importance of beryllium erosion and co-deposition for tritium retention in ITER, significant efforts have been made to understand the behaviour of beryllium under fusion-relevant conditions with high particle and heat loads. This paper provides a comprehensive report on the state of knowledge of beryllium behaviour under fusion-relevant conditions: the erosion mechanisms and their consequences, beryllium migration in JET, fuel retention and dust generation. The paper reviews basic laboratory studies, advanced computer simulations and experience from laboratory plasma experiments in linear simulators of plasma–wall interactions and in controlled fusion devices using beryllium plasma-facing components. A critical assessment of analytical methods and simulation codes used in beryllium studies is given. The overall objective is to review the existing set of data with a broad literature survey and to identify gaps and research needs to broaden the database for ITER.

Erosion–deposition↗

Braided Composites for Aerospace Applications. (Latest citations from the Aerospace Database)

The bibliography contains citations concerning the design, fabrication, and testing of structural composites formed by braiding machines. Topics include computer aided design and associated computer aided manufacture of braided tubular and flat forms. Applications include aircraft and spacecraft structures, where high shear strength and stiffness are required.

COMPOSITE STRUCTURES↗

Monolithic ATF MiniFuel Sample Capsules Ready for HFIR Insertion

Several advanced nuclear fuel concepts are being considered throughout the nuclear industry. Implementation of these concepts could increase accident tolerance or enhance performance beyond the capabilities of the UO₂-based nuclear fuel currently in use. Qualification and deployment of any new fuel requires rigorous irradiation testing to demonstrate performance under representative normal and off-normal operating conditions. The traditional approach for qualifying new fuels requires exhaustive execution of many integral fuel tests. However, due to the long timeframe for executing these integral tests and the limited number of available materials test reactors, this approach is becoming impractical. To accelerate fuel qualification, Oak Ridge National Laboratory developed the MiniFuel irradiation vehicle for use in conducting accelerated separate effects irradiation testing of a wide range of nuclear fuel materials in the High Flux Isotope Reactor (HFIR). The first MiniFuel irradiations performed in the facility tested sol gel–derived uranium nitride kernels and tristructural isotropic (TRISO)-coated particle fuels. This report describes the preparation and assembly of the first set of monolithic MiniFuel irradiations conducted to support accident-tolerant fuel (ATF) development and accelerated fuel qualification. Two irradiation targets containing a variety of UO₂ and U₃Si₂ disk fuel specimens were fabricated and assembled for irradiation to burnups of 8-10 and 28-40 MWd/kg U. The target irradiation temperature is 450-550°C. Irradiation of U₃Si₂ will provide new data regarding the irradiation performance of a candidate ATF to complement current ATF-1 integral experiments being performed in the Advanced Test Reactor. UO₂ samples were included as a reference so that the results from the MiniFuel experiments can be compared with the extensive UO₂ fuel performance database. The monolithic MiniFuel capsules were successfully assembled, welded, and tested per HFIR requirements and are ready for insertion into the reactor. Pictures of the assembly process are included in this report. The experiment is planned for insertion into the HFIR during cycle 487 in April 2020.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ab initio property predictions of quinary solid solutions using small binary cells

The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.

36 MATERIALS SCIENCE↗

The Potential of Wearable Sensor Technology for EVA Glove Ergonomic Evaluation

Injuries to the hands are common among astronauts who train for extravehicular activity (EVA). Many of these injuries refer to the gloves worn during EVA as the root cause. While pressurized, the bladder and outer material of these gloves restrict movement and create pressure points while performing tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally a more severe injury, onycholysis (fingernail delamination). The most common injury causes are glove contact (pressure point/rubbing), ill-fitting gloves, and/or performing EVA tasks in pressurized gloves. A brief review of the Lifetime Surveillance of Astronaut Health's injury database reveals over 57% of the total injuries to the upper extremities during EVA training occurred either to the metacarpophalangeal (MCP) joint, fingernail, or the fingertip. Twenty-five of these injuries resulted in a diagnosis of onycholysis.

Reid, Christopher R.↗

The Potential of Wearable Sensor Technology for EVA Glove Ergonomic Evaluation

Injuries to the hands are common among astronauts who train for extravehicular activity (EVA). Many of these injuries refer to the gloves worn during EVA as the root cause. While pressurized, the bladder and outer material of these gloves restrict movement and create pressure points while performing tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally a more severe injury, onycholysis (fingernail delamination). The most common injury causes are glove contact (pressure point/rubbing), ill-fitting gloves, and/or performing EVA tasks in pressurized gloves. A brief review of the Lifetime Surveillance of Astronaut Health's injury database reveals over 57% of the total injuries to the upper extremities during EVA training occurred either to the metacarpophalangeal (MCP) joint, fingernail, or the fingertip. Twenty-five of these injuries resulted in a diagnosis of onycholysis

Reid, Christopher R.↗

In‐Silico Device Performance Prediction of Cosensitizer Dye Pairs for Dye‐Sensitized Solar Cells

Abstract Endeavors in the field of dye‐sensitized solar cells (DSCs) have shown great promise when adopting a data‐driven approach to materials discovery, such as successful molecular‐scale predictions of light‐harvesting chromophores. However, predictions of DSC dyes would become much more sophisticated if a molecular‐to‐macroscopic DSC device prediction methodology existed. Thereby, a fully computational pipeline is presented that predicts device‐performance parameters of DSCs which contain varying dye combinations. Optimal pairing of complementary dyes is identified via a data‐driven workflow that affords cosensitized DSCs with maximum power‐conversion efficiencies. Six high‐performing DSC dyes are paired with partner dyes that are screened from a database of 8488 compounds using sequential heuristic filters. Existing models that predict short‐circuit‐current density ( J SC ) and open‐circuit voltage ( V OC ) parameters are adapted to predict singly sensitized and cosensitized DSC performance. The predictions for J sc values of singly sensitized devices match experimental literature values with comparable accuracy to more computationally costly methods. Five out of six dye pairings are predicted to have greater J SC values when cosensitized compared to their corresponding singly sensitized devices, including two pairs that show strong J sc boosts of +13% and +12% when cosensitized. Thus, the prospect of an entirely in‐silico prediction pipeline for DSC performance that can be used to realize the fully automated design of optimized cosensitized DSCs is demonstrated.

14 SOLAR ENERGY↗

Solute-vacancy clustering in aluminum

In this study, we present an extensive first-principles database of solute-vacancy, homoatomic, heteroatomic solute-solute, and solute-solute-vacancy binding energies of relevant alloying elements in aluminum. We particularly focus on the systems with major alloying elements in aluminum, i.e., Cu, Mg, and Si. The computed binding energies of solute-vacancy, solute-solute pairs, and solute-solute-vacancy triplets agree with available experiments and theoretical results in literature. We consider physical factors such as solute size and formation energies of intermetallic compounds to correlate with binding energies. Systematic studies of the homoatomic solute-solute-vacancy and heteroatomic (Cu, Mg, or Si)-solute-vacancy complexes reveal the overarching effect of the vacancy in stabilizing solute-solute pairs. The binding energy database presented here elucidates the interaction between solute cluster and vacancy in aluminum, and it is expected to provide insight into the design of advanced Al alloys with tailored properties.

36 MATERIALS SCIENCE↗

FY21 Status Report on the Molten Salt Thermal Properties Database (MSTDB) Development

This report describes the thermodynamic assessments for the ZrF 4 -BeF 2 , AlCl 3 -NaCl, AlCl3-KCl and the PuCl 3 -CsCl pseudo-binary subsystems. Calculation results are compared to the inputs used to optimize the adjustable model parameters. The data came from experimental studies reported in the open literature, from the MSR research community, and/or computational results generated within the NEAMS program and from collaborators. The models from the thermodynamic assessment of these salt systems are integrated into the MSTDB-TC (Molten Salt Thermal Properties Database-Thermochemical). A brief description of the companion MSTDB-TP (Molten Salt Thermal Properties Database-Thermophysical) is given along with an overview of the approach for predicting both thermodynamic and thermophysical property behavior of multicomponent systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

LLNL International Working Group on Gamma Spectrometry - Preparation of IDB Dataset

The spectral information and associated metadata, including source information, detector setup, and shielding configuration is described in human readable, comma-separated text files (csv). Five csv files are associated with each material type and include the following information (where [Isotope] is U, Pu, and MOX): [Isotope]_measurement_metadata - Metadata of the measurement configuration, including material composition at time of acquisition (decay corrected from certificate date). Data that is unique to a measurement configuration e.g. detector geometry, source-detector distance, analyzer and other electronics used, attenuating materials are provided in this file. [Isotope]_spectrum_metadata - The information that is unique to the spectrum. This includes detector specifications (e.g. date of acquisition, number of channels, gain (keV/channel), energy range, real and live time, full width half-maximum (FWHM) of the 186 or 208 peak for uranium or plutonium measurements, respectively. [Isotope]_source_metadata - The source material used for the measurement, this includes the ratio and uncertainties of isotopes present and processing information of the material. In addition, the certificate information for the source material is listed. [Isotope]_spectrum_counts_metadata - The counts per channel for each spectrum. This data is linked via the UID.spectrum index to the measurement_metadata file. [Isotope]_spectrum_checksum_metadata The MD5 checksum for the original spectrum file. This data is linked via the UID.spectrum index to the measurement_metadata file. This information is provided to prevent duplication of entries in the database.

42 ENGINEERING↗

Cryogenic Reflectance Spectroscopy in Support of Planetary Missions

Present understanding of planetary composition is based primarily on remotely-sensed data, and in particular upon ultraviolet, visible, and infrared spectroscopy. Spectra acquired by telescopic and spacecraft instruments are compared to laboratory measurements of pure materials in order to identify surface components based on characteristic absorption features. Cryogenic spectral measurements are necessary for the study of worlds beyond the Earth's orbit. While some materials exhibit only small spectral changes as a function of temperature, many others are strongly temperature-dependent. For example, hydrated salts exhibit different spectral behavior under conditions appropriate to Europa than at terrestrial temperatures. The icy satellites of the outer solar system contain significant quantities of volatile ices which do not even exist at standard temperature and pressure (STP). A comprehensive spectral database of ices and minerals covering a wide temperature range will have applications ranging from the study of comets and Kuiper Belt objects to outer planet satellites and the polar regions of Mars. Efforts are presently underway at NASA-Ames to develop capabilities which will contribute to such a database. As spacecraft instruments feature increasing spatial and spectral resolution, appropriate laboratory reference spectra become increasingly critical to accurate interpretation of the spacecraft data.

Dalton, J. B.↗

Design guidance for ferrites: Insights from density functional theory on magnetic properties

A grand challenge in materials research is identifying the relationship between composition and performance. Herein, we explore this relationship for magnetic properties, specifically magnetic saturation (M s ) and magnetocrystalline anisotropy energy (K) of ferrites. Ferrites are materials derived from magnetite (chemical formula = Fe 3 O 4 ) that comprise metallic elements such as Fe, Mn, Ni, Co, Cu and Zn. Experimentally, synthesizing and characterizing ferrites is time consuming. Further, selection of compositions to achieve particular magnetic properties currently relies on intuition. To address this, in this work, density functional theory (DFT) is used to predict M s and K for 571 ferrite structures. These structures are primarily double-substituted non-stoichiometric ferrites with formulae M1 x M2 y Fe 3–x–y O 4 , where M1 and M2 can be Mn, Ni, Co, Cu and/or Zn and 0 ≤ x ≤ 1 and y = 1–x. Calculated magnetic properties for the structures in this study vary from 0.04 × 10 5 to 9.6 × 10 5 A m −1 for M s and from 0.02 × 10 5 to 14.08 × 10 5 J m −3 for K. All structures are made publicly available in a FAIR database.

36 MATERIALS SCIENCE↗

Grain boundary segregation in BCC vanadium-based alloys: Quantum-accurate computed segregation spectra and targeted experimental validations

Grain boundaries are critically important to the material performance of fusion reactor materials such as vanadium, particularly mechanical properties and irradiation resistance. A key challenge to the design and control of grain boundaries in vanadium alloys is the lack of quantitative data on grain boundary segregation. In this study, we combine computational and experimental methods to address this gap. Furthermore, using a machine learning-accelerated quantum mechanics/molecular mechanics approach, we calculated the segregation spectra for 28 transition metal elements in polycrystalline vanadium, and validated these predictions experimentally for a subset of solutes that sample a range of segregation behavior, specifically zirconium, titanium, and tungsten, using analytical transmission electron microscopy. Furthermore, the agreement between experiment and theory highlights the predictive capability of our approach. Critically, this work provides a comprehensive database of quantum-accurate solute segregation enthalpies in vanadium, enabling the development of advanced alloys for fusion reactors applications.

Fusion materials↗

Lithium-Ion Batteries for Aerospace Applications

This presentation reviews: (1) the goals and objectives, (2) the NASA and Airforce requirements, (3) the potential near term missions, (4) management approach, (5) the technical approach and (6) the program road map. The objectives of the program include: (1) develop high specific energy and long life lithium ion cells and smart batteries for aerospace and defense applications, (2) establish domestic production sources, and to demonstrate technological readiness for various missions. The management approach is to encourage the teaming of universities, R&D organizations, and battery manufacturing companies, to build on existing commercial and government technology, and to develop two sources for manufacturing cells and batteries. The technological approach includes: (1) develop advanced electrode materials and electrolytes to achieve improved low temperature performance and long cycle life, (2) optimize cell design to improve specific energy, cycle life and safety, (3) establish manufacturing processes to ensure predictable performance, (4) establish manufacturing processes to ensure predictable performance, (5) develop aerospace lithium ion cells in various AH sizes and voltages, (6) develop electronics for smart battery management, (7) develop a performance database required for various applications, and (8) demonstrate technology readiness for the various missions. Charts which review the requirements for the Li-ion battery development program are presented.

Surampudi, S.↗

Database development and exploration of process–microstructure relationships using variational autoencoders

The paper demonstrates graphical representation of a large database containing process–microstructure relationships using an unsupervised machine learning algorithm. Correlating microstructural features to processing is an essential first step to answer the difficult problem of process sequence design. Here, a large database of 346,200 orientation distribution functions resulting from a variety of process sequences is constructed, where each sequence comprises up to four stages of tension, compression and rolling along different directions in various permutations. This open-source database is constructed for collaborative development of process design algorithms. The paper demonstrates a novel application of the large database: graphical representation of texture–process relationships. A variational autoencoder is used to reduce the entire database to a two dimensional latent space where variations in processes and properties can be visualized. Using proximity analysis in this latent space, we can quickly unearth multiple process solutions to the problem of texture or property design.

36 MATERIALS SCIENCE↗

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗

Scintillator Library: A database of inorganic and organic scintillator properties

The Scintillator Library (scintillator.lbl.gov) is a database of scintillator properties hosted by Lawrence Berkeley National Laboratory in a web-accessible format. It contains a variety of measured inorganic and organic scintillator properties extracted from peer-reviewed literature and manufacturer specifications. Data housed within the Scintillator Library supply an important resource for developers of scintillator-based detection systems and an aid for scientists seeking to establish connections between fundamental material and chemical properties and the associated scintillation performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Recommended DSMC Collision Model Parameters for Planetary Entry

Hybrid simulation frameworks combining Computational Fluid Dynamics (CFD) and Direct Simulation Monte Carlo (DSMC) are frequently employed to efficiently perform high-fidelity simulations of environments consisting of both continuum and rarified flow. DSMC is a stochastic, particle-based method which solves the fundamental Boltzmann equation and is therefore necessary for high-Knudsen flow where continuum-based assumptions governing CFD break down. However, the DSMC methodology is generally computationally inefficient to model the continuum regime. In a CFD/DSMC hybrid approach, obtaining an accurate, high-fidelity solution hinges on the consistent treatment of transport properties and the thermo-chemical models employed within the two solvers. In principle, in regions where CFD and DSMC are both employed, the same gas mixture under the same conditions should have the same properties, regardless of simulation type. Observed differences should be due to non-equilibrium processes, rather than differences in physical models. The goal of this work is to provide a comprehensive DSMC transport database encompassing the vast majority of known gas species encountered during Earth or other planetary atmospheric entry. This goal is largely possible due to recently performed ab initio quantum chemistry calculations. Combined with other high-fidelity data, the planned database will consist of collision integral data for over 200 neutral and ionized species and over 20000 binary collisions. From these collision integrals, Nelder-Mead optimization is used to compute collision-specific Variable Soft Sphere (VSS) collision model parameters, fitted from 300 K to 20000 K. Initial comparisons of transport properties of relevant equilibrium gas mixtures show great agreement between CFD and DSMC-derived results. The completed database can be readily applied to model binary collisions of any gas mixture containing the included species over the specified temperature range, making it a valuable tool for future planetary probe modeling efforts. An example is shown below in Fig. 1. Equilibrium mixture transport properties for a 35-species mixture composed originally of 10% air and 90% pyrolysis species of a carbon-phenolic ablator material [4] are computed using both fitted VSS Parameters and the original CFD collision integral values. Deviations in computed properties between the two approaches are less than 5% for the entire temperature range.

M. R. Gosma↗