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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Dynamical instability as the cause of the massive outbursts in Eta Carinae and other luminous blue variables

A new type of stellar envelope structure has been computationally discovered at very high stellar masses. The outer part of the envelope resembles a nearly detached, diffusely filled shell overlying an ultrahot surface of small radius. This structural anomaly is caused by a large iron bump occurring in the new opacities of Iglesias et al. (1992). The new stellar models with normal metallicity encounter a strong ionization-induced dynamical instability in the outer envelope as they rapidly transit the H-R diagram after the end of central hydrogen burning. Preliminary evolutionary and hydrodynamical calculations successfully mimic the most basic observed properties of Eta Carinae and other very luminous blue variables. The Humphreys-Davidson sloped line in the H-R diagram, however, seems to be unrelated to these variables, and is instead the observed terminus of the main-sequence phase of evolution if convective core overshooting is insignificant.

Stothers, Richard B.↗
NASA NTRS1995

Concurrent engineering research center

The projects undertaken by The Concurrent Engineering Research Center (CERC) at West Virginia University are reported and summarized. CERC's participation in the Department of Defense's Defense Advanced Research Project relating to technology needed to improve the product development process is described, particularly in the area of advanced weapon systems. The efforts committed to improving collaboration among the diverse and distributed health care providers are reported, along with the research activities for NASA in Independent Software Verification and Validation. CERC also takes part in the electronic respirator certification initiated by The National Institute for Occupational Safety and Health, as well as in the efforts to find a solution to the problem of producing environment-friendly end-products for product developers worldwide. The 3M Fiber Metal Matrix Composite Model Factory Program is discussed. CERC technologies, facilities,and personnel-related issues are described, along with its library and technical services and recent publications.

Callahan, John R.↗
NASA NTRS1995

Silicon Micromachining in RF and Photonic Applications

Texas Instruments (TI) has developed membrane and micromirror devices since the late 1970s. An eggcrate space membrane was used as the spatial light modulator in the early years. Discrete micromirrors supported by cantilever beams created a new era for micromirror devices. Torsional micromirror and flexure-beam micromirror devices were promising for mass production because of their stable supports. TI's digital torsional micromirror device is an amplitude modulator (known as the digital micromirror device (DMD) and is in production development, discussed elsewhere. We also use a torsional device for a 4 x 4 fiber-optic crossbar switch in a 2 cm x 2 cm package. The flexure-beam micromirror device is an analog phase modulator and is considered more efficient than amplitude modulators for use in optical processing systems. TI also developed millimeter-sized membranes for integrated optical switches for telecommunication and network applications. Using a member in radio frequency (RF) switch applications is a rapidly growing area because of the micromechanical device performance in microsecond-switching characteristics. Our preliminary membrane RF switch test structure results indicate promising speed and RF switching performance. TI collaborated with MIT for modeling of metal-based micromachining.

Lin, Tsen-Hwang↗
NASA NTRS2001

Creep-Fatigue Interaction Testing

Fatigue fives in metals are nominally time independent below 0.5 T(sub Melt). At higher temperatures, fatigue lives are altered due to time-dependent, thermally activated creep. Conversely, creep rates are altered by super. imposed fatigue loading. Creep and fatigue generally interact synergistically to reduce material lifetime. Their interaction, therefore, is of importance to structural durability of high-temperature structures such as nuclear reactors, reusable rocket engines, gas turbine engines, terrestrial steam turbines, pressure vessel and piping components, casting dies, molds for plastics, and pollution control devices. Safety and lifecycle costs force designers to quantify these interactions. Analytical and experimental approaches to creep-fatigue began in the era following World War II. In this article experimental and life prediction approaches are reviewed for assessing creep-fatigue interactions of metallic materials. Mechanistic models are also discussed briefly.

Halford, Gary R.↗
NASA NTRS2014

STAGS Developments for Residual Strength Analysis Methods for Metallic Fuselage Structures

A summary of advances in the Structural Analysis of General Shells (STAGS) finite element code for the residual strength analysis of metallic fuselage structures, that were realized through collaboration between the structures group at NASA Langley, and Dr. Charles Rankin is presented. The majority of the advancements described were made in the 1990's under the NASA Airframe Structural Integrity Program (NASIP). Example results from studies that were conducted using the STAGS code to develop improved understanding of the nonlinear response of cracked fuselage structures subjected to combined loads are presented. An integrated residual strength analysis methodology for metallic structure that models crack growth to predict the effect of cracks on structural integrity is demonstrated

Young, Richard D.↗
NASA NTRS2017

Sonora: A New Generation Model Atmosphere Grid for Brown Dwarfs and Young Extrasolar Giant Planets

Brown dwarf and giant planet atmospheric structure and composition has been studied both by forward models and, increasingly so, by retrieval methods. While indisputably informative, retrieval methods are of greatest value when judged in the context of grid model predictions. Meanwhile retrieval models can test the assumptions inherent in the forward modeling procedure. In order to provide a new, systematic survey of brown dwarf atmospheric structure, emergent spectra, and evolution, we have constructed a new grid of brown dwarf model atmospheres. We ultimately aim for our grid to span substantial ranges of atmospheric metallilcity, C/O ratios, cloud properties, atmospheric mixing, and other parameters. Spectra predicted by our modeling grid can be compared to both observations and retrieval results to aid in the interpretation and planning of future telescopic observations. We thus present Sonora, a new generation of substellar atmosphere models, appropriate for application to studies of L, T, and Y-type brown dwarfs and young extrasolar giant planets. The models describe the expected temperature-pressure profile and emergent spectra of an atmosphere in radiative-convective equilibrium for ranges of effective temperatures and gravities encompassing 200 less than or equal to T(sub eff) less than or equal to 2400 K and 2.5 less than or equal to log g less than or equal to 5.5. In our poster we briefly describe our modeling methodology, enumerate various updates since our group's previous models, and present our initial tranche of models for cloudless, solar metallicity, and solar carbon-to-oxygen ratio, chemical equilibrium atmospheres. These models will be available online and will be updated as opacities and cloud modeling methods continue to improve.

emergent spectra↗
DOE OSTI2022

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

Abstract We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Commutative Algebra Modeling in Materials Science – A Case Study on Metal–Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry’s constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.

Khaemba, Caleb S.↗
DOE OSTI2024

Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles

Interactions between gold metallic nanoparticles and molecular dyes have been well described by the nanometal surface energy transfer (NSET) mechanism. However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. In this study, the NSET formula was slightly modified in the size-dependent dampening constant and skin depth terms to allow for modeling of different metals as well as testing the quenching effects created by variously sized gold, silver, copper, and platinum nanoparticles. Overall, the metal nanoparticles followed more closely the NSET prediction than for Förster resonance energy transfer, though scattering effects began to occur at 20 nm in the nanoparticle diameter. To further improve the NSET theoretical equation, an attempt was made to set a best-fit line of the NSET theoretical equation curve onto the Au and Ag data points. An exhaustive grid search optimizer was applied in the ranges for two variables, 0.1≤C≤2.0 and 0≤α≤4, representing the metal dampening constant and the orientation of donor to the metal surface, respectively. Three different grid searches, starting from coarse (entire range) to finer (narrower range), resulted in more than one million total calculations with values C=2.0 and α=0.0736. The results improved the calculation, but further analysis needed to be conducted in order to find any additional missing physics. With that motivation, two artificial intelligence/machine learning (AI/ML) algorithms, multilayer perception and least absolute shrinkage and selection operator regression, gave a correlation coefficient, R2, greater than 0.97, indicating that the small dataset was not overfitting and was method-independent. This analysis indicates that an investigation is warranted to focus on deeper physics informed machine learning for the NSET equations.

Demers, Steven M. E. (ORCID:0000000192213246)↗
DOE OSTI2023

Application of an Empirical Density Law via Python for Aqueous Plutonium Chloride Systems in MCNP6

Current aqueous plutonium processing models for criticality safety often contain significant bias due to material modeling assumptions. These solutions include plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution. Furthermore, there is no current predictive capability for modeling plutonium metal-water mixtures that is approved for use at Los Alamos National Laboratory (LANL). Recent density measurements for aqueous plutonium chloride systems (PuCl 3 -HCl-H 2 O) now allow for the development and application of a more realistic density law. This work develops a Python-based density law for this ternary solution using an empirical method. This code can be used in conjunction with an MCNP6 input to determine the density and composition of a solution based upon user inputs of plutonium concentration, hydrochloric acid concentration, and temperature. The tool allows users to input plutonium and acid content of a solution in terms of molality, molarity, or concentration, and predicts density within the current data range within 1.4% of experimental data. Current preliminary MCNP6 calculations utilizing this tool have demonstrated a minimum decrease in system reactivity of 5% in comparison to the current modeling conventions. Thus, this tool enables more accurate criticality safety operational limits by better crediting chorine content while still maintaining necessary conservatism.

Density Law↗
DOE OSTI2020

Visualizing strange metallic correlations in the two-dimensional Fermi-Hubbard model with artificial intelligence

Strongly correlated phases of matter are often described in terms of straightforward electronic patterns. This has so far been the basis for studying the Fermi-Hubbard model realized with ultracold atoms. Here, we show that artificial intelligence (AI) can provide an unbiased alternative to this paradigm for phases with subtle, or even unknown, patterns. Long- and short-range spin correlations spontaneously emerge in filters of a convolutional neural network trained on snapshots of single atomic species. In the less well-understood strange metallic phase of the model, we find that a more complex network trained on snapshots of local moments produces an effective order parameter for the non-Fermi-liquid behavior. We report our technique can be employed to characterize correlations unique to other phases with no obvious order parameters or signatures in projective measurements, and has implications for science discovery through AI beyond strongly correlated systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Dynamic modelling and control strategy of a temperature-driven metal hydride cooling system for buildings

A temperature-driven coupled metal hydride (MH) based thermal energy storage (TES) system can allow to shave and shift the peak energy demand in buildings. The high energy density and long-term (seasonal) energy storage capability are its major advantages over other energy storage methods. The dynamic nature of the MH operation, however, requires controlled hydrogen transfer between the coupled MHs at a rate needed to meet the building's transient load. While temperature-driven MH systems are studied in the literature, their application in buildings and control are scarcely reported. Here, this paper presents a control-based dynamic modeling of the temperature-driven coupled MH-TES system for building cooling applications. The dynamic model is developed in MATLAB(R) Simulink environment, considering the thermodynamic and kinetic behaviors of the MH systems. Based on a preliminary analysis of a property database of over 337 hydrides, we select around 1600 MH pairs suitable for building cooling applications. Each of these MH pairs is studied for their performance using the dynamic model, and among all, Zr 0.76 Ti 0.24 Ni 1.16 Mn 0.63 V 0.14 Fe 0.18 -Ti 0.85 Zr 0.15 Cr 1.2 Mn 0.8 MH pair showed fast dynamics along with high coefficient of performance (COP) of 0.71. A parametric investigation is performed on this MH pair to understand the effect of operating temperatures. Finally, three proportional-integral (PI) feedback controllers are investigated to regulate the temperature, pressure and mass exchange between the coupled MH pairs. The developed PI controller is sufficiently capable of rejecting the signal noise from the hydrogen flow and internal heat exchange processes with root mean square error of 5.78 W between reference and actual cooling load.

08 HYDROGEN↗
NASA NTRS2012

Verilog-A Device Models for Cryogenic Temperature Operation of Bulk Silicon CMOS Devices

Verilog-A based cryogenic bulk CMOS (complementary metal oxide semiconductor) compact models are built for state-of-the-art silicon CMOS processes. These models accurately predict device operation at cryogenic temperatures down to 4 K. The models are compatible with commercial circuit simulators. The models extend the standard BSIM4 [Berkeley Short-channel IGFET (insulated-gate field-effect transistor ) Model] type compact models by re-parameterizing existing equations, as well as adding new equations that capture the physics of device operation at cryogenic temperatures. These models will allow circuit designers to create optimized, reliable, and robust circuits operating at cryogenic temperatures.

Akturk, Akin↗
DOE OSTI2021

Impact of Integration Scheme on Performance of Anisotropic Plasticity Models

Given the prevalent role of metals in a variety of industries, schemes to integrate corresponding constitutive models in finite element applications have long been studied. A number of formulations have been developed to accomplish this task; each with their own advantages and costs. Often the focus has been on ensuring the accuracy and numerical stability of these algorithms to enable robust integration. While important, emphasis on these performance metrics may often come at the cost of computational expense potentially neglecting the needs of individual problems. In the current work, the performance of two of the most common integration methods for anisotropic plasticity -- the convex cutting plane (CCP) and closest point projection (CPP) -- across a variety of metrics is assessed; including accuracy and cost. A variety of problems are considered ranging from single elements to large representative simulations including both implicit quasistatic and explicit transient dynamic type responses. The relative performance of each scheme in the different instances is presented with an eye towards guidance on when the different algorithms may be beneficial.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Best Practices for Shielding Analyses of Activated Metals and Spent Resins from Reactor Operation

This report investigated best practices for performing shielding evaluations of Type B waste packages, as defined in 10 CFR Part 71 regulations on packaging and transportation of radioactive material, or packages for which the contents are not defined before loading and may include a broad range of nuclides, geometries, and non-fuel materials. The following non-fuel waste streams were analyzed: Activated metals from decommissioned commercial power reactors, including Type 304 stainless steel, reactor vessel steel, and Inconel, Control blades from boiling water reactors, Neutron-activated corrosion products on surfaces of activated metals, and Spent resins from power plant operations. Measured elemental compositions, including major constituents and impurities, for steel and Inconel samples from commercial power reactors were used in activation calculations to determine radionuclide inventories in activated metals. For a simplified cask model, 60 Co contribution to the total external package dose rate at 30 days after shutdown varied from approximately 60% to 95%, depending on the activated metal, initial cobalt impurity concentration in the metal, and the thickness of the overpack gamma shield. Its maximum contribution to the total external package dose rate of approximately 100% was reached within the time interval of 2 to 5 years after shutdown and was maintained for up to 45 to 60 years after shutdown, depending on material, initial cobalt impurity concentration, and shield thickness. Thereafter, the 60 Co contribution to external package dose rate decreased with increasing decay time. Cobalt-60 is primarily produced by neutron reactions with the cobalt impurity in steel and Inconel. Other important radionuclides in activated metals contributing to package external dose rate are radionuclides with relatively short decay times, including 51 Cr, 59 Fe, 58 Co, and 54 Mn. These radionuclides may be represented as an equivalent 60 Co activity/source because 60 Co gamma ray emissions are bounding in terms of source strength and energy to other important radionuclides identified in the analyzed activated metals. Approaches for modeling the neutron-activated corrosion products that may be attached to activated reactor components were analyzed in this report. It was demonstrated that a surface source is more conservative than a uniform volumetric source for the treatment of neutron-activated corrosion products with respect to external package dose rates. An analysis of the maximum radionuclide loadings reported on spent resins identified the radionuclides 137 Cs, 60 Co, 134 Cs, 65 Zn, and 58 Co as the primary contributors to external package dose rate. For a resin cooled for 3.08 years, the external package dose rate was entirely produced by the reported 137 Cs and 60 Co inventory. The neutron sources from actinides found on spent resins or activated metals produced negligible dose rates and may be ignored in dose rate analyses. Effects of idealized waste material, source geometry, and spatial material/source distributions on external package dose rates were determined based on dose rate results for a simplified cask model under normal conditions of transport. Type 304 stainless steel, zirconium, and aluminum with adjusted mass densities based on a maximum content weight were analyzed for material modeling effects on external package dose rate. These materials produced identical external package dose rates within the statistical uncertainties of the dose rate estimates. Among four different source geometry configurations with homogeneous material of different mass densities, uniform volumetric source distribution, and the same source strength, the geometry configuration with lowest mass density (i.e., minimum self-shielding effect among the four cases) was most conservative. Spatial source distributions that better represent localized peak 60 Co activity values were more conservative than a uniform volumetric source distribution, assuming the same weight and total source strength per package. The increase in external dose rate caused by localized source peaks can be as much as the ratio between source peak activity density to average activity density, depending on the location of the activated metal with peak activity density. Therefore, the shielding analysis may be simplified if localized peak activities and the average activity per package can be measured/determined and documented at the time of cask loading. For simplicity, external package dose rates may be determined based on average source activity and a uniform volumetric source distribution. The dose rate results from that calculation model multiplied by the ratio of peak activity density to average activity density will produce maximum dose rate values for conservative estimates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Development of a conduction-based model for analyzing frozen startup of alkali-metal heat pipes

One key area of interest in heat pipe modeling/simulation is to analyze the startup behavior of the liquid-metal heat pipes (LMHPs) from a frozen state. This so-called ‘frozen startup’ process involves a complex set of nonlinear mass and heat transport phenomena, including phase transitions from solid to liquid and vapor, multiphase interactions, microporous wick flow, and compressible vapor dynamics. The complexity of these processes makes it challenging to simulate LMHP’s frozen startup using conventional numerical methods or commercial computational fluid dynamics (CFD) software. This paper presents a simplified conduction-based modeling approach that can provide practical insights into the entire LMHP frozen startup process, while alleviating the challenges of modeling its complex physics. The theoretical foundation and physical assumptions of the proposed model are based solely on heat-conduction equation, allowing for a more tractable simulation without sacrificing essential physical accuracy. The proposed model was implemented in a commercial CFD software, and its prediction was compared with the experimental data obtained from sodium heat-pipe startup experiments. The comparison highlights the proposed model's ability to capture the transient thermal behavior of LMHP during frozen startup. This study not only validates the conduction-based frozen startup modeling method but also shows its potential as a practical and efficient tool for understanding the startup performance of the LMHP systems.

Microreactor↗
DOE OSTI2021

Bulk Diffusion of Cl through O Vacancies in α-Cr 2 O 3 : A Density Functional Theory Study

Many metals form passive oxides which are broken or weakened by anionic-induced degradation leading to material failure and anionic diffusion is an important step of this degradation process. The diffusion of anionic species through oxides involves a combination of diffusion along grain boundaries, cracks, and channels, as well as bulk diffusion via point defects which is the focus of this study. Using density functional theory, we study bulk diffusion of Cl through O vacancies in α -Cr 2 O 3 as a model system for passive metal oxides. Little is known about Cl diffusion and bonding characteristics, so we benchmark our work through comparison to numerous studies on O diffusion in α -Cr 2 O 3 to analyze similarities and differences between the O and Cl diffusion in the passivation and degradation process of α -Cr 2 O 3 respectively. Unlike O diffusion, the lowest diffusion barrier for Cl is cross-plane diffusion between two (0001) planes through a vacant cation site but the much shorter in-plane diffusion path within the same coordination polyhedron has 35% higher barrier. This work provides the basis for considering the contributions of Cl bulk-diffusion in the overall diffusion kinetics of Cl through α -Cr 2 O 3 .

Oware Sarfo, Kofi↗
NASA NTRS1985

Galactic chemical evolution and nucleocosmochronology - Analytic quadratic models

Quadratic models of the chemical evolution of the Galaxy for a star formation rate proportional to the square of the gas mass are studied. The search for analytic solutions to the gas mass and star mass for time-dependent rates of gaseous infall onto the disk is examined. The quadratic models are compared to models having linear star formation rates. The mass, metallicity, number of stars, and U-235/U-238 isotopic ratio for the models which are subjected to the same infall rate, the same initial disk mass, and the same final gas fraction are compared. The results of the comparison indicate that: (1) the average dwarf age is greater in the quadratic model, (2) the metallicity grows initially faster in the quadratic model, (3) the quadratic model has a smaller percentage of low-Z dwarfs, and (4) the U-235/U-238 isotopic ratio indicates a younger quadratic model.

Clayton, D. D.↗