Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “space Science”

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.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Grain boundary segregation beyond the dilute limit: Separating the two contributions of site spectrality and solute interactions

Solute segregation at grain boundaries (GBs) is known to have a profound impact on material properties, and as such is becoming routinely used as an element in alloy design. Beyond the dilute limit, the extent of solute GB segregation is known to be concentration dependent. Using hybrid Monte Carlo/Molecular Statics simulations of Mg segregation in Al, in this work we decouple the two contributions to this composition dependence: (i) spectrality of atomic environments at the boundary and (ii) solute-solute interactions. Although only contribution (ii) is typically considered in the literature, we argue that both contributions are equally important to understand concentration dependence and correctly quantify GB solute segregation in a binary alloy. Finally, a thermodynamic segregation isotherm is outlined that accounts for both the spectrality of grain boundary sites and solute-solute interactions. Unlike classical isotherms like those of McLean or Fowler-Guggenheim, which can be successfully fitted to GB segregation data only over a limited range of composition and temperature, our proposed model is shown to be accurate across the composition-temperature space.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mesoscale modeling and semi-analytical approach for the microstructure-aware effective thermal conductivity of porous polygranular materials

Here we established a comprehensive modeling approach for investigating the microstructure-aware effective thermal conductivity ($κ_{eff}$) for porous microstructures containing solid particles and gaseous pores. Our approach combines the mesoscale computational modeling framework and the semi-analytical method, allowing for efficient prediction of $κ_{eff}$ for realistic porous microstructures, while considering complicated microstructural thermal conduction pathways effectively in the prediction. We used the diffuse-interface mesoscale computational model to generate extensive simulated $κ_{eff}$ data for realistic digital representations of microstructures with wide ranges of porosity ($f_p$), thermal conductivity of the gas phase ($κ_g$), and thermal conductivity of the solid phase ($κ_s$). From the simulated data, we identified two property variation regimes for $κ_{eff}$: (1) a slow $κ_{eff}$ increase for $κ_s ~ κ_g$; and (2) a faster $κ_{eff}$ increase for $κ_s \gg κ_g$. To capture the key features of the relationship between the microstructure and $κ_{eff}$, we derived a semi-analytical model by introducing structure and intensification factors. The two new factors incorporate the calibrated effective contribution of the solid volume with $κ_s$ and additional interfacial effects into the prediction of $κ_{eff}$, respectively, allowing for consideration of parallel, serial, and interfacial conduction mechanisms effectively. Using the selected simulation data, we quantified key model parameters within the semi-analytical model and verified that the parameterized model exhibits excellent agreement with simulated $κ_{eff}$ for the entire range of the parameter space.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermal stability and coarsening of eutectic and near-eutectic Ni–Ce alloys

Ni–Ce alloys are currently being studied as a castable alternative to conventional Ni-based superalloys. To understand the evolution of microstructure and mechanical behavior at elevated temperatures, this study investigates the mechanism of coarsening behavior in eutectic and near eutectic Ni–Ce at 900 °C. The as-cast eutectic Ni–Ce consists of a combination of fine lamellar and rod eutectic colonies with coarser boundary regions. Upon annealing, continuous coarsening, via process of globularization, initiates at colony boundaries or primary dendrites where faults (termination and branches) in the lamellar structure are plentiful. Coarsening then proceeds by a combination of fault migration mechanism and lamellar boundary splitting, growing toward the center of the eutectic colonies with increasing annealing time. Coarsening near the center of a colony is extremely slow, indicating the eutectic microstructure itself is very stable. Here, the near-eutectic alloys containing primary dendrites coarsen and stabilize faster compared to the fully eutectic alloy. Moreover, an anomaly is observed in the hardness of the fully eutectic alloy after long exposure at elevated temperature compared to the near-eutectic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quadratic pseudospectrum for identifying localized states

Here we examine the utility of the quadratic pseudospectrum for understanding and detecting states that are somewhat localized in position and energy, in particular, in the context of condensed matter physics. Specifically, the quadratic pseudospectrum represents a method for approaching systems with incompatible observables {A j |1 ≤ j ≤ d} as it minimizes collectively the errors $\parallel$A j v - λ j v$\parallel$ while defining a joint approximate spectrum of incompatible observables. Moreover, we derive an important estimate relating the Clifford and quadratic pseudospectra. Finally, we prove that the quadratic pseudospectrum is local and derive the bounds on the errors that are incurred by truncating the system in the vicinity of where the pseudospectrum is being calculated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Reaction–drift–diffusion models from master equations: application to material defects

We present a general method to produce well-conditioned continuum reaction–drift–diffusion equations directly from master equations on a discrete, periodic state space. We assume the underlying data to be kinetic Monte Carlo models (i.e. continuous-time Markov chains) produced from atomic sampling of point defects in locally periodic environments, such as perfect lattices, ordered surface structures or dislocation cores, possibly under the influence of a slowly varying external field. Our approach also applies to any discrete, periodic Markov chain. Here, the analysis identifies a previously omitted non-equilibrium drift term, present even in the absence of external forces, which can compete in magnitude with the reaction rates, thus being essential to correctly capture the kinetics. To remove fast modes which hinder time integration, we use a generalized Bloch relation to efficiently calculate the eigenspectrum of the master equation. A well conditioned continuum equation then emerges by searching for spectral gaps in the long wavelength limit, using an established kinetic clustering algorithm to define a proper reduced, Markovian state space.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CSGL: chemical synthesis graph learning for molecule representation

Abstract Motivation Molecule representation learning (MRL) translates molecules into a real vector space, serving as input to downstream tasks in biology, chemistry, and computer science. This article introduces a chemical synthesis graph learning (CSGL) framework, which enhances MRL by considering both the atomic structures of molecules and their roles in chemical reactions through a hierarchical graph representation. Specifically, molecules are first modeled based on their molecular graphs, which capture atomic-level structural information. They are then further refined using a chemical synthesis graph, where nodes represent reactant and product molecule sets, and edges encode chemical transformations between reactants and products (e.g. changes in molecular structures). CSGL optimizes molecular embeddings of reactant and product nodes in a fashion that ensures the embeddings conform to a chemical balance constraint. Results Experimental results show that our method CSGL achieves strong performance on a variety of tasks, including product prediction, reaction classification, and molecular property prediction. Availability and implementation https://github.com/li-2023/CSGL.

Biochemistry & Molecular Biology↗
DOE OSTI2020

EQSIM—A multidisciplinary framework for fault-to-structure earthquake simulations on exascale computers part I: Computational models and workflow

Computational simulations have become central to the seismic analysis and design of major infrastructure over the past several decades. Most major structures are now “proof tested” virtually through representative simulations of earthquake-induced response. More recently, with the advancement of high-performance computing (HPC) platforms and the associated massively parallel computational ecosystems, simulation is beginning to play a role in increased understanding and prediction of ground motions for earthquake hazard assessments. However, the computational requirements for regional-scale geophysics-based ground motion simulations are extreme, which has restricted the frequency resolution of direct simulations and limited the ability to perform the large number of simulations required to numerically explore the problem parametric space. In this article, recent developments toward an integrated, multidisciplinary earth science-engineering computational framework for the regional-scale simulation of both ground motions and resulting structural response are described with a particular emphasis on advancing simulations to frequencies relevant to engineered systems. This multidisciplinary computational development is being carried out as part of the US Department of Energy (DOE) Exascale Computing Project with the goal of achieving a computational framework poised to exploit emerging DOE exaflop computer platforms scheduled for the 2022–2023 timeframe.

58 GEOSCIENCES↗
DOE OSTI2023

Early Results from GLASS-JWST. XI. Stellar Masses and Mass-to-light Ratio of z > 7 Galaxies

We exploit James Webb Space Telescope (JWST) NIRCam observations from the GLASS-JWST-Early Release Science program to investigate galaxy stellar masses at z > 7. We first show that JWST observations reduce the uncertainties on the stellar mass by a factor of at least 5–10, when compared with the highest-quality data sets available to date. We then study the UV mass-to-light ratio, finding that galaxies exhibit a a two orders of magnitude range of M / L UV values for a given luminosity, indicative of a broad variety of physical conditions and star formation histories. As a consequence, previous estimates of the cosmic stellar-mass density—based on an average correlation between UV luminosity and stellar mass—can be biased by as much as a factor of ~6. Our first exploration demonstrates that JWST represents a new era in our understanding of stellar masses at z > 7 and, therefore, of the growth of galaxies prior to cosmic reionization.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Substantial Diel Changes of Cloud Adjustments to Aerosols in Ship‐Tracks

Clouds adjust their albedo, amount and liquid water path to anthropogenic aerosols, and produce a climate forcing. Such cloud adjustments are complex functions of both environmental conditions and interaction time. However, direct observations of temporal changes in cloud adjustments are limited. Here, we develop a method to show observational evidence of substantial diel changes in cloud adjustments within ship-tracks. Polluted clouds experiencing extended nighttime exposure exhibit higher increases in cloud fraction while liquid-water path adjustments follow a non-monotonic evolution. The higher cloud fraction increase persists through daytime. Such diel variations likely stem from diel changes in solar heating and background cloud precipitation, and are important because nighttime changes persist and affect solar radiation during the day. Accounting for diel variations produces a stronger aerosol forcing, by −0.1 ∼−0.4 W⁢m −2 . Our approach reveals how the temporal evolution of cloud adjustments can have important implications for aerosol-cloud interactions.

Yuan, Tianle [NASA Goddard Space Flight Center (GS↗
DOE OSTI2022

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Towards satellite tests combining general relativity and quantum mechanics through quantum optical interferometry: progress on the deep space quantum link

The Deep Space Quantum Link (DSQL) is a space-mission concept that aims to explore the interplay between general relativity and quantum mechanics using quantum optical interferometry. This mission concept was formally presented to the United States National Academy of Science Decadal Survey as a research campaign for Fundamental Physics in 2022. Since then, advances have been made in the space-based quantum optical technologies required to conduct a DSQL-type mission. In addition, other research efforts have defined alternative measurement concepts to explore the same scientific questions motivating the DSQL mission. This paper serves as an update to the community on the status of the DSQL mission concept and related research and technology development efforts.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the 300 deg 2 DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3σ on scales below approximately 10', but large scales are unaffected. We fit Ω m and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Male mating season range expansion results from an increase in scale of daily movements for a polygynous–promiscuous bird

Abstract Males of species with promiscuous mating systems are commonly observed to use larger ranges during the mating season relative to non‐mating seasons, which is often attributed to a change in movements related to reproductive activities. However, few studies link seasonal range sizes to variation in daily space use patterns to provide insight into the behavioral mechanisms underlying mating season range expansion. We studied 20 GPS‐tagged male wild turkeys ( Meleagris gallopavo ), a large upland gamebird, during the mating and summer non‐mating seasons to test the hypothesis that larger mating season ranges resulted from male wild turkeys expanding the scale of daily movement activities to locate and court females. We delineated mating and non‐mating seasons based on intensity of gobbling, a vocalization tied to courtship behavior, recorded by autonomous recording units distributed across the study area. Mating season ranges were significantly larger than non‐mating season ranges. Daily ranges were larger in the mating season, as were distances between roost sites used on consecutive nights. Variance in daily range size was greater in the mating season, but low temporal autocorrelation suggested considerable daily variability in both seasons. We found no evidence that male wild turkeys changed how they distributed daily movements within seasonal ranges, or differences in habitat use, suggesting larger mating season ranges result from male wild turkeys increasing the scale of their daily movements, rather than a systematic shift to a nomadic movement strategy. Likely, the distribution of females is more dynamic and ephemeral compared to other resources, prompting males to traverse larger daily ranges during the mating season to locate and court females. Our work illustrates the utility of using daily movement to understand the behavioral process underlying larger space use patterns.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nuclear and Chemical Sciences Division: Investment Strategy 2023

The mission of the Nuclear and Chemical Sciences (NACS) Division within the Physical and Life Sciences (PLS) Directorate is to advance scientific understanding, capabilities, and technologies in nuclear and particle physics, radiochemistry, forensic science, and isotope systems to support LLNL’s national security mission. NACS Division personnel conduct a diverse range of research activities in particle physics, nuclear physics, radiation detection, nuclear measurements, chemical and nuclear forensic science, nuclear and radiochemistry, isotope geochemistry, and environmental science. These areas are leveraged to address evolving national security challenges. Scientific research provides the foundation for addressing these challenges, and it is also the principal means of attracting, training, and retaining staff scientists who can deliver solutions across the Laboratory’s mission space. The overarching strategy is to position the NACS Division at the nexus between fundamental nuclear and chemical science research and nuclear security applications. This approach will support efforts to recruit, train, and retain top-flight scientists and engineers who will play a key role in executing the Laboratory’s core nuclear security missions, while also enhancing LLNL’s reputation as a center for innovative scientific research. This document describes the strategic vision that will be used to guide key investments aimed at enabling NACS scientists to lead new efforts and meet future challenges.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

Hot Hydrogen Exposure of U x Zr 1-x C y Nuclear Fuel: The Influence of Composition and Density

Refractory carbide nuclear fuel has been one of the most promising fuel candidates for space nuclear propulsion due to its high melting point, temperature stability, and compatibility in a hot hydrogen environment. In this study, U x Zr 1-x C y fuel was produced by means of a carbothermic reduction process in different UC compositions including 5,10, 20, and 30 at.% UC in the fuel compound. The powder feedstock was consolidated via direct current sintering with densities up to 97% of the theoretical density. The samples with different U x Zr 1-x C y compositions were exposed to hot hydrogen at 2600 K for a cumulative time of 300 min. The samples were characterized by SEM, XRD, density, and measured for mass losses. The high-density samples displayed improved performance in hot hydrogen by minimizing porous sites and reducing areas of direct contact with hydrogen gas, leading to reduced mass losses. Variations in sample density proved to induce large changes in mass loss rates, increasing them up to 90%. The compositions with higher UC content reported the largest mass losses in the study. The loss of uranium occurred primarily at the surfaces exposed to the hot hydrogen where changes in the lattice constant confirmed losses exceeding 50% of the initial UC content in higher compositions, specifically to U 0.3 Zr 0.7 C y . XRD analyses revealed the presence of UH 3 in U 0.3 Zr 0.7 C y suggesting that metallic uranium formed inside the sample as a product of carbon losses. High-density U x Zr x-1 C y fuel with UC concentrations at or below 20 at.% UC exhibited stability and negligible density changes in a high temperature hydrogen environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Pathways to Discovery in Astronomy and Astrophysics for the 2020s

We live in an extraordinary period of discovery in astronomy and astrophysics. Six Nobel Prizes have been awarded over the past decade alone for discoveries based on astronomical data (dark energy, gravitational waves, neutrino oscillations, the discovery of exoplanets, cosmology, and supermassive black holes). Many of the ambitious scientific visions of the 2010 New Worlds, New Horizons (Astro2010)1 decadal survey are being fulfilled, but momentum has only grown. We stand on the threshold of new endeavors that will transform not only our understanding of the universe and the processes and physical paradigms that govern it but also humanity’s place in it. This report of the Committee for a Decadal Survey on Astronomy and Astrophysics 2020 (Astro2020) proposes a broad, integrated plan for space- and ground-based astronomy and astrophysics for the decade 2023–2032.2 It also lays the foundations for further advances in the following decade. This is the seventh in a sequence of decadal survey studies in this field from the National Academies of Sciences, Engineering, and Medicine. This survey examines the program of record, providing advice on the major projects from prior surveys that are yet to be completed. It also lays out priorities for future investments driven by scientific opportunities. The recommendations in this report advance foundational activities that support the people who drive innovation and discovery, and that promote the technologies and tools needed to carry out the science. The report also recommends sustaining activities on a broad range of cost and time scales, as well as activities that enable future visionary projects by maturing them scientifically and technically. Last, the recommendations set in motion the construction of frontier facilities that will change the view and understanding of the cosmos. The survey is bounded by plausible budget scenarios based on briefings from the sponsoring agencies— the Department of Energy (DOE), the National Aeronautics and Space Administration (NASA), and the National Science Foundation (NSF). Within these bounds, the survey aims high, reflecting this time of great scientific promise and progress, with opportunities to pursue some of the most compelling scientific quests of our times.

79 ASTRONOMY AND ASTROPHYSICS↗