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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Materials processing - A matter of gravity

The paper examines the pervasive influences of gravitational forces on processes used in the preparation of materials employed in earth-based applications and considers the knowledge and benefits which may be derived from the microgravity environment of space in improving upon these constraints. Particular attention is given to the NASA Materials Processing in Space program, which is focused on crystal growth processes, solidification processes, containerless processing, fluid and chemical processes, and bioseparation processes.

Zoller, L. K.↗
NASA NTRS1993

Constraints on chemical evolution models from QSOALS abundances

Models of the formation and early chemical evolution of our Galaxy are guided and constrained by our knowledge of abundances in globular cluster stars and halo field stars. The abundance patterns identified in halo and disk stars should be discernible in absorption lines of gas clouds in forming galaxies which are accidentally lying in front of background QSO's. Conversely, the ensemble of QSO absorption line systems (QSOALS) at each redshift may suggest a detailed model for the formation of our Galaxy that is testable using abundance patterns in halo stars.

Lauroesch, J. T.↗
DOE OSTI2020

Current and future neutrino oscillation constraints on leptonic unitarity

The unitarity of the lepton mixing matrix is a critical assumption underlying the standard neutrino-mixing paradigm. However, many models seeking to explain the as-yet-unknown origin of neutrino masses predict deviations from unitarity in the mixing of the active neutrino states. Motivated by the prospect that future experiments may provide a precise measurement of the lepton mixing matrix, we revisit current constraints on unitarity violation from oscillation measurements and project how next-generation experiments will improve our current knowledge. With the next-generation data, the normalizations of all rows and columns of the lepton mixing matrix will be constrained to ≲10% precision, with the e-row best measured at ≲1% and the τ-row worst measured at ~10% precision. The measurements of the mixing matrix elements themselves will be improved on average by a factor of 3. We highlight the complementarity of DUNE, T2HK, JUNO, and IceCube Upgrade for these improvements, as well as the importance of ντ appearance measurements and sterile neutrino searches for tests of leptonic unitarity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Revisiting leptonic nonunitarity

In the presence of extra neutrino states at high scales, the low-energy effective 3 × 3 leptonic mixing matrix (LMM) is in general nonunitary. We revisit the question of what is our current knowledge of individual LMM matrix elements without assuming unitarity. We first demonstrate that a minimal set of experimental constraints suffices in bounding LMM nonunitarity parameters to the level of O ( 10 − 3 ) , without the use of neutrino oscillation data. We then revisit oscillation results as a complementary cross-check, using different physics and different experimental techniques to probe a similar parameter space. We correct some common misconceptions in the neutrino nonunitarity literature resulting from an incautious treatment of input parameters. We find that neutrino oscillation experiments can constrain LMM nonclosure, but, contrary to claims in the literature, are completely insensitive to the overall normalization of the LMM. Thus, we conclude that oscillation experiments, including the future DUNE experiment, have no power in excluding nonunitarity altogether. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

State Dependent Optimization with Quantum Circuit Cutting

Quantum circuits can be reduced through optimization to better fit the constraints of quantum hardware. One such method, initial-state dependent optimization (ISDO), reduces gate count by leveraging knowledge of the input quantum states. Surprisingly, we found that ISDO is broadly applicable to the downstream circuits produced by circuit cutting. Circuit cutting also requires measuring upstream qubits and has some flexibility of selection observables to do reconstruction. Therefore, we propose a state-dependent optimization (SDO) framework that incorporates ISDO, our newly proposed measure-state dependent optimization (MSDO), and a biased observable selection strategy. Building on the strengths of the SDO framework and recognizing the scalability challenges of circuit cutting, we propose nonseparate circuit cutting-a more flexible approach that enables optimizing gates without fully separating them. We validate our methods on noisy simulations of QAOA, QFT, and BV circuits. Results show that our approach consistently mitigates noise and improves overall circuit performance, demonstrating its promise for enhancing quantum algorithm execution on near-term hardware.

Li, Xinpeng↗
DOE OSTI2021

Co-Optimization of Velocity and Charge-Depletion for Plug-In Hybrid Electric Vehicles: Accounting for Acceleration and Jerk Constraints

Abstract Recent advances in vehicle connectivity and automation technologies promote advanced control algorithms that co-optimize the longitudinal dynamics and powertrain operation of hybrid electric vehicles. Typically, a sequential optimization with the vehicle dynamics optimized followed by powertrain optimization is adopted to manage a number of complexities such as the inherent mixed-integer nature of the hybrid powertrain, the numerous state and control variables, the differing time scales of vehicle and powertrain subsystems, time-varying state constraints, and large horizon lengths. Instead, we solve the offline optimization problem in a centralize manner assuming exact knowledge of the lead vehicle's position over the entire trip by applying a discrete-time single shooting-based numerical approach, Discrete Mixed-Integer Shooting (DMIS), including a linearly increasing computational complexity to the problem horizon. In particular, the hierarchical problem structure is exploited to decompose the computationally intensive Hamiltonian minimization step into a set of low-dimensional optimizations. DMIS allows us to compute the direct fuel minimization problem including the vehicle and powertrain dynamics in a centralized manner to its full horizon while systematically tuning weighting factors that penalize passenger discomfort. For the first time, this study reveals that practically implemented sequential optimization exhibits similar fuel optimality as co-optimization when a certain level of passenger comfort is required.

Automation & Control Systems↗
DOE OSTI2023

Estimating National-Scale Wind Potential Using Spatially Explicit Turbine Layout Optimization

National renewable energy potential assessments play a broad and critical role in analysis of the clean energy transition by providing foundational estimates of developable clean resources. Common to all past wind potential assessments is an assumption that wraps the complexity of wind plant layout (arrangement of turbines) into a single metric known as capacity density, or rated power capacity per unit of land area. Quite often, a singular capacity density or rotor-diameter driven capacity density is used in wind potential assessments across broad geographies despite the complexities of local drivers. Here, we present a new wind technical potential assessment for the United States, leveraging a spatial optimization approach in lieu of the traditional uniform capacity density. The optimization approach is a spatially explicit method for determining the potential locations of individual wind turbines-taking into account the turbine configuration, plant economics and losses, wind resource, and siting considerations. Our approach accounts for the interactions between wind technology design, wind plant layout, and the vast array of regulatory, land use and infrastructure conflicts with wind development. Our results highlight the potential ability of larger turbines to enable increased wind capacity, up to a point, and increased generation when siting turbines in and around spatial constraints; moreover, they demonstrate and capture the LCOE benefit of relatively lower capacity densities and reduced wake losses when land is relatively abundant. These insights provide foundational knowledge for the wind sector as it develops and pursues future turbine models and as wind energy markets expand in zero-carbon futures. Further, when applied in capacity expansion models, supply curves developed by these methods can provide detailed local insights about where wind turbines might be deployed in and among known siting constraints for those regions where wind energy is determined to be economic, providing critical nuance to local decision-makers and stakeholders.

17 WIND ENERGY↗
DOE OSTI2023

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ~ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ~ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Assembly of objects with not fully predefined shapes

An assembly problem in a non-deterministic environment, i.e., where parts to be assembled have unknown shape, size and location, is described. The only knowledge used by the robot to perform the assembly operation is given by a connectivity rule and geometrical constraints concerning parts. Once a set of geometrical features of parts has been extracted by a vision system, applying such a rule allows the dtermination of the composition sequence. A suitable sensory apparatus allows the control the whole operation.

Arlotti, M. A.↗
NASA NTRSDate not supplied

The Aguas Zarcas Breccia - Similarities to Surface Features of C-Complex Asteroids Ryugu and Bennu

Knowledge of the materials originally present in the proto-solar nebula is one of the most significant constraints for models concerning the formation of our solar system. The physicochemical properties of these original materials can be determined through two distinct and complementary approaches: astronomical observations of nascent stellar systems and the dense clouds from which they originated; and laboratory studies of available astromaterials such as meteorites, interplanetary dust particles, comets, as well as returned mission samples (e.g., from Hayabusa -1 -2;OSIRIS -Rex). Laboratory study of these extraterrestrial materials provides valuable information about the first solids portion of the early solar system and their evolution. Here, we present petrographic and mineralogical characteristics of the polymic beccias Aguas Zarcas based on the research results of [1].On April 23, 2019, at 21:07 local time, a meteorite fall occurred in Aguas Zarcas, San Carlos County, Alajuela province, Costa Rica. The rapid recovery of this brecciated carbonaceous chondrite after its fall provides an opportunity to study a freshly fallen, relatively uncontaminated, and highly brecciated meteorite to compare with samples returned by theHayabusa2 and OSIRIS-REx spacecraft from C-group asteroids. The study includes several pre-rain fragments [1].The X-ray Computed Tomography (XCT) results show many different lithologies. We describe the petrography and mineralogy of five different lithologies of the Aguas Zarcas meteorite. We also present data on bulk oxygen isotopes. We describe all fragments in detail and attempt to classify each lithology in order to understand the origin and formation history of the Aguas Zarcas parent body. Our results show that some lithologies of Aguas Zarcas are similar to those in CM chondrites, but others are unique. The different lithologies [1] also represent different degrees of hydration and heating, which are good analogues for the types of materials returned by the Bennu and Ryugu asteroids. Spectroscopic observations of the Ryugu and Bennu asteroids compared to laboratory measurements of meteorites suggest that the asteroids have some similarities to heated CM, heated CI, or CI chondrites[2-5]. Both asteroids are thought to be composed of materials altered by aqueous alteration (e.g., [5]) and formed by reaccretion after destruction by impacts and brecciation (e.g., [6-7]). Considering the different lithologies in Aguas Zarcas [2] and other CM chondrites [8-9], these types of carbonaceous chondrites can be considered good analogues for samples from the Ryugu and Bennu asteroids. The presence of unique and rare lithologies in the Aguas Zarcas, different from the typical CM chondrite lithologies, suggests complex mixing of different materials in a highly dynamic environment.

Imene Kerraouch↗
NASA NTRS2023

Modeling Dust Mineralogical Composition: Sensitivity to Soil Mineralogy Atlases and Their Expected Climate Impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ∼ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

Soil dust↗
NASA NTRS1991

Extensions to the Parallel Real-Time Artificial Intelligence System (PRAIS) for fault-tolerant heterogeneous cycle-stealing reasoning

Extensions to an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS) are discussed. PRAIS strives for transparently parallelizing production (rule-based) systems, even under real-time constraints. PRAIS accomplished these goals (presented at the first annual C Language Integrated Production System (CLIPS) conference) by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors. Results using the original PRAIS architecture over a network of Sun 3's, Sun 4's and VAX's are presented. Mechanisms using the producer-consumer model to extend the architecture for fault-tolerance and distributed truth maintenance initiation are also discussed.

Goldstein, David↗
NASA NTRS1992

The state of knowledge concerning the Kuiper belt

The arguments for and against the idea that most short-period comets originate in the Kuiper belt are discussed. Observational constraints on the distribution of mass in the Kuiper belt are reviewed as well as a model of the physical conditions that now exist. Finally, predictions from this model about the detectability of the Kuiper belt are compared to optical surveys.

Levison, Harold F.↗
NASA NTRS2013

Design Constraints Regarding The Use Of Fluids In Emergency Medical Systems For Space Flight

The Exploration Medical Capability Project of the Human Research Program is tasked with identifying, investigating and addressing gaps existing gaps in either knowledge or technology that need to be addressed in order to enable safer exploration missions. There are several gaps that involve treatment for emergency medical situations. Some of these treatments involve the handling of liquids in the spacecraft environment which involve gas-liquid mixtures handling, dissolution chemistry and thermal issues. Some of the recent technology efforts include the Intravenous fluid generation (IVGEN) experiment, the In-Suit Injection System (ISIS) experiment, and medical suction. Constraints include limited volume, shelf life, handling biohazards, availability of power, crew time and medical training.

McQuillen, John↗
DOE OSTI2026

Towards a self-driving trigger at the LHC: adaptive response in real time

Real-time data filtering and selection—or trigger—systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider must process extremely high-rate data streams under stringent bandwidth, latency, and storage constraints. Yet these systems are typically designed as static, hand-tuned menus of selection criteria grounded in prior knowledge and simulation. In this work, we further explore the concept of a self-driving trigger, an autonomous data-filtering framework that reallocates resources and adjusts thresholds dynamically in real-time to optimize signal efficiency, rate stability, and computational cost as instrumentation and environmental conditions evolve. We introduce a benchmark ecosystem to emulate realistic collider scenarios and demonstrate real-time optimization of a menu including canonical energy sum triggers as well as modern anomaly-detection algorithms that target non-standard event topologies using machine learning. Using simulated data streams and publicly available collision data from the Compact Muon Solenoid experiment, we demonstrate the capability to dynamically and automatically optimize trigger performance under specific cost objectives without manual retuning. Our adaptive strategy shifts trigger design from static menus with heuristic tuning to intelligent, automated, data-driven control, unlocking greater flexibility and discovery potential in future high-energy physics analyses.

Emami, Shaghayegh [Michigan U.] (ORCID:00090007589↗
DOE OSTI2022

Multi-process tooling for discontinuous carbon and hybrid glass fiber thermoplastics

Expensive tooling often constraints the use of composites in the design and development of automotive parts. While there is significant confidence and knowledge in sheet and bulk metals, composite processes are less understood in mass production environment. The processes used to produce composites and resulting properties are influenced by fiber length attrition, resin to fiber ratio, process waste etc. Tool designs are determined very early in the engineering process. It is cost prohibitive to build additional tools, in the event it becomes obvious a better processing method and material would be beneficial, the original decision is not easily changed. In the present work we recognize the bottleneck of tooling costs and provide an approach of multi-process tooling. The innovation of this work is the design and demonstration of a single tool for different processes namely injection, injection-compression and extrusion-compression. The materials used in this study were long and short fiber thermoplastics (LFTs and SFTs). The resulting structure-property relationships have been reported for the materials and processing methods with a battery tray (BT) tool.

Vaidya, Uday↗
NASA NTRS1984

The role of DBMS in design research

Research in integrated design systems which is almost invariable predicated on the existence of a data base that acts as a common repository of data representing the emerging specification of the system or artifact designed is discussed. The role of data base management systems (DBMS) in design reserch is outlined as follows: (1) the representation and processing of detailed constraints is presented, including a dynamic mechanism for activating cnstraints as a design is firmed up, (2) a concept of treating multiple sets of constraints as data residing in the data base is presented; (3) exploratory work on the interaction of DBMS with knowledge based expert design systems is given.

Fenves, S. J.↗
NASA NTRS1993

High redshift QSOs and the x ray background

ROSAT pointed observations were made of 9 QSO's from the Large Bright Quasar Survey (LBQS). The LBQS is based on machine measurement of objective prism plates taken with the UK Schmidt Telescope. Software has been used to select QSO's by both color and by the presence of spectral features and continuum breaks. The probability of detection can be calculated as a function of magnitude, redshift and spectral features, and the completeness of the survey can be accurately estimated. Nine out of 1040 QSO's in the LBQS have z greater than 3. The observations will provide an important data point in the X-ray luminosity function of QSO's at high redshift. The QSO's with z greater than 3 span less than a magnitude in M(sub B), so can be combined as a homogeneous sample. This analysis is only possible with a sample drawn from a large and complete catalog such as the LBQS. Four of the 9 QSO's that were observed with the ROSAT PSPC for this proposal were detected, including one of the most luminous X-ray sources ever observed. The April 1992 version of the PROS DETECT package was used to reduce the data. The results have been used to search for evolution of the X-ray properties of QSO's in redshift. The 9 QSO's lie in the range -28.7 less than M(sub B) less than -27.8. When combined with data for 16 QSO's in a similar luminosity range at lower redshift correlations with luminosity and redshift can be separated out. The LBQS sample also yields a new constraint on the contribution of high redshift QSO's to the X-ray background. An initial requirement is knowledge of the X-ray properties (alpha(sub OX)) as a function of redshift. Integration over the evolving luminosity function of the LBQS then gives the QSO contribution to the source counts.

Impey, Chris↗