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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Load Variation Influences on Joint Work During Squat Exercise in Reduced Gravity

Resistance exercises that load the axial skeleton, such as the parallel squat, are incorporated as a critical component of a space exercise program designed to maximize the stimuli for bone remodeling and muscle loading. Astronauts on the International Space Station perform regular resistance exercise using the Advanced Resistive Exercise Device (ARED). Squat exercises on Earth entail moving a portion of the body weight plus the added bar load, whereas in microgravity the body weight is 0, so all load must be applied via the bar. Crewmembers exercising in microgravity currently add approx.70% of their body weight to the bar load as compensation for the absence of the body weight. This level of body weight replacement (BWR) was determined by crewmember feedback and personal experience without any quantitative data. The purpose of this evaluation was to utilize computational simulation to determine the appropriate level of BWR in microgravity necessary to replicate lower extremity joint work during squat exercise in normal gravity based on joint work. We hypothesized that joint work would be positively related to BWR load.

DeWitt, John K.↗
DOE OSTI2026

Quantifying market volume sensitivity to material property modifications in polyhydroxybutyrate: A parametric analysis approach

Polyhydroxybutyrate (PHB), a biodegradable biopolymer, represents a promising alternative to petroleum-based thermoplastics. However, despite consistent market growth, PHB faces persistent commercialization challenges that limit widespread adoption. Existing research has focused predominantly on optimizing PHB production processes, leaving a critical gap in understanding which material property modifications would most effectively enhance market competitiveness. This study addresses this gap by systematically analyzing the relationship between polymer material properties and market performance using U.S. market data from 2008 to 2021 for 21 thermoplastic polymers across 19 material properties. We employed principal component regression to identify property modifications that could maximize market volume while reducing CO 2 emissions. Our parametric analysis revealed that two specific material properties – Hardness Shore A and Sheet Extrusion Temperature – significantly influence PHB marketability across different price points. Market simulations demonstrated that a 10% increase in Hardness Shore A could increase PHB market volume by 431.5 million kg while reducing emissions by 188.7 kg CO 2 . A similar 10% increase to Sheet Extrusion Temperature could yield a 297.5 million kg volume increase and a 99.2 kg CO 2 reduction in emissions. Critically, this approach is agnostic to the specific methods required to achieve these property changes, instead providing material scientists with quantitative, data-driven targets for R&D prioritization. Here, this framework offers a novel methodology for evaluating biopolymer competitiveness and supporting strategic decisions to accelerate PHB market adoption and contribute to decarbonization of the plastics industry.

09 BIOMASS FUELS↗
NASA NTRS1994

Ultraviolet-Infrared Mapping Interferometic Spectrometer

Prism and grating spectrometers have been the defacto devices for spectral mapping and imaging (hereafter referred to as hyperspectra). We have developed a new, hybrid instrument with many superior capabilities, the Digital Array Scanned Interferometer, DASI. The DASI performs the hyperspectral data acquisition in the same way as a grating or prism spectrograph, but retains the substantial advantages of the two-beam (Michelson) interferometer with additional capabilities not possessed by either of the other devices. The DASI is capable of hyperspectral studies in virtually any space or surface environment at any wavelength from below 50 nm to beyond 12 microns with available array detectors. By our efforts, we have defined simple, low cost, no-moving parts DASI's capable of carrying out hyperspectral science measurements for solar system exploration missions, e.g. for martian, asteroid, lunar, or cometary surveys. DASI capabilities can be utilized to minimize cost, weight, power, pointing, and other physical requirements while maximizing the science data return for spectral mapping missions. Our success in the development of DASI's has become and continues to be an important influence on the efforts of the best research groups developing remote sensing instruments for space and other applications.

Source record↗
NASA NTRS1994

Computational modelling of Er(3+): Garnet laser materials

The Er(3+) ion has attracted a lot of interest for four reasons: (1) Its (4)I(sub 13/2) yields (4)I(sub 15/2) transition lases in the eyesafe region near 1.5 micron; (2) the (4)I(sub 13/2) transition lases near 2.8 micron, an important wavelength for surgical purposes; (3) it displays surprisingly efficient upconversion with lasing observed at 1.7, 1.2, 0.85, 0.56, 0.55, and 0.47 micron following 1.5 micron pumping; and (4) it has absorption bands at 0.96 and 0.81 micron and thus can be diode pumped. However, properties desirable for upconversion reduce the efficiency of 1.5 and 3 micron laser operation and vice versa. Since all of the processes are influenced by the host via the crystal field induced stark splittings in the Er levels, this project undertook modelling of the host influence on the Er lasinng behavior. While growth and measurement of all ten Er(3+) doped garnets is the surest way of identifying hosts which maximize upconversion (or conversly, 1.5 and 3 micron performance), it is also expensive - costing approximately $10,000/material or approximately $100,000 for the materials computationally investigated here. The calculations were performed using a quantum mechanical point charge model developed by Clyde Morrison at Harry Diamond Laboratories. The programs were used to fit the Er:YAG experimental energy levels so that the crystal field parameters, B(sub nm) could be extracted. From these radial factors, rho (sub n) were determined for Er(3+) in garnets. These, in combination with crystal field components, Anm, available from X-ray data, were used to predict energy levels for Er in the other nine garnet hosts. The levels in Er:YAG were fit with an rms error of 12.2/cm over a 22,000/cm range. Predicted levels for two other garnets for which literature values were available had rms errors of less than 17/cm , showing the calculations to be reliable. Based on resonances between pairs of calculated stark levels, the model predicts GSGG as the best host for 1.5 micron laser operation, GSGG or YSAG as the best host for a 2.8 micron operation, and LuGG as the best host for an upconversion material.

Spangler, Lee H.↗
NASA NTRS1982

Influence of maneuverability on helicopter combat effectiveness

A computational procedure employing a stochastic learning method in conjunction with dynamic simulation of helicopter flight and weapon system operation was used to derive helicopter maneuvering strategies. The derived strategies maximize either survival or kill probability and are in the form of a feedback control based upon threat visual or warning system cues. Maneuverability parameters implicit in the strategy development include maximum longitudinal acceleration and deceleration, maximum sustained and transient load factor turn rate at forward speed, and maximum pedal turn rate and lateral acceleration at hover. Results are presented in terms of probability of skill for all combat initial conditions for two threat categories.

Falco, M.↗
DOE OSTI2025

Astrocyte FABP7 Modulates Seizure Activity-Dependent Protein Expression in Mouse Brain

Background/Objectives: Patients with epilepsy commonly experience patterns of seizures that change with sleep/wake behavior or diurnal rhythms. The cellular and molecular mechanisms that underlie these patterns in seizure activity are not well understood but may involve non-neuronal cells, such as astrocytes. Our previous studies show the critical importance of one specific astrocyte factor, the brain-type fatty acid binding protein Fabp7, in the regulation of time-of-day-dependent electroshock seizure threshold and neural activity-dependent gene expression in mice. Here, we examined whether Fabp7 influences differential seizure activity-dependent protein expression, by comparing Fabp7 knockout (KO) to wild-type (WT) mice under control conditions and after reaching the maximal electroshock seizure threshold (MEST). Methods: We analyzed the proteome in cortical–hippocampal extracts from MEST and SHAM groups of WT and KO mice using mass spectrometry (MS), followed by Gene Ontology (GO) and pathway analyses. GO and pathway analyses of all groups revealed a diverse set of up- and downregulated differentially expressed proteins (DEPs). Results: We identified 65 significant DEPs in the comparison of KO SHAM versus WT SHAM; 33 proteins were upregulated and 32 were downregulated. We found downregulation in mitochondrial-associated proteins in WT MEST compared to WT SHAM controls, including Slc1a4, Slc25a27, Cox7a2, Cox8a, Micos10, and Atp5mk. Several upregulated DEPs in the KO SHAM versus WT SHAM comparison were associated with the 20S proteasomal subunit, suggesting proteasomal activity is elevated in the absence of Fabp7 expression. We also observed 92 DEPs significantly altered in the KO MEST versus WT MEST, with 49 proteins upregulated and 43 downregulated. Conclusions: Together, these data suggest that the astrocyte Fabp7 regulation of time-of-day-mediated neural excitability is modulated by multiple cellular mechanisms, which include proteasomal pathways, independent of its role in activity-dependent gene expression.

Neural Excitability↗
NASA NTRSDate not supplied

Lunar Gateway Charging and Effects on Low-Energy Electron Measurements

The Electron Electrostatic Analyzer (EEA) is part of the HERMES instrument suite on Lunar Gateway and is designed to measure electrons in the energy range from 1 eV to 18 keV. Electrons in this range can be deflected or blocked from entering a detector by electric fields from a charged spacecraft platform, so many heliophysics missions (MMS, Cluster, etc.) use active potential control to minimize stray electric fields which would corrupt low-energy plasma measurements. Gateway, however, does not have such capabilities so the surface charging effects will influence the electron data. Further, some elements of Gateway partially block the instrument’s field of view to space. The effects of the Gateway platform on the low-energy electron population must be understood to maximize the accuracy of the EEA data. To investigate the electrostatic environment near Gateway and its effects on the EEA measurements, we use Nascap-2K to model the expected charging of Gateway under representative solar wind, magnetosheathic, and magnetospheric conditions. Next, we use the potential and electric field outputs from Nascap-2K along with in-house particle tracing codes to investigate how low-energy electrons are perturbed, blocked, or deflected by the spacecraft. We discuss how these perturbations impact the plasma moments computed from the EEA data and possible approaches for correcting the charging effects including application of advanced methods such as neural networks. In addition to electrons from the space environment being influenced by the electrostatic environment around Gateway, photoelectrons generated on Gateway surfaces will also be measured by EEA. We are investigating how knowledge of the potentials of various Gateway surfaces can be extracted from these measured photoelectrons using advanced numerical modeling and analysis. Such information would be valuable for validating charging models and planning mission operations around the platform. Finally, we discuss how the specific workflow developed for Gateway can be extended to a generalized process that is applicable to other future missions. As the space industry prepares for human exploration beyond low-Earth orbit, the need to obtain accurate space weather data from rideshare science payloads is critical. Our process for removing platform effects from the science data serves as a pathfinder for leveraging advanced simulations to maximize science returns and ensure the safety and success of future crewed missions.

Miles Bengtson↗
DOE OSTI2025

Numerical Investigation of a Small Low-Flow Marine Hydrokinetic (MHK) Turbine for Small Autonomous Unmanned Mobile Recharge Stations (CRADA Final Report)

This project will improve the hydrodynamic performance of the undershot waterwheel turbine with a flow concentrator designed by the Participant, using a computational fluid dynamics study. The influence of different result parameters including the number of blades, turbine profile, submerged depth, tip speed ratio, concentrator geometry and wave + current conditions will be assessed to maximize power performance and minimize structural loads.

16 TIDAL AND WAVE POWER↗
NASA NTRS2013

A Tool for the Automated Design and Evaluation of Habitat Interior Layouts

The objective of space habitat design is to minimize mass and system size while providing adequate space for all necessary equipment and a functional layout that supports crew health and productivity. Unfortunately, development and evaluation of interior layouts is often ignored during conceptual design because of the subjectivity and long times required using current evaluation methods (e.g., human-in-the-loop mockup tests and in-depth CAD evaluations). Early, more objective assessment could prevent expensive design changes that may increase vehicle mass and compromise functionality. This paper describes a new interior design evaluation method to enable early, structured consideration of habitat interior layouts. This interior layout evaluation method features a comprehensive list of quantifiable habitat layout evaluation criteria, automatic methods to measure these criteria from a geometry model, and application of systems engineering tools and numerical methods to construct a multi-objective value function measuring the overall habitat layout performance. In addition to a detailed description of this method, a C++/OpenGL software tool which has been developed to implement this method is also discussed. This tool leverages geometry modeling coupled with collision detection techniques to identify favorable layouts subject to multiple constraints and objectives (e.g., minimize mass, maximize contiguous habitable volume, maximize task performance, and minimize crew safety risks). Finally, a few habitat layout evaluation examples are described to demonstrate the effectiveness of this method and tool to influence habitat design.

Simon, Matthew A.↗
NASA NTRS1992

Maximum life spiral bevel reduction design

Optimization is applied to the design of a spiral bevel gear reduction for maximum life at a given size. A modified feasible directions search algorithm permits a wide variety of inequality constraints and exact design requirements to be met with low sensitivity to initial values. Gear tooth bending strength and minimum contact ratio under load are included in the active constraints. The optimal design of the spiral bevel gear reduction includes the selection of bearing and shaft proportions in addition to gear mesh parameters. System life is maximized subject to a fixed backcone distance of the spiral bevel gear set for a specified speed reduction, shaft angle, input torque, and power. Design examples show the influence of the bearing lives on the gear parameters in the optimal configurations. For a fixed back-cone distance, optimal designs with larger shaft angles have larger service lives.

Savage, M.↗
DOE OSTI2026

Queue wait time prediction in high performance computing (HPC) systems

High Performance Computing (HPC) systems are critical enablers for groundbreaking scientific research across various domains. Efficient resource allocation, facilitated by job scheduling, is paramount for maximizing the utilization of HPC systems. However, the variability in wait times for queued jobs poses challenges for users, necessitating accurate job wait time estimation. This paper explores the influence of job characteristics, including job size (the number of nodes requested and walltime), the queue to which the job is submitted and other resource requirements, on job wait times in leadership-class HPC systems. Focusing on the Theta Cray XC40 and Polaris machines at Argonne National Laboratory, the study evaluates the performance of different supervised learning algorithms in predicting job wait times. It also evaluates the impact of data preprocessing, including outlier detection, Principal Component Analysis (PCA), and feature selection, on the performance of wait time prediction models. The findings reveal insights into the relationship between job characteristics and wait times, offering a foundation for optimizing resource allocation and enhancing user experience. The methodologies and tools developed in this study are adaptable to other leadership-class HPC systems, providing a valuable contribution to the broader HPC community aiming to improve job scheduling efficiency and user satisfaction.

Okafor, Nwamaka↗
DOE OSTI2024

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗
DOE OSTI2026

Deep nonparametric estimation of operators between infinite dimensional spaces

Learning operators between infinitely dimensional spaces is an important learning task arising in machine learning, imaging science, mathematical modeling and simulations, etc. This paper studies the nonparametric estimation of Lipschitz operators using deep neural networks. Non-asymptotic upper bounds are derived for the generalization error of the empirical risk minimizer over a properly chosen network class. Under the assumption that the target operator exhibits a low dimensional structure, our error bounds decay as the training sample size increases, with an attractive fast rate depending on the intrinsic dimension in our estimation. Our assumptions cover most scenarios in real applications and our results give rise to fast rates by exploiting low dimensional structures of data in operator estimation. We also investigate the influence of network structures (e.g., network width, depth, and sparsity) on the generalization error of the neural network estimator and propose a general suggestion on the choice of network structures to maximize the learning efficiency quantitatively.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Relating ground truth collection to model sensitivity

The importance of collecting high quality ground truth before a SAR mission over a forested area is two fold. First, the ground truth is used in the analysis and interpretation of the measured backscattering properties; second, it helps to justify the use of a scattering model to fit the measurements. Unfortunately, ground truth is often collected based on visual assessment of what is perceived to be important without regard to the mission itself. Sites are selected based on brief surveys of large areas, and the ground truth is collected by a process of selecting and grouping different scatterers. After the fact, it may turn out that some of the relevant parameters are missing. A three-layer canopy model based on the radiative transfer equations is used to determine, before hand, the relevant parameters to be collected. Detailed analysis of the contribution to scattering and attenuation of various forest components is carried out. The goal is to identify the forest parameters which most influence the backscattering as a function of frequency (P-, L-, and C-bands) and incident angle. The influence on backscattering and attenuation of branch diameters, lengths, angular distribution, and permittivity; trunk diameters, lengths, and permittivity; and needle sizes, their angular distribution, and permittivity are studied in order to maximize the efficiency of the ground truth collection efforts. Preliminary results indicate that while a scatterer may not contribute to the total backscattering, its contribution to attenuation may be significant depending on the frequency.

Amar, Faouzi↗
NASA NTRS1989

Influence of hook position on phototropic and gravitropic curvature by etiolated hypocotyls of Arabidopsis thaliana

Phototropic and gravitropic curvature by hypocotyls of Arabidopsis thaliana is minimal when the side of the hook with the cotyledons attached is positioned toward the direction of tropistic curvature, and maximal when that side of the hook is positioned away from the direction of tropistic curvature. Based on these data, it is proposed that the position of the hook with attached cotyledons affects curvature and not stimulus perception. A randomly oriented population of plants exhibited considerable heterogeneity in tropistic curvature. This heterogeneity arises at least in part from the dependence of curvature on the position of the hook.

NASA Program Space Biology↗
NASA NTRS1999

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows little geographical relationship to the high cloud input. Considering whether these effects would be observable, changing upper level cloud cover by as little as 0.4% produces warming greater than 2 standard deviations in the Microwave Sounding Unit (MSU) channels 4, 2 and 2r, in flight path regions and in the subtropics. Despite the simplified nature of these experiments, the results emphasize the sensitivity of the modeled climate to high level cloud cover changes, and thus the potential ability of aircraft to influence climate by altering clouds in the upper troposphere.

Rind, David↗
DOE OSTI2025

Analysis and optimization of seismic monitoring networks with Bayesian optimal experimental design

SUMMARY Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations or experiments which can optimally reduce uncertainty and hence increase the performance of a monitoring network. Information theory guides OED by formulating the choice of experiment or sensor placement as an optimization problem that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge and models of expected observation data. Therefore, within the context of seismo-acoustic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize a sensor network’s ability to locate seismic events from arrival time data of detected seismic phases at the regional-scale. This framework requires five elements: (i) A likelihood function that describes the distribution of detection and traveltime data from the sensor network, (ii) A prior distribution that describes a priori belief about seismic events, (iii) A Bayesian solver that uses a prior and likelihood to identify the posterior distribution of seismic events given the data, (iv) An algorithm to compute EIG about seismic events over a data set of hypothetical prior events, (v) An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we explore many relevant questions to monitoring such as: how to trade off sensor fidelity and earth model uncertainty; how sensor types, number and locations influence uncertainty; and how prior models and constraints influence sensor placement.

58 GEOSCIENCES↗
DOE OSTI2024

Shape Optimization of Header Pipes in Power Plants for Enhanced Efficiency and Environmental Sustainability

In a power plant, the header pipe plays a pivotal role in optimizing the performance of diverse systems by serving as a central conduit for the collection and distribution of steam within the plant. This paper investigates the significance of header pipes within power plant setups, highlighting their critical influence on reliability, efficiency, and the performance of the power plant as a whole. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint of power plant installations. In this paper, we initially developed a methodology designed for optimizing header shapes with the primary goal of reducing the usage of costly new alloy materials and lowering the overall maintenance operation expenses. Secondly, we conducted a case study based on an authentic header sourced from an operational power plant.

20 FOSSIL-FUELED POWER PLANTS↗