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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Effects of Adiabatic Heating on the High Strain Rate Deformation of Polymer Matrix Composites

Polymer matrix composites (PMCs) are increasingly being used in aerospace structures that are expected to experience complex dynamic loading conditions throughout their lifetime. As such, a detailed understanding of the high strain rate behavior of the constituents, particularly the strain rate, temperature, and pressure dependent polymer matrix, is paramount. In this paper, preliminary efforts in modeling experimentally observed temperature rises due to plastic deformation in PMCs subjected to dynamic loading are presented. To this end, an existing isothermal viscoplastic polymer constitutive formulation is extended to model adiabatic conditions by incorporating temperature dependent elastic properties and modifying the components of the inelastic strain rate tensor to explicitly depend on temperature. It is demonstrated that the modified polymer constitutive model is capable of capturing strain rate and temperature dependent yield as well as thermal softening associated with the conversion of plastic work to heat at high rates of strain. The modified constitutive model is then embedded within a strength of materials based micromechanics framework to investigate the manifestation of matrix thermal softening, due to the conversion of plastic work to heat, on the high strain rate response of a T700Epon 862 (T700E862) unidirectional composite. Adiabatic model predictions for high strain rate composite longitudinal tensile, transverse tensile, and in-plane shear loading are presented. Results show a substantial deviation from isothermal conditions; significant thermal softening is observed for matrix dominated deformation modes (transverse tension and in-plane shear), highlighting the importance of accounting for the conversion of plastic work to heat in the polymer matrix in the high strain rate analysis of PMC structures.

polymer matrix composites↗
NASA NTRS2017

Self Assembled Particles

A self-assembling structure using non-equilibrium driving forces leading to 'living crystals' and other maniputable particles with a complex dynamics. The dynamic self-assembly assembly results from a competition between self-propulsion of particles and an attractive interaction between the particles. As a result of non-equilibrium driving forces, the crystals form, grow, collide, anneal, repair themselves and spontaneously self-destruct, thereby enabling reconfiguration and assembly to achieve a desired property.

Palacci, Jeremie↗
NASA NTRS2018

Cyclic Symmetry Finite Element Forced Response Analysis of a Distortion-Tolerant Fan with Boundary Layer Ingestion

Accurate prediction of the blade vibration stress is required to determine overall durability of fan blade design under Boundary Layer Ingestion (BLI) distorted flow environments. Traditional single blade modeling technique is incapable of representing accurate modeling for the entire rotor blade system subject to complex dynamic loading behaviors and vibrations in distorted flow conditions. A particular objective of our work was to develop a high-fidelity full-rotor aeromechanics analysis capability for a system subjected to a distorted inlet flow by applying cyclic symmetry finite element modeling methodology. This reduction modeling method allows computationally very efficient analysis using a small periodic section of the full rotor blade system. Experimental testing by the use of the 8-foot by 6-foot Supersonic Wind Tunnel Test facility at NASA Glenn Research Center was also carried out for the system designated as the Boundary Layer Ingesting Inlet/Distortion-Tolerant Fan (BLI2DTF) technology development. The results obtained from the present numerical modeling technique were evaluated with those of the wind tunnel experimental test, toward establishing a computationally efficient aeromechanics analysis modeling tool facilitating for analyses of the full rotor blade systems subjected to a distorted inlet flow conditions. Fairly good correlations were achieved hence our computational modeling techniques were fully demonstrated. The analysis result showed that the safety margin requirement set in the BLI2DTF fan blade design provided a sufficient margin with respect to the operating speed range.

forced response analysis↗
NASA NTRS2019

Quantifying Contributions of Land Carbon Fluxes Variability and Atmospheric Transport Variability to Atmospheric CO2 Variability

Much of the uncertainty in predicting variations in greenhouse gases originates in the complex dynamics of the land ecosystem and the atmosphere. To reduce the uncertainties, it is useful to decouple the contributions of land carbon fluxes and atmospheric transport to atmospheric carbon variability. Here we isolate these contributions using a version of the NASA GEOS model that couples carbon, energy and water cycles between the land and the atmosphere. Our current study is a follow-on to a preliminary analysis that suggested that an extreme event (e.g., imposed drought) in a free running AGCM simulation affects atmospheric CO2 more through its impact on atmospheric transport than through a modification of land carbon fluxes. In order to more carefully isolate the effects of the land carbon variability and atmospheric transport variability on atmospheric CO2 variability, we conducted two coupled-AGCM simulations in replay mode, a mode that forces the model's evolution of weather to match that of the MERRA-2 reanalysis. In the control simulation, the land carbon fluxes and the atmospheric CO2 concentrations, as well as the meteorology, are simulated over 2001-2015. We compute the climatological seasonal cycles of net land carbon production from this control simulation and then prescribe, in a second simulation, these climatological carbon fluxes to the atmosphere in the same replay mode. By comparing the atmospheric CO2 variability produced in the two simulations, we fully isolate the part of this variability associated with land surface fluxes. Relative contributions of land flux variability and atmospheric transport variability to CO2 variability are quantified both on a regional basis and as a function of height into the atmosphere to support interpretation of both ground-based and satellite observations.

Lee, Eunjee↗
NASA NTRS2018

PACE Technical Report Series, Volume 4: Cloud Retrievals in the PACE Mission: PACE Science Team Consensus Document

Earth is a complex dynamical system exhibiting continuous change in its atmosphere, ocean,and surface elements. Nearly all (99.97%) of the energy driving these systems is linked to the Sun. Measurements of reflected sunlight contain a unique signature of wavelength-specific scattering and absorption interactions occurring between incoming solar energy and atmospheric (molecules, aerosols,clouds) and surface features Clouds can affect significantly both shortwave and long wave radiation, depending on altitude/vertical structure, thermodynamic phase, and optical properties. Low, warm, and optically thick clouds predominantly have a cooling effect, while high, cold, optically thin clouds can cause warming by absorbing warmer radiation emitted from the surface and lower atmosphere.When the net difference between outgoing and incoming solar radiation is matched by the net infrared radiation emitted to space, the Earth's climate is in radiative balance. While radiative forcing components (GHGs, aerosols - direct and indirect) contribute to a net radiative imbalance, climate sensitivity is ultimately determined by the contribution of various system feed backs. The role of cloud feedback in a warming climate is currently the largest inter-model uncertainty in climate sensitivity and therefore in climate prediction [Bony and Dufresne 2005]. A comprehensive understanding of current cloud propertiesand dynamic/microphysical processes requires a global perspective from satellites.

Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)↗
NASA NTRS2017

AIDA: Measuring Asteroid Binary System Parameters and DART-Imparted Deflection Using the AIM Spacecraft

The Asteroid Impact and Deflection Assessment (AIDA) mission concept would demonstrate an asteroid deflection through a high velocity spacecraft impact on the moon of the binary asteroid system Didymos. The NASA DART spacecraft would be launched on an impacting trajectory, while the ESA AIM spacecraft would be orbiting and observing the system before and after the impact. Radio science measurements with AIM provides information on the complex dynamics of the binary system. Combined with the DART experiment, the ability to measure the imparted delta-v has significant implications for how well the proposed AIDA mission would serve as a deflection demonstration. In addition, the impact-induced deflection, cratering, and mass transfer can be interpreted as indicators of surface properties. We provided preliminary analyses of the measurability of the DART impact as function of generic AIM spacecraft proximity operations and knowledge of the Didymos system from radio science techniques.

Bellerose, Julie↗
NASA NTRS2017

Observations, Modeling, and Predictions of Solar Activity From the Deep Interior to the Corona

Solar activity is a manifestation of magnetic self-organization processes that involve complex dynamical coupling of various layers of the Sun acting over a broad range of spatial and temporal scales. Synergy of observational, theoretical, and modeling efforts is key to understanding solar activity variation, dynamics, and evolution and to developing reliable physics-based forecasts of long-term solar cycles and short-term activity manifestations, “seasons of solar activity”, such as periods of enhanced flaring and CME activity. The session welcomes observers, modelers, and theoreticians to share their results and ideas and to discuss current challenges, development of emerging fields (such as data assimilation), and the analysis of historical and modern observational data using theoretical modeling, interpretations, and predictions.

Deep Interior↗
NASA NTRS2019

A Design Methodology for Optimizing and Integrating Composite Materials in Gear Structures

The application of composite materials to gear structures is complex because of the gear shape, the need for precise dimensional tolerances, and the complex dynamic load condition. Methods are presented in this work to design and optimize an integrated composite hub-web structure that can be used as part of a hybrid composite-steel gear. The composite hub-web structure is a planar structure with a large decrease in thickness from the hub to the rim. Methods for design and optimization of this variable-thickness structure are presented along with a method for forming braided prepreg material to conform to the shape of this structure. A layered approach is presented that integrates cut plies or filler materials for thickness buildup with continuous-fiber layers for the primary load path. An additional gear design concept is presented that has an axially extended continuous-fiber composite structure that can be combined with the planar structure. A proposed optimization methodology is introduced where an optimized design is output for each type of optimization simulation. Through this process, composite knowledge can be incorporated in the optimization, and more control is given over the design during the process. The methods in this study provide a tool for designing and optimizing composite structures for gears and other high-power-density applications.

optimization↗
NASA NTRS2019

Water Storage Trends in High Mountain Asia

Changes in terrestrial water storage (TWS) in High Mountain Asia (HMA) could have major societal impacts, as the region’s large reservoirs of glaciers, snow, and groundwater provide a freshwater source to more than one billion people. We seek to quantify and close the budget of secular changes in TWS over the span of the GRACE satellite mission (2003–2016). To assess the TWS trend budget we consider a new high-resolution mass trend product determined directly from GRACE L1B data, glacier mass balance derived from Digital Elevation Models (DEMs), groundwater variability determined from confined and unconfined well observations, and terrestrial water budget estimates from a suite of land surface model simulations with the NASA Land Information System (LIS). This effort is successful at closing the aggregated TWS trend budget over the entire HMA region, the glaciated portion of HMA, and the Indus and Ganges basins, where the full-region trends are primarily due to the glacier mass balance and groundwater signals. Additionally, we investigate the closure of TWS trends at individual 1-arc-degree mascons (area ≈12,000 km2); a significant improvement in spatial resolution over previous analyses of GRACE-derived trends. This mascon-level analysis reveals locations where the TWS trends are well-explained by the independent datasets, as well as regions where they are not; identifying specific geographic areas where additional data and model improvements are needed. The accurate characterization of total TWS trends and its components presented here is critical to understanding the complex dynamics of the region, and is a necessary step toward projecting future water mass changes in HMA.

Bryant D Loomis↗
NASA NTRS2019

Heliocentric Escape and Lunar Impact from Near Rectilinear Halo Orbits

Spacecraft departing from the Gateway in a Near Rectilinear Halo Orbit (NRHO) experience gravitational forces from the Moon, the Earth, and the Sun, all of which can be simultaneously significant. These complex dynamics influence the post-separation risk of recontact with the Gateway and the eventual destinations of the departing spacecraft. The current investigation examines the flow of objects leaving NRHOs in the Bicircular Restricted Four-Body Problem, and results are applied to heliocentric escape and lunar impact trajectories in a higher-fidelity ephemeris model. Separation maneuver magnitude, direction, and location are correlated with risk of recontact with the Gateway and successful departure to various destinations.

Davis, Diane C.↗
NASA NTRS2018

A Persistent Simulation Environment for Autonomous Systems

The age of Autonomous Unmanned Aircraft Systems (AUAS) is creating new challenges for the accreditation and certification requiring new standards, policies and procedures that sanction whether a UAS is safe to fly. Establishing a basis for certification of autonomous systems via research into trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautics Solution (CAS) project. Simulation Environments to test and evaluate AUAS decision making may be a low-cost solution to help certify that various AUAS systems are trustworthy enough to be allowed to fly in current general and commercial aviation airspace. NASA is working to build a peer-to-peer persistent simulation (P3 Sim) environment. The P3 Sim will be a Massively Multiplayer Online (MMO) environment were AUAS avatars can interact with a complex dynamic environment and each other. The focus of the effort is to provide AUAS researchers a low-cost intuitive testing environment that will aid training for and assessment of decisions made by autonomous systems such as AUAS. This presentation focuses on the design approach and challenges faced in development of the P3 Sim Environment is support of investigating trustworthiness of autonomous systems.

Kelley, Benjamin N.↗
NASA NTRS1997

Modal Test of the Cassini Spacecraft

Modal testing of the Cassini spacecraft posed a challenge due to the large size and dynamic complexity of the spacecraft...This paper presents an overview of the test methods and results, with an emphasis on lessons learned.

modal↗
NASA NTRS2018

Online Self-Supervised Long-Range Scene Segmentation for MAVs

Recently, there have been numerous advances in the development of payload and power constrained lightweight Micro Aerial Vehicles (MAVs). As these robots aspire for high-speed autonomous flights in complex dynamic environments, robust scene understanding at long-range becomes critical. The problem is heavily characterized by either the limitations imposed by sensor capabilities for geometry-based methods, or the need for large-amounts of manually annotated training data required by data-driven methods. This motivates the need to build systems that have the capability to alleviate these problems by exploiting the complimentary strengths of both geometry and data-driven methods. In this paper, we take a step in this direction and propose a generic framework for adaptive scene segmentation using self-supervised online learning. We present this in the context of vision-based autonomous MAV flight, and demonstrate the efficacy of our proposed system through extensive experiments on benchmark datasets and real world field tests.

Matthies, Larry↗
NASA NTRSDate not supplied

How Do Different Knowledge Frameworks Help Us Learn From Aviation Line Observations?

Human performance includes actions that increase safety, as well as actions that can reduce safety. Ensuring safety in complex dynamic operations like commercial aviation depends on the ability to institute appropriate responses based on what is learned from flightcrew performance and the contexts in which it occurs. To do this systemically at the organization level requires collecting data on flightcrew performance, developing effective approaches to analyzing those data, and understanding how to translate what has been learned into policies, procedures, and practice. Systematic observation of front-line operators is a vital source of human performance data. Much has been learned from such observations, including methodological principles. Most observations have been based on a framework focused on managing safety challenges and the ensuing unsafe events. A complementary perspective focuses on flexibility and actions that promote continued safe and effective operation. We consider lessons learned about observational methods from an established framework focused on undesired actions and how these might be extended for a framework focused on desired actions.

safety↗
NASA NTRSDate not supplied

Noise Reduction and Calibration for Aeroacoustic Loads from Unsteady Pressure-Sensitive Paint

Unsteady pressure-sensitive paint (uPSP) is a significant new technology for high spatial resolution measurement of complex dynamic surface pressure loading on a wind tunnel model, to better define flight vehicle buffet and aeroacoustic loads. Compared with the very sparse surface pressure measurements of traditional sensors, the pressure sensitivity of uPSP light reflectivity provides a visual measure of surface pressure fluctuations over a wide area illuminated by high intensity light, captured by a high-speed digital camera. Panda et al (AIAA Journal, May 2019) have shown good data is recoverable up to 10 kHz. In cases where available uPSP luminescence is low for a painted wind tunnel test model, significant noise levels have been observed primarily due to the discrete photon arrival variability of low intensity light (termed “shot noise”). In this case, uPSP measurements can exhibit unusually low signal to noise ratio (SNR of 0.1 or less). This paper will report on latest work to recover calibrated uPSP measurements which are noise free over a useful dynamic range of 10-15 dB. It will be shown how the distinct spatial correlations of both the shot noise and the underlying aeroacoustic surface pressure play an important role in obtaining a reliable measurement.

pressure-sensitive paint↗
NASA NTRS2022

Isotropization and Evolution of Energy-Containing Eddies in Solar Wind Turbulence: Parker Solar Probe, Helios 1, ACE, WIND, and Voyager 1

We examine the radial evolution of correlation lengths perpendicular (l^ C) and parallel (  lC) to the magnetic-field direction, computed from solar wind magnetic-field data measured by Parker Solar Probe (PSP) during its first eight orbits, Helios 1, Advanced Composition Explorer (ACE), WIND, and Voyager 1 spacecraft. Correlation lengths are grouped by an interval’s alignment angle; the angle between the magnetic-field and solar wind velocity vectors (ΘBV). Parallel and perpendicular angular channels correspond to angles 0° < ΘBV < 40° and 50° < ΘBV < 90°, respectively. We observe an anisotropy in the inner heliosphere within 0.40 au, with  l l »^ 0.75 C C at 0.10 au. This anisotropy reduces with increasing heliocentric distance and the correlation lengths roughly isotropize within 1 au. Results from ACE and WIND support a reversal of the anisotropy, such that  l l »^ 1.29 C C at 1 au. The ratio does not appear to change significantly beyond 1 au, although the small number of parallel intervals in the Voyager data set precludes unambiguous conclusions from being drawn. This study provides insights regarding the radial evolution of the large, most energetic interacting turbulent fluctuations in the heliosphere. We also emphasize the importance of tracking the changes in sampling direction in PSP measurements as the spacecraft approaches the Sun, when using these data to study the radial evolution of turbulence. This can prove to be vital in understanding the more complex dynamics of the solar wind in the inner heliosphere and can assist in improving related simulations.

Manuel Enrique Cuesta↗
NASA NTRS2023

Constraining the Venus Interior Structure With Future VERITAS Measurements of the Gravitational Atmospheric Loading

The complex dynamics of the Venus atmosphere produces a periodic mass redistribution pattern that creates a time-variable modulation of the gravity field of Venus. This gravity signal depends on the net transport of mass across the globe and on the response of the solid body to the normal loading of its crust imparted by the atmosphere. In this work, we explore the possibility of measuring this phenomenon with VERITAS, a NASA Discovery-class mission. By simulating the gravity science experiment, we explore the possibility of measuring the response of Venus to the atmospheric loading, parametrized by the loading Love numbers ( 𝑘 𝑙 ' ), and assess the dependence of these parameters on fundamental interior structure properties. Using the most recent models of Venus' interior, we compute the Venus Love numbers in a compressible viscoelastic setting and compare them with the predicted uncertainty of the VERITAS measurements. We show that VERITAS will measure 𝑘 2 ' at the 4% level and that this measurement could possibly help to distinguish between different equally plausible interior structure models, especially allowing us to distinguish different rheological laws. We also show that a measurement campaign such as the VERITAS gravity science investigation has the potential of measuring 𝑘 2 ' not only at the loading forcing frequency, but also at the tidal frequency, ultimately providing a way to probe the response of the planet at different forcing periods.

Atmospheric tides↗
NASA NTRSDate not supplied

Risks of Increased Earth Independence

As human space exploration begins to extend beyond the immediate vicinity of Earth, the ability of expertise on the ground to support operations will progressively decrease. Ground control expertise has been the primary countermeasure preventing loss of life and mission over the past sixty years and it will be gradually stripped away as expeditions reach further into space. The large, flexible and adaptive teams of experts on the ground, provide not only engineering analysis and problem-solving but also greatly increased work capacity. Monitoring of the large and fast moving stream of telemetry data is carried out around the clock by 20-30 flight controllers per shift. Analysis of that data and troubleshooting is carried out by an additional 50-100 engineers per shift. Artificial intelligence capabilities will need to be part of the solution but will not the entire solution. As progress continues to be made on intelligent systems, especially those for use in complex, dynamic environments where humans will remain a part of the activity, there is an ever increasing need to focus on how those systems will interact with the humans. Although capabilities such as natural language processing and facial recognition have become common place, even basic aspects of problem-solving, causal reasoning and generative decision-making remain well-beyond of our current capabilities. Advanced data visualization, procedure execution support, and new training approaches will be needed to close the gap between what is currently provided by experts on the ground and what the crew will need to do in increasingly autonomous ways with greater distance from Earth.

human-systems integration architecture↗