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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 415 records · Page 23

Cryogenic Fluid Management Technologies for Advanced Green Propulsion Systems

In support of the Exploration Vision for returning to the Moon and beyond, NASA and its partners are developing and testing critical cryogenic fluid propellant technologies that will meet the need for high performance propellants on long-term missions. Reliable knowledge of low-gravity cryogenic fluid management behavior is lacking and yet is critical in the areas of tank thermal and pressure control, fluid acquisition, mass gauging, and fluid transfer. Such knowledge can significantly reduce or even eliminate tank fluid boil-off losses for long term missions, reduce propellant launch mass and required on-orbit margins, and simplify vehicle operations. The Propulsion and Cryogenic Advanced Development (PCAD) Project is performing experimental and analytical evaluation of several areas within Cryogenic Fluid Management (CFM) to enable NASA's Exploration Vision. This paper discusses the status of the PCAD CFM technology focus areas relative to the anticipated CFM requirements to enable execution of the Vision for Space Exploration.

Motil, Susan M.↗

Three Orbital Burns to Molniya Orbit via Shuttle Centaur G Upper Stage

An unclassified analytical trajectory design, performance, and mission study was done for the 1982-86 joint NASA-USAF Shuttle/Centaur G upper stage development program to send performance-demanding payloads to high orbits such as Molniya using an unconventional orbit transfer. This optimized three orbital burn transfer to Molniya orbit was compared to the then-baselined two burn transfer. The results of the three dimensional trajectory optimization performed include powered phase steering data and coast phase orbital element data. Time derivatives of the orbital elements as functions of thrust components were evaluated and used to explain the optimization's solution. Vehicle performance as a function of parking orbit inclination was given. Performance and orbital element data was provided for launch windows as functions of launch time. Ground track data was given for all burns and coasts including variation within the launch window. It was found that a Centaur with fully loaded propellant tanks could be flown from a 37deg inclination low Earth parking orbit and achieve Molniya orbit with comparable performance to the baselined transfer which started from a 57deg inclined orbit: 9,545 lb vs. 9,552 lb of separated spacecraft weight respectively. There was a significant reduction in the need for propellant launch time reserve for a one hour window: only 78 lb for the three burn transfer vs. 320 lb for the two burn transfer. Conversely, this also meant that longer launch windows over more orbital revolutions could be done for the same amount of propellant reserve. There was no practical difference in ground tracking station or airborne assets needed to secure telemetric data, even though the geometric locations of the burns varied considerably. There was a significant adverse increase in total mission elapsed time for the three vs. two burn transfer (12 vs. 11/4 hrs), but could be accommodated by modest modifications to Centaur systems. Future applications were discussed. The three burn transfer was found to be a viable, arguably preferable, alternative to the two burn transfer.

Orbital trajectory design↗

Three Orbital Burns to Molniya Orbit Via Shuttle_Centaur G Upper Stage

An unclassified analytical trajectory design, performance, and mission study was done for the 1982 to 1986 joint National Aeronautics and Space Administration (NASA)-United States Air Force (USAF) Shuttle/Centaur G upper stage development program to send performance-demanding payloads to high orbits such as Molniya using an unconventional orbit transfer. This optimized three orbital burn transfer to Molniya orbit was compared to the then-baselined two burn transfer. The results of the three dimensional trajectory optimization performed include powered phase steering data and coast phase orbital element data. Time derivatives of the orbital elements as functions of thrust components were evaluated and used to explain the optimization's solution. Vehicle performance as a function of parking orbit inclination was given. Performance and orbital element data was provided for launch windows as functions of launch time. Ground track data was given for all burns and coasts including variation within the launch window. It was found that a Centaur with fully loaded propellant tanks could be flown from a 37 deg inclination low Earth parking orbit and achieve Molniya orbit with comparable performance to the baselined transfer which started from a 57 deg inclined orbit: 9,545 versus 9,552 lb of separated spacecraft weight, respectively. There was a significant reduction in the need for propellant launch time reserve for a 1 hr window: only 78 lb for the three burn transfer versus 320 lb for the two burn transfer. Conversely, this also meant that longer launch windows over more orbital revolutions could be done for the same amount of propellant reserve. There was no practical difference in ground tracking station or airborne assets needed to secure telemetric data, even though the geometric locations of the burns varied considerably. There was a significant adverse increase in total mission elapsed time for the three versus two burn transfer (12 vs. 1-1/4 hr), but could be accommodated by modest modifications to Centaur systems. Future applications were discussed. The three burn transfer was found to be a viable, arguably preferable, alternative to the two burn transfer.

Orbital trajectory design↗

Experimental and Numerical Analysis of Triaxially Braided Composites Utilizing a Modified Subcell Modeling Approach

A combined experimental and analytical approach was performed for characterizing and modeling triaxially braided composites with a modified subcell modeling strategy. Tensile coupon tests were conducted on a [0deg/60deg/-60deg] braided composite at angles of 0deg, 30deg, 45deg, 60deg and 90deg relative to the axial tow of the braid. It was found that measured coupon strength varied significantly with the angle of the applied load and each coupon direction exhibited unique final failures. The subcell modeling approach implemented into the finite element software LS-DYNA was used to simulate the various tensile coupon test angles. The modeling approach was successful in predicting both the coupon strength and reported failure mode for the 0deg, 30deg and 60deg loading directions. The model over-predicted the strength in the 90deg direction; however, the experimental results show a strong influence of free edge effects on damage initiation and failure. In the absence of these local free edge effects, the subcell modeling approach showed promise as a viable and computationally efficient analysis tool for triaxially braided composite structures. Future work will focus on validation of the approach for predicting the impact response of the braided composite against flat panel impact tests.

Micromechanics↗

Experimental and Numerical Analysis of Triaxially Braided Composites Utilizing a Modified Subcell Modeling Approach

A combined experimental and analytical approach was performed for characterizing and modeling triaxially braided composites with a modified subcell modeling strategy. Tensile coupon tests were conducted on a [0deg/60deg/-60deg] braided composite at angles [0deg, 30deg, 45deg, 60deg and 90deg] relative to the axial tow of the braid. It was found that measured coupon strength varied significantly with the angle of the applied load and each coupon direction exhibited unique final failures. The subcell modeling approach implemented into the finite element software LS-DYNA was used to simulate the various tensile coupon test angles. The modeling approach was successful in predicting both the coupon strength and reported failure mode for the 0deg, 30deg and 60deg loading directions. The model over-predicted the strength in the 90deg direction; however, the experimental results show a strong influence of free edge effects on damage initiation and failure. In the absence of these local free edge effects, the subcell modeling approach showed promise as a viable and computationally efficient analysis tool for triaxially braided composite structures. Future work will focus on validation of the approach for predicting the impact response of the braided composite against flat panel impact tests.

Polymer Matrix Composites↗

Propulsion Powertrain Real-Time Simulation Using Hardware-in-the-Loop (HIL) for Aircraft Electric Propulsion System

It is essential to design a propulsion powertrain real-time simulator using the hardware-in-the-loop (HIL) system that emulates an electrified aircraft propulsion (EAP) systems power grid. This simulator would enable us to facilitate in-depth understanding of the system principles, to validate system model analysis and performance prediction, and to demonstrate the proof-of-concept of the EAP electrical system. This paper describes how subscale electrical machines with their controllers can mimic the power components in an EAP powertrain. In particular, three powertrain emulations are presented to mimic 1) a gas turbo-=shaft engine driving a generator, consisting of two permanent magnet (PM) motors with brushless motor drives, coupled by a shaft, 2) a motor driving a propulsive fan, and 3) a turbo-shaft engine driven fan (turbofan engine) operation. As a first step towards the demonstration, experimental dynamic characterization of the two motor drive systems, coupled by a mechanical shaft, were performed. The previously developed analytical motor models1 were then replaced with the experimental motor models to perform the real-time demonstration in the predefined flight path profiles. This technique can convert the plain motor system into a unique EAP power grid emulator that enables rapid analysis and real-time simulation performance using hardware-in-the-loop (HIL).

turbo-electric propulsion↗

SWIM: A Semi-Analytical Ocean Color Inversion Algorithm for Optically Shallow Waters

In clear shallow waters, light that is transmitted downward through the water column can reflect off the sea floor and thereby influence the water-leaving radiance signal. This effect can confound contemporary ocean color algorithms designed for deep waters where the seafloor has little or no effect on the water-leaving radiance. Thus, inappropriate use of deep water ocean color algorithms in optically shallow regions can lead to inaccurate retrievals of inherent optical properties (IOPs) and therefore have a detrimental impact on IOP-based estimates of marine parameters, including chlorophyll-a and the diffuse attenuation coefficient. In order to improve IOP retrievals in optically shallow regions, a semi-analytical inversion algorithm, the Shallow Water Inversion Model (SWIM), has been developed. Unlike established ocean color algorithms, SWIM considers both the water column depth and the benthic albedo. A radiative transfer study was conducted that demonstrated how SWIM and two contemporary ocean color algorithms, the Generalized Inherent Optical Properties algorithm (GIOP) and Quasi-Analytical Algorithm (QAA), performed in optically deep and shallow scenarios. The results showed that SWIM performed well, whilst both GIOP and QAA showed distinct positive bias in IOP retrievals in optically shallow waters. The SWIM algorithm was also applied to a test region: the Great Barrier Reef, Australia. Using a single test scene and time series data collected by NASA's MODIS-Aqua sensor (2002-2013), a comparison of IOPs retrieved by SWIM, GIOP and QAA was conducted.

shallow waters↗

The Next Generation X-Ray Galaxy Survey with eROSITA

eROSITA, launched on 13 July 2019, will be completing the first all-sky survey in the soft and medium X-ray band in nearly three decades. This 4-year survey, finishing in late 2023, will present a rich legacy for the entire astrophysics community and complement upcoming multi-wavelength surveys (with, e.g. the Large Synoptic Survey Telescope and the Dark Energy Survey). Besides the major scientific aim to study active galactic nuclei (AGN) and galaxy clusters, eROSITA will contribute significantly to X-ray studies of normal (i.e. not AGN) galaxies. Starting from multi-wavelength catalogues, we measure star formation rates and stellar masses for 60 212 galaxies constrained to distances of 50–200 Mpc. We chose this distance range to focus on the relatively unexplored volume outside the local Universe, where galaxies will be largely spatially unresolved and probe a range of X-ray luminosities that overlap with the low luminosity and/or highly obscured AGN population. We use the most recent X-ray scaling relations as well as the on-orbit eROSITA instrument performance to predict the X-ray emission from XRBs and diffuse hot gas and to perform both an analytic prediction and an end-to-end simulation using the mission simulation software, SIXTE. We consider potential contributions from hidden AGN and comment on the impact of normal galaxies on the measurement of the faint end of the AGN luminosity function. We predict that the eROSITA 4-year survey, will detect ≳15 000 galaxies (3σ significance) at 50–200 Mpc, which is ~ 100× more normal galaxies than detected in any X-ray survey to date.

Surveys↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

Evaluation and expansion of an analytical model for fatigue of notched composite laminates

The analytical and experimental study performed to expand the existing static and fatigue failure analysis is described. The analytical effort extended the analysis to include interlaminar effects, while the experimental effort developed methods to obtain basic experimental data required as input to the analysis. The static failure analysis for notched laminates was modified to include interlaminar effects near the notch. Three dimensional elastic and two dimensional elasticplastic finite element analysis were performed for some notched laminates.

Ramkumar, R. L.↗

Effects of higher harmonic control on rotor performance and control loads

An analytical study, based on an advanced Higher Harmonic Control (HHC) analysis for helicopter rotor systems, is carried out to investigate HHC application for rotor performance enhancement. The effects of HHC on stall characteristics of rotor and blade pitch-link loads when the system is configured to suppress vibration are also examined. For vibration control, simulated results indicate that HHC may promote early blade stall. Effects of blade torsion frequencies on HHC performance are moderate, and torsionally stiff blades require less actuator power than torsionally soft blades. For rotor performance improvement, a 3 to 5 percent reduction in rotor shaft power can be achieved with 2 deg of two-per-rev blade pitch control.

Nguyen, Khanh↗

Study of helicopterroll control effectiveness criteria

A study of helicopter roll control effectiveness based on closed-loop task performance measurement and modeling is presented. Roll control critieria are based on task margin, the excess of vehicle task performance capability over the pilot's task performance demand. Appropriate helicopter roll axis dynamic models are defined for use with analytic models for task performance. Both near-earth and up-and-away large-amplitude maneuvering phases are considered. The results of in-flight and moving-base simulation measurements are presented to support the roll control effectiveness criteria offered. This Volume contains the theoretical analysis, simulation results and criteria development.

Heffley, Robert K.↗

Aeroelasticity of Axially Loaded Aerodynamic Structures for Truss-Braced Wing Aircraft

This paper presents an aeroelastic finite-element formulation for axially loaded aerodynamic structures. The presence of axial loading causes the bending and torsional sitffnesses to change. For aircraft with axially loaded structures such as the truss-braced wing aircraft, the aeroelastic behaviors of such structures are nonlinear and depend on the aerodynamic loading exerted on these structures. Under axial strain, a tensile force is created which can influence the stiffness of the overall aircraft structure. This tension stiffening is a geometric nonlinear effect that needs to be captured in aeroelastic analyses to better understand the behaviors of these types of aircraft structures. A frequency analysis of a rotating blade structure is performed to demonstrate the analytical method. A flutter analysis of a truss-braced wing aircraft is performed to analyze the effect of geometric nonlinear effect of tension stiffening on the flutter speed. The results show that the geometric nonlinear tension stiffening effect can have a significant impact on the flutter speed prediction. In general, increased wing loading results in an increase in the flutter speed. The study illustrates the importance of accounting for the geometric nonlinear tension stiffening effect in analyzing the truss-braced wing aircraft.

Aeroelasticity↗

High-Performance X-ray Detection in a New Analytical Electron Microscope

X-ray detection by energy-dispersive spectrometry in the analytical electron microscope (AEM) is often limited by low collected X-ray intensity (P), modest peak-to-background (P/B) ratios, and limitations on total counting time (tau) due to specimen drift and contamination. A new AFM has been designed with maximization of P. P/B, and tau as the primary considerations. Maximization of P has been accomplished by employing a field-emission electron gun, X-ray detectors with high collection angles, high-speed beam blanking to allow only one photon into the detector at a time, and simultaneous collection from two detectors. P/B has been maximized by reducing extraneous background signals generated at the specimen holder, the polepieces and the detector collimator. The maximum practical tau has been increased by reducing specimen contamination and employing electronic drift correction. Performance improvments have been measured using the NIST standard Cr thin film. The 0-3 steradian solid angle of X-ray collection is the highest value available. The beam blanking scheme for X-ray detection provides 3-4 times greater throughput of X-rays at high count rates into a recorded spectrum than normal systems employing pulse-pileup rejection circuits. Simultaneous X-ray collection from two detectors allows the highest X-ray intensity yet recorded to be collected from the NIST Cr thin film. The measured P/B of 6300 is the highest level recorded for an AEM. In addition to collected X-ray intensity (cps/nA) and P/B measured on the standard Cr film, the product of these can be used as a figure-of-merit to evaluate instruments. Estimated minimum mass fraction (MMF) for Cr measured on the standard NIST Cr thin film is also proposed as a figure-of-merit for comparing X-ray detection in AEMs. Determinations here of the MMF of Cr detectable show at least a threefold improvement over previous instruments.

Lyman, C. E.↗

A compendium of millimeter wave propagation studies performed by NASA

Key millimeter wave propagation experiments and analytical results were summarized. The experiments were performed with the Ats-5, Ats-6 and Comstar satellites, radars, radiometers and rain gage networks. Analytic models were developed for extrapolation of experimental results to frequencies, locations, and communications systems.

Kaul, R.↗