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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Mapping Past, Present, and Future Climatic Suitability for Invasive Aedes Aegypti and Aedes Albopictus in the United States: A Process-Based Modeling Approach Using CMIP5 Downscaled Climate Scenarios

The ongoing spread of the mosquitoes, Aedes aegypti and Aedes albopictus, in the continental United States leaves new areas at risk for local transmission of dengue, chikungunya, and Zika viruses. All three viruses have caused major disease outbreaks in the Americas with infected travelers returning regularly to the U.S. The expanding range of these mosquitoes raises questions about whether recent spread has been enabled by climate change or other anthropogenic influences. In this analysis, we used downscaled climate scenarios from the NASA Earth Exchange Global Daily Downscaled Projections (NEX GDDP) dataset to model Ae. aegypti and Ae. albopictus population growth rates across the United States. We used a stage-structured matrix population model to understand past and present climatic suitability for these vectors, and to project future suitability under CMIP5 climate change scenarios. Our results indicate that much of the southern U.S. is suitable for both Ae. aegypti and Ae. albopictus year-round. In addition, a large proportion of the U.S. is seasonally suitable for mosquito population growth, creating the potential for periodic incursions into new areas. Changes in climatic suitability in recent decades for Ae. aegypti and Ae. albopictus have occurred already in many regions of the U.S., and model projections of future climate suggest that climate change will continue to reshape the range of Ae. aegypti and Ae. albopictus in the U.S., and potentially the risk of the viruses they transmit.

process-based modeling↗
NASA NTRS1981

On the presence of electric currents in the solar atmosphere. I - A theoretical framework

The general magnetic field above the solar photosphere is divided by an elementary analysis based on Ampere's law into two parts: a potential field due to electric currents below the photosphere and a field produced by electric currents above the photosphere combined with the induced mirror currents. The latter, by symmetry, has a set of field lines lying in the plane taken to be the photosphere which may be constructed from given vector magnetograph measurements. These field lines also represent all the information on the electric currents above the photosphere that a magnetograph can provide. Theoretical illustrations are given, and implications for data analysis are discussed.

Hagyard, M.↗
NASA NTRS1984

A multilevel method for structural synthesis

A multilevel method for structural synthesis based on finite element modeling at both the system and the substructure level is set forth. At the system level, the design is described using basis vectors generated via substructure design modification. Whenever possible, substructure constraints are satisfied via local material redistribution. At both the system level and the substructure level, design modification is carried out by solving a sequence of approximate problems. The method generates upper bound approximations for the optimum design and it has potential for substantial gains in computational efficiency, because the uncoupled substructure design modification problems can be processed in parallel.

Schmit, L. A.↗
NASA NTRS1987

Grid generation and inviscid flow computation about cranked-winged airplane geometries

An algebraic grid generation procedure that defines a patched multiple-block grid system suitable for fighter-type aircraft geometries with fuselage and engine inlet, canard or horizontal tail, cranked delta wing and vertical fin has been developed. The grid generation is based on transfinite interpolation and requires little computational power. A finite-volume Euler solver using explicit Runge-Kutta time-stepping has been adapted to this grid system and implemented on the VPS-32 vector processor with a high degree of vectorization. Grids are presented for an experimental aircraft with fuselage, canard, 70-20-cranked wing, and vertical fin. Computed inviscid compressible flow solutions are presented for Mach 2 at 3.79, 7 and 10 deg angles of attack. Conmparisons of the 3.79 deg computed solutions are made with available full-potential flow and Euler flow solutions on the same configuration but with another grid system. The occurrence of an unsteady solution in the 10 deg angle of attack case is discussed.

Eriksson, L.-E.↗
NASA NTRS1991

The numerical simulation of a high-speed axial flow compressor

The advancement of high-speed axial-flow multistage compressors is impeded by a lack of detailed flow-field information. Recent development in compressor flow modeling and numerical simulation have the potential to provide needed information in a timely manner. The development of a computer program is described to solve the viscous form of the average-passage equation system for multistage turbomachinery. Programming issues such as in-core versus out-of-core data storage and CPU utilization (parallelization, vectorization, and chaining) are addressed. Code performance is evaluated through the simulation of the first four stages of a five-stage, high-speed, axial-flow compressor. The second part addresses the flow physics which can be obtained from the numerical simulation. In particular, an examination of the endwall flow structure is made, and its impact on blockage distribution assessed.

Mulac, Richard A.↗
NASA NTRS1994

Automated path planning of the Payload Inspection and Processing System

The Payload Changeout Room Inspection and Processing System (PIPS) is a highly redundant manipulator intended for performing tasks in the crowded and sensitive environment of the Space Shuttle Orbiter payload bay. Its dexterity will be exploited to maneuver the end effector in a workspace populated with obstacles. A method is described by which the end effector of a highly redundant manipulator is directed toward a target via a Lyapunov stability function. A cost function is constructed which represents the distance from the manipulator links to obstacles. Obstacles are avoided by causing the vector of joint parameters to move orthogonally to the gradient of the workspace cost function. A C language program implements the algorithm to generate a joint history. The resulting motion is graphically displayed using the Interactive Graphical Robot Instruction Program (IGRIP) produced by Deneb Robotics. The graphical simulation has the potential to be a useful tool in path planning for the PIPS in the Shuttle Payload Bay environment.

Byers, Robert M.↗
NASA NTRS1997

Upper-Tropospheric Winds Derived from Geostationary Satellite Water Vapor Observations

The coverage and quality of remotely sensed upper-tropospheric moisture parameters have improved considerably with the deployment of a new generation of operational geostationary meteorological satellites: GOES-8/9 and GMS-5. The GOES-8/9 water vapor imaging capabilities have increased as a result of improved radiometric sensitivity and higher spatial resolution. The addition of a water vapor sensing channel on the latest GMS permits nearly global viewing of upper-tropospheric water vapor (when joined with GOES and Meteosat) and enhances the commonality of geostationary meteorological satellite observing capabilities. Upper-tropospheric motions derived from sequential water vapor imagery provided by these satellites can be objectively extracted by automated techniques. Wind fields can be deduced in both cloudy and cloud-free environments. In addition to the spatially coherent nature of these vector fields, the GOES-8/9 multispectral water vapor sensing capabilities allow for determination of wind fields over multiple tropospheric layers in cloud-free environments. This article provides an update on the latest efforts to extract water vapor motion displacements over meteorological scales ranging from subsynoptic to global. The potential applications of these data to impact operations, numerical assimilation and prediction, and research studies are discussed.

Velden, Christopher S.↗
NASA NTRS2018

Contributions of Spherical Harmonics to Gravitational Moment

A scalar gravitational potential function expressed as a series of spherical harmonics frequently serves as the basis for a model of an astronomical body's gravitational field. The contribution of a generic spherical harmonic to gravitational gradient is expressed as a dyadic, which is then used to obtain an analytical expression in vector-dyadic form for the contribution to the moment of gravitational forces about the mass center of a small body such as a spacecraft. The expression developed for a harmonic's contribution to gravitational gradient can be applied in areas beyond the scope of the paper; for example, gravitational gradient plays an important role in the state propagation matrix and the state transition matrix that are used in spacecraft trajectory targeting and Kalman filtering. Additionally, it can be employed in numerical simulations of orbit determination based on measurements obtained with a gradiometer in low-Earth orbit. Contributions of spherical harmonics to gravitational moment may be of interest in connection with attitude control of a spacecraft in the vicinity of a body with an irregular shape, such as an asteroid. Normalized spherical harmonic coefficients up to degree and order 10 are obtained for the asteroid 216 Kleopatra and used in numerical evaluations of contributions to gravitational moment.

Roithmayr, Carlos M.↗
NASA NTRS2020

Terrain Relative Navigation for Guided Descent on Titan

Titan’s dense atmosphere, low gravity, and high winds at high altitudes create descent times of >90 minutes with standard entry/descent/landing (EDL) architectures and result in large unguided landing ellipses, with 99% values of 110x110 km and 149x72 km in recent Titan lander proposals. Enabling precision landing on Titan could increase science return for the types of missions proposed to date and make additional types of landing sites accessible, opening up new possibilities for science investigations. Precision landing on Titan has unique challenges, because the hazy atmosphere makes it difficult to see the surface and because it requires guided descent with divert ranges that are one to two orders of magnitude larger than needed for other target bodies, i.e. up to on the order of 100 km. It is conceivable that such a divert capability could be provided economically by a parafoil or other steerable aerodynamic decelerator deployed several 10s of km above the surface. The long descent times lead to large inertial navigation errors, hence a need for terrain relative navigation (TRN). This would require a TRN capability that can operate at such altitudes, despite challenges of seeing the surface sufficiently clearly and of depending on map products that are two orders of magnitude lower in spatial resolution than those for Mars and airless bodies. We then develop algorithms for map matching and feature tracking with descent images and test these with synthetic images created from Cassini/Huygens data sets and our radiative transfer model. We also introduce new possibilities for TRN based on the potential to discriminate some specific types of terrain onboard in descent imagery, such as lake vs adjacent ground and dune vs interdune. We use sensor measurement noise models in simulations of state estimation with an extended Kalman filter that includes coordinates of a set of tracked features in the state vector. Case studies were done for two notional landing sites, one in a site with only dry ground and one in a Titan lake district. In both cases, the filter error model shows 3 position error at touchdown on the order of 2 km. More work is needed to validate these results with higher fidelity camera models and larger data sets, but this is very promising.

Matthies, Larry↗
NASA NTRS1995

The Duffin-Kemmer-Petiau oscillator

In view of current interest in relativistic spin-one systems and the recent work on the Dirac Oscillator, we introduce the Duffin-Kemmer-Petiau (DKP) equation obtained by using an external potential linear in r. Since, in the non-relativistic limit, the spin 1 representation leads to a harmonic oscillator with a spin-orbit coupling of the Thomas form, we call the equation the DKP oscillator. This oscillator is a relativistic generalization of the quantum harmonic oscillator for scalar and vector bosons. We show that it conserves total angular momentum and that it is exactly solvable. We calculate and discuss the eigenspectrum of the DKP oscillator in the spin 1 representation.

Nedjadi, Youcef↗
NASA NTRS2001

A Closed-Loop Optimal Neural-Network Controller to Optimize Rotorcraft Aeromechanical Behaviour: Theory and Methodology - Volume 1

Given the predicted growth in air transportation, the potential exists for significant market niches for rotary wing subsonic vehicles. Technological advances which optimise rotorcraft aeromechanical behaviour can contribute significantly to both their commercial and military development, acceptance, and sales. Examples of the optimisation of rotorcraft aeromechanical behaviour which are of interest include the minimisation of vibration and/or loads. The reduction of rotorcraft vibration and loads is an important means to extend the useful life of the vehicle and to improve its ride quality. Although vibration reduction can be accomplished by using passive dampers and/or tuned masses, active closed-loop control has the potential to reduce vibration and loads throughout a.wider flight regime whilst requiring less additional weight to the aircraft man that obtained by using passive methads. It is ernphasised that the analysis described herein is applicable to all those rotorcraft aeromechanical behaviour optimisation problems for which the relationship between the harmonic control vector and the measurement vector can be adequately described by a neural-network model.

Leyland, Jane Anne↗
NASA NTRS2005

Pushing Human Frontiers

With human colonization of Mars, I think you will see a higher standard of civilization, just as America set a higher standard of civilization which then promulgated back into Europe. I think that if you want to maximize human potential, you need a higher standard of civilization, and that becomes an example that benefits everyone. Without an open frontier, closed world ideologies, such as the Malthus Theory, tend to come to the forefront. It is that there are limited resources; therefore, we are all in deadly competition with each other for the limited pot. The result is tyrannical and potentially genocidal regimes, and we've already seen this in the twentieth century. There s no truth in the Malthus Theory, because human beings are the creators of their resources. With every mouth comes a pair of hands and a brain. But if it seems to be true, you have a vector in this direction, and it is extremely unfortunate. It is only in a universe of infinite resources that all humans can be brothers and sisters. The fundamental question which affects humanity s sense of itself is whether the world is changeable or fixed. Are we the makers of our world or just its inhabitants? Some people have a view that they re living at the end of history within a world that s already defined, and there is no fundamental purpose to human life because there is nothing humans can do that matters. On the other hand, if humans understand their own role as the creators of their world, that s a much more healthy point of view. It raises the dignity of humans. Indeed, if we do establish a new branch of human civilization on Mars that grows in time and potency to the point where it cannot really settle Mars, but transforms Mars, and brings life to Mars, we will prove to everyone and for all time the precious and positive nature of the human species and every member of it.

Zubrin, Robert↗
NASA NTRS1975

A Survey of the Utility of Satellite Magnetometer Data for Application to Solid-earth Geophysical and Geological Studies

A survey of potential users of low altitude satellite magnetic measurements for solid-earth and geological studies was conducted. The principal objectives of this survey were to: document the utility and application of the data and resultant products obtained from such a satellite mission, and establish a users committee for the proposed low altitude vector magnetometer satellite.

Source record↗
NASA NTRS2006

Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

One of the responsibilities of the NASA Glenn Principal Investigator Microgravity Services is to support NASA sponsored investigators in the area of reduced-gravity acceleration data analysis, interpretation and the monitoring of the reduced-gravity environment on-board various carriers. With the International Space Station currently operational, a significant amount of acceleration data is being down-linked and processed on ground for both the space station onboard environment characterization (and verification) and scientific experiments. Therefore, to help principal investigator teams monitor the acceleration level on-board the International Space Station to avoid undesirable impact on their experiment, when possible, the NASA Glenn Principal Investigator Microgravity Services developed an artificial intelligence monitoring system, which detects in near real time any change in the environment susceptible to affect onboard experiments. The main objective of the monitoring system is to help research teams identify the vibratory disturbances that are active at any instant of time onboard the International Space Station that might impact the environment in which their experiment is being conducted. The monitoring system allows any space research scientist, at any location and at any time, to see the current acceleration level on-board the Space Station via the World Wide Web. From the NASA Glenn s Exploration Systems Division web site, research scientists can see in near real time the active disturbances, such as pumps, fans, compressor, crew exercise, re-boost, extra-vehicular activity, etc., and decide whether or not to continue operating or stopping (or making note of such activity for later correlation with science results) their experiments based on the g-level associated with that specific event. A dynamic graphical display accessible via the World Wide Web shows the status of all the vibratory disturbance activities with their degree of confidence as well as their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗
NASA NTRSDate not supplied

Space-borne Doppler Weather Radar Modeling for Radar Design Evaluation

A model has been developed to predict the reflectivity and Doppler performance of a spaceborne weather radar for atmospheric aerosol and cloud monitoring. The goal is to predict radar sensitivity, resolution, uncertainties and other key performance metrics vs. radar design parameters and hardware nonidealities. Analytical formulas are readily available to predict key performance metrics of a space-borne radar system as a function of design parameters such as antenna size, spacecraft velocity, transmit power, and receive noise figure. Effects of some system nonidealities such as antenna pointing errors, power amplifier nonlinearity and phase noise can be estimated using idealized methods. These analytical formulas use idealized forms of the antenna radiation pattern and weather statistics to predict system performance. However, it is desirable to have a more physical model based on discretized weather volumes in which the particle size distribution, Doppler distribution, and other parameters can be varied to study how the radar hardware design parameters and nonidealities affect the measurement of the weather reflectivity and Doppler characteristics. This would allow the radar designers to have more insight into what is being measured and the hardware parameters and errors that need to be carefully controlled to achieve best radar performance, as well as potential methods to calibrate the system or correct errors. This presentation will demonstrate some proof-of-concept Ka-band simulations where the discretized model agrees with the analytical formulas for a simple case where the elements in the discretized weather volume are defined by a constant reflectivity and simple velocity vectors. In particular, the system sensitivity and Doppler uncertainty are evaluated by analytical formulas as well as the discretized model. Future work will expand on this to include more complex weather scenarios and the addition of system nonidealities.

Sara Tucker↗
NASA NTRSDate not supplied

Algorithmic Classification of Raman Spectra Biosignatures: Improving Life Detection Confidence

“Agnostic” biosignatures – indicators of life (or the absence of life), independent of a particular biochemistry – are increasingly considered a high standard for life detection. The Ladder of Life Detection (2018) called for investigating how combinations of independent and different potential biosignatures affect confidence. To address this gap, statistical classification of elemental abundances, isotopic fractionation, and reflectance spectroscopy (VNIR) has been implemented. Raman spectroscopy, highly desirable due to its wide availability, has the potential to improve this predictive power. This work implemented biosignature classification algorithms on Raman data alone, in preparation for combination with the other data types. Raman spectroscopy data was collected from published databases and papers as part of a manually curated dataset of “indicative” and “non-indicative of life” samples. These currently include 61 non-indicative samples (meteorites, magnetite); 3 indicative living samples (bacteria); 20 indicative non-living samples (chalk, bone); and 12 indicative mixed (with non-indicative material) samples (soil, microbial mats). Laboratory work is ongoing to characterize additional samples, particularly a greater breadth of mixed systems. Spectra were interpolated, filtered with the Savitzsky-Golay filter, and de-noised. For a preliminary examination, agnostic features were manually extracted including mean intensity, number of peaks, and mean peak width. Different peak prominences and filtering polynomials were used to refine features. Classification algorithms were implemented: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), random forest (RF), Gaussian naïve bayes (GNB). Lastly, Monte Carlo simulations on 1,000 50%-train-test-splits were used to validate classification performance and feature significance. The preliminary feature set achieved its highest AUC of 0.52 with LR, with no strongly discriminatory features. Work to improve feature extraction, such as through deep learning with back propagation, is planned. In future work, the Raman data will be combined with the other data types, and potentially new data types such as enantiomeric excess. This project was partially supported through the NASA Ames Project EXcellence (APEX) incubator program.

Astrobiology↗
NASA NTRSDate not supplied

Statistical Classification of Biosignature Information using Multiple Instrument Observations

The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.

Statistical↗
NASA NTRS1975

Electron temperatures in the wake of an ionospheric satellite

We present measurements of electron temperature (Te) made by a retarding potential analyzer and a Langmuir probe (both flush-mounted on the spin-stabilized satellite Explorer 31) to investigate the variation of Te around the satellite. Most of the time there is a Te variation, which repeats for given ionospheric conditions. The variation is strongly controlled by the angle between the velocity vector and the probe normal, Te usually being enhanced in the near wake of the satellite. Magnetic field control of Te, if it is present, is hidden by the stronger velocity vector control. Our results indicate that the magnitude of the Te enhancement in the wake does not depend on the average ion mass (M), although the electron density depletion in the wake is strongly correlated with M.

Troy, B. E., Jr.↗