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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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NASA NTRS1985

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Tomberlin, T. J.↗
NASA NTRS2004

Numerical Propulsion System Simulation Architecture

The Numerical Propulsion System Simulation (NPSS) is a framework for performing analysis of complex systems. Because the NPSS was developed using the object-oriented paradigm, the resulting architecture is an extensible and flexible framework that is currently being used by a diverse set of participants in government, academia, and the aerospace industry. NPSS is being used by over 15 different institutions to support rockets, hypersonics, power and propulsion, fuel cells, ground based power, and aerospace. Full system-level simulations as well as subsystems may be modeled using NPSS. The NPSS architecture enables the coupling of analyses at various levels of detail, which is called numerical zooming. The middleware used to enable zooming and distributed simulations is the Common Object Request Broker Architecture (CORBA). The NPSS Developer's Kit offers tools for the developer to generate CORBA-based components and wrap codes. The Developer's Kit enables distributed multi-fidelity and multi-discipline simulations, preserves proprietary and legacy codes, and facilitates addition of customized codes. The platforms supported are PC, Linux, HP, Sun, and SGI.

Naiman, Cynthia G.↗
NASA NTRS2004

Grist : grid-based data mining for astronomy

The Grist project is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed grid services controlled by a workflow system, compliant with standards emerging from the grid computing, web services, and virtual observatory communities. This new technology is being used to find high redshift quasars, study peculiar variable objects, search for transients in real time, and fit SDSS QSO spectra to measure black hole masses. Grist services are also a component of the 'hyperatlas' project to serve high-resolution multi-wavelength imagery over the Internet. In support of these science and outreach objectives, the Grist framework will provide the enabling fabric to tie together distributed grid services in the areas of data access, federation, mining, subsetting, source extraction, image mosaicking, statistics, and visualization.

grid computing↗
NASA NTRS2007

SPENVIS Implementation of End-of-Life Solar Cell Calculations Using the Displacement Damage Dose Methodology

This paper presents a method for using the SPENVIS on-line computational suite to implement the displacement damage dose (D(sub d)) methodology for calculating end-of-life (EOL) solar cell performance for a specific space mission. This paper builds on our previous work that has validated the D(sub d) methodology against both measured space data [1,2] and calculations performed using the equivalent fluence methodology developed by NASA JPL [3]. For several years, the space solar community has considered general implementation of the D(sub d) method, but no computer program exists to enable this implementation. In a collaborative effort, NRL, NASA and OAI have produced the Solar Array Verification and Analysis Tool (SAVANT) under NASA funding, but this program has not progressed beyond the beta-stage [4]. The SPENVIS suite with the Multi Layered Shielding Simulation Software (MULASSIS) contains all of the necessary components to implement the Dd methodology in a format complementary to that of SAVANT [5]. NRL is currently working with ESA and BIRA to include the Dd method of solar cell EOL calculations as an integral part of SPENVIS. This paper describes how this can be accomplished.

Walters, Robert↗
NASA NTRS2003

Switching and Rectification in Carbon-Nanotube Junctions

Multi-terminal carbon-nanotube junctions are under investigation as candidate components of nanoscale electronic devices and circuits. Three-terminal "Y" junctions of carbon nanotubes (see Figure 1) have proven to be especially interesting because (1) it is now possible to synthesize them in high yield in a controlled manner and (2) results of preliminary experimental and theoretical studies suggest that such junctions could exhibit switching and rectification properties. Following the preliminary studies, current-versus-voltage characteristics of a number of different "Y" junctions of single-wall carbon nanotubes connected to metal wires were computed. Both semiconducting and metallic nanotubes of various chiralities were considered. Most of the junctions considered were symmetric. These computations involved modeling of the quantum electrical conductivity of the carbon nanotubes and junctions, taking account of such complicating factors as the topological defects (pentagons, heptagons, and octagons) present in the hexagonal molecular structures at the junctions, and the effects of the nanotube/wire interfaces. A major component of the computational approach was the use of an efficient Green s function embedding scheme. The results of these computations showed that symmetric junctions could be expected to support both rectification and switching. The results also showed that rectification and switching properties of a junction could be expected to depend strongly on its symmetry and, to a lesser degree, on the chirality of the nanotubes. In particular, it was found that a zigzag nanotube branching at a symmetric "Y" junction could exhibit either perfect rectification or partial rectification (asymmetric current-versus-voltage characteristic, as in the example of Figure 2). It was also found that an asymmetric "Y" junction would not exhibit rectification.

Srivastava, Deepak↗
NASA NTRS2014

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

Trajectory optimization methods using monotonic basin hopping (MBH) have become well developed during the past decade [1, 2, 3, 4, 5, 6]. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing random variable (RV)s from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by J. Englander [3, 6]) significantly improves monotonic basin hopping (MBH) performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness. Efficiency is finding better solutions in less time. Robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive random walks (RWs) originally developed in the field of statistical physics.

autonomous↗
NASA NTRS2014

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

Trajectory optimization methods using MBH have become well developed during the past decade. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing RVs from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by Englander significantly improves MBH performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness, where efficiency is finding better solutions in less time, and robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive RWs originally developed in the field of statistical physics.

mission design↗
NASA NTRS2013

A Hybrid FPGA/Tilera Compute Element for Autonomous Hazard Detection and Navigation

To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

Multicore↗
NASA NTRS2015

Framework and Method for Controlling a Robotic System Using a Distributed Computer Network

A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.

Sanders, Adam M.↗
NASA NTRS2016

Development and Implementation of a Generic Analysis Template for Structural-Thermal-Optical-Performance Modeling

Performance-related effects of system level temperature changes can be a key consideration in the design of many types of optical instruments. This is especially true for space-based imagers, which may require complex thermal control systems to maintain alignment of the optical components. Structural-Thermal-Optical-Performance (STOP) analysis is a multi-disciplinary process that can be used to assess the performance of these optical systems when subjected to the expected design environment. This type of analysis can be very time consuming, which makes it difficult to use as a trade study tool early in the project life cycle. In many cases, only one or two iterations can be performed over the course of a project. This limits the design space to best practices since it may be too difficult, or take too long, to test new concepts analytically. In order to overcome this challenge, automation, and a standard procedure for performing these studies is essential. A methodology was developed within the framework of the Comet software tool that captures the basic inputs, outputs, and processes used in most STOP analyses. This resulted in a generic, reusable analysis template that can be used for design trades for a variety of optical systems. The template captures much of the upfront setup such as meshing, boundary conditions, data transfer, naming conventions, and post-processing, and therefore saves time for each subsequent project. A description of the methodology and the analysis template is presented, and results are described for a simple telescope optical system.

Scola, Salvatore↗
NASA NTRS2018

Land Surface Reflectances from Geostationary Sensors

GEONEX is a processing pipeline that produces a suite of satellite land surface products using data streams from the latest geostationary (GEO) sensors including the GOES016/ABI and the Himawari-8/AHI. The suite, created collaboratively by scientists from NASA and NOAA, includes top-of-atmosphere (TOA) reflectances, land surface reflectances (LSRs), vegetation indices, LAI/fPAR, and other downstream products. As a key component of the GEONEX product processing, we have adapted the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce LSRs from the TOA data. Because the algorithm depends on building "stacks" of images, we first run internal geo-registration checks to ensure geo-spatial accuracy and consistency of the input (L1B) data before transferring them from the geostationary projection into a tile system in geographic grids. Scan-time is inferred from metadata and applied to calculate the sun-sensor angles for each grid cell. The MAIAC algorithm is run to detect clouds/shadows, estimate aerosol optical thickness (AOT), perform atmospheric corrections, and generate LSRs. We have processed 18-months (from 2016/04 onward) of AHI data over East Asia and Oceania at a 10-minute time step and 10-months (from 2018/01 onward) of ABI data over North and South Americas at a 15-minute time step. As a verification measure, we compare the GEONEX (AHI/ABI) surface reflectances with the standard MODIS products (MOD09GA) and the MODIS MAIAC products over pixels that have similar sun-view geometries. The results indicate general linear relationships between GEONEX and corresponding MODIS LSRs. In particular, the RMSEs between GEONEX and MOD09 data are comparable to those between MOD09 and MODIS MAIAC products, suggesting that the uncertainties of GEONEX LSRs fall into an acceptable range. However, direct comparisons of LSRs over pixels with different sun-view angles are not as straightforward and require more modeling efforts to correct the directional effects. Evaluation of such angular influences on the downstream products (e.g., vegetation indices) is also under investigation.

Geostationary satellite; Remote Sensing; Atmospher↗
NASA NTRS2019

In Space Assembled Telescope (ISAT) Study Preliminary Findings

“When is it advantageous to assemble telescopes in space rather than deploying them from launch vehicle fairings”? This question forms the crux of the objectives of a NASA study we have been conducting in collaboration with colleagues from different NASA centers, industry and academia. In this study, we have engaged a broad cross section of experts from the various fields of optics engineering, that is, telescope design and instrument design, structure and thermal engineering, robotics, launch system engineering, orbital mechanics, integration and testing, astrophysics, and NASA programmatics among others. Initial efforts began with a quick review of the current state of art of the component technologies that contribute towards an in-space assembled telescope. Then, leveraging the collective expertise of the diverse group of experts, we formulated a reference telescope design and attempted to develop a baseline approach to modularize the telescope into components amenable for robotic assembly. The group identified different trades associated with modularization and also developed a set of criteria to discern between the different options as revealed by the trades. Based on the modularization of the telescope, we will assess the impact of various launch vehicles, orbits for assembly and operation, robotic systems and operational approaches, and other related variables. From this, a concept to assemble the reference telescope in space from modular components will be developed. Based on this concept, and definition of the modules, we will develop a mission lifecycle plan for an assembled telescope over different phases of preliminary design, detailed design, assembly-test-and-integration, and in space operations. The mission lifecycle plan will be used to evaluate cost and risk implications of in-space assembly toward answering our fundamental question of the advantages, if any, of assembling a telescope in space as compared to self-deployment. In this paper, we summarize the objectives of the study, a review of the status of the underlying component technologies, a description of the methodology, including three different multi-day technical interchange meetings (TIMs), summary of findings from the TIMs and other related activities. In addition, a detailed description of the various factors that impact in-space assembly, their interplay and criteria for discerning among them, a preliminary description of the life cycle plan, including the test and integration plan, and initial observations on cost and risk implications will be included in the paper.

Mukherjee, Rudranarayan↗
NASA NTRSDate not supplied

Analyzing Natural Language Context in Human-Machine Teaming using Supervised Machine Learning

Building a foundation for trustworthiness and trust verification in multi-asset teaming is the research challenge of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Design Reference Mission (DRM) for ATTRACTOR is a search and rescue mission objective governed by a multi-member team consisting of human and machine operators. A crucial component to the effort is the communication between humans and autonomous agents throughout both planning and execution stages of the mission. Intuitive communication methods and modalities are posited as critical enablers for certifying trust and trustworthiness. This paper reports on the data collection and analysis conducted in support of the Human Informed Natural-language GANs Evaluation (HINGE)project to attain explainable and trusted communication between human-machine assets. Two identically curated image description datasets were acquired for HINGE, both consisting of two unique input modalities (typed vs. verbal) and retrieved in two distinct contexts (general vs. specific). The gathered datasets were assessed and compared using Parts-of-Speech (POS)features, sentence similarity metrics, and linguistic analysis. Then, the datasets were modeled and tested separately and in combination with one another using machine learning algorithms. The comparison and testing results reveal a superior dataset, by which a preferred context and input is understood, for generating image representations of missing persons using a Generative Adversarial Network (GAN).

Bryan A Barrows↗
NASA NTRS2013

A hybrid FPGA/Tilera compute element for autonomous hazard detection and navigation

To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

Trawny, Nikolas↗
NASA NTRSDate not supplied

The Stratospheric Aerosol and Gas Experiment IV

Atmospheric composition continues to be a key Earth science focus for international space agencies and research organizations. The target constituent varies depending upon the topic area of interest such as monitoring the ozone layer and the efficacy of the Montreal Protocol, assessing the influence of volcanic eruptions and large wildfires on the atmosphere, improving our knowledge of transport processes, or evaluating the impacts of greenhouse gases on climate. Additionally, there is a growing need for measurement continuity of many trace gases both from an inability to properly assess long-term trends without it as well as the reliance of reanalyses and chemistry climate models on observational input. To this end, proper continuity requires continuous and overlapping multi-instrument data records of which spaceborne measurements are a critical component. However, most current satellite systems are well beyond their expected lifetimes, and so we look toward the future to develop the Stratospheric Aerosol and Gas Experiment (SAGE) IV as a future mission concept. Enabled by the NASA Earth Science Technology Office’s (ESTO) Instrument Incubator Program, the SAGE IV Pathfinder project has developed and validated a prototype demonstration that paves the way for a future SAGE IV spaceflight mission. Utilizing solar occultation imaging, SAGE IV will be capable of measuring key species in the stratosphere and upper troposphere with the same quality as previous SAGE instruments but with greatly improved pointing knowledge and extensibility to new science targets. Furthermore, current technological advancements allow SAGE IV to fit within a CubeSat framework and make use of commercial hardware, significantly reducing the size and cost when compared with traditional missions and enabling sustainability of future measurements.

Robert Damadeo↗
NASA NTRSDate not supplied

Reanalysis Activities at the NASA Global Modeling and Assimilation Office

This talk presents an overview of recent reanalysis activities at the NASA Global Modeling and Assimilation Office (GMAO) as part of a multi-faceted strategy towards an Integrated Earth System retrospective analysis, coupling components of the atmosphere, ocean, chemistry, land, and ice. While elements of the atmosphere-ocean coupled Goddard Earth Observing System (GEOS) model and data assimilation are being actively developed, a suite of reanalysis products is designed to provide further understanding of key aspects of Earth system coupling in a reanalysis context: The baseline atmospheric reanalysis, the GEOS Retrospective analysis for the early 21st Century (GEOS-R21C), features recent advances in the GEOS model and data assimilation, and targets the NASA’s Earth Observing System EOS and post-EOS satellite observations; GEOS-IT, a user-tailored low-resolution atmospheric reanalysis, serves as a second baseline to the NASA Instrument Teams for validation and calibration and drives a one-way coupled ocean reanalysis, GEOSIT-Ocean; PolarMERRA, a high-resolution downscaled product for the polar regions, focuses on improving the representation of polar atmospheric processes with an assessment of current cryospheric biases, and targeted improvements to surface sea ice and glacier conditions; Finally, R21C-Chem, an off-line atmospheric chemistry and composition reanalysis, includes both tropospheric and stratospheric trace gases. The diversity of these reanalysis activities presents unique opportunities for collaborations cross-teams/institutions, with new commercial data partners, and with end-user groups. This talk will discuss these opportunities and explore leveraging the lessons learned along the way on key drivers in Earth system interactions as we converge towards the next generation of the Modern-Era Retrospective analysis for Research and Applications (MERRA) suite.

Amal El Akkraoui↗
NASA NTRSDate not supplied

The Stratospheric Aerosol and Gas Experiment (SAGE) IV

Atmospheric composition continues to be a key Earth science focus for international space agencies and research organizations. The target constituent varies depending upon the topic area of interest such as monitoring the ozone layer and the efficacy of the Montreal Protocol, assessing the influence of volcanic eruptions and large wildfires on the atmosphere, improving our knowledge of transport processes, or evaluating the impacts of greenhouse gases on climate. Additionally, there is a growing need for measurement continuity of many trace gases both from an inability to properly assess long-term trends without it as well as the reliance of reanalyses and chemistry climate models on observational input. To this end, proper continuity requires continuous and overlapping multi-instrument data records of which spaceborne measurements are a critical component. However, most current satellite systems are well beyond their expected lifetimes, and so we look toward the future to develop the Stratospheric Aerosol and Gas Experiment (SAGE) IV as a future mission concept. Enabled by the NASA Earth Science Technology Office’s (ESTO) Instrument Incubator Program, the SAGE IV Pathfinder project developed and validated a prototype demonstration that paves the way for a future SAGE IV spaceflight mission. Utilizing solar occultation imaging, SAGE IV will be capable of measuring key species in the stratosphere and upper troposphere with the same quality as previous SAGE instruments but with greatly improved pointing knowledge and extensibility to new science targets. The precision and stability of a well-designed occultation instrument can act as a calibration reference standard for other spaceborne instruments, ensuring proper continuity of the desired science targets. Furthermore, current technological advancements allow SAGE IV to fit within a CubeSat framework and make use of commercial hardware, significantly reducing the size and cost when compared with traditional missions and enabling sustainability of future measurements.

Robert Damadeo↗
NASA NTRSDate not supplied

Data Simulation Using VLIDORT and PCRTM and its Use for Radiometric Calibration of Hyperspectral UV-NIR-SWIR Sensors

Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer discrete ordinate scattering codes, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate the radiation fields for hyperspectral UV-NIR-SWIR sensors from 250nm to 2500nm with a very high speed. Since the accurate gas absorptions, molecules and aerosol/cloud particle scatterings, and the surface reflectance have been considered in these simulations, these model data can be used for satellite or airborne sensor design, characterization, or end-to-end system level uncertainty assessment. Comparison of the modelled data with measured results has been a general practice for operational satellite sensor calibrations, such as the Ozone Mapping and Profiler Suite (OMPS) onboard on SNPP and NOAA-20. This presentation will give more details of this simulation system and models. Some examples of the generation of simulations data for CLARREO PathFinder (CPF) and the Surface Biology and Geology (SBG), as well as some examples to use these data for CPF and OMPS radiometric calibration will be presented.

Xiaozhen Xiong↗