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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 1,621 records · Page 90
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NASA NTRS2013

Integrated Design and Engineering Analysis (IDEA) Environment - Propulsion Related Module Development and Vehicle Integration

This report documents the work performed during the period from May 2011 - October 2012 on the Integrated Design and Engineering Analysis (IDEA) environment. IDEA is a collaborative environment based on an object-oriented, multidisciplinary, distributed framework using the Adaptive Modeling Language (AML). This report will focus on describing the work done in the areas of: (1) Integrating propulsion data (turbines, rockets, and scramjets) in the system, and using the data to perform trajectory analysis; (2) Developing a parametric packaging strategy for a hypersonic air breathing vehicles allowing for tank resizing when multiple fuels and/or oxidizer are part of the configuration; and (3) Vehicle scaling and closure strategies.

Kamhawi, Hilmi N.↗
NASA NTRS2014

Exit Presentation Fall 2013

Our current International Space Station Probabilistic Risk Assessment (ISS PRA) model assumes all collisions between a visiting vehicle (VV) and the ISS result in worst case loss of the ISS crew and the vehicle (LOCV). Drawing results from the Mir-Progress collision, we know this assumption is inaccurate because that collision did not lead to LOCV. Therefore the PRA team is conducting a study to determine the likelihood of LOCV when a collision occurs between a VV and the ISS. Kinetic energy is calculated and converted to pounds of TNT for the moving VVs when they collide with the ISS. Different scenarios are evaluated to obtain collision related data such as translational kinetic energy and rotational kinetic energy. These calculated data are integrated into the results from the expert elicitation performed on the Mir- Progress collision. As a result of this study, the PRA model will now calculate the probability of a VV collision with ISS, the probability that collision will result in Loss of Soyuz Crew (LOC) or Loss of ISS Crew and Vehicle (LOCV).

Yang, Qi Rong↗
NASA NTRS2014

Global Top-Down Smoke-Aerosol Emissions Estimation Using Satellite Fire Radiative Power Measurements

Fire emissions estimates have long been based on bottom-up approaches that are not only complex, but also fraught with compounding uncertainties. We present the development of a global gridded (1 deg ×1 deg) emission coefficients (Ce) product for smoke total particulate matter (TPM) based on a top-down approach using coincident measurements of fire radiative power (FRP) and aerosol optical thickness (AOT) from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra and Aqua satellites. This new Fire Energetics and Emissions Research version 1.0 (FEER.v1) Ce product has now been released to the community and can be obtained from http://feer.gsfc. nasa.gov/, along with the corresponding 1-to-1 mapping of their quality assurance (QA) flags that will enable the Ce values to be filtered by quality for use in various applications. The regional averages of Ce values for different ecosystem types were found to be in the ranges of 16-21/gMJ−1 for savanna and grasslands, 15-32/gMJ−1 for tropical forest, 9-12/gMJ−1 for North American boreal forest, and 18- 26/MJ−1 for Russian boreal forest, croplands and natural vegetation. The FEER.v1 Ce product was multiplied by time-integrated FRP data to calculate regional smoke TPM emissions, which were compared with equivalent emissions products from three existing inventories. FEER.v1 showed higher and more reasonable smoke TPM estimates than two other emissions inventories that are based on bottom-up approaches and already reported in the literature to be too low, but portrayed an overall reasonable agreement with another top-down approach. This suggests that top-down approaches may hold better promise and need to be further developed to accelerate the reduction of uncertainty associated with fire emissions estimation in air-quality and climate research and applications. Results of the analysis of FEER.v1 data for 2004-2011 show that 65-85 Tg yr−1 of TPM is emitted globally from open biomass burning, with a generally decreasing trend over this short time period. The FEER.v1 Ce product is the first global gridded product in the family of "emission factors", that is based essentially on satellite measurements, and requires only direct satellite FRP measurements of an actively burning fire anywhere to evaluate its emission rate in near-real time, which is essential for operational activities, such as the monitoring and forecasting of smoke emission impacts on air quality.

biomass burning↗
NASA NTRS2013

Quantifying the Impact of BOReal Forest Fires on Tropospheric Oxidants Over the Atlantic Using Aircraft and Satellites (BORTAS) Experiment: Design, Execution, and Science Overview

We describe the design and execution of the BORTAS (Quantifying the impact of BOReal forest fires on Tropospheric oxidants using Aircraft and Satellites) experiment, which has the overarching objective of understanding the chemical aging of airmasses that contain the emission products from seasonal boreal wildfires and how these airmasses subsequently impact downwind atmospheric composition. The central focus of the experiment was a two-week deployment of the UK BAe-146-301 Atmospheric Research Aircraft (ARA) over eastern Canada. The planned July 2010 deployment of the ARA was postponed by 12 months because of activities related to the dispersal of material emitted by the Eyjafjallaj¨okull volcano. However, most other planned model and measurement activities, including ground-based measurements at the Dalhousie University Ground Station (DGS), enhanced ozonesonde launches, and measurements at the Pico Atmospheric Observatory in the Azores, went ahead and constituted phase A of the experiment. Phase B of BORTAS in July 2011 included the same measurements, but included the ARA, special satellite observations and a more comprehensive measurement suite at the DGS. Integrating these data helped us to describe pyrogenic plumes from wildfires on a wide spectrum of temporal and spatial scales. We interpret these data using a range of chemistry models, from a near-explicit gas-phase chemical mechanism to regional and global models of atmospheric transport and lumped chemistry. We also present an overview of some of the new science that has originated from this project.

BORTAS↗
NASA NTRS2016

Big Data in the Earth Observing System Data and Information System

Approaches that are being pursued for the Earth Observing System Data and Information System (EOSDIS) data system to address the challenges of Big Data were presented to the NASA Big Data Task Force. Cloud prototypes are underway to tackle the volume challenge of Big Data. However, advances in computer hardware or cloud won't help (much) with variety. Rather, interoperability standards, conventions, and community engagement are the key to addressing variety.

data systems↗
NASA NTRS2017

Characterization of Orbital Debris via Hyper-Velocity Laboratory-Based Tests

Existing DoD and NASA satellite breakup models are based on a key laboratory test, Satellite Orbital debris Characterization Impact Test (SOCIT), which has supported many applications and matched on-orbit events involving older satellite designs reasonably well over the years. In order to update and improve these models, the NASA Orbital Debris Program Office, in collaboration with the Air Force Space and Missile Systems Center, The Aerospace Corporation, and the University of Florida, replicated a hypervelocity impact using a mock-up satellite, DebriSat, in controlled laboratory conditions. DebriSat is representative of present-day LEO satellites, built with modern spacecraft materials and construction techniques. Fragments down to 2 mm in size will be characterized by their physical and derived properties. A subset of fragments will be further analyzed in laboratory radar and optical facilities to update the existing radar-based NASA Size Estimation Model (SEM) and develop a comparable optical-based SEM. A historical overview of the project, status of the characterization process, and plans for integrating the data into various models will be discussed herein.

Cowardin, Heather↗
NASA NTRS2017

Characterization of Orbital Debris via Hyper-Velocity Laboratory-Based Tests

Existing DOD and NASA satellite breakup models are based on a key laboratory test, Satellite Orbital debris Characterization Impact Test (SOCIT), which has supported many applications and matched on-orbit events involving older satellite designs reasonably well over the years. In order to update and improve these models, the NASA Orbital Debris Program Office, in collaboration with the Air Force Space and Missile Systems Center, The Aerospace Corporation, and the University of Florida, replicated a hypervelocity impact using a mock-up satellite, DebriSat, in controlled laboratory conditions. DebriSat is representative of present-day LEO satellites, built with modern spacecraft materials and construction techniques. Fragments down to 2 mm in size will be characterized by their physical and derived properties. A subset of fragments will be further analyzed in laboratory radar and optical facilities to update the existing radar-based NASA Size Estimation Model (SEM) and develop a comparable optical-based SEM. A historical overview of the project, status of the characterization process, and plans for integrating the data into various models will be discussed herein.

Cowardin, Heather↗
NASA NTRS2017

NASA Update for Unidata Stratcomm

The NASA representative to the Unidata Strategic Committee presented a semiannual update on NASAs work with and use of Unidata technologies. The talk updated Unidata on the program of cloud computing prototypes underway for the Earth Observing System Data and Information System (EOSDIS). Also discussed was a trade study on the use of the Open source Project for a Network Data Access Protocol (OPeNDAP) with Web Object Storage in the cloud.

data systems↗
NASA NTRS2017

NASA Technology Transfer System

NTTS is the IT infrastructure for the Agency's Technology Transfer (T2) program containing 60,000+ technology portfolio supporting all ten NASA field centers and HQ. It is the enterprise IT system for facilitating the Agency's technology transfer process, which includes reporting of new technologies (e.g., technology invention disclosures NF1679), protecting intellectual properties (e.g., patents), and commercializing technologies through various technology licenses, software releases, spinoffs, and success stories using custom built workflow, reporting, data consolidation, integration, and search engines.

enterprise information technology↗
NASA NTRS2018

GEOS-5 Seasonal Forecast System: ENSO Prediction Skill and Bias

The GEOS-5 AOGCM known as S2S-1.0 has been in service from June 2012 through January 2018 (Borovikov et al. 2017). The atmospheric component of S2S-1.0 is Fortuna-2.5, the same that was used for the Modern-Era Retrospective Analysis for Research and Applications (MERRA), but with adjusted parameterization of moist processes and turbulence. The ocean component is the Modular Ocean Model version 4 (MOM4). The sea ice component is the Community Ice CodE, version 4 (CICE). The land surface model is a catchment-based hydrological model coupled to the multi-layer snow model. The AGCM uses a Cartesian grid with a 1 deg × 1.25 deg horizontal resolution and 72 hybrid vertical levels with the upper most level at 0.01 hPa. OGCM nominal resolution of the tripolar grid is 1/2 deg, with a meridional equatorial refinement to 1/4 deg. In the coupled model initialization, selected atmospheric variables are constrained with MERRA. The Goddard Earth Observing System integrated Ocean Data Assimilation System (GEOS-iODAS) is used for both ocean state and sea ice initialization. SST, T and S profiles and sea ice concentration were assimilated.

GEOS-↗
NASA NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.

Vital signs↗
NASA NTRS2015

Open Source Mission Control for Chrome

New technology presents the possibility to evolve mission control. WARP (Web Applications for Resource Prospector) a new open source toolset for mission visualization, brings mission control to the Chrome Web Browser. WARP integrates multiple data sources into a coherent visualization toolset from which users may assemble their own software, thus giving mission controllers more flexibility. This frees us to operate based on mission needs, rather than constraints enforced by software application boundaries.

software engineering↗
NASA NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.

Astroskin↗
NASA NTRS2019

A New Laser Beam Pointing Method Using Laser Arrays

A new method is described for optical data transmissions from satellites using laser arrays for laser beam pointing. It combines a lens system and a vertical-cavity surface-emitting laser (VCSEL)/Photodetector Array, both mature technologies, in a novel way. This system is applied to satellites in low-Earth orbit, (LEO). It can replace current architectures which use dynamical systems, (i.e., moving parts) to point the laser, and which may use vibration isolation platforms. Results of computer simulations show diffraction limited beam propagation. Possible additional applications are to planetary distances (deep space optical communications, (DSOC)), to optical multiple access, (OMA), to communication between a constellation of close satellites, and to satellites that use modulating retro-reflectors. Keywords: laser beam pointing, free-space optical communication, low-Earth orbit (LEO) data communications, integrated VCSEL/ photodetector arrays, deep space optical communications (DSOC), optical multiple access (OMA), constellation of close satellites, modulating retro-reflectors.

Goorjian, P. M.↗
NASA NTRS2018

Introduction to NASA Goddard Workshop on Artificial Intelligence

Artificial Intelligence (AI) is a collection of advanced technologies that allows machines to think and act, both humanly and rationally, through sensing, comprehending, acting and learning. AI's foundations lie at the intersection of several traditional fields Philosophy, Mathematics, Economics, Neuroscience, Psychology and Computer Science. Although the inception of AI started in the 1950's, it has recently made a strong comeback in all aspects of society and all over the world; this is mainly due to the timely combination of increased data volumes, advanced and mature algorithms, and improvements in computing power and storage. Current AI applications include big data analytics, robotics, intelligent sensing, assisted decision making, and speech recognition just to name a few.This workshop will be investigating how AI technologies can be adapted or developed to address the following challenges: Discover events of interest and correlations in large amounts of science data; improve the outcomes of science modeling and data assimilation using improved data processing, integration, and analysis. Design advisors for mission planning and operations, including anomaly detection and spacecraft health monitoring. Develop tools for engineering support, including advanced manufacturing, orbit determination, new component design and system engineering. Customize intelligent user interfaces, including visual analytics and natural language processing.

Le Moigne, Jacqueline↗
NASA NTRS2018

NASA Observations and Modeling During ICE-POP

Recap: NASA-Specific Objectives for ICE-POP: Provide real-time observational and NWP data in support of ICE-POP, participate in significant international science effort; GPM (Global Precipitation Measurement) Ground Validation and NASA Weather Program -Direct/physical validation of active/passive satellite-based snowfall retrieval algorithms over coastline and mountains; melting layer interaction with terrain -Physics of snow, coupling to snow water equivalent rate and satellite remote sensor retrieval algorithm assumptions - -Size distributions, types/habit, water equivalent, profiles -NU-WRF (NASA-Unified Weather Research and Forecasting) Model plus Observational analyses: Movement toward “level IV products” leverage intensive and multi-faceted NWP (Numerical Weather Prediction) component -Model precipitation processes (liquid, mixed phase and frozen); Build model testing database for further active/passive remote sensing algorithm development (e.g., satellite data simulators) -"Integrated" validation of products in operational context.

Precipitation Science↗