Condition-based-maintenance of Electrical Motors for INSIGHT (Intelligent Stennis Gas House Technology) and NPAS (NASA Platform for Autonomous Systems)
No abstract available
Figeuroa, Fernando↗
Engineering topics
Underwood, Lauren
Publications and source records attributed to Underwood, Lauren.
NASA Platform for Autonomous Systems (NPAS)
Autonomous operations are critical for the success, safety and crew survival of NASA deep space missions beyond low Earth orbit, including Gateway. For the past 10 years, Stennis Space Center (SSC) has been developing, and has demonstrated an innovative software platform, along with expertise and processes for implementation of autonomous operations.
Integrated Power Avionics and Software↗
NASA Platform for Autonomous Systems (NPAS)
NASA Platform for Autonomous Systems (NPAS) is a disruptive software platform and processes being developed by SSC Autonomous Systems Laboratory (ASL). Autonomous operations are critical for the success, safety and crew survival of NASA deep space missions beyond low Earth orbit, including Lunar Orbital Platform-Gateway, and for the future of cost-effective ground mission operations. NPAS represents the embodiment of an innovative implementation for "thinking" autonomy in contrast to brute-force autonomy. It also uniquely addresses the requirements and integrates five primary functionalities for autonomous operations including: (1) Integrated System Health Management (ISHM), (2) autonomy, guided by health and system concepts of operations; (3) knowledge models of applications; (4) infrastructure to create, schedule, and execute mission plans; and (5) infrastructure to integrate distributed autonomous applications across networks.
Figueroa, Fernando↗
NASA Platform for Autonomous Systems (NPAS)
NASA Platform for Autonomous Systems (NPAS) is a disruptive software platform and processes being developed by the NASA Stennis Space Center (SSC) Autonomous Systems Laboratory (ASL). Autonomous operations are critical for the success, safety and crew survival of NASA deep space missions beyond low Earth orbit, including the Gateway, and for the future of cost-effective ground mission operations. NPAS represents the embodiment of an innovative paradigm for “thinking” autonomy in contrast to brute-force autonomy. NPAS uniquely addresses the requirements and integrates the primary functionalities for autonomous operations, in one platform that includes: (1) Integrated System Health Management (ISHM); (2) autonomy strategies, guided by system health and concepts of operations; (3) domain objects (system elements) and infrastructure to create complete application domain knowledge models (4) infrastructure to create, schedule, and execute mission plans; (5) infrastructure to develop user interfaces for comprehensive awareness; and (6) infrastructure to integrate distributed autonomous applications across networks. NPAS is a single platform that can be used to make any system operate with any desirable degree of autonomy, as well as provide comprehensive system awareness to operators and users.
Figueroa, Fernando↗
Oyster Fisheries App
This project is creating a cloud‐enabled, HTML 5 web application to help oyster fishermen and state agencies apply Earth science to improve the management of this important natural and economic resource. The Oyster Fisheries app gathers and analyzes environmental and water quality information, and alerts fishermen and resources managers about problems in oyster fishing waters. An intuitive interface based on Google Maps displays the geospatial information and provides familiar interactive controls to the users. Alerts can be tailored to notify users when conditions in specific leases or public fishing areas require attention. The app is hosted on the Amazon Web Services cloud. It is being developed and tested using some of the latest web development tools such as web components and Polymer.
Perez Guerrero, Geraldo A.↗
Interagency Collaborators Develop and Implement ForWarn, a National, Near Real Time Forest Monitoring Tool
ForWarn is a satellite-based forest monitoring tool that is being used to detect and monitor disturbances to forest conditions and forest health. It has been developed through the synergistic efforts, capabilities and contributions of four federal agencies, including the US Forest Service Eastern Forest and Western Wildland Environmental Threat Assessment Centers, NASA Stennis Space Center (SSC), Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL) and US Geological Survey Earth (USGS) Earth Research Observation System (EROS), as well as university partners, including the University of North Carolina Asheville's National Environmental Modeling and Analysis Center (NEMAC). This multi-organizational partnership is key in producing a unique, path finding near real-time forest monitoring system that is now used by many federal, state and local government end-users. Such a system could not have been produced so effectively by any of these groups on their own. The forests of the United States provide many societal values and benefits, ranging from ecological, economic, cultural, to recreational. Therefore, providing a reliable and dependable forest and other wildland monitoring system is important to ensure the continued health, productivity, sustainability and prudent use of our Nation's forests and forest resources. ForWarn does this by producing current health indicator maps of our nation's forests based on satellite data from NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) sensors. Such a capability can provide noteworthy value, cost savings and significant impact at state and local government levels because at those levels of government, once disturbances are evident and cause negative impacts, a response must be carried out. The observations that a monitoring system like ForWarn provide, can also contribute to a much broader-scale understanding of vegetation disturbances.
Underwood, Lauren↗
Studying the Use of Photocatalytic Coatings to Increase Building/Structure Sustainability and Cleanliness at NASA Stennis Space Center
TiO2 coated surfaces demonstrated both visually through photographic representation, and quantitatively, through reflectance measurements that they improved upon the current state of cleanliness upon the surfaces that they were applied to. TiO2 has the potential to both maintain and increase building s sustainability and the overall appearance of cleanliness TiO2 coated slides degraded soot under UV light compared to soot samples on plain uncoated slides under the same conditions Degradation of soot by photocatalysis was far more apparent than degradation of soot by UV light alone This demonstration provides the foundation for a laboratory model that could be used to simulate real world applications for photocatalytic materials Additional research is required to better understand the full potential of TiO2
Underwood, Lauren↗
Coastal Changes in Temperature and Salinity Observed during Hurricane Isaac Recorded and Downloaded by NASA DRIFTERs Moored in Heron Bay and at Half Moon Island, Louisiana
Major changes in salinity (approx.14 ppt.) and temperature (approx.40C) were continuously registered by two prototype NASA DRIFTERs, surface moored floaters, that NASA's Applied Science and Technology Project Office (ASTPO) has developed. The DRIFTER floating sensor module is equipped with an Arduino open-source electronics prototyping platform and programming language (http://www.arduino.cc), a GPS (Global Positioning System) module with antenna, a cell phone SIM (Subscriber Identity Module) card and a cellular antenna which is used to transmit data, and a probe to measure temperature and conductivity (from which salinity can be derived). The DRIFTER is powered by a solar cell panel and all the electronic components are mounted and sealed in [ waterproof encasement. Position and measurement data are transmitted via short message service (SMS) messaging to a Twitter site (DRIFTER 002@NASADRIFTER_002 and DRIFTER 004@NASADRIFTER_004), which provides a live feed. These data are the imported into a Google spreadsheet where conductivity is converted to salinity, and graphed in real-time. The spreadsheet data will be imported into a webpage maintained by ASTPO, where it will be displayed available for dO\\1lload.
Kalcic, Maria↗
Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing
Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.
Brown, Richard B.↗
Adding Remote Sensing Data Products to the Nutrient Management Decision Support Toolbox
Some of the primary issues that manifest from nutrient enrichment and eutrophication (Figure 1) may be observed from satellites. For example, remotely sensed estimates of chlorophyll a (chla), total suspended solids (TSS), and light attenuation (Kd) or water clarity, which are often associated with elevated nutrient inputs, are data products collected daily and globally for coastal systems from satellites such as NASA s MODIS (Figure 2). The objective of this project is to inform water quality decision making activities using remotely sensed water quality data. In particular, we seek to inform the development of numeric nutrient criteria. In this poster we demonstrate an approach for developing nutrient criteria based on remotely sensed chla.
Lehrter, John↗
Self-Cleaning Coatings and Materials for Decontaminating Field-Deployable Land and Water-Based Optical Systems
This technology exploits the organic decomposition capability and hydrophilic properties of the photocatalytic material titanium dioxide (TiO2), a nontoxic and non-hazardous substance, to address contamination and biofouling issues in field-deployed optical sensor systems. Specifically, this technology incorporates TiO2 coatings and materials applied to, or integrated as a part of, the optical surfaces of sensors and calibration sources, including lenses, windows, and mirrors that are used in remote, unattended, ground-based (land or maritime) optical sensor systems. Current methods used to address contamination or biofouling of these optical surfaces in deployed systems are costly, toxic, labor intensive, and non-preventative. By implementing this novel technology, many of these negative aspects can be reduced. The functionality of this innovative self-cleaning solution to address the problem of contamination or biofouling depends on the availability of a sufficient light source with the appropriate spectral properties, which can be attained naturally via sunlight or supplemented using artificial illumination such as UV LEDs (light emitting diodes). In land-based or above-water systems, the TiO2 optical surface is exposed to sunlight, which catalyzes the photocatalytic reaction, facilitating both the decomposition of inorganic and organic compounds, and the activation of superhydrophilic properties. Since underwater optical surfaces are submerged and have limited sunlight exposure, supplementary UV light sources would be required to activate the TiO2 on these optical surfaces. Nighttime operation of land-based or above-water systems would require this addition as well. For most superhydrophilic self-cleaning purposes, a rainwater wash will suffice; however, for some applications an attached rainwater collector/ dispenser or other fresh water dispensing system may be required to wash the optical surface and initiate the removal of contaminates. Deployment of this non-toxic,non-hazardous-technology will take advantage of environmental elements (i.e. rain and sunlight), increase the longevity of unattended optical systems, increase the amount of time between required maintenance, and improve the long-term accuracy of sensor measurements.
Ryan, Robert↗
NASA Satellite Data for Seagrass Health Modeling and Monitoring
Time series derived information for coastal waters will be used to provide input data for the Fong and Harwell model. The current MODIS land mask limits where the model can be applied; this project will: a) Apply MODIS data with resolution higher than the standard products (250-m vs. 1-km). b) Seek to refine the land mask. c) Explore nearby areas to use as proxies for time series directly over the beds. Novel processing approaches will be leveraged from other NASA projects and customized as inputs for seagrass productivity modeling
Spiering, Bruce A.↗
Needs Assessment for the Use of NASA Remote Sensing Data in the Development and Implementation of Estuarine and Coastal Water Quality Standards
The goals of the project are to provide information from satellite remote sensing to support numeric nutrient criteria development and to determine data processing methods and data quality requirements to support nutrient criteria development and implementation. The approach is to identify water quality indicators that are used by decision makers to assess water quality and that are related to optical properties of the water; to develop remotely sensed data products based on algorithms relating remote sensing imagery to field-based observations of indicator values; to develop methods to assess estuarine water quality, including trends, spatial and temporal variability, and seasonality; and to develop tools to assist in the development and implementation of estuarine and coastal nutrient criteria. Additional slides present process, criteria development, typical data sources and analyses for criteria process, the power of remote sensing data for the process, examples from Pensacola Bay, spatial and temporal variability, pixel matchups, remote sensing validation, remote sensing in coastal waters, requirements for remotely sensed data products, and needs assessment. An additional presentation examines group engagement and information collection. Topics include needs assessment purpose and objectives, understanding water quality decision making, determining information requirements, and next steps.
Spiering, Bruce↗
Needs Assessment for the Use of NASA Remote Sensing Data for Regulatory Water Quality
This slide presentation reviews the assessment of the needs that NASA can use for the remote sensing of water quality. The goal of this project is to provide information for decision-making activities (water quality standards) using remotely sensed/satellite based water quality data from MODIS and Landsat data.
Spiering, Bruce↗
Seagrass Health Modeling and Prediction with NASA Science Data
Previous research has demonstrated that MODIS data products can be used as inputs into the seagrass productivity model developed by Fong and Harwell (1994). To further explore this use to predict seagrass productivity, Moderate Resolution Imaging Spectroradiometer (MODIS) custom data products, including Sea Surface Temperature, Light Attenuation, and Chlorophyll-a have been created for use as model parameter inputs. Coastal researchers can use these MODIS data products and model results in conjunction with historical and daily assessment of seagrass conditions to assess variables that affect the productivity of the seagrass beds. Current monitoring practices involve manual data collection (typically on a quarterly basis) and the data is often insufficient for evaluating the dynamic events that influence seagrass beds. As part of a NASA-funded research grant, the University of Mississippi, is working with researchers at NASA and Radiance Technologies to develop methods to deliver MODIS derived model output for the northern Gulf of Mexico (GOM) to coastal and environmental managers. The result of the project will be a data portal that provides access to MODIS data products and model results from the past 5 years, that includes an automated process to incorporate new data as it becomes available. All model parameters and final output will be available through the use National Oceanic and Atmospheric Administration?s (NOAA) Environmental Research Divisions Data Access Program (ERDDAP) tools as well as viewable using Thematic Realtime Environmental Distributed Data Services (THREDDS) and the Integrated Data Viewer (IDV). These tools provide the ability to create raster-based time sequences of model output and parameters as well as create graphs of model parameters versus time. This tool will provide researchers and coastal managers the ability to analyze the model inputs so that the factors influencing a change in seagrass productivity can be determined over time.
Robinson, Harold D.↗
Solutions Network Formulation Report. NASA's Potential Contributions for Using Solar Ultraviolet Radiation in Conjunction with Photocatalysis for Urban Air Pollution Mitigation and Increasing Air Quality
This Candidate Solution is based on using NASA Earth science research on atmospheric ozone and aerosols data as a means to predict and evaluate the effectiveness of photocatalytically created surfaces (building materials like glass, tile and cement) for air pollution mitigation purposes. When these surfaces are exposed to near UV light, organic molecules, like air pollutants and smog precursors, will degrade into environmentally friendly compounds. U.S. EPA (Environmental Protection Agency) is responsible for forecasting daily air quality by using the Air Quality Index (AQI) that is provided by AIRNow. EPA is partnered with AIRNow and is responsible for calculating the AQI for five major air pollutants that are regulated by the Clean Air Act. In this Solution, UV irradiance data acquired from the satellite mission Aura and the OMI Surface UV algorithm will be used to help understand both the efficacy and efficiency of the photocatalytic decomposition process these surfaces facilitate, and their ability to reduce air pollutants. Prediction models that estimate photocatalytic function do not exist. NASA UV irradiance data will enable this capability, so that air quality agencies that are run by state and local officials can develop and implement programs that utilize photocatalysis for urban air pollution control and, enable them to make effective decisions about air pollution protection programs.
Underwood, Lauren↗
Polar Lunar Regions: Exploiting Natural and Augmented Thermal Environments
In polar regions of the Moon, some areas within craters are permanently shadowed from solar illumination and can reach temperatures of 100 K or less. These regions could serve as cold traps, capturing ice and other volatile compounds. These potential ice stores have many applications for lunar exploration. Within double-shaded craters, even colder regions exist, with temperatures never exceeding 50 K in many cases. Observed temperatures suggest that these regions could enable equivalent liquid nitrogen cryogenic functions. These permanently shaded polar craters also offer unprecedented high-vacuum cryogenic environments, which in their current state could support cryogenic applications. Besides ice stores, the unique conditions at the lunar poles harbor an environment that provides an opportunity to reduce the power, weight, and total mass that needs to be carried from the Earth to the Moon for lunar exploration and research. Reducing the heat flux of geothermal, black body radiation can have significant impacts on the achievable temperature. With a few manmade augmentations, permanently shaded craters located near the lunar poles achieve temperatures even lower than those that naturally exist. Our analysis reveals that lightweight thermal shielding within shaded craters could create an environment several Kelvin above absolute zero. The temperature ranges of both naturally shaded and thermally augmented craters could enable the long-term storage of most gases, low-temperature superconductors for large magnetic fields, devices and advanced high-speed computing instruments. Augmenting thermal conditions in these craters could then be used as a basis for the development of an advanced thermal management architecture that would support a wide variety of cryogenically based applications. Lunar exploration and habitation capabilities would significantly benefit if permanently shaded craters, augmented with thermal shielding, were used to facilitate the operation of near absolute zero instruments, including a wide variety of cryogenically based propulsion, energy, communication, sensing, and computing devices. The required burden of carrying massive life-supporting components from the Earth to the Moon for lunar exploration and research potentially could be reduced.
Ryan, Robert E.↗
Acquisition of Earth Science Remote Sensing Observations from Commercial Sources: Lessons Learned from the Space Imaging IKONOS Example
In an effort to more full explore the potential of commercial remotely sensed land data sources, the NASA Earth Science Enterprise (ESE) implemented an experimental Scientific Data Purchase (SDP) that solicited bids from the private sector to meet ESE-user data needs. The images from the Space Imaging IKONOS system provided a particularly good match to the current ESE missions such as Terra and Landsat 7 and therefore serve as a focal point in this analysis.
Goward, Samuel N.↗