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NASA NTRS1977

A life sciences Spacelab mission simulation

The paper describes the purposes of a seven-day simulated life-sciences mission conducted in a Spacelab simulator. A major objective was the evaluation of in-orbit Spacelab operations and those mission control support functions which will be required from the Payload Operations Center. Tested equipment and procedures included experiment racks, common operational research equipment, commercial off-the-shelf equipment, experiment hardware interfaces with Spacelab, experiment data handling concepts, and Spacelab trash management.

Mason, J. A.↗

NASA NTRS1987

Artificial intelligence and space power systems automation

Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development.

Weeks, David J.↗

NASA NTRS1994

Advanced information processing system: The Army Fault-Tolerant Architecture detailed design overview

The Army Avionics Research and Development Activity (AVRADA) is pursuing programs that would enable effective and efficient management of large amounts of situational data that occurs during tactical rotorcraft missions. The Computer Aided Low Altitude Night Helicopter Flight Program has identified automated Terrain Following/Terrain Avoidance, Nap of the Earth (TF/TA, NOE) operation as key enabling technology for advanced tactical rotorcraft to enhance mission survivability and mission effectiveness. The processing of critical information at low altitudes with short reaction times is life-critical and mission-critical necessitating an ultra-reliable/high throughput computing platform for dependable service for flight control, fusion of sensor data, route planning, near-field/far-field navigation, and obstacle avoidance operations. To address these needs the Army Fault Tolerant Architecture (AFTA) is being designed and developed. This computer system is based upon the Fault Tolerant Parallel Processor (FTPP) developed by Charles Stark Draper Labs (CSDL). AFTA is hard real-time, Byzantine, fault-tolerant parallel processor which is programmed in the ADA language. This document describes the results of the Detailed Design (Phase 2 and 3 of a 3-year project) of the AFTA development. This document contains detailed descriptions of the program objectives, the TF/TA NOE application requirements, architecture, hardware design, operating systems design, systems performance measurements and analytical models.

Harper, Richard E.↗

NASA NTRS2001

National Environmental Change Information System Case Study

The Global Hydrology and Climate Center and NASA's Marshall Space Flight Center conducted a fact-finding case study for the Data Management Working Group (DMWG), now referred to as the Data and Information Working Group (DIWG), of the U.S. Global Change Research Program (USGCRP) to determine the feasibility of an interagency National Environmental Change Information System (NECIS). In order to better understand the data and information needs of policy and decision makers at the national, state, and local level, the DIWG asked the case study team to choose a regional water resources issue in the southeastern United States that had an impact on a diverse group of stakeholders. The southeastern United States was also of interest because the region experiences interannual climatic variations and impacts due to El Nino and La Nina. Jointly, with input from the DIWG, a focus on future water resources planning in the Apalachicola-Chattahoochee-Flint (ACF) River basins of Alabama, Georgia, and Florida was selected. A tristate compact and water allocation formula is currently being negotiated between the states and U.S. Army Corps of Engineers (COE) that will affect the availability of water among competing uses within the ACF River basin. All major reservoirs on the ACF are federally owned and operated by the U.S. Army COE. A similar two-state negotiation is ongoing that addresses the water allocations in the adjacent Alabama-Coosa-Tallapoosa (ACT) River basin, which extends from northwest Georgia to Mobile Bay. The ACF and ACT basins are the subject of a comprehensive river basin study involving many stakeholders. The key objectives of this case study were to identify specific data and information needs of key stakeholders in the ACF region, determine what capabilities are needed to provide the most practical response to these user requests, and to identify any limitations in the use of federal data and information. The NECIS case study followed the terms of reference developed by the interagency DIWG. The case study "lessons learned" and "key findings" offer guidelines and considerations to the DMWG for the development and implementation of a NECIS that would support the data and information needs of policy and decision makers at the national, state, and local level.

Goodman, S. J.↗

NASA NTRS2002

CAD/CAE Integration Enhanced by New CAD Services Standard

A Government-industry team led by the NASA Glenn Research Center has developed a computer interface standard for accessing data from computer-aided design (CAD) systems. The Object Management Group, an international computer standards organization, has adopted this CAD services standard. The new standard allows software (e.g., computer-aided engineering (CAE) and computer-aided manufacturing software to access multiple CAD systems through one programming interface. The interface is built on top of a distributed computing system called the Common Object Request Broker Architecture (CORBA). CORBA allows the CAD services software to operate in a distributed, heterogeneous computing environment.

Claus, Russell W.↗

NASA NTRS2024

Narragansett Bay Water Resources: Using Earth Observations to Identify Trends in Harmful Algal Blooms in Narragansett Bay

Narragansett Bay in Rhode Island is known for its quahog, or hard-shell clam, shellfisheries. However, increased levels in harmful algal blooms (HABs) and high phytoplankton biomass events pose threats to quahog populations, creating conditions that limit quahog growth and reproduction. Quahog shortages, along with public health concerns associated with contamination of shellfish from HAB-produced neurotoxins, have contributed to shellfishery closures. NASA DEVELOP partnered with the Environmental Protection Agency’s National Health and Environmental Effects Research Laboratory and Rhode Island’s Department of Environmental Management to use Earth observations and the partners’ in-situ data to visualize phytoplankton bloom events within the bay. We used Sentinel-3 Ocean and Land Color Instrument (OLCI), Landsat 8 and 9 Operational Land Imager (OLI)data to track several proxies of phytoplankton biomass from June 2016 to October 2023. Multiple sensors and in situ datasets were used to assess the feasibility of monitoring phytoplankton biomass accurately in the relatively small sized Narragansett Bay. We determined that Phytoplankton fluorescence line height was the best parameter to monitor phytoplankton biomass in the bay. Although the relatively small size of the bay and the optical complexity of these nearshore waters can pose a challenge, this assessment showed that Earth observations can be a useful complement to the in-situ monitoring of phytoplankton biomass in Narragansett Bay.

Sentinel-3↗

NASA NTRS2014

Development of Super Ensemble-Based Aviation Turbulence Guidance (SEATG) for Air Traffic Management

A new method for forecasting turbulence is developed and evaluated using the high resolution weather model and in situ turbulence observations from commercial aircraft. The new method is an ensemble of various turbulence metrics from multiple time-lagged ensemble forecasts created using a sequence of four procedures. These include weather modeling, calculation of turbulence metrics, mapping the metrics into a common turbulence-scale, and production of final forecast. The new method uses similar methodology as current operational turbulence forecast with three improvements. First, it uses a higher resolution ((delta)x = 3 km) weather model to capture cloud resolving scale phenomena. Second, it computes the metrics for multiple forecasts that are combined at the same valid time resulting in a time-lagged ensemble of multiple turbulence metrics. Finally, it provides both deterministic and probabilistic turbulence forecasts. Results show the new forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on research period. Overall performance skill of the new turbulence forecast compared with the observed EDR data during the research period is superior to any single turbulence metric. The probabilistic turbulence forecast is used in an example air traffic management application for creating a wind-optimal route considering turbulence information. The wind-optimal route passing through areas of 50% potential for moderate-or-greater turbulence and the lateral turbulence avoidance routes starting from three different waypoints along the wind-optimal route from Los Angeles international airport to John F. Kennedy international airport are calculated using different turbulence forecasts. This example shows additional flight time is required to avoid potential turbulence encounters.

modeling↗

NASA NTRS2016

Ontologies for Aviation Data Management

Managing complex aviation data can be a significant challenge for any enterprise – whether a government agency, airline, airframe manufacturer, or aviation service provider. To handle this challenge, data models are typically developed to characterize and manage the data generated, used, and stored by a given enterprise. Unfortunately, different data providers employ qualitatively different data models, and this gives rise to problems exchanging data across organizational boundaries. Over the past decade, these problems have motivated data producers and consumers to look toward standardized data exchange models to address data interoperability. In this paper we examine some of these standardized data exchange models and compare them with a new type of data model based on ontologies. Ontology models have emerged in recent years from a confluence of research in the artificial intelligence, semantic web, and information science communities. This paper introduces ontology models, provides several use cases for ontologies relevant to aviation data management, and summarizes state of the art aviation prototype applications that utilize ontologies.

artificial intelligence↗

NASA NTRS2002

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

Shaw, J.↗

NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗

NASA NTRS1998

OARE and SAMS on STS-94/MSL-1

Four microgravity acceleration measurement instruments were included on MSL-1 to measure the accelerations and vibrations to which science experiments were exposed during their operation on the mission. The data were processed and presented to the principal investigators in a variety of formats to aid their assessment of the microgravity environment during their experiment operations. Two accelerometer systems managed by the NASA Lewis Research Center (LeRC) supported the MSL-1 mission: the Orbital Acceleration Research Experiment (OARE), and the Space Acceleration Measurement System (SAMS). In addition, the Microgravity Measurement Assembly (MMA) and the Quasi- Steady Acceleration Measurement (QSAM) system, both sponsored by the Microgravity Research Division, collected acceleration data as a part of the MSL-1 mission. The NIMA was funded and designed by the European Space Agency in the Netherlands (ESA/ESTEC), and the QSAM system was funded and designed by the German Space Agency (DLR). The Principal Investigator Microgravity Services (PIMS) project at the NASA Lewis Research Center (LeRC) supports Principal Investigators (PIs) of the Microgravity science community as they evaluate the effects of acceleration on their experiments. PIMS primary responsibility is to support NASA-sponsored investigators in the area of acceleration data analysis and interpretation. A mission summary report was prepared and published by PIMS in order to furnish interested experiment investigators with a guide for evaluating the acceleration environment during the MSL-1 mission.

Moskowitz, Milton↗

NASA NTRS2017

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗

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 NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

Astroskin↗

NASA NTRS1981

Remote sensing aided procedure for conifer growth modeling in the northeastern Sierra Nevada

The objective of this study was to use remotely-sensed data with ground-acquired data for preparing inputs to a mathematical model for generation of a potential conifer growth map of a wildland area. The study area, jointly selected by the resource managers of the U.S. Forest Service at the Plumas National Forest and researchers, covers approximately 500 sq km in the northeastern scrapment of Sierra Nevada. The approach involved a computerized databank based on both remotely-sensed and ground-acquired data. The remotely-sensed data included Landsat Multispectral Scanner (MSS) data, NOAA-5 Very High Resolution Radiometer (VHRR) data and U-2 Color infrared photography. The ground data included U.S. Geological Survey (USGS) topographic maps, Defense Mapping Agency (DMA)/USGS digital terrain data, soil maps, and vegetation data. The results included a series of maps for the final product as well as the intermediate products. The intermediate products were potential evapotranspiration, aspect, and soil plant available water.

Smith, H. G.↗

NASA NTRS1981

The non-Federal oceanographic community: An overview

A portion of the broad domestic non-Federal oceanographic community that represents a potential market for satellite remote sensor derived oceanographic data and/or marine environmental information is presented. The overview consists of listings of individuals and/or organizations who have used, or are likely to use such data or information for scientific research, offshore engineering purposes, marine resources exploration and utilization, marine related operational applications, or coastal zone management.

Swetnick, M. A.↗

NASA NTRS1988

Application of intelligent systems to wind tunnel test facilities

An approach to the application of intelligent-systems technology to the wind tunnel facilities at NASA Ames Research Center is outlined. To help fulfill the long-range goals of improving data quality and increasing personnel efficiency and management effectiveness, three major areas of intelligent systems application are recommended. The available state-of-the-art technology for developing the proposed systems is reviewed including the application of commercial software packages. The initial tasks and effort to develop these systems are recommended. A prototype expert system for selection of internal strain-gage balances has been built and is presented herein as an example model for the future systems.

Lo, Ching F.↗

NASA NTRS1991

Early-EOS data and information system

NASA's Earth Observing System (EOS), an integral part of the U.S. Global Change Research Program, will provide simultaneous observations from a suite of instruments in low-earth orbit. The EOS Data and Information System (EOSDIS) will handle the data from those instruments, as well as provide access to observations and related information from other earth science missions. The Early-EOSDIS Program will provide initial improved support for global change research by building upon present capabilities and data, and will establish a working prototype EOSDIS for selected archiving, distribution, and information management functions by mid-1994.

Ludwig, George H.↗