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At least 577 records · Page 32
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NASA NTRS2020

UAS Integration in the NAS Project: Overview of Flight Test Series 6

The National Aeronautics and Space Administration (NASA) Unmanned Aircraft Systems Integration in the National Airspace System (UAS-NAS) Project has conducted a series of flight test campaigns intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration (FAA). The 2019 Flight Test Series 6 (FT6) campaign furthered this path and supported three test configurations: 1) Radar Characterization, 2) Scripted Encounters and 3) Full Mission. Radar Characterization assessed the performance of Honeywell’s low size, weight, and power (low SWaP) radar system; Scripted Encounters investigated the timing of Detect and Avoid (DAA) alerting thresholds using a Department of Defense (DoD) Group 3 unmanned aircraft system (UAS) equipped with low SWaP sensors and three different live intruder aircraft flown at varying encounter geometries; and Full Mission validated human-in-the-loop simulations by collecting pilot performance data from a ground control station while controlling a live unmanned aircraft on a mission in both virtual and live air traffic controlled airspace. The subject pilot observed a research display that presented DAA advisories to maintain separation from live and virtual aircraft. The test was conducted over a twenty-week period within the R-2508 special use airspace located near Edwards Air Force Base (EAFB), CA. Over 240 encounters were flown during the test series and FT6 proved to be invaluable for the purposes of planning, managing, and executing this type of integrated flight test in both live and virtual environments. Data collected from FT6 was provided to the RTCA Special Committee 228 (SC-228) to help inform the Phase 2 Minimum Operational Performance Standards (MOPS). FT6 was the final test series for the UAS-NAS project that began in 2012. This paper provides an overview of FT6 and its success can be directly attributed to the diligent work of the men and women who supported this effort.

UAS in the NAS↗
NASA NTRS1999

Theory and Modeling in Support of Tether

This final report summarizes the work performed by SAIC's Applied Physics Operation on the modeling and support of Tethered Satellite System missions (TSS-1 and TSS-1R). The SAIC team, known to be Theory and Modeling in Support of Tether (TMST) investigation, was one of the original twelve teams selected in July, 1985 for the first TSS mission. The accomplishments described in this report cover the period December 19, 1985 to September 31, 1999 and are the result of a continuous effort aimed at supporting the TSS missions in the following major areas. During the contract period, the SAIC's TMST investigation acted to: Participate in the planning and the execution on both of the TSS missions; Provide scientific understanding on the issues involved in the electrodynamic tether system operation prior to the TSS missions; Predict ionospheric conditions encountered during the re-flight mission (TSS-lR) based on realtime global ionosounde data; Perform post mission analyses to enhance our understanding on the TSS results. Specifically, we have 1) constructed and improved current collection models and enhanced our understanding on the current-voltage data; 2) investigated the effects of neutral gas in the current collection processes; 3) conducted laboratory experiments to study the discharge phenomena during and after tether-break; and 4) perform numerical simulations to understand data collected by plasma instruments SPES onboard the TSS satellite; Design and produce multi-media CD that highlights TSS mission achievements and convey the knowledge of the tether technology to the general public. Along with discussions of this work, a list of publications and presentations derived from the TMST investigation spanning the reporting period is compiled.

Chang, C. L.↗
NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗
NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗
NASA NTRS1973

Mariner Mars 1971 sun sensor model development and simulation

The sun sensor flight performance data were analyzed along with the results of a newly developed cruise sensor life in order to better understand cadmium sulfide sun sensor performance. A set of mathematical models was constructed which closely approximated the observed sun sensor flight and laboratory test results. These models revealed, among other things, that (1) the aging phenomena in the sintered cadmium sulfide light detector varies across the detector width in proportion to the illumination history, (2) the current cruise sun sensor design is extremely sensitive to changes in the reflected illumination within the sensor housing, (3) the reflected illumination within the detector housing is proportional to the area and intensity of the solar disk observed at the spacecraft, and (4) the acquisition sun sensor becomes a low impedance path across the sensor bridge when in the vicinity of a large-angular-diameter, low-intensity light source.

Schumacher, L.↗
NASA NTRS1981

NASA preprototype redox storage system for a photovoltaic stand-alone application

A 1 kW preprototype redox storage system underwent characterization tests and was operated as the storage device for a 5 kW (peak) photovoltaic array. The system is described and performance data are presented. Loss mechanisms are discussed and simple design changes leading to significant increases in efficiency are suggested. The effects on system performance of nonequilibrium between the predominant species of complexed chromic ion in the negative electrode reactant solution are indicated.

Hagedorn, N. H.↗
NASA NTRS1981

NASA preprototype redox storage system for a photovoltaic stand-alone application

A 1-kW preprototype redox storage system that has undergone characterization tests and been operated as the storage device for a 5-kW (peak) photovoltaic array is described and performance data are presented. Loss mechanisms are discussed, and simple design changes leading to appreciable increases in efficiency are suggested. The effects on system performance of nonequilibrium between the predominant species of complexed chromic ion in the negative electrode reactant solution are summarized. It is noted that with the aid of the prototype system, control concepts have been shown to be valid and trouble free and some insight has been gained into interactions at the mutual interfaces of the redox system, the photovoltaic array, the load, and the control devices.

Hagedorn, N. H.↗
NASA NTRS1983

LANDSAT-4 TM image data quality analysis for energy-related applications

LANDSAT-4 Thematic Mapper (TM) data performance and utility characteristics from an energy research and technology perspective is evaluated. The program focuses on evaluating applicational implications of using such data, in combination with other digital data, for current and future energy research and technology activities. Prime interest is in using TM data for siting, developing and operating federal energy facilities. Secondary interests involve the use of such data for resource exploration, environmental monitoring and basic scientific initiatives such as in support of the Continental Scientific Drilling Program.

Wukelic, G. E.↗
NASA NTRS1986

Dynamic remapping of parallel computations with varying resource demands

A large class of computational problems is characterized by frequent synchronization, and computational requirements which change as a function of time. When such a problem must be solved on a message passing multiprocessor machine, the combination of these characteristics lead to system performance which decreases in time. Performance can be improved with periodic redistribution of computational load; however, redistribution can exact a sometimes large delay cost. We study the issue of deciding when to invoke a global load remapping mechanism. Such a decision policy must effectively weigh the costs of remapping against the performance benefits. We treat this problem by constructing two analytic models which exhibit stochastically decreasing performance. One model is quite tractable; we are able to describe the optimal remapping algorithm, and the optimal decision policy governing when to invoke that algorithm. However, computational complexity prohibits the use of the optimal remapping decision policy. We then study the performance of a general remapping policy on both analytic models. This policy attempts to minimize a statistic W(n) which measures the system degradation (including the cost of remapping) per computation step over a period of n steps. We show that as a function of time, the expected value of W(n) has at most one minimum, and that when this minimum exists it defines the optimal fixed-interval remapping policy. Our decision policy appeals to this result by remapping when it estimates that W(n) is minimized. Our performance data suggests that this policy effectively finds the natural frequency of remapping. We also use the analytic models to express the relationship between performance and remapping cost, number of processors, and the computation's stochastic activity.

Nicol, D. M.↗
NASA NTRS1998

Results of a 24-inch Hybrid Motor Performance Uncertainty Analysis

The subscale (11 and 24-inch) hybrid motors at the Marshall Space Flight Center (MSFC) have been used as versatile and cost effective testbeds for developing new technology. Comparisons between motor configuration, ignition systems, feed systems, fuel formulations, and nozzle materials have been carried out without detailed consideration as to haw "good" the motor performance data were. For the 250,000 lb/thrust motor developed by the Hybrid Propulsion Demonstration Program consortium, this shortcoming is particularly risky because motor performance will likely be used as put of a set of downselect criteria to choose between competing ignition and feed systems under development. This analysis directly addresses that shortcoming by applying uncertainty analysis techniques to the experimental determination of the characteristic velocity, theoretical characteristic velocity, and characteristic velocity efficiency for a 24-inch motor firing. With the adoption of fuel-lined headends, flow restriction, and aft mixing chambers, state of the an 24-inch hybrid motors have become very efficient However, impossibly high combustion efficiencies (some computed as high as 108%) have been measured in some tests with 11-inch motors. This analysis has given new insight into explaining how these efficiencies were measured to be so high, and into which experimental measurements contribute the most to the overall uncertainty.

Sims, Joseph D.↗
NASA NTRS1995

Radio-science performance analysis software

The Radio Science Systems Group (RSSG) provides various support functions for several flight project radio-science teams. Among these support functions are uplink and sequence planning, real-time operations monitoring and support, data validation, archiving and distribution functions, and data processing and analysis. This article describes the support functions that encompass radio-science data performance analysis. The primary tool used by the RSSG to fulfill this support function is the STBLTY program set. STBLTY is used to reconstruct observable frequencies and calculate model frequencies, frequency residuals, frequency stability in terms of Allan deviation, reconstructed phase, frequency and phase power spectral density, and frequency drift rates. In the case of one-way data, using an ultrastable oscillator (USO) as a frequency reference, the program set computes the spacecraft transmitted frequency and maintains a database containing the in-flight history of the USO measurements. The program set also produces graphical displays. Some examples and discussions on operating the program set on Galileo and Ulysses data will be presented.

Morabito, D. D.↗
NASA NTRS2008

Subscale Injector Testing to Support J-2X Engine Development

The J-2X engine being pursued for the Ares I will be a derivative of the J-2 engine developed by Pratt & Whitney Rocketdyne (PWR). As part of the engine development, a subscale injector was fabricated by PWR and hot-fire tested at NASA s Marshall Space Flight Center (MSFC) to evaluate performance data. This subscale injector had a reduced injector diameter and fewer elements than the full scale design, but the element density (#elements / injector area), and element geometries nearly identical to the full scale design. Three different materials were used for the LOX posts in order to test for durability. The subscale injector included 46 standard elements and 6 baffle elements, corresponding to the ratio of baffled elements to core elements in the full scale design. The baffle elements were included to demonstrate thermal compatibility of the baffles and to more closely represent the full scale performance. Fifteen hot-fire tests were conducted totaling over 200 seconds of mainstage time on the injector. Chamber pressures with oxygen/hydrogen propellants ranged from 870-1380 psig with mixture ratios ranging from 4.8-6.1. Fuel manifold inlet temperatures were varied from 190 to 300 R. Modular, water cooled, calorimeter chamber assemblies were used to provide heating rate data and evaluate the effects of characteristic length (L*). Performance was evaluated relative to the resulting characteristic velocity (C*) efficiency. Performance met the value required in order to proceed with this design for the full scale hardware. Hardware inspections show no evidence of cracking at the tip of the LOX post for any of the materials tested. Minor erosion of the baffle element tips was observed in the early testing. A design change was quickly implemented and tested, and this change resolved the issue. Development of the J-2X is continuing with this element density and design.

Protz, Christopher↗
NASA NTRS1974

Power spectral density analysis of the electromyogram from a work task performed in a full pressure suit

Surface electromyograms (EMG) taken from three upper torso muscles during a push-pull task were analyzed by a power spectral density technique to determine the utility of the spectral analysis for identifying changes in the EMG caused by muscular fatigue. The results confirmed the value of the frequency analysis for identifying fatigue producing muscular performance. Data revealed reliable differences between muscles in fatigue induced responses to various locations in the reach envelope at which the subjects were required to perform the push-pull exercise, and the differential sensitivity of individual muscles to the various reach positions; i.e., certain reach positions imposed more fatigue related shifts in EMG power than did others. It was found that a pressurized space suit changed the pattern of normal shirtsleeve muscle fatigue responses in all three of the muscles.

Lafevers, E. V.↗
NASA NTRS1975

Shuttle freezer conceptual design

A conceptual design for a kit freezer for operation onboard shuttle was developed. The freezer features a self-contained unit which can be mounted in the orbiter crew compartment and is capable of storing food at launch and returning with medical samples. Packaging schemes were investigated to provide the optimum storage capacity with a minimum weight and volume penalty. Several types of refrigeration systems were evaluated to select one which would offer the most efficient performance and lowest hazard of safety to the crew. Detailed performance data on the selected, Stirling cycle principled refrigeration unit were developed to validate the feasibility of its application to this freezer. Thermal analyses were performed to determine the adequacy of the thermal insulation to maintain the desired storage temperature with the design cooling capacity. Stress analyses were made to insure the design structure integrity could be maintained over the shuttle flight regime. A proposed prototype freezer development plan is presented.

Proctor, B. W.↗
NASA NTRS1979

Unconventional nozzle tradeoff study

Plug cluster engine design, performance, weight, envelope, operational characteristics, development cost, and payload capability, were evaluated and comparisons were made with other space tug engine candidates using oxygen/hydrogen propellants. Parametric performance data were generated for existing developed or high technology thrust chambers clustered around a plug nozzle of very large diameter. The uncertainties in the performance prediction of plug cluster engines with large gaps between the modules (thrust chambers) were evaluated. The major uncertainty involves, the aerodynamics of the flow from discrete nozzles, and the lack of this flow to achieve the pressure ratio corresponding to the defined area ratio for a plug cluster. This uncertainty was reduced through a cluster design that consists of a plug contour that is formed from the cluster of high area ratio bell nozzles that have been scarfed. Light-weight, high area ratio, bell nozzles were achieved through the use of AGCarb (carbon-carbon cloth) nozzle extensions.

Obrien, C. J.↗
NASA NTRS1987

Model helicopter performance degradation with simulated ice shapes

An experimental program using a commercially available model helicopter has been conducted in the Texas A&M University Subsonic Wind Tunnel to investigate main rotor performance degradation due to generic ice. The simulated ice, including both primary and secondary formations, was scaled by chord from previously documented artificial ice accretions. Base and iced performance data were gathered as functions of fuselage incidence, blade collective pitch, main rotor rotational velocity, and freestream velocity. It was observed that the presence of simulated ice tends to decrease the lift to equivalent drag ratio, as well as thrust coefficient for the range of velocity ratios tested. Also, increases in torque coefficient due to the generic ice formations were observed. Evaluation of the data has indicated that the addition of roughness due to secondary ice formations is crucial for proper evaluation of the degradation in main rotor performance.

Tinetti, Ana F.↗