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NASA NTRS1990

Muscle preservation in long duration space missions: The eccentric factor

In our quest to understand, and eventually prevent, the loss of muscle strength and mass that occurs during prolonged periods in microgravity, we have organized our research approach by systems and useful terrestrial analogs. Our hypothesis was that: The eccentric movement, or lengthening component, of dynamic, resistive exercise, is required for the production of the greatest gains in strength and muscle hypertrophy in the most metabolically efficient, and time effective manner. The exercises selected were leg presses, leg (knee) extensions, and hamstring curls. In this 30 week study, 38 male subjects, between the ages of 25 and 50, were divided into four groups. One group performed 5 sets of 8-12 repetitions per set of conventional concentric/eccentric (CON/ECC) exercises. Another group performed only the concentric (CON) movement on the same schedule. The third group performed twice the number of sets in the concentric only mode (CON/CON), and the last group served as controls. We interpret these data as convincing evidence that the eccentric component of heavy resistance training is required along with the concentric for the most effective increase in strength and muscle fiber size in the least time. We also conclude that such heavy exercise of any such muscle group need not consume inordinately long periods of time, and is quite satisfactorily effective when performed on 72 hour centers.

Buchanan, Paul↗

NASA NTRS2006

A-Train Data Depot: Integrating and Visualizing Atmospheric Measurements Along the A-Train Tracks

The succession of US and international satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000) The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot, to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The A-Train Data Depot (ATDD) will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth s Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archwing for fast data access, and Cooperative Institute for Research in the Atmosphere (CRA) data co-registration tools. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be followed by associated measurements from MLS, OMI, HIRDLS, and TES. Given the independent nature of instrument/platform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be discussed. The project s resulting visualizations and analysis illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗

NASA NTRS2001

Possible Evidence for an Event Horizon in Cyg XR-1

The X-ray emitting component in the Cyg XR-1/HDE226868 system is a leading candidate for identification as a stellar-mass sized black hole. The positive identification of a black hole as predicted by general relativity requires the detection of an event horizon surrounding the point singularity. One signature of such an event horizon would be the existence of dying pulse trains emitted by material spiraling into the event horizon from the last stable orbit around the black hole. We observed the Cyg XR-1 system at three different epochs in a 1400 - 3000 A bandpass with 0.1 ms time resolution using the Hubble Space Telescope's High Speed Photometer. Repeated excursions of the detected flux by more than three standard deviations above the mean are present in the UV flux with FWHM 1 - 10 ms. If any of these excursions are pulses of radiation produced in the system (and not just stochastic variability associated with the Poisson distribution of detected photon arrival times), then this short a timescale requires that the pulses originate in the accretion disk around Cyg XR-1. Two series of pulses with characteristics similar to those expected from dying pulse trains were detected in three hours of observation.

Dolan, Joseph F.↗

NASA NTRS2006

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗

NASA NTRS1991

Pulsed response of a TWT

The consequence of frequency domain multiple access channelization in a satellite communications system is that the ground- and space-based components often are required to operate in a linear region to prevent the generation of distortion signals. Components of a time division multiple access (TDMA) satellite system, such as a traveling-wave tube (TWT), can operate in the highest output power state because the channelization technique is relatively insensitive to the distortions resulting from saturated operation. A 30 GHz TWT was tested to determine the suitability of such a device in a TDMA system. Testing was focused on the ability of the TWT's output signal to rise up to full power at the leading edge of TDMA bursts, simulated by a pulse train. A peak power meter was used to display and measure the pulsed signal waveform. Measurements on the TWT output pulse rise time indicate that the TWT lengthened the rise time by 10 to 20 ns. Imposing modulator turn on timing that precedes the data burst by the TWT rise time is a logical approach to coordination of the two subsystem specification.

May, Brian D.↗

NASA NTRS2000

The Strategy for Polar Exploration: Planes, Trains, and Automobiles

The polar regions are both interesting and challenging to explore. The record of climate history and the behavior of Martian volatiles over time are thought to be contained in the polar terrains. Furthermore, the polar regions are probably the best environment to search for evidence of living organisms on Mars because they have both the presence of water ice and summertime temperatures at the surface that exceed the freezing point of water. In addition, melting at the base of the polar caps is predicted to occur which could result in a deep aquifer beneath the polar caps. Such an aquifer is potentially another habitat for life. Clearly, assessing the question of volaties, climate, and life in the polar regions would benefit from landed missions that can sample and interact with the surface. Mobility on the surface is also important for polar exploration due to the apparent wide diversity of terrains that occur on both local and regional scales. Additional information is contained in the original extended abstract.

Stoker, C.↗

NASA NTRS2016

The Trick Simulation Toolkit: A NASA/Open source Framework for Running Time Based Physics Models

This paper describes the design and use at of the Trick Simulation Toolkit, a simulation development environment for creating high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. It describes Trick's design goals and how the development environment attempts to achieve those goals. It describes how Trick is used in some of the many training and engineering simulations at NASA. Finally it describes the Trick NASA/Open source project on Github.

Penn, John M.↗

NASA NTRSDate not supplied

Psychophysiological Methods to Assess Pilot Productive Safety Behaviors

The NASA System-Wide Safety (SWS) Project is focused on developing new technologies and operational concepts for the aviation industry to meet the increasing global demand while maintaining the current ultra-safe system safety levels. To achieve this, the SWS Project is developing research priorities, including In-time System-wide Safety Assurance (ISSA) and In-time Aviation Safety Management System (IASMS; Ellis et al., 2019). A critical component of the IASMS is the human as pilot and in other roles in aviation operations as demonstrated by SWS human factors research on rare occurrences of human error and the far more prevalent human safety producing behaviors (e.g., Hollnagel, 2016). The talk presented by Chad Stephens of NASA Langley Research Center and NASA SWS Project will describe the history of human factors research involving psychophysiological and biocybernetics methods supporting aviation safety conducted at NASA. Specific examples of recent NASA crew state monitoring research focused on a psychophysiological assessment method and system to enable Training for Attention Management will be demonstrated. Current SWS research including the SWS Operations and Technologies for Enabling Resilient In-Time Assurance (SOTERIA) flight simulation study and a data testbed created to enable study of Human Contributions to Safety (HC2S) will be presented. Ongoing collaborative research efforts with Boeing researchers will be highlighted and opportunities for further collaboration will be discussed.

psychophysiology↗

NASA NTRS2003

Development of Methodologies for IV and V of Neural Networks

Non-deterministic systems often rely upon neural network (NN) technology to "lean" to manage flight systems under controlled conditions using carefully chosen training sets. How can these adaptive systems be certified to ensure that they will become increasingly efficient and behave appropriately in real-time situations? The bulk of Independent Verification and Validation (IV&V) research of non-deterministic software control systems such as Adaptive Flight Controllers (AFC's) addresses NNs in well-behaved and constrained environments such as simulations and strict process control. However, neither substantive research, nor effective IV&V techniques have been found to address AFC's learning in real-time and adapting to live flight conditions. Adaptive flight control systems offer good extensibility into commercial aviation as well as military aviation and transportation. Consequently, this area of IV&V represents an area of growing interest and urgency. ISR proposes to further the current body of knowledge to meet two objectives: Research the current IV&V methods and assess where these methods may be applied toward a methodology for the V&V of Neural Network; and identify effective methods for IV&V of NNs that learn in real-time, including developing a prototype test bed for IV&V of AFC's. Currently. no practical method exists. lSR will meet these objectives through the tasks identified and described below. First, ISR will conduct a literature review of current IV&V technology. TO do this, ISR will collect the existing body of research on IV&V of non-deterministic systems and neural network. ISR will also develop the framework for disseminating this information through specialized training. This effort will focus on developing NASA's capability to conduct IV&V of neural network systems and to provide training to meet the increasing need for IV&V expertise in such systems.

Taylor, Brian↗

NASA NTRS2008

A Multi-Season Study of the Effects of MODIS Sea-Surface Temperatures on Operational WRF Forecasts at NWS Miami, FL

Studies at the Short-term Prediction Research and Transition (SPORT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) sea-surface temperature (SST) composites in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. Recent work by LaCasse et al (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPORT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The project's goal is to determine whether more accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run dally initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution (approx.9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPORT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water, The MODIS SST composites for initializing the SPORT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST data into the SPORT WRF runs is staggered such that SSTs are updated with a new composite every six hours in each of the WRF runs. From mid-February to July 2007, over 500 parallel WRF simulations have been collected for analysis and verification. This paper will present verification results comparing the NWS MIA operational WRF runs to the SPORT experimental runs, and highlight any substantial differences noted in the predicted mesoscale phenomena for specific cases.

Case, Jonathan L.↗

NASA NTRSDate not supplied

The Application of Remote Sensing and Machine Learning to Improve Early Warning Systems for Harmful Algal Events in the Highland Lake Chain, TX

Beginning in 2019, harmful algal events have caused canine deaths in both Lady Bird Lake and Lake Travis located near Austin, Texas. These two reservoirs are part of the larger Highland Lakes chain, managed by the City of Austin Department of Watershed Protection (COA DWP) and the Lower Colorado River Authority (LCRA), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable environmental conditions for algal events in central Texas, NASA DEVELOP partnered with LCRA and COA DWP to improve monitoring and early detection of algal events, utilizing satellite remote sensing and machine learning. Spatially and temporally varied chlorophyll a concentrations, cyanobacteria detections, turbidity, and water surface temperature products are used as environmental proxies. Landsat 8 Operational Land Imager (OLI) and the Sentinel-2 MultiSpectral Instrument (MSI) data were used to provide a combined revisit time of up to ~3 days and < 30 m per pixel products. Chlorophyll a concentrations were estimated using a pre-trained Mixture Density Network, and cyanobacteria detection was accomplished using the Broad Wavelength Algae Index, which can differentiate algal blooms from algal proliferations (mats). In situ data were used to validate remotely sensed measurements and quantify uncertainties. Preliminary results show a good fit between the modeled output and in situ observations, suggesting that remote sensing data can be used to retrieve biogeochemical properties and/or inherent optical properties (IOPs) of water columns in these inland human-made lakes. Uncertainties were introduced from the sensitivity to atmospheric correction, inherent mismatch between satellite and sampling data, and a relatively lower signal-to-noise ratio over water. The resulting products enable near real-time monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain, and will ultimately support water management, decision making, and risk communication.

Shuyu Chang↗

NASA NTRS1993

Radial basis function network learns ceramic processing and predicts related strength and density

Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.

Cios, Krzysztof J.↗

NASA NTRS2005

Sunspot Pattern Classification using PCA and Neural Networks (Poster)

The sunspot classification scheme presented in this paper is considered as a 2-D classification problem on archived datasets, and is not a real-time system. As a first step, it mirrors the Zuerich/McIntosh historical classification system and reproduces classification of sunspot patterns based on preprocessing and neural net training datasets. Ultimately, the project intends to move from more rudimentary schemes, to develop spatial-temporal-spectral classes derived by correlating spatial and temporal variations in various wavelengths to the brightness fluctuation spectrum of the sun in those wavelengths. Once the approach is generalized, then the focus will naturally move from a 2-D to an n-D classification, where "n" includes time and frequency. Here, the 2-D perspective refers both to the actual SOH0 Michelson Doppler Imager (MDI) images that are processed, but also refers to the fact that a 2-D matrix is created from each image during preprocessing. The 2-D matrix is the result of running Principal Component Analysis (PCA) over the selected dataset images, and the resulting matrices and their eigenvalues are the objects that are stored in a database, classified, and compared. These matrices are indexed according to the standard McIntosh classification scheme.

Rajkumar, T.↗

NASA NTRS1967

Fast-response frequency-to-analog converter

Frequency-to-analog converter has a fast response time and a low ripple. The circuit uses a frequency-to-pulse converter which provides two pulse trains, both at the same frequency as that of the input signal, but with a 10 microsecond difference between the trains.

Hagihara, F. S.↗

NASA NTRS1975

Problems, questions and results in the use of the BBN-model

A hierarchical structured control model was used to describe pilot performance in a multivariable control problem. The model is based on the assumption that a well trained operator optimized a quadratic optimization criterion. The model considers some special characteristics of the human operator as time delay, neuromuscular time lag, observation and motor noise and the ability to extract the first derivative of a displaced value. Numerical results of a simple human engineering example using the BBN model demonstrate the influence of the variation of different parameters on covariance matrices of the state and observation vectors.

Dey, D.↗

NASA NTRS1977

Rotor systems research aircraft simulation mathematical model

An analytical model developed for evaluating and verifying advanced rotor concepts is discussed. The model was used during in both open loop and real time man-in-the-loop simulation during the rotor systems research aircraft design. Future applications include: pilot training, preflight of test programs, and the evaluation of promising concepts before their implementation on the flight vehicle.

Houck, J. A.↗

NASA NTRS1977

Remote sensing data processing: Two years ago, today, and two years from today

Beginning with a survey of the state-of-the-art of processing remotely sensed data in early 1975, significant developments between that time and the present are chronicled, and technologies for early 1979 are projected. Current technical issues discussed include: training selection and labeling; classification and mensuration; use of satellite indicators to supplement predictions; small scale field structures; physical factors; ancillary data; geometric quality; and the cost of processing.

Holmes, Q. A.↗

NASA NTRS1977

Research requirements to improve safety of civil helicopters

Helicopter and fixed-wing accident data were reviewed and major accident causal factors were established. The impact of accidents on insurance rates was examined and the differences in fixed-wing and helicopter accident costs discussed. The state of the art in civil helicopter safety was compared to military helicopters. Goals were established based on incorporation of known technology and achievable improvements that require development, as well as administrative-type changes such as the impact of improved operational planning, training, and human factors effects. Specific R and D recommendations are provided with an estimation of the payoffs, timing, and development costs.

Waters, K. T.↗