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It is tempting to seek universal combat simulations, optimized for both analysis and training. Such a quest would be quixotic, however, because the two environments place conflicting requirements.
The purpose of this document is to define the software training approach and plans for the Jet Propulsion Laboratory.
This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.
The commuter and freight railroad industry is required to implement Positive Train Control (PTC) by 2015 (2012 for Metrolink), a challenging network communications problem. This paper will discuss present technologies developed by the National Aeronautics and Space Administration (NASA) to overcome comparable communication challenges encountered in deep space mission operations. PTC will be based on a new cellular wireless packet Internet Protocol (IP) network. However, ensuring reliability in such a network is difficult due to the "dead zones" and transient disruptions we commonly experience when we lose calls in commercial cellular networks. These disruptions make it difficult to meet PTC s stringent reliability (99.999%) and safety requirements, deployment deadlines, and budget. This paper proposes innovative solutions based on space-proven technologies that would help meet these challenges: (1) Delay Tolerant Networking (DTN) technology, designed for use in resource-constrained, embedded systems and currently in use on the International Space Station, enables reliable communication over networks in which timely data acknowledgments might not be possible due to transient link outages. (2) Policy-Based Management (PBM) provides dynamic management capabilities, allowing vital data to be exchanged selectively (with priority) by utilizing alternative communication resources. The resulting network may help railroads implement PTC faster, cheaper, and more reliably.
The collaborative science obtained from the satellites in the A-Train is an unparalleled success. The constellation framework that has evolved is well-formulated and documented by its international members. Communication between teams is enhanced by a web-based Constellation Coordination System. Safety and correlated observations are ensured by defining independent control boxes with buffers in between. Each mission stays within its control box by regular drag makeup maneuvers. Annual inclination adjustments are coordinated by all missions to maintain their absolute and relative Mean Local Time of Ascending Node (MLTAN). Since the satellites are in different orbit planes their separation involves a three-dimensional triad made up of the along track separations, reference groundtracks and MLTAN's. For further safety, a Constellation Envelope has been defined to determine safe entry and exit orbits.
We have developed a technique for combining CALIOP aerosol backscatter, MODIS spectral AOD (aerosol optical depth), and OMI AAOD (absorption aerosol optical depth) retrievals for the purpose of estimating full spectral sets of aerosol radiative properties, and ultimately for calculating the 3-D distribution of direct aerosol radiative forcing. We present results using one year of data collected in 2007 and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the recently released MODIS Collection 6 data for aerosol optical depths derived with the dark target and deep blue algorithms has extended the coverage of the multi-sensor estimates towards higher latitudes. We compare the spatio-temporal distribution of our multi-sensor aerosol retrievals and calculations of seasonal clear-sky aerosol radiative forcing based on the aerosol retrievals to values derived from four models that participated in the latest AeroCom model intercomparison initiative. We find significant inter-model differences, in particular for the aerosol single scattering albedo, which can be evaluated using the multi-sensor A-Train retrievals. We discuss the major challenges that exist in extending our clear-sky results to all-sky conditions. On the basis of comparisons to suborbital measurements, we present some of the limitations of the MODIS and CALIOP retrievals in the presence of adjacent or underlying clouds. Strategies for meeting these challenges are discussed.
In the recent years, New Delhi, the capital city of India, has ranked among the most polluted cities in the world regarding its air quality related to the submicron Particulate Matter (PM(sub 2.5)). Using NASA's A-train satellite data (MODIS, OMI, and CALIOP), ground-level PM2.5 measured in New Delhi (2013-2016), and back-trajectory calculations, we show that the PM(sub 2.5). over New Delhi is strongly affected by the agricultural fires in the northwestern Indian states of Punjab and Haryana during the post-monsoon season (October and November). The mass concentration of PM2.5 escalates from ~50 μg m(exp -3) measured prior to the onset of residue burning in early October to as high as 300 μg m(exp -3) (24-hour averaged, 7- day running mean) during the peak burning period in early November. A linear regression analysis reveals that the variations in PM(sub 2.5) over New Delhi can be attributed to the concurrent changes in the satellite retrievals of fire counts and aerosols over the crop burning area. The back-trajectory analysis shows that most clusters (> 80%) of the northwesterly flow near the ground intercepted the crop burning region before arriving at the receptor location in New Delhi; this further corroborates the transport patterns inferred from the satellite data. A 15-year long satellite record (2002-2016) reveals an increasing trend in agricultural fires (~617 per year) and aerosol loading (0.031 and 0.04 per year in aerosol optical depth and UV aerosol index) in November. Increasing levels of crop residue burning and resulting particulate matter pollution at an alarming rate over northern India is a pressing concern demanding corrective measures to substantially reduce or completely diminish the crop burning through an effective residue management system.
This is the ATD-2 training presentation for ZDC. The original presentation was completed September 2017.The metering modes are described above. These will be updated depending on Modeset by the Ramp Manager, STBO Client will also display the Metering Mode Icon onthe right hand corner of the Toolbar.
This document is a compilation of the New Releases/New Features training materials accompanying various software releases during ATD-2 Phase 1.
During terrestrial activities, sensation of pressure on the skin and tension in muscles and joints provides information about how the body is oriented relative to gravity and how the body is moving relative to the surrounding environment. In contrast, in aquatic environments when suspended in a state of neutral buoyancy, the weight of the body and limbs is offloaded, rendering these cues uninformative. It is not yet known how this altered sensory environment impacts virtual reality experiences. To investigate this question, we converted a full-face SCUBA mask into an underwater head-mounted display and developed software to simulate jetpack locomotion outside the International Space Station. Our goal was to emulate conditions experienced by astronauts during training at NASA's Neutral Buoyancy Lab. A user study was conducted to evaluate both sickness and presence when using virtual reality in this altered sensory environment. We observed an increase in nausea related symptoms underwater, but we cannot conclude that this is due to VR use. Other measures of sickness and presence underwater were comparable to measures taken above water. We conclude with suggestions for improved underwater VR systems and improved methods for evaluation of these systems based on our experience.
Automating the task of training development always sounded like a great idea, and recently, a system was developed that actually does just that.
This video highlights the Virtual Reality Laboratory. It shows off the different systems the lab supports for crew training including Charlotte Mass Handling, Robotics and hardware checkout and SAFER. It focuses on the SAFER (Simplified Aid for EVA Rescue) system and shows briefly how to perform a SAFER rescue in Virtual Reality.
This paper reports our investigation of flight path monitoring in aviation. We interviewed experienced pilots to understand the knowledge and skills underlying effective monitoring and we developed an example learning environment to improve these skills. We explore how design of pilot training and learning, like the design of interfaces and of the underlying automation, benefits from cognitive engineering methods and perspective. In aviation, monitoring and managing flight path are critical activities. The influences on flight path are complex and come from the autoflight system, from control actions by the pilot, and from external factors, including weather and Air Traffic Control (ATC). Indeed, inadequate flight path monitoring is a current aviation concern as it has been implicated in accidents and incidents. Effective piloting depends on strategies for noticing, understanding, and anticipating these influences to monitor and manage flight path. Lack of such skills reduces pilots' ability to maintain safety margin and resilience. Although flightdeck automation is intended to aid pilot understanding and prediction, the Fight Management Systems (FMS) can mislead as well as aid the pilot's understanding and projection of what will happen. In dynamic conditions, FMS predictions may be based on old or incomplete information. Understanding such vulnerabilities is an important part of pilot-autoflight coordination. The learning environment we developed is designed to help pilots proactively monitor and manage flight path. We consider how a broad cognitive engineering approach might inform the "what" and "how" of learning in dynamic work domains.
Motion sickness is a common physiological reaction to provocative motion and is characterized by a constellation of symptoms, including stomach awareness, nausea, emesis, pallor, sweating, hypersalivation, and fatigue. The emergence of these symptoms can pose a significant threat to safety, particularly in the context of aviation. Given its prevalence among aviators and its detrimental impact on performance, researchers have endeavored to identify effective countermeasures for motion sickness. Currently, many of the existing interventions are pharmacological in nature and while effective, they present a problem due to their associated adverse side effects. A modified two-hour version of Autogenic Feedback Training Exercise (AFTE) could be an effective countermeasure to motion sickness without adverse side effects. AFTE combines principles of autogenic therapy, biofeedback, and learning to teach individuals to control their own internal physiological reactions through a series of relaxation and arousal exercises. AFTE was administered over six days. On the first day, participants were exposed to provocative motion via a rotating chair test to collect baseline physiological data. AFTE sessions were conducted on four consecutive days and lasted approximately 30 minutes each session. Participants were exposed to the rotating chair again on the 6th day. Results: Participants (n = 16) were evaluated on the number of rotations experienced and cumulative minutes spun in the chair. Participants tended to ride longer (M = 21.0 min, SD = 16.56) and tolerated more rotations (M = 244.8 rotations, SD = 310.62) on their second rotating chair test compared to baseline (M = 14.0 min, SD = 9.35; M = 125.8 rotations, SD = 124.08; t(15) = 2.21, p = .02). A moderate effect size was recorded (Hedges’s g = 0.44). A modified two-hour version of the AFTE is effective at increasing tolerance of symptoms associated with motion sickness.
INTRODUCTION: The development of Motion Sickness (MS) symptoms is correlated with increased sympathetic influence and irregular patterns of vagal activity. Such autonomic actions can be characterized by indices of heart rate variability (HRV), which reflect autonomic balance through neurocardiac function. Nonpharmacological interventions aimed at attenuating MS symptoms may therefore produce an effect on HRV. One such intervention that has been shown to mitigate MS symptoms is Autogenic Feedback Training Exercise (AFTE), which combines principles of autogenic therapy and biofeedback. AFTE teaches individuals to manipulate various physiological parameters in provocative environments and shows promise as a potential MS intervention in military aviators. The effects of AFTE on HRV have not previously been examined. Understanding HRV changes following AFTE may help to elucidate its indirect effects and inform its implementation for MS mitigation. METHODS: Twenty-four subjects received 2 hours of AFTE over 4 days. Pre- and post-AFTE rotating chair tests, which included stationary periods of baseline data, were conducted to evaluate the effects of AFTE. HRV data were recorded by SOMNOtouch™ NIBP. Post hoc analysis of pre- and post-AFTE short-term HRV (RMSSD, LF, HF, LF/HF) was performed. RESULTS: RMSSD, HF, and LF/HF were not significantly changed following AFTE. However, LF showed a statistically significant (p=0.015) decrease following AFTE. DISCUSSION: AFTE prescribes a respiratory rate of 15 breaths per minute (BPM), which is typically faster than participants’ pre-AFTE BPM (M=12.65). Healthy individuals can increase respiratory sinus arrhythmia (RSA) by slow, deep breathing. However, increasing the respiratory rate to 15 BPM may decrease RSA and subsequently HF. Increasing RSA potentially negates any influence of AFTE on HF, resulting in no significant change. RMSSD is correlated with HF power and was likewise not affected by AFTE. LF power, however, decreased significantly following AFTE, potentially indicating a lower sympathetic response in the post-AFTE measurement.
Missions to Mars will differ from all previous human spaceflight missions in that the crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays, making the decision on crew size critical to mission success. To support National Aeronautics and Space Administration (NASA) decision makers, NASA’s Engineering and Safety Center (NESC) developed a quantitative methodology for assessing the number of crew necessary to meet primary mission objectives and respond to unforeseen failures based on modeling of NASA’s crew training qualifications. We present results of a custom-built model of a Mars crew qualification and responsibility matrix (CQRM) and discuss the implications on trade space analysis of Mars mission crew size.
Missions to Mars will differ from all previous human spaceflight missions in that the crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays, making the decision on crew size critical to mission success. To support National Aeronautics and Space Administration (NASA) decision makers, NASA’s Engineering and Safety Center (NESC) developed a quantitative methodology for assessing the number of crew necessary to meet primary mission objectives and respond to unforeseen failures based on modeling of NASA’s crew training qualifications. We present results of a custom-built model of a Mars crew qualification and responsibility matrix (CQRM) and discuss the implications on trade space analysis of Mars mission crew size.
Since the Fukushima reactor accident in 2011, there has been an increased interest worldwide in developing national capabilities to rapidly map and assess ground contamination resulting from nuclear reactor accidents. The capability to rapidly measure the size of the contaminated area, determine the activity level, and identify the radionuclides can aid emergency managers and decision makers in providing timely protective action recommendations to the public and first responders. The development of an aerial detection capability requires interagency coordination to assemble the radiation experts, detection system operators, and aviation aircrews to conduct the aerial measurements, analyze and interpret the data, and provide technical assessments. The Office of International Emergency Management and Cooperation (IEMC) at the U.S. Department of Energy, National Nuclear Security Administration (DOE/NNSA) sponsors an International - Aerial Measuring System (I-AMS) training program for partner nations to develop and enhance their response to radiological emergencies. An initial series of courses can be conducted in the host country to assist in developing an aerial detection capability. As the capability develops and expands, additional experience can be gained through advanced courses with the opportunity to conduct aerial missions over a broad range of radiation environments.