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NASA NTRS2013

Gear Design Effects on the Performance of High Speed Helical Gear Trains as Used in Aerospace Drive Systems

The performance of high-speed helical gear trains is of particular importance for tiltrotor aircraft drive systems. These drive systems are used to provide speed reduction/torque multiplication from the gas turbine output shaft and provide the necessary offset between these parallel shafts in the aircraft. Four different design configurations have been tested in the NASA Glenn Research Center, High Speed Helical Gear Train Test Facility. The design configurations included the current aircraft design, current design with isotropic superfinished gear surfaces, double helical design (inward and outward pumping), increased pitch (finer teeth), and an increased helix angle. All designs were tested at multiple input shaft speeds (up to 15,000 rpm) and applied power (up to 5,000 hp). Also two lubrication, system-related, variables were tested: oil inlet temperature (160 to 250 F) and lubricating jet pressure (60 to 80 psig). Experimental data recorded from these tests included power loss of the helical system under study, the temperature increase of the lubricant from inlet to outlet of the drive system and fling off temperatures (radially and axially). Also, all gear systems were tested with and without shrouds around the gears. The empirical data resulting from this study will be useful to the design of future helical gear train systems anticipated for next generation rotorcraft drive systems.

Handschuh, R.↗
NASA NTRS2013

Gear Design Effects on the Performance of High Speed Helical Gear Trains as Used in Aerospace Drive Systems

The performance of high-speed helical gear trains is of particular importance for tiltrotor aircraft drive systems. These drive systems are used to provide speed reduction / torque multiplication from the gas turbine output shaft and provide the necessary offset between these parallel shafts in the aircraft. Four different design configurations have been tested in the NASA Glenn Research Center, High Speed Helical Gear Train Test Facility. The design configurations included the current aircraft design, current design with isotropic superfinished gear surfaces, double helical design (inward and outward pumping), increased pitch (finer teeth), and an increased helix angle. All designs were tested at multiple input shaft speeds (up to 15,000 rpm) and applied power (up to 5,000 hp). Also two lubrication, system-related, variables were tested: oil inlet temperature (160 to 250 degF) and lubricating jet pressure (60 to 80 psig). Experimental data recorded from these tests included power loss of the helical system under study, the temperature increase of the lubricant from inlet to outlet of the drive system and fling off temperatures (radially and axially). Also, all gear systems were tested with and without shrouds around the gears. The empirical data resulting from this study will be useful to the design of future helical gear train systems anticipated for next generation rotorcraft drive systems.

Handschuh, R.↗
NASA NTRS2014

Portable Simulator for On-Board International Space Station Emergency Training

The crew on-board the International Space Station (ISS) have to be prepared for any possible emergency. The emergencies of most concern are a fire, depressurization or a toxic atmosphere. The crew members train on the ground before launch but also need to practice their emergency response skills while they are on orbit for 6 months. On-Board Training (OBT) events for emergency response proficiency used to require the crew and ground teams to use paper "scripts" that showed the path through the emergency procedures. This was not very realistic since the participants could read ahead and never deviate from this scripted path. The new OBT emergency simulator allows the crew to view dynamic information on an iPad only when it would become available during an event. The simulator interface allows the crew member to indicate hatch closures, don and doff masks, read pressures, and sample smoke or atmosphere levels. As the crew executes their actions using the on-board simulator, the ground teams are able to monitor those actions via ground display data flowing through the ISS Ku Band communication system which syncs the on-board simulator software with a ground simulator which is accessible in all the control centers. The OBT Working Group (OBT WG), led by the Chief Training Office (CTO) at Johnson Space center is a Multilateral working group with partners in Russia, Japan, Germany and U.S.A. The OBTWG worked together to create a simulator based on these principles: (a) Create a dynamic simulation that gives real-time data feedback; (b) Maintain real-time interface between Mission Control Centers and crew during OBTs; (c) Provide flexibility for decision making during drill execution; (d) Materially reduce Instructor and Flight Control Team man-hour costs involved with developing, updating, and maintaining emergency OBT cases/scenarios; and (e) Introduce an element of surprise to emergency scenarios so the team can't tell the outcome of the case by reading ahead in a paper script. This paper details some of the background as the project evolved with the International Partners. It also provides more details on how the simulator information for the crew is also shared with the ground teams. Finally, the paper will discuss how this remote simulator concept can be useful for future, longer term space missions.

Bolt, Kathy↗
NASA NTRS2013

Adaptive Distributed Environment for Procedure Training (ADEPT)

ADEPT (Adaptive Distributed Environment for Procedure Training) is designed to provide more effective, flexible, and portable training for NASA systems controllers. When creating a training scenario, an exercise author can specify a representative rationale structure using the graphical user interface, annotating the results with instructional texts where needed. The author's structure may distinguish between essential and optional parts of the rationale, and may also include "red herrings" - hypotheses that are essential to consider, until evidence and reasoning allow them to be ruled out. The system is built from pre-existing components, including Stottler Henke's SimVentive instructional simulation authoring tool and runtime. To that, a capability was added to author and exploit explicit control decision rationale representations. ADEPT uses SimVentive's Scalable Vector Graphics (SVG)- based interactive graphic display capability as the basis of the tool for quickly noting aspects of decision rationale in graph form. The ADEPT prototype is built in Java, and will run on any computer using Windows, MacOS, or Linux. No special peripheral equipment is required. The software enables a style of student/ tutor interaction focused on the reasoning behind systems control behavior that better mimics proven Socratic human tutoring behaviors for highly cognitive skills. It supports fast, easy, and convenient authoring of such tutoring behaviors, allowing specification of detailed scenario-specific, but content-sensitive, high-quality tutor hints and feedback. The system places relatively light data-entry demands on the student to enable its rationale-centered discussions, and provides a support mechanism for fostering coherence in the student/ tutor dialog by including focusing, sequencing, and utterance tuning mechanisms intended to better fit tutor hints and feedback into the ongoing context.

Domeshek, Eric↗
NASA NTRS2012

Quasi-periodic Fast-mode Wave Trains Within a Global EUV Wave and Sequential Transverse Oscillations Detected by SDO-AIA

We present the first unambiguous detection of quasi-periodic wave trains within the broad pulse of a global EUV wave (so-called EIT wave) occurring on the limb. These wave trains, running ahead of the lateral coronal mass ejection (CME) front of 2-4 times slower, coherently travel to distances greater than approximately solar radius/2 along the solar surface, with initial velocities up to 1400 kilometers per second decelerating to approximately 650 kilometers per second. The rapid expansion of the CME initiated at an elevated height of 110 Mm produces a strong downward and lateral compression, which may play an important role in driving the primary EUV wave and shaping its front forwardly inclined toward the solar surface. The wave trains have a dominant 2 minute periodicity that matches the X-ray flare pulsations, suggesting a causal connection. The arrival of the leading EUV wave front at increasing distances produces an uninterrupted chain sequence of deflections and/or transverse (likely fast kink mode) oscillations of local structures, including a flux-rope coronal cavity and its embedded filament with delayed onsets consistent with the wave travel time at an elevated (by approximately 50%) velocity within it. This suggests that the EUV wave penetrates through a topological separatrix surface into the cavity, unexpected from CME-caused magnetic reconfiguration. These observations, when taken together, provide compelling evidence of the fast-mode MHD wave nature of the primary (outer) fast component of a global EUV wave, running ahead of the secondary (inner) slow component of CME-caused restructuring.

Solar Corona↗
NASA NTRS2014

Virtual Reality as a Medium for Sensorimotor Adaptation Training and Spaceflight Countermeasures

Astronauts experience a profound sensorimotor adaptation during transition to and from the microgravity environment of space. With the upcoming shift to extra‐long duration missions (upwards of 1 year) aboard the International Space Station, the immediate risks to astronauts during these transitory periods become more important than ever to understand and prepare for. Recent advances in virtual reality technology enable everyday adoption of these tools for entertainment and use in training. Embedding an individual in a virtual environment (VE) allows the ability to change the perception of visual flow, elicit automatic motor behavior and produce sensorimotor adaptation, not unlike those required during long duration microgravity exposure. The overall goal of this study is to determine the feasibility of present head mounted display technology (HMD) to produce reliable visual flow information and the expected adaptation associated with virtual environment manipulation to be used in future sensorimotor adaptability countermeasures. To further understand the influence of visual flow on gait adaptation during treadmill walking, a series of discordant visual flow manipulations in a virtual environment are proposed. Six healthy participants (3 male and 3 female) will observe visual flow information via HMD (Oculus Rift DK2) while walking on an instrumented treadmill at their preferred walking speed. Participants will be immersed in a series of VE's resembling infinite hallways with different visual characteristics: an office hallway, a hallway with pillars and the hallway of a fictional spacecraft. Participants will perform three trials of 10 min. each, which include walking on the treadmill while receiving congruent or incongruent visual information via the HMD. In the first trial, participants will experience congruent visual information (baseline) where the hallway is perceived to move at the same rate as their walking speed. The final two trials will be randomized among participants where the hallway is perceived to move at either half (0.5x) or twice (2.0x) their preferred walking speed. Participants will remain on the treadmill between trials and will not be warned of the upcoming change to visual flow to minimize preparatory adjustments. Stride length, step frequency and dual‐support time will be quantified during each trial. We hypothesize that participants will experience a rapid modification in gait performance during periods of adaptive change, expressed as a decrease in step length, an increase in step frequency and an increase in dual‐support time, followed by a period of adaptation where these movement parameters will return to near‐baseline levels. As stride length, step frequency and dual support times return to baseline values, an adaptation time constant will be derived to establish individual time‐to‐adapt (TTA). HMD technology represents a paradigm shift in sensorimotor adaptation training where gait adaptability can be stressed using off‐the‐shelf consumer products and minimal experimental equipment, allowing for greater training flexibility in astronaut and terrestrial applications alike.

Madansingh, S.↗
NASA NTRS2016

Self-Guided Multimedia Stress Management and Resilience Training for Flight Controllers

Stress and anxiety-related problems are among the most common and costly behavioral health problems in society, and for those working in operational environments (i.e. astronauts, flight controllers, military) this can seriously impact crew performance, safety, and wellbeing. Technology-based interventions are effective for treating behavioral health problems, and can significantly improve the delivery of evidence-based health care. This study is evaluating the effectiveness, usefulness, and usability of a self-guided multimedia stress management and resilience training program in a randomized controlled trial (RCT) with a sample of flight controllers at Johnson Space Center. The intervention, SMART-OP (Stress Management and Resilience Training for Optimal Performance), is a six-session, cognitive behavioral-based computer program that uses self-guided, interactive activities to teach skills that can help individuals build resilience and manage stress. In a prior RCT with a sample of stressed but otherwise healthy individuals, SMART-OP reduced perceived stress and increased perceived control over stress in comparison to an Attention Control (AC) group. SMART-OP was rated as "highly useful" and "excellent" in usability and acceptability. Based on α-amylase data, individuals in SMART-OP recovered quicker and more completely from a social stress test as compared to the AC group [1]. In the current study, flight controllers are randomized either to receive SMART-OP training, or to a 6-week waitlist control period (WLC) before beginning SMART-OP. Eligible participants include JSC flight controllers and instructors without any medical or psychiatric disorder, but who are stressed based on self-report. Flight controllers provide a valid analog sample to astronauts in that they work in an operational setting, use similar terminology to astronauts, are mission-focused, and work under the same broader work culture. The study began in December 2014, and to date 79 flight controllers and instructors have expressed interest in the study, 49 of those were cleared for participation, we have screened 44 for eligibility, and 23 have met inclusion criteria. Recruitment is ongoing and the study will continue until December 2016. Outcome measures include perceived stress, perceived control over stress, resilience, mood, personality, emotion regulation, sleep, health behaviors, and psychophysiological data such as 24-hour heart rate, alpha amylase, and urinary and salivary cortisol. We are also collecting user feedback such as usability, working alliance, usefulness, and treatment credibility.

Rose, R. D.↗
NASA NTRS2016

Mission X: Train Like an Astronaut Challenge

The Mission X: Train Like an Astronaut Challenge was developed in 2011 to encourage proper exercise and nutrition at an early age by teaching young people to live and eat like space explorers. The strong correlation between an unhealthy childhood diet and adolescent fitness, and the onset of chronic diseases as an adult is the catalyst for Mission X. Mission X is dedicated to assisting people on a global scale to live healthier lifestyles and learn about human space exploration. The Mission X: Train Like an Astronaut 2015 (MX15) International Challenge hosted almost 40,000 children on 800 teams, 28 countries affiliated with 12 space agencies. The MX15 website included 17 languages. MX15, the fifth annual international fitness challenges sponsored by the NASA Human Research Program worked with the European Space Agency and other space agencies from around the world. In comparison to MX14, MX15 expanded to include four additional new countries, increased the number of students by approximately 68% and the number of teams by 29%. Chile' and South Korea participated in the new fall Astro Charlie Walk Around the Earth Challenge. Pre-challenge training materials were made more readily available from the website. South Korea completed a prospective assessment of the usability of the MX content for improving health and fitness in 212 preschool children and their families. Mission X is fortunate to have the support of the NASA, ESA and JAXA astronaut corps. In MX15, they participated in the opening and closing events as well as while on-board the International Space Station. Italian Astronaut Samantha Cristoretti participated as the MX15 Astronaut Ambassador for health and fitness providing the opening video and other videos from ISS. United Kingdom Astronaut Tim Peake and US Astronaut Kate Rubins have agreed to be the MX Ambassadors for 2016 and 2017 respectively. The MX15 International Working Group Face-to-Face meeting and Closing Event were held at the Agenzia Spaziale Italiana (ASI) in Rome, Italy. A record number of twenty-eight countries participated. Austria and Norway have offered to host the 2016 and 2017 working group meetings. MX16 planning began with the working group meetings and areas of improvement will include another second early challenge to accommodate countries in the Southern Hemisphere, recommended changes to the MX website, development of a more defined approach to metrics, a change to the format of future MX International Working Group meetings, and proposed new activities to be developed by the MX International Educator Working Group. We look forward to welcoming many new participants in 2016!

Lloyd, Charles W.↗
NASA NTRS2016

Analysis of Potential Glove-Induced Hand Injury Metrics During Typical Neutral Buoyancy Training Operations

Injuries to the hands are common among astronauts who train for extravehicular activity. When the gloves are pressurized, they restrict movement and create pressure points during tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally more severe injuries such as onycholysis. A brief review of NASA's Lifetime Surveillance of Astronaut Health's injury database reveals that 76 percent of astronaut hand and arm injuries from training between 1993 and 2010 occurred either to the fingernail, finger crotch, metacarpophalangeal joint, or fingertip. The purpose of this study was to assess the potential of using small sensors to measure forces acting on the fingers and hand within pressurized gloves and other variables such as skin temperature, humidity, and fingernail strain of a NASA crewmember during typical NBL (Neutral Buoyancy Laboratory) training activity. During the 5-hour exercise, the crewmember seemed to exhibit very large forces on some fingers, resulting in higher strain than seen in previous glove-box testing. In addition, vital information was collected on the glove cavity environment with respect to temperature and humidity. All of this information gathered during testing will be carried forward into future testing, potentially in glove-box- or 1G- (1 gravitational force) or NBL-suited environments, to better characterize and understand the possible causes of hand injury amongst NASA crew.

McFarland, Shane↗
NASA NTRS2016

Top-of-the-Atmosphere Shortwave Flux Estimation from Satellite Observations: An Empirical Neural Network Approach Applied with Data from the A-Train Constellation

Estimates of top-of-the-atmosphere (TOA) radiative flux are essential for the understanding of Earth's energy budget and climate system. Clouds, aerosols, water vapor, and ozone (O3) are among the most important atmospheric agents impacting the Earth's shortwave (SW) radiation budget. There are several sensors in orbit that provide independent information related to these parameters. Having coincident information from these sensors is important for understanding their potential contributions. The A-train constellation of satellites provides a unique opportunity to analyze data from several of these sensors. In this paper, retrievals of cloud/aerosol parameters and total column ozone (TCO) from the Aura Ozone Monitoring Instrument (OMI) have been collocated with the Aqua Clouds and Earth's Radiant Energy System (CERES) estimates of total reflected TOA outgoing SW flux (SWF). We use these data to develop a variety of neural networks that estimate TOA SWF globally over ocean and land using only OMI data and other ancillary information as inputs and CERES TOA SWF as the output for training purposes. OMI-estimated TOA SWF from the trained neural networks reproduces independent CERES data with high fidelity. The global mean daily TOA SWF calculated from OMI is consistently within 1% of CERES throughout the year 2007. Application of our neural network method to other sensors that provide similar retrieved parameters, both past and future, can produce similar estimates TOA SWF. For example, the well-calibrated Total Ozone Mapping Spectrometer (TOMS) series could provide estimates of TOA SWF dating back to late 1978.

CERES data with high fidelity↗
NASA NTRS2017

Crew State Monitoring and Line-Oriented Flight Training for Attention Management

Loss of control - inflight (LOC-I) has historically represented the largest category of commercial aviation fatal accidents. A review of worldwide transport airplane accidents (2001-2010) indicated that loss of airplane state awareness (ASA) was responsible for the majority of the LOC-I fatality rate. The Commercial Aviation Safety Team (CAST) ASA study identified 12 major themes that were indicated across the ASA accident and incident events. One of the themes was crew distraction or ineffective attention management, which was found to be involved in all 18 events including flight crew channelized attention, startle/surprise, diverted attention, and/or confirmation bias. Safety Enhancement (SE)-211, "Training for Attention Management" was formed to conduct research to develop and assess commercial airline training methods and realistic scenarios that can address these attention-related human performance limitations. This paper describes NASA SE-211 research for new design approaches and validation of line-oriented flight training (LOFT). Recent accident and incident data suggests that Spatial Disorientation (SD) and Loss-of-Energy State Awareness (LESA) for transport category aircraft are becoming an increasingly prevalent safety concern in all domestic and international operations (Commercial Aviation Safety Team, 2014a). SD is defined as an erroneous perception of aircraft attitude that can lead directly to a Loss-of-Control Inflight (LOC-I) event and result in an accident or incident. LESA is typically characterized by a failure to monitor or understand energy state indications (e.g., airspeed, altitude, vertical speed, commanded thrust) and a resultant failure to maintain safe flight.

Stephens, Chad↗
NASA NTRS2016

An A-Train Climatology of Extratropical Cyclone Clouds

Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the clouds they generate. However, general circulation models (GCMs) have trouble representing precipitation and clouds in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, CloudSat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of clouds and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of clouds and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of cloud and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, CloudSat and CALIPSO have for the first time provided information on the vertical distribution of clouds in ETCs and across warm and cold fronts. We will also discuss how these observations have helped identify key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and cloud cover in ETCs using MODIS, CloudSat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to cloud cover.

clouds↗
NASA NTRS2018

ATC Tower and TRACON Training

This training material was created to train ATCT and TRACON controllers on the ATD-2 system. It includes an overview of the ATD-2 STBO Client. It discusses data exchange and integration, APREQ procedures, the web-basd DASH and the What-If system. It concludes with interactive exercises on all topics of the training course.

Stevens, Lindsay K.↗
NASA NTRS2019

System and Method for Training of State-Classifiers

Method and systems are disclosed for training state-classifiers for classification of cognitive state. A set of multimodal signals indicating physiological responses of an operator are sampled over a time period. A depiction of operation by the operator during the time period is displayed. In response to user input selecting a cognitive state for a portion of the time period, the one or more state-classifiers are trained. In training the state-classifiers, the set of multimodal signals sampled in the portion of the time period are used as input to the one or more state-classifiers and the selected one of the set of cognitive states is used as a target result to be indicated by the one or more state-classifiers.

Stephens, Chad L.↗
NASA NTRS2019

The Rise of Micro-Training Related to User Applications of New Satellite Products

A growing trend in the e-learning community is related to 'micro-training' or micro-lessons. This training concept has been a part of the formats used by NASA's Short-term Prediction, Research, and Transition (SPoRT) Program for many years in order to meet the training needs of operational users for satellite applications.

Satellite↗
NASA NTRS2020

NeMO-Net – The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗
NASA NTRS2018

Augmented Reality Data Generation for Training Deep Learning Neural Network

One of the major challenges in deep learning is retrieving sufficiently large labeled training datasets, which can become expensive and time consuming to collect. A unique approach to training segmentation is to use Deep Neural Network (DNN) models with a minimal amount of initial labeled training samples. The procedure involves creating synthetic data and using image registration to calculate affine transformations to apply to the synthetic data. The method takes a small dataset and generates a highquality augmented reality synthetic dataset with strong variance while maintaining consistency with real cases. Results illustrate segmentation improvements in various target features and increased average target confidence.

Torres, Gil↗
NASA NTRS2022

FY22 X-Hab: Rochester Institute of Technology: Gamification and Performance-Based Monitoring of Sensorimotor Training Activities

Proprioception is the body’s ability to sense movement, action, and location. Proprioceptive training is crucial for astronauts because humans balance system, cognitive functions, and muscle tone heavily rely on Earth’s gravity. The goal of this project is to create a training system that strengthens those characteristics to ensure astronauts not only maintain their coordination and cognitive skills, but improve upon them as well. Furthermore, the system’s live biofeedback provides astronauts with sensorimotor feedback to correct any balance dysfunction. The completed system prototype and data collected from it will support NASA’s knowledge base about the use of gamification for sensorimotor training activities.

Griffin Brown↗