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Data pertaining to nonmotion factors affecting ride quality of transport aircraft were obtained as part of NASA in-house and sponsored research studies carried out onboard commuter-airline and research aircraft. From these data, quantitative effects on passenger discomfort of seat width, seat legroom, change in cabin pressure, and cabin noise are presented. Visual cue effects are also discussed.
Many factors other than retinal image defocus have been found to influence the visual accommodation response. Experimental results reported herein demonstrate the effect on accommodation of four factors that previously have been only tangentially discussed in other research or have not been stated specifically to exist.
Helicopter flight is among the most demanding of all human-machine integrations. The inherent manual control complexities of rotorcraft are made even more challenging by the small margin for error created in certain operations, such as nap-of-the-Earth (NOE) flight, by the proximity of the terrain. Accident data recount numerous examples of unintended conflict between helicopters and terrain and attest to the perceptual and control difficulties associated with low altitude flight tasks. Ames Research Center, in cooperation with the U.S. Army Aeroflightdynamics Directorate, has initiated an ambitious research program aimed at increasing safety margins for both civilian and military rotorcraft operations. The program is broad, fundamental, and focused on the development of scientific understandings and technological countermeasures. Research being conducted in several areas is reviewed: workload assessment, prediction, and measure validation; development of advanced displays and effective pilot/automation interfaces; identification of visual cues necessary for low-level, low-visibility flight and modeling of visual flight-path control; and pilot training.
This study is a continuation of an FAA effort to alleviate the growing problems of assimilating and managing the flow of data and flight related information in the air transport flight deck. The nature and extent of known pilot interface problems arising from new NAS data management programs were determined by a comparative timeline analysis of crew tasking requirements. A baseline of crew tasking requirements was established for conventional and advanced flight decks operating in the current NAS environment and then compared to the requirements for operation in a future NAS environment emphasizing Mode-S data link and TCAS. Results showed that a CDU-based pilot interface for Mode-S data link substantially increased crew visual activity as compared to the baseline. It was concluded that alternative means of crew interface should be available during high visual workload phases of flight. Results for TCAS implementation showed substantial visual and motor tasking increases, and that there was little available time between crew tasks during a TCAS encounter. It was concluded that additional research should be undertaken to address issues of ATC coordination and the relative benefit of high workload TCAS features.
The paper describes a high performance HUD guidance system installed on the experimental powered-lift STOL aircraft Aska. Since the maiden flight in October 1985, the HUD system has been used in all the flight tests. The HUD has an accurate flight path symbol generated by inertial velocity from the IRS which is updated by up-linked precision radar position data. The flight path symbol is very useful for precise approach and flare control for Aska which has large ground effects. A synthetic runway is also presented, which is conformal with the real runway, using the position data from the ground tracking radar system. Under instrument meteorological conditions, the pilot can approach and land using the HUD synthetic runway as well as in visual meteorological conditions. The HUD system proved to be a valuable aid to the pilot for all the Aska flight tests. A NASA Ames Research Center test pilot demonstrated touch down accuracy of less than 8 meters (peak to peak) for a series of three landings.
The research results described here are intended to enhance the effectiveness of the DATALINK interface that is scheduled by the Federal Aviation Administration (FAA) to be deployed during the 1990's to improve the safety of various aspects of aviation. While voice has a natural appeal as the preferred means of communication both among humans themselves and between humans and machines as the form of communication that people find most convenient, the complexity and flexibility of natural language are problematic, because of the confusions and misunderstandings that can arise as a result of ambiguity, unclear reference, intonation peculiarities, implicit inference, and presupposition. The DATALINK interface will avoid many of these problems by replacing voice with vision and speech with written instructions. This report describes results achieved to date on an on-going research effort to refine the protocol of the DATALINK system so as to avoid many of the linguistic problems that still remain in the visual mode. In particular, a working prototype DATALINK simulator system has been developed consisting of an unambiguous, context-free grammar and parser, based on the current air-traffic-control language and incorporated into a visual display involving simulated touch-screen buttons and three levels of menu screens. The system is written in the C programming language and runs on the Macintosh II computer. After reviewing work already done on the project, new tasks for further development are described.
The breadth of subject material in this 1994 edition of the Research and Technology Report illustrates the broad scope of activities at the Goddard Space Flight Center. The numerous entries dealing with data processing and visualization show the strong emphasis on data and its interpretation. Reports are presented in the following sections: data processing and visualization; space sciences - high energy astronomy, solar system, and new techniques; earth system science - atmospheres, oceans and ice, solid earth, and soils and vegetation; networks, planning, and information systems - mission scheduling and operations, spacecraft operation and status, software engineering, and infrastructure support; engineering and materials - spacecraft subsystems, launch vehicles, thermal control, new mechanisms, and testing and evaluation; and flight projects.
A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.
Topics include: Computational Ghost Imaging for Remote Sensing; Digital Architecture for a Trace Gas Sensor Platform; Dispersed Fringe Sensing Analysis - DFSA; Indium Tin Oxide Resistor-Based Nitric Oxide Microsensors; Gas Composition Sensing Using Carbon Nanotube Arrays; Sensor for Boundary Shear Stress in Fluid Flow; Model-Based Method for Sensor Validation; Qualification of Engineering Camera for Long-Duration Deep Space Missions; Remotely Powered Reconfigurable Receiver for Extreme Environment Sensing Platforms; Bump Bonding Using Metal-Coated Carbon Nanotubes; In Situ Mosaic Brightness Correction; Simplex GPS and InSAR Inversion Software; Virtual Machine Language 2.1; Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction; Pandora Operation and Analysis Software; Fabrication of a Cryogenic Bias Filter for Ultrasensitive Focal Plane; Processing of Nanosensors Using a Sacrificial Template Approach; High-Temperature Shape Memory Polymers; Modular Flooring System; Non-Toxic, Low-Freezing, Drop-In Replacement Heat Transfer Fluids; Materials That Enhance Efficiency and Radiation Resistance of Solar Cells; Low-Cost, Rugged High-Vacuum System; Static Gas-Charging Plug; Floating Oil-Spill Containment Device; Stemless Ball Valve; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Oxygen-Methane Thruster; Lunar Navigation Determination System - LaNDS; Launch Method for Kites in Low-Wind or No-Wind Conditions; Supercritical CO2 Cleaning System for Planetary Protection and Contamination Control Applications; Design and Performance of a Wideband Radio Telescope; Finite Element Models for Electron Beam Freeform Fabrication Process Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System; Vehicle Detection for RCTA/ANS (Autonomous Navigation System); Image Mapping and Visual Attention on the Sensory Ego-Sphere; HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis; and IMAGESEER - IMAGEs for Education and Research.
One of the current challenges in tropical cyclone (TC) research is how to improve our understanding of TC interannual variability and the impact of climate change on TCs. Recent advances in global modeling, visualization, and supercomputing technologies at NASA show potential for such studies. In this article, the authors discuss recent scalability improvement to the multiscale modeling framework (MMF) that makes it feasible to perform long-term TC-resolving simulations. The MMF consists of the finite-volume general circulation model (fvGCM), supplemented by a copy of the Goddard cumulus ensemble model (GCE) at each of the fvGCM grid points, giving 13,104 GCE copies. The original fvGCM implementation has a 1D data decomposition; the revised MMF implementation retains the 1D decomposition for most of the code, but uses a 2D decomposition for the massive copies of GCEs. Because the vast majority of computation time in the MMF is spent computing the GCEs, this approach can achieve excellent speedup without incurring the cost of modifying the entire code. Intelligent process mapping allows differing numbers of processes to be assigned to each domain for load balancing. The revised parallel implementation shows highly promising scalability, obtaining a nearly 80-fold speedup by increasing the number of cores from 30 to 3,335.
A recent study conducted by the Commercial Aviation Safety Team (CAST) determined 40 percent of all fixed-wing fatal accidents, between 2001 and 2011, were caused by Loss-of-Control (LOC) in flight (National Transportation Safety Board, 2015). Based on their findings, CAST recommended manufacturers develop and implement virtual day-visual meteorological conditions (VMC) display systems, such as synthetic vision or equivalent systems (CAST, 2016). In a 2015 simulation study conducted at NASA Langley Research Center (LaRC), researchers gathered to test and evaluate virtual day-VMC displays under realistic flight operation scenarios capable of inducing reduced attention states in pilots. Each display concept was evaluated to determine its efficacy to improve attitude awareness. During the experiment, Evaluation Pilots (EPs) were shown the following three display concepts on the Primary Flight Display (PFD): Baseline, Synthetic Vision (SV) with color gradient, and SV with texture. The baseline configuration was a standard, conventional 'blue over brown' display. Experiment scenarios were simulated over water to evaluate Unusual Attitude (UA) recovery over 'featureless terrain' environments. Thus, the SV with color gradient configuration presented a 'blue over blue' display with a linear blue color progression, to differentiate attitude changes between sky and ocean. The SV with texture configuration presented a 'blue over blue' display with a black checkerboard texture atop a synthetic ocean. These displays were paired with a Background Attitude Indicator (BAI) concept. The BAI was presented across all four Head-Down Displays (HDDs), displaying a wide field-of-view blue-over-blue attitude indicator. The BAI aligned with the PFD and showed through the background of the navigation displays with opaque transparency. Each EP participated in a two-part experiment series with a total seventy-five trial runs: Part I included a set of twenty-five Unusual Attitude Recovery (UAR) scenarios; Part II included a set of fifty Attitude Memory Recall Tasks (AMRT). At the conclusion of each trial, EPs were asked to complete a set post-run questionnaires. Quantitative results showed that there were no significant statistical effects on UA recovery times when utilizing SV with or without the presence of a BAI. Qualitative results show the SV displays (color, texture) with BAI On are most preferred for both UA recognition and recovery when compared with the baseline display. When only comparing SV display concepts, EPs performed better when using the SV with texture, BAI On, than any other display configuration. This is an interesting find considering most EPs noted their preference towards the SV with color gradient when the BAI was on.
During the summer of 2007, as part of the second year of a NASA-funded project in partnership with Christopher Newport University called SPHERE (Students as Professionals Helping Educators Research the Earth), a group of undergraduate students spent 8 weeks in a research internship at or near NASA Langley Research Center. Three students from this group formed the Clouds group along with a NASA mentor (Chambers), and the brief addition of a local high school student fulfilling a mentorship requirement. The Clouds group was given the task of exploring and analyzing ground-based cloud observations obtained by K-12 students as part of the Students' Cloud Observations On-Line (S'COOL) Project, and the corresponding satellite data. This project began in 1997. The primary analysis tools developed for it were in FORTRAN, a computer language none of the students were familiar with. While they persevered through computer challenges and picky syntax, it eventually became obvious that this was not the most fruitful approach for a project aimed at motivating K-12 students to do their own data analysis. Thus, about halfway through the summer the group shifted its focus to more modern data analysis and visualization tools, namely spreadsheets and Google(tm) Earth. The result of their efforts, so far, is two different Excel spreadsheets and a Google(tm) Earth file. The spreadsheets are set up to allow participating classrooms to paste in a particular dataset of interest, using the standard S'COOL format, and easily perform a variety of analyses and comparisons of the ground cloud observation reports and their correspondence with the satellite data. This includes summarizing cloud occurrence and cloud cover statistics, and comparing cloud cover measurements from the two points of view. A visual classification tool is also provided to compare the cloud levels reported from the two viewpoints. This provides a statistical counterpart to the existing S'COOL data visualization tool, which is used for individual ground-to-satellite correspondences. The Google(tm) Earth file contains a set of placemarks and ground overlays to show participating students the area around their school that the satellite is measuring. This approach will be automated and made interactive by the S'COOL database expert and will also be used to help refine the latitude/longitude location of the participating schools. Once complete, these new data analysis tools will be posted on the S'COOL website for use by the project participants in schools around the US and the world.
Initial efforts are underway to enhance the Human Research Program (HRP)'s identification and support of potential cross-disciplinary scientific collaborations. To increase the emphasis on integration in HRP's science portfolio management, concepts are being explored through the development of a set of tools. These tools are intended to enable modeling, analysis, and visualization of the state of the human system in the spaceflight environment; HRP's current understanding of that state with an indication of uncertainties; and how that state changes due to HRP programmatic progress and design reference mission definitions. In this talk, we will discuss proof-of-concept work performed using a subset of publications captured in the HRP publications database. The publications were tagged in the database with words representing factors influencing health and performance in spaceflight, as well as with words representing the risks HRP research is reducing. Analysis was performed on the publication tag data to identify relationships between factors and between risks. Network representations were then created as one type of visualization of these relationships. This enables future analyses of the structure of the networks based on results from network theory. Such analyses can provide insights into HRP's current human system knowledge state as informed by the publication data. The network structure analyses can also elucidate potential improvements by identifying network connections to establish or strengthen for maximized information flow. The relationships identified in the publication data were subsequently used as inputs to a model captured in the Systems Modeling Language (SysML), which functions as a repository for relationship information to be gleaned from multiple sources. Example network visualization outputs from a simple SysML model were then also created to compare to the visualizations based on the publication data only. We will also discuss ideas for building upon this proof-of-concept work to further support an integrated approach to human spaceflight risk reduction.
As early as 1980, Donald MacLeod coined the term "optoretinogram" to describe a change in the near-infrared reflectance of the retina following visual stimulation. The hope that such signals might exist was stimulated by an observation of a change in the infrared transmission of isolated toad retinae. This signal showed a time course of several seconds, much slower than the electroretinogram, and was thought to be related to some chemical step in the phototransduction cascade. During the early 1980's, we made several attempts to observe such signals in vivo in humans, without success. In the intervening decades, however, researchers have succeeded in observing what are now known as "intrinsic optical signals" or IOSs. Responses from single photoreceptors (obtained using adaptive optics) are surprisingly heterogenous, with some cells increasing their reflectance in response to visual stimulation, while others decrease. This talk will review our early work, survey recent findings, and consider various theories for the origin of the effect.
Well characterized experimental data for consequence model validation is important in progressing the use of liquid hydrogen as an energy carrier. In 2019, the Health and Safety Executive (HSE) undertook a series of liquid hydrogen dispersion and combustion experiments as a part of the Pre-normative Research into the Safe Use of Liquid Hydrogen (PRESLHY) project. In partnership between the National Renewable Energy Laboratory (NREL) and HSE, time and spatially varying hydrogen concentration measurements were made in 25 dispersion experiments and 23 congested ignition experiments associated with PRESLHY WP3 and WP5, respectively. These measurements were undertaken using the hydrogen wide area monitoring system developed by NREL. During the 23 congested ignition experiments, high variability was observed in the measured explosion severity during experiments with similar initial conditions. This led to the conclusion that wind, including localized gusts, had a large influence on the dispersion of the hydrogen, and therefore the quantity of hydrogen that was present in the congested region of the explosions. Using the hydrogen concentration measurements taken immediately prior to ignition, the hydrogen clouds were visualized in an attempt to rationalize the variability in overpressure between the tests. Gaussian process regression was applied to quantify the variability of the measured hydrogen concentrations. This analysis could also be used to guide modifications in experimental designs for future research on hydrogen combustion behavior.
Analytical and experimental studies of the combustion process in a stratified charge rotary engine (SCRE) continue to be the subject of active research in recent years. Specifically to meet the demand for more sophisticated products, a detailed understanding of the engine system of interest is warranted. With this in mind the objective of this work is to develop an understanding of the controlling factors that affect the SCRE combustion process so that an efficient power dense rotary engine can be designed. The influence of the induction-exhaust systems and the rotor geometry are believed to have a significant effect on combustion chamber flow characteristics. In this report, emphasis is centered on Laser Doppler Velocimetry (LDV) measurements and on qualitative flow visualizations in the combustion chamber of the motored rotary engine assembly. This will provide a basic understanding of the flow process in the RCE and serve as a data base for verification of numerical simulations. Understanding fuel injection provisions is also important to the successful operation of the stratified charge rotary engine. Toward this end, flow visualizations depicting the development of high speed, high pressure fuel jets are described. Friction is an important consideration in an engine from the standpoint of lost work, durability and reliability. MSU Engine Research Laboratory efforts in accessing the frictional losses associated with the rotary engine are described. This includes work which describes losses in bearing, seal and auxillary components. Finally, a computer controlled mapping system under development is described. This system can be used to map shapes such as combustion chamber, intake manifolds or turbine blades accurately.
Solid hydrogen particles have been selected as a means of storing atomic propellants in future launch vehicles (refs. 1 to 2). In preparation for this, hydrogen particle formation in liquid helium was tested experimentally. These experiments were conducted to visually characterize the particles and to observe their formation and molecular transformations (aging) while in liquid helium. The particle sizes, molecular transformations, and agglomeration times were estimated from video image analyses. The experiments were conducted at the NASA Glenn Research Center in the Supplemental Multilayer Insulation Research Facility (SMIRF, ref. 3). The facility has a vacuum tank, into which the experimental setup was placed. The vacuum tank prevented heat leaks and subsequent boiloff of the liquid helium, and the supporting systems maintained the temperature and pressure of the liquid helium bath where the solid particles were created. As the operation of the apparatus was developed, the hydrogen particles were easily visualized. The figures (ref. 1) show images from the experimental runs. The first image shows the initial particle freezing, and the second image shows the particles after the small particles have agglomerated. The particles finally all clump, but stick together loosely. The solid particles tended to agglomerate within a maximum of 11 min, and the agglomerate was very weak. Because the hydrogen particles are buoyant in the helium, the agglomerate tends to compact itself into a flat pancake on the surface of the helium. This pancake agglomerate is easily broken apart by reducing the pressure above the liquid. The weak agglomerate implies that the particles can be used as a gelling agent for the liquid helium, as well as a storage medium for atomic boron, carbon, or hydrogen. The smallest particle sizes that resulted from the initial freezing experiments were about 1.8 mm. About 50 percent of the particles formed were between 1.8 to 4.6 mm in diameter. These very small particle sizes are encouraging for future formation experiments, where simpler operations will reduce the costs of production.
The following are discussed: Geophysical Modeling and Processes; Land Surface Processes and Atmospheric Interactions; Remote Sensing Technology and Geophysical Retrievals; and Scientific Data Management and Visual Analysis.