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An analysis of the aeronautical engineering situation and the relationship to the U.S. aircraft industry is presented. Some of the problems encountered in undergraduate aeronautical engineering education are explained. A reorganization of the educational structure for aeronautical engineering is proposed. The human factors aspect of aeronautical engineering discipline is described.
The structure and initial work performed toward the creation of a handbook for workload analysis directed at the operational community of engineers and human factors psychologists are described. The goal, when complete, will be to make accessible to such individuals the results of theoretically-based research that are of practical interest and utility in the analysis and prediction of operator workload in advanced and existing systems. In addition, the results of laboratory study focused on the development of a subjective rating technique for workload that is based on psychophysical scaling techniques are described.
Papers presented at the Third Annual Workshop on Space Operations Automation and Robotics (SOAR '89), hosted by the NASA Lyndon 8. Johnson Space Center at Houston, Texas, on July 25-27, 1989, are documented herein. During the three days, approximately 100 technical papers wer3 presented by experts from NASA, the USAF, universities, and technical companies. Also held were panel discussions on Air Force/NASA AI Overview and Expert System Verification and Validation. Tutorial sessions included Neural Networks; Theory and Application of Back Propagation; Verification and Validation of Expert Systems/ Evaluation of Expert System Tools; and Technical Environment for Modular Architectures for Robotics in Space; and are not documented herein. Technical topics addressed included intelligent systems, robotics, human factors, and environment.
The development and impact is described of new visually coupled system (VCS) equipment designed to support engineering and human factors research in the military aircraft cockpit environment. VCS represents an advanced man-machine interface (MMI). Its potential to improve aircrew situational awareness seems enormous, but its superiority over the conventional cockpit MMI has not been established in a conclusive and rigorous fashion. What has been missing is a 'systems' approach to technology advancement that is comprehensive enough to produce conclusive results concerning the operational viability of the VCS concept and verify any risk factors that might be involved with its general use in the cockpit. The advanced VCS configuration described here, was ruggedized for use in military aircraft environments and was dubbed the Virtual Panoramic Display (VPD). It was designed to answer the VCS portion of the systems problem, and is implemented as a modular system whose performance can be tailored to specific application requirements. The overall system concept and the design of the two most important electronic subsystems that support the helmet mounted parts, a new militarized version of the magnetic helmet mounted sight and correspondingly similar helmet display electronics, are discussed in detail. Significant emphasis is given to illustrating how particular design features in the hardware improve overall system performance and support research activities.
The Traffic Management Advisor (TMA), the sequence and schedule tool of the Center/TRACON Automation System (CTAS), was evaluated at the Fort Worth Center (ZFW) in the summer of 1996. This paper describes the challenges encountered during the various phases of the TMA field evaluation, which included system (hardware and software) installation, personnel training, and data collection. Operational procedures were developed and applied to the evaluation process that would ensure air safety. The five weeks of field evaluation imposed minimal impact on the hosting facility and provided valuable engineering and human factors data. The collection of data was very much an opportunistic affair, due to dynamic traffic conditions. One measure of the success of the TMA evaluation is that, rather than remove TMA after the evaluation until it could be fully implemented, the prototype TMA is in continual use at ZFW as the fully operational version is readied for implementation.
No abstract available
The goal of this report is to identify Human System Integration (HSI) and automation issues that contribute to improved effectiveness and efficiency in the operation of U.S. military Small Unmanned Aerial Vehicles (SUAVs). HSI issues relevant to SUAV operations are reviewed and observations from field trials are summarized. Short-term improvements are suggested research issues are identified and an overview is provided of automation technologies applicable to future SUAV design.
The annual 'President's Report' is a good summary of the Government's aerospace activities each year. Mandated by law, it contains information on aerospace activities conducted by 14 Federal departments and agencies. It also contains an executive summary organized by agency, narrative sections organized by subject, as well as extensive appendices containing useful historical data on spacecraft launches, budget figures, key policy documents from the fiscal year, and a glossary.
Reviewed NTSB reports of the 19 U.S. airline accidents between 1991-2000 attributed primarily to crew error. Asked: Why might any airline crew in situation of accident crew--knowing only what they knew--be vulnerable. Can never know with certainty why accident crew made specific errors but can determine why the population of pilots is vulnerable. Considers variability of expert performance as function of interplay of multiple factors.
Abstract Handling qualities embody those qualities or characteristics of an aircraft that govern the ease and precision with which a pilot is able to perform the tasks required in support of an aircraft role. These same qualities are as critical, if not more so, in the operation of spacecraft. A research, development, test, and evaluation process was put into effect to identify, understand, and interpret the engineering and human factors principles which govern the pilot-vehicle dynamic system as they pertain to space exploration missions and tasks. Toward this objective, piloted simulations were conducted at the NASA Langley Research Center and Ames Research Center for earth-orbit proximity operations and docking and lunar landing. These works provide broad guidelines for the design of spacecraft to exhibit excellent handling characteristics. In particular, this work demonstrates how handling qualities include much more than just stability and control characteristics of a spacecraft or aircraft. Handling qualities are affected by all aspects of the pilot-vehicle dynamic system, including the motion, visual and aural cues of the vehicle response as the pilot performs the required operation or task. A holistic approach to spacecraft design, including the use of manual control, automatic control, and pilot intervention/supervision is described. The handling qualities implications of design decisions are demonstrated using these pilot-in-the-loop evaluations of docking operations and lunar landings.
The Interface Anywhere Project was funded through Innovation Charge Account (ICA) at NASA JSC in the Fall of 2012. The project was collaboration between human factors and engineering to explore the possibility of designing an interface to control basic habitat operations through gesture and voice control; (a) Current interfaces require the users to be physically near an input device in order to interact with the system; and (b) By using voice and gesture commands, the user is able to interact with the system anywhere they want within the work environment.
Long duration space travel to destinations such as Mars or an asteroid will expose astronauts to extended periods of reduced gravity. Astronauts will use an exercise regime for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Since the area available in the spacecraft for an exercise device is limited and gravity is not present to aid loading, compact resistance exercise device prototypes are being developed. Since it is difficult to rigorously test these proposed devices in space flight, computational modeling provides an estimation of the muscle forces, joint torques and joint loads during exercise to gain insight on the efficacy to protect the musculoskeletal health of astronauts.
This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.
With the anticipated explosion of small unmanned aerial vehicles, it is highly likely that operators will be controlling fleets of autonomous vehicles. To fulfill the promise of autonomy, vehicle operators will not be concerned with manual control of the vehicle; instead, they will deal with the overall mission. Furthermore, the one operator to many vehicles is becoming a constant meme with various industries including package delivery, search and rescue, and utility companies. In order for an operator to concurrently control several vehicles, his station must look and behave very differently than the current ground control station instantiations. Furthermore, the vehicle will have to be much more autonomous, especially during non-normal operations, in order to accommodate the knowledge deficit or the information overload of the operator in charge of several vehicles. The expected usage increase of small drones requires presenting the operational information generated by a fleet of heterogeneous autonomous agents to an operator. NASA Langley Research Center's Autonomy Incubator has brought together researchers in various disciplines including controls, trajectory planning, systems engineering, and human factors to develop an integrated system to study autonomy issues. The initial human factors effort is focusing on mission displays that would give an operator the overall status of all autonomous agents involved in the current mission. This paper will discuss the specifics of the mission displays for operators controlling several vehicles.
Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited. Therefore, compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Rigorous testing of these proposed devices in space flight is difficult so computational modeling provides an estimation of the muscle forces and joint loads during exercise to gain insight on the efficacy to protect the musculoskeletal health of astronauts. The NASA Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) project and the National Space Biomedical Research Institute (NSBRI) funded researchers by developing computational models of exercising with these new advanced exercise device concepts
As NASA moves beyond exploring low earth orbit and into deep space exploration, increased communication delays between astronauts and earth drive a need for crew to become more autonomous (earth-independent). Currently crew on board the International Space Station (ISS) have limited insight into specific vehicle system performance because of the dependency on monitoring and real-time communication with Mission Control. Wearable technology provides a method to bridge the gap between the human (astronaut) and the system (spacecraft) by providing mutual monitoring between the two. For example, vehicle or environmental information can be delivered to astronauts through on-body devices and in return wearables provide data to the spacecraft regarding crew health, location, etc. The Wearable Electronics and Applications Research (WEAR) Lab at the NASA Johnson Space Center utilizes a collaborative approach between engineering and human factors to investigate the use of wearables for spaceflight. Zero and partial gravity environments present unique challenges to wearables that require collaborative, user-centered, and iterative approaches to the problems. Examples of the WEAR Lab's recent wearable projects for spaceflight will be discussed.
Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and the musculoskeletal forces that occur during exercises performed on the prototype devices. The computational models currently under development utilize the OpenSim software, an open source code for musculoskeletal modeling, with biomechanical input data from test subjects for estimation of muscle and joint loads. The subjects are instrumented with reflective markers for motion capture data collection while exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device. Ground reaction force data is collected with force plates under the feet and device loading is recorded through load cells internal to the HULK. Test variables include applied device load, narrow or wide foot stance, slow or fast cadence and the harness or long bar interface between the test subject and the device. Data is also obtained using free weights for a comparison to the resistively loaded exercise device. This data is input into the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the body loads. The focus of this presentation is to summarize the results from the full squat exercises across the different test variables.
INTRODUCTION: Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to assist loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft for travel to the Moon or to Mars is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and the musculoskeletal forces that occur during exercises performed on the prototype devices. METHODS The computational models currently under development utilize the OpenSim [1] software platform, consisting of open source code for musculoskeletal modeling, using biomechanical input data from test subjects for estimation of muscle and joint loads. The OpenSim Full Body Model [2] is used for all analyses. The model incorporates simplified wrap surfaces, a new knee model and updated lower body muscle parameters derived from cadaver measurements and magnetic resonance imaging of young adults. The upper body uses torque actuators at the lumbar and extremity joints. The test subjects who volunteer for this study are instrumented with reflective markers for motion capture data collection while performing squat exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device (ZIN Technologies, Middleburg Heights, OH). Ground reaction force data is collected with force plates under the feet, and device loading is recorded through load cells internal to the HULK. Test variables include the applied device load and the dual cable long bar or single cable T-bar interface between the test subject and the device. Data is also obtained using free weights with the identical loading for a comparison to the resistively loaded exercise device trials. The data drives the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the body loads. RESULTS Lower body kinematics, joint moments, joint forces and muscle forces are obtained from the OpenSim biomechanical analysis of the squat exercises under different loading conditions. Preliminary results from the model for the loading conditions will be presented as will hypotheses developed for follow on work.