Effect of some control system nonlinearities on single loop compensatory tracking
Effect of control system nonlinearities on human operator single loop compensatory tracking performance
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Effect of control system nonlinearities on human operator single loop compensatory tracking performance
As the concept of on-demand electric air taxis gains popularity and begins to take shape, many research efforts are underway to address the challenges of integrating this new class of passenger-carrying air vehicles into the already congested U.S. National Airspace System. Through collaborations between the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration, and industry, this concept, commonly referred to as Urban Air Mobility (UAM), envisions a safe, reliable, and efficient mode of transportation traversing metropolitan and urban areas. Among the many challenges being tackled, airspace procedures and information requirements are critical areas of research that need to be addressed. In a joint effort between NASA and Joby Aviation, a human-in-the-loop study was conducted at the NASA Ames Research Center to evaluate initial and midterm operations with air traffic controllers and on-board UAM pilots in the Dallas area. This area was chosen due to its complex Class Bravo Airspace that extends to the surface over a relatively large area. To achieve the goals and objectives of the study, multiple preceding efforts were conducted to develop the candidate procedures and information requirements. This paper provides an overview of the operational concept used for the study, the process that was followed, and the findings from the two tabletop meetings and a shakedown activity. The combination of these led to a set of airspace procedures, letters of agreement, and information requirements that were evaluated in the human-inthe-loop study.
An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.
Our objective is to develop an Autonomous Chemical Experimentation (ACE) platform that accelerates discovery of new catalytic transformations and other energy-relevant chemical reactions and processes. We intentionally designed ACE to be highly modular, both with respect to its rapid deployment to different chemistries and experimental workflows as well as incorporation of a wide range of different AI algorithms. In addition to the development of the core software architecture, initial efforts were made to incorporate Large Language Models to provide human-interpretable reasoning of the optimizer’s actions, and to develop a user-friendly graphical interface for experimental researchers. ACE was demonstrated using a flow electrocatalysis platform containing an inline FTIR spectrometer for real-time analysis and quantification of the reaction outcome. Human-in-the-loop experiments were performed in which a human researcher conducted an experiment using electrode potentials suggested by ACE, then fed the spectral data back to ACE for decision making. After confirming the successful function of the optimizer, efforts were next directed to automation of the hardware and performed full autonomy tests using three reactions: catalytic oxidation of formate, catalytic oxidation of cyclohexanol, and oxidation of hydroquinone. These studies confirm that ACE can close the loop between reaction execution, analysis, and optimization. They also reveal that more improved product detection methods will be essential for ACE to make well-informed decisions for reactions with low conversions.
The presentation will describe the architecture, current capabilities and some future enhancements of the testbed that is being developed at the National Aeronautics and Space Administration (NASA) to enable benefit, impact, safety and cost assessments for accelerating the deployment of air traffic management concept and technologies in the national airspace system. The testbed will support analysis of operational feasibility of urban air mobility operations, a part of NASA's Air Traffic Management eXploration project, and provide the data needed by regulatory agencies charged with public safety. Introduction of concepts and technologies, especially new concepts and technologies, is difficult and often takes decades because of the inability to assess the operational impact of the interaction between the proposed concept and technology and operationally deployed systems in terms of system-wide safety, traffic flow efficiency, roles and workload of controllers and traffic managers, and impact on airlines and other operators. To overcome these limitations, the testbed is developing infrastructure to enable mathematical modeling, human-in-the-loop evaluations and testing with operational systems in a simulated environment. In addition to the difficulty of establishing communications between geographically distributed systems, downloading/installing software, and management of startup, error-handling and shutdown, a major impediment for conducting simulations and human-in-the-loop testing with operational systems is the tedious manual scenario generation process. Several of these difficulties have been addressed in the current state of the testbed. The testbed can be described in terms of the following elements (1) web-based frontend and backend, (2) Testbed Builder, (3) Data Distribution Service, (4) Component Library, (5) Simulation Management, and (6) Scenario Generation. The web-based frontend and backend enable the user to interact with the testbed for tasks such as composing a simulation, running a simulation and retrieving output data. The Testbed Builder application launched from the web frontend is a graphical user interface for the user to drag-and-drop and connect predefined blocks for composing a simulation/scenario generation task. The Builder writes a set of instructions for Simulation Management based on the links between the blocks and the block properties such as the component (executable) associated with a particular block. Management of the distributed simulation is accomplished by Execution and Component Managers. Execution Manager interprets the instructions provided by the Builder to instruct the Component Managers to download components from the Component Library to specified computers and to start them up. Once started, the components communicate with each other by publishing messages and subscribing to messages that are delivered by the Data Distribution Service. The Scenario Generation capability can be used for creating traffic scenarios for Multi-Aircraft Control System, which has been used extensively at NASA for human-in-the-loop-based concept evaluations. The presentation will provide a testbed enabled example scenario of Multi-Aircraft Control System based simulation in which the urban air mobility pilot using the conflict detection and resolution system would interact with the air traffic controllers for resolving conflicts with other aircraft during terminal area operations.
The presentation will describe the architecture, current capabilities and some future enhancements of the testbed that is being developed at the National Aeronautics and Space Administration (NASA) to enable benefit, impact, safety and cost assessments for accelerating the deployment of air traffic management concept and technologies in the national airspace system. The testbed will support analysis of operational feasibility of urban air mobility operations, a part of NASA's Air Traffic Management eXploration project, and provide the data needed by regulatory agencies charged with public safety. Introduction of concepts and technologies, especially new concepts and technologies, is difficult and often takes decades because of the inability to assess the operational impact of the interaction between the proposed concept and technology and operationally deployed systems in terms of system-wide safety, traffic flow efficiency, roles and workload of controllers and traffic managers, and impact on airlines and other operators. To overcome these limitations, the testbed is developing infrastructure to enable mathematical modeling, human-in-the-loop evaluations and testing with operational systems in a simulated environment. In addition to the difficulty of establishing communications between geographically distributed systems, downloading/installing software, and management of startup, error-handling and shutdown, a major impediment for conducting simulations and human-in-the-loop testing with operational systems is the tedious manual scenario generation process. Several of these difficulties have been addressed in the current state of the testbed. The testbed can be described in terms of the following elements- (1) web-based frontend and backend, (2) Testbed Builder, (3) Data Distribution Service, (4) Component Library, (5) Simulation Management, and (6) Scenario Generation. The web-based frontend and backend enable the user to interact with the testbed for tasks such as composing a simulation, running a simulation and retrieving output data. The Testbed Builder application launched from the web frontend is a graphical user interface for the user to drag-and-drop and connect predefined blocks for composing a simulation/scenario generation task. The Builder writes a set of instructions for Simulation Management based on the links between the blocks and the block properties such as the component (executable) associated with a particular block. Management of the distributed simulation is accomplished by Execution and Component Managers. Execution Manager interprets the instructions provided by the Builder to instruct the Component Managers to download components from the Component Library to specified computers and to start them up. Once started, the components communicate with each other by publishing messages and subscribing to messages that are delivered by the Data Distribution Service. The Scenario Generation capability can be used for creating traffic scenarios for Multi-Aircraft Control System, which has been used extensively at NASA for human-in-the-loop-based concept evaluations. The presentation will provide a testbed enabled example scenario of Multi-Aircraft Control System based simulation in which the urban air mobility pilot using the conflict detection and resolution system would interact with the air traffic controllers for resolving conflicts with other aircraft during terminal area operations.
BACKGROUND: In preparation for human exploration to Mars, there is a need to define the development and test program that will validate deep space operations and systems. In that context, a Proving Grounds CisLunar habitat spacecraft is being defined as the next step towards this goal. This spacecraft will operate differently from the ISS or other spacecraft in human history. The performance envelope of this spacecraft (mass, volume, power, specifications, etc.) is being defined by the Future Capabilities Study Team. This team has recognized the need for a human-centered approach for the internal architecture of this spacecraft and has commissioned a CisLunar Phase-1 Habitat Internal Architecture Study Team to develop a NASA reference configuration, providing the Agency with a "smart buyer" approach for future acquisition. THE CISLUNAR HABITAT INTERNAL ARCHITECTURE STUDY: Overall, the CisLunar Habitat Internal Architecture study will address the most significant questions and risks in the current CisLunar architecture, habitation, and operations concept development. This effort is achieved through definition of design criteria, evaluation criteria and process, design of the CisLunar Habitat Phase-1 internal architecture, and the development and fabrication of internal architecture concepts combined with rigorous and methodical Human-in-the-Loop (HITL) evaluations and testing of the conceptual innovations in a controlled test environment. The vision of the CisLunar Habitat Internal Architecture Study is to design, build, and test a CisLunar Phase-1 Habitat Internal Architecture that will be used for habitation (e.g. habitability and human factors) evaluations. The evaluations will mature CisLunar habitat evaluation tools, guidelines, and standards, and will interface with other projects such as the Advanced Exploration Systems (AES) Program integrated Power, Avionics, Software (iPAS), and Logistics for integrated human-in-the-loop testing. The mission of the CisLunar Habitat Internal Architecture Study is to become a forcing function to establish a common understanding of CisLunar Phase-1 Habitation Internal Architecture design criteria, processes, and tools. The scope of the CisLunar Habitat Internal Architecture study is to design, develop, demonstrate, and evaluate a Phase-1 CisLunar Habitat common module internal architecture based on design criteria agreed to by NASA, the International Partners, and Commercial Exploration teams. This task is to define the CisLunar Phase-1 Internal Architecture Government Reference Design, assist NASA in becoming a "smart buyer" for Phase-1 Habitat Concepts, and ultimately to derive standards and requirements from the Internal Architecture Design Process. The first step was to define a Habitat Internal Architecture Design Criteria and create a structured philosophy to be used by design teams as a filter by which critical aspects of consideration would be identified for the purpose of organizing and utilizing interior spaces. With design criteria in place, the team will develop a series of iterative internal architecture concept designs which will be assessed by means of an evaluation criteria and process. These assessments will successively drive and refine the design, leading to the combination and down-selection of design concepts. A single refined reference design configuration will be developed into in a medium-to-high fidelity mockup. A multi-day human-in-the-loop mission test will fully evaluate the reference design and validate its configuration. Lessons learned from the design and evaluation will enable the team to identify appropriate standards for Phase-1 CisLunar Habitat Internal Architecture and will enable NASA to develop derived requirements in support of maturing CisLunar Habitation capabilities. This paper will describe the criteria definition process, workshop event, and resulting CisLunar Phase-1 Habitat Internal Architecture Design Criteria.
Cybersecurity breaches targeting electrical substations constitute a significant threat to the integrity of the power grid, necessitating comprehensive defense and mitigation strategies. Any anomaly in information and communication technology (ICT) should be detected for secure communications between devices in digital substations. This paper proposes large language models (LLMs), e.g., ChatGPT, for the cybersecurity of IEC 61850-based communications. Multi-cast messages such as generic object oriented system events (GOOSE) and sampled values (SV) are used for case studies. The proposed LLM-based cybersecurity framework includes, for the first time, data pre-processing of communication systems and human-in-the-loop (HITL) training (considering the cybersecurity guidelines recommended by humans). The results show a comparative analysis of detected anomaly data carried out based on the performance evaluation metrics for different LLMs. A hardware-in-the-loop (HIL) testbed is used to generate and extract a dataset of IEC 61850 communications.
Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, while automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies to be carried out that can inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. The paper describes the initial validation of the automated simulation capability against results from previous IDM HITL experiments, quantifying the differences. The simulator is then used to explore the performance of the IDM concept under the simple scenario of a capacity constrained airport under a wide range of wind conditions.
Introduction: The Lightweight Surface Manipulation System (LSMS) AutoNomy capabilities Development for surface Operations and construction (LANDO) project is an Early Career Initiative selected for funding by NASA Space Technology Mission Directorate. LANDO is developing a general-purpose autonomy framework applicable to serial and tension-actuated manipulation agents, that will be validated using an existing prototype of the LSMS-L35 (35-kg wrist lift capacity on the lunar surface [Fig. 1], sized for a Commercial Lunar Pay-load Services (CLPS) mission). The autonomous LSMS-L35 will be used to demonstrate autonomous payload handling capabilities for Lunar and other planetary surfaces, directly addressing STMD capability gaps in autonomous excavation and construction operations, advanced robotics and spacecraft autonomy technologies, and technologies supporting emerging space industries including the In-Space Servicing, Assembly and Manufacturing national strategy. LSMS: The LSMS is a tension actuated robotic agent that is scalable (reach and lifting capacity in different gravity environments), versatile (types of surface operations), and reusable. Compared to serial arms, the LSMS provides significantly higher structural efficiency and mechanical advantage, enabling a greater payload lift capacity at a lower system mass. The LSMS is envisioned to be a crucial part of the excavation and construction portfolio, capable of supporting a variety of activities on the lunar surface. Autonomous payload handling is one of the first activities the LSMS can support that develops capabilities that are extensible to other surface operations. Payload handling is required to: remove payloads from a lander; place payloads on mobile agents for transport from a lander to construction site/assembly point; emplace payloads in their operational configuration, and aggregate components to create an asset. As an example of this critical gap, manifested CLPS missions do not currently have a ubiquitous payload offloading capability; payloads (excluding rovers) are designed to remain on the lander. Why Autonomy? Autonomous robotic systems capable of carrying out excavation and construction operations are a fundamental and critical capability required for realizing the NASA Artemis program vision to “emplace and build the infrastructure, systems, and robotic missions that can enable a sustained lunar surface presence.” While teleoperation is still feasible for lunar surface operations, increased latency at Mars will require validated supervised autonomous technologies capable of operating with minimal human involvement (human-on-the-loop) unless an unexpected event occurs requiring human intervention. Autonomy reduces operator burden, allows operations to continue during uncrewed periods, in-creases the safety of operations by automatically detecting and handling faults, and allows operating in high latency environments. Development Activities: LANDO is extending critical autonomous operations to the manipulation domain and creating an integrated system, based on reusable software modules, that is capable of planning and executing payload handling and autonomous surface operations without requiring hu-man intervention beyond a supervisory role. The priority features under development are 1) autonomously offload payloads from a tilted lander deck without buckling the LSMS; 2) sensing whether a payload is safe to lift and handle; and 3) integrate with Astrobotic’s CLPS lander. The poster presentation will highlight current development activities over the past year on LSMS-L35 prototype hard-ware design, and autonomy software.
This paper describes some elements in the development of realistic performance and behavior in the synthetic entities (players) which support Modeling and Simulation (M&S) applications, particularly military training. Modern human-in-the-loop (virtual) training systems incorporate sophisticated synthetic environments, which provide: 1. The operational environment, including, for example, terrain databases; 2. Physical entity parameters which define performance in engineered systems, such as aircraft aerodynamics; 3. Platform/system characteristics such as acoustic, IR and radar signatures; 4. Behavioral entity parameters which define interactive performance, including knowledge/reasoning about terrain, tactics; and, 5. Doctrine, which combines knowledge and tactics into behavior rule sets. The resolution and fidelity of these model/database elements can vary substantially, but as synthetic environments are designed to be compose able, attributes may easily be added (e.g., adding a new radar to an aircraft) or enhanced (e.g. Amending or replacing missile seeker head/ Electronic Counter Measures (ECM) models to improve the realism of their interaction). To a human in the loop with synthetic entities, their observed veridicality is assessed via engagement responses (e.g. effect of countermeasures upon a closing missile), as seen on systems displays, and visual (image) behavior. The realism of visual models in a simulation (level of detail as well as motion fidelity) remains a challenge in realistic articulation of elements such as vehicle antennae and turrets, or, with human figures; posture, joint articulation, response to uneven ground. Currently the adequacy of visual representation is more dependant upon the quality and resolution of the physical models driving those entities than graphics processing power per Se. Synthetic entities in M&S applications traditionally have represented engineered systems (e.g. aircraft) with human-in-the-loop performance characteristics (e.g. visual acuity) included in the system behavioral specification. As well, performance affecting human parameters such as experience level, fatigue and stress are coming into wider use (via AI approaches) to incorporate more uncertainty as to response type as well as performance (e.g. Where an opposing entity might go and what it might do, as well as how well it might perform).
This paper describes the Shadow-Mode Assessment Using Realistic Technologies for the National Airspace System (SMART-NAS) Test Bed. The SMART-NAS Test Bed is an air traffic simulation platform being developed by the National Aeronautics and Space Administration (NASA). The SMART-NAS Test Bed's core purpose is to conduct high-fidelity, real-time, human-in-the-loop and automation-in-the-loop simulations of current and proposed future air traffic concepts for the United States' Next Generation Air Transportation System called NextGen. The setup, configuration, coordination, and execution of realtime, human-in-the-loop air traffic management simulations are complex, tedious, time intensive, and expensive. The SMART-NAS Test Bed framework is an alternative to the current approach and will provide services throughout the simulation workflow pipeline to help alleviate these shortcomings. The principle concepts to be simulated include advanced gate-to-gate, trajectory-based operations, widespread integration of novel aircraft such as unmanned vehicles, and real-time safety assurance technologies to enable autonomous operations. To make this possible, SNTB will utilize Web-based technologies, cloud resources, and real-time, scalable, communication middleware. This paper describes the SMART-NAS Test Bed's vision, purpose, its concept of use, and the potential benefits, key capabilities, high-level requirements, architecture, software design, and usage.
The purpose of this design process is to apply Human Engineering (HE) requirements and guidelines to hardware/software and to provide HE design, analysis and evaluation of crew interfaces. The topics include: 1) Background/Purpose; 2) HE Activities; 3) CASE STUDY: Net Habitable Volume (NHV) Study; 4) CASE STUDY: Human Modeling Approach; 5) CASE STUDY: Human Modeling Results; 6) CASE STUDY: Human Modeling Conclusions; 7) CASE STUDY: Human-in-the-Loop Evaluation Approach; 8) CASE STUDY: Unsuited Evaluation Results; 9) CASE STUDY: Suited Evaluation Results; 10) CASE STUDY: Human-in-the-Loop Evaluation Conclusions; 11) Near-Term Plan; and 12) In Conclusion
NASA’s Artemis campaign is making heavy use of simulation to help return humans to the lunar surface by the end of the decade. There are several aspects of the lunar surface and its environment which must be accurately modeled before these simulations can be relied upon to influence decisions being made under these programs. Digital Lunar Exploration Sites, a paper submitted to the 2022 IEEE Aerospace Conference, outlined the process used to generate the lunar surface in a digital environment. This paper will expand upon this topic and delve into the steps being taken by the NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center (JSC) to properly verify and validate these simulations, with a focus on the visual aspects of the environment. Natural lighting validation relies in part on the wealth of data generated during the Apollo program. Many images taken by Apollo astronauts on the lunar surface have been replicated in the simulated environments to gain confidence in the accuracy of terrain and lighting models. However, because the environment the Artemis astronauts will experience at the Lunar South Pole (LSP) is dissimilar from the near-equatorial Apollo sites, other validation techniques must be applied. At the LSP, the sun crests only about three degrees above the horizon and when combined with the lack of a lunar atmosphere, lighting in this region is often very different than what a human would experience on Earth. Solar illumination, earthshine, human eye response, solar blooming, lunar regolith optical properties, and shadows cast by rocks and crater walls will play a significant role in an astronaut’s ability to safely conduct an Extra-Vehicular Activity (EVA) or perform a traverse with a lunar rover. Approaches for validation of these aspects of the rendered LSP environment are considered in this paper. In addition to natural lighting, approaches for the validation of artificial lighting models at the LSP are discussed. The JSC Lighting Lab has been studying the illumination profile of the Exploration Infomatics Subsystem (xINFO) lighting on the Exploration EVA Mobility Unit (xEMU). How these lights interact with the solar illumination and the shadows being cast on the lunar surface is of particular interest, so the validity of models representing these lights in a human-in-the-loop virtual reality environment becomes very important. This paper also touches on some of the simulation performance considerations when a Human in the Loop (HITL) is present, which drives the need for real time rendering of the environment. Natural and artificial lighting will play a crucial role to decisions being made when planning and executing missions at the Lunar South Pole (LSP) and it is vitally important to understand the LSP environment before we return.
NASA’s Artemis campaign is making heavy use of simulation to help return humans to the lunar surface by the end of the decade. There are several aspects of the lunar surface and its environment which must be accurately modeled before these simulations can be relied upon to influence decisions being made under these programs. Digital Lunar Exploration Sites, a paper submitted to the 2022 IEEE Aerospace Conference, outlined the process used to generate the lunar surface in a digital environment. This paper will expand upon this topic and delve into the steps being taken by the NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center (JSC) to properly verify and validate these simulations, with a focus on the visual aspects of the environment. Natural lighting validation relies in part on the wealth of data generated during the Apollo program. Many images taken by Apollo astronauts on the lunar surface have been replicated in the simulated environments to gain confidence in the accuracy of terrain and lighting models. However, because the environment the Artemis astronauts will experience at the Lunar South Pole (LSP) is dissimilar from the near-equatorial Apollo sites, other validation techniques must be applied. At the LSP, the sun crests only about 1.5 degrees above the horizon and when combined with the lack of a lunar atmosphere, lighting in this region is often very different than what a human would experience on Earth. Solar illumination, earthshine, human eye response, solar blooming, lunar regolith optical properties, and shadows cast by rocks and crater walls will play a significant role in an astronaut’s ability to safely conduct an Extra-Vehicular Activity (EVA) or perform a traverse with a lunar rover. Approaches for validation of these aspects of the rendered LSP environment are considered in this paper. In addition to natural lighting, approaches for the validation of artificial lighting models at the LSP are discussed. The JSC Lighting Lab has been studying the illumination profile of the Exploration Informatics Subsystem (xINFO) lighting on the Exploration EVA Mobility Unit (xEMU). How these lights interact with the solar illumination and the shadows being cast on the lunar surface is of particular interest, so the validity of models representing these lights in a human-in-the-loop virtual reality environment becomes very important. This paper also touches on some of the simulation performance considerations when a Human in the Loop (HITL) is present, which drives the need for realtime rendering of the environment. Natural and artificial lighting will play a crucial role to decisions being made when planning and executing missions at the Lunar South Pole (LSP) and it is vitally important to understand the LSP environment before we return.
Growing interest in Urban Air Mobility (UAM) has been demonstrated by a great deal of investment in related research made by industry, government, and academia. Based on this research effort along with considerations of the maturing concept for UAM airspace integration, a cognitive walkthrough exercise and a human-in-the-loop simulation were conducted with controller subject matter experts (SMEs) to evaluate Dallas-Fort Worth (DFW) current day helicopter routes for near-term use as UAM routes. One of the outcomes of this work is a set of heuristics that should be applied when designing UAM routes in the future. The following heuristics were identified as critical to UAM route design: the proximity of routes to surrounding airports (including approach and departure paths of traditional commercial traffic), the configuration of surrounding airports, avoiding congested or heavily populated areas, avoiding route segments that would go through several sectors, avoiding route segments that would go in and out of Class B airspace, creating routes outside of Class B airspace when able, using routes with two-way, altitude-separated traffic when able, minimizing the length of the route, avoiding commonly placed Temporary Flight Restrictions, and creating Non-Movement Areas or UNICOM Areas. This paper describes each of these identified heuristics and relevant examples based on a human-in-the-loop study conducted using the DFW area airspace.
This paper will describe the purpose, architecture, and implementation of a gate-to-gate, high-fidelity air traffic simulation environment called the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Test Bed.The overarching purpose of the SMART-NAS Test Bed (SNTB) is to conduct high-fidelity, real-time, human-in-the-loop and automation-in-the-loop simulations of current and proposed future air traffic concepts for the Next Generation Air Transportation System of the United States, called NextGen. SNTB is intended to enable simulations that are currently impractical or impossible for three major areas of NextGen research and development: Concepts across multiple operational domains such as the gate-to-gate trajectory-based operations concept; Concepts related to revolutionary operations such as the seamless and widespread integration of large and small Unmanned Aerial System (UAS) vehicles throughout U.S. airspace; Real-time system-wide safety assurance technologies to allow safe, increasingly autonomous aviation operations. SNTB is primarily accessed through a web browser. A set of secure support services are provided to simplify all aspects of real-time, human-in-the-loop and automation-in-the-loop simulations from design (i.e., prior to execution) through analysis (i.e., after execution). These services include simulation architecture and asset configuration; scenario generation; command, control and monitoring; and analysis support.
A Human-In-The-Loop (HITL) Portable Life Support System 2.0 (PLSS 2.0) test has been conducted at NASA Johnson Space Center in the PLSS Development Laboratory from October 27, 2014 to December 19, 2014. These closed-loop tests of the PLSS 2.0 system integrated with human subjects in the Mark III Suit at 3.7 psi to 4.3 psi above ambient pressure performing treadmill exercise at various metabolic rates from standing rest to 3000 BTU/hr (880 W). The bulk of the PLSS 2.0 was at ambient pressure but effluent water vapor from the Spacesuit Water Membrane Evaporator (SWME) and the Auxiliary Membrane Evaporator (Mini-ME), and effluent carbon dioxide from the Rapid Cycle Amine (RCA) were ported to vacuum to test performance of these components in flight-like conditions. One of the objectives of this test was to determine the heat transfer coefficient (UA) of the Liquid Cooling Garment (LCG). The UA, an important factor for modeling the heat rejection of an LCG, was determined in a variety of conditions by varying inlet water temperature, flowrate, and metabolic rate. Three LCG configurations were tested: the Extravehicular Mobility Unit (EMU) LCG, the Oceaneering Space Systems (OSS) LCG, and the OSS auxiliary LCG. Other factors influencing accurate UA determination, such as overall heat balance, LCG fit, and the skin temperature measurement, will also be discussed.