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System manages Deep Space Instrumentation Facilities /DSIF/ equipment construction and modification planning. Versatile program applies to such tasks as employee time and task schedules, pay schedules, operations schedules, and plant and equipment procurement, construction, modification or service.
A plan is described for supporting USDA crop production forecasting and estimation by (1) testing, evaluating, and selecting crop yield models for application testing; (2) identifying areas of feasible research for improvement of models; and (3) conducting research to modify existing models and to develop new crop yield assessment methods. Tasks to be performed for each of these efforts are described as well as for project management and support. The responsibilities of USDA, USDC, USDI, and NASA are delineated as well as problem areas to be addressed.
A pilot training program in communication skills, listening, conflict solving, and task orientation, for a small but growing commuter airline is discussed. The interactions between pilots and management, and communication among crew members are examined. Methods for improvement of cockpit behavior management personnel relations are investigated.
The following potential applications of AI to the study of earth science are described: (1) intelligent data management systems; (2) intelligent processing and understanding of spatial data; and (3) automated systems which perform tasks that currently require large amounts of time by scientists and engineers to complete. An example is provided of how an intelligent information system might operate to support an earth science project.
The focus of this report is the consideration of one form of cognition, judgment and decision making, while examining some information management issues associated with the implementation of new forms of automation. As technology matures and more tasks become suitable to automation, human factors researchers will have to consider the effect that increasing automation will have on operator performance. Current technology allows flight deck designers the opportunity to automate activities involving substantially more cognitive processing.
As emphasis shifts from optimum-performance aerospace systems to least lift-cycle costs, systems designs must seek, adapt, and innovate cost improvement techniques in design through operations. The systems design process of concept, definition, and design was assessed for the types and flow of total quality management techniques that may be applicable in a launch vehicle systems design analysis. Techniques discussed are task ordering, quality leverage, concurrent engineering, Pareto's principle, robustness, quality function deployment, criteria, and others. These cost oriented techniques are as applicable to aerospace systems design analysis as to any large commercial system.
The System Management and Production Laboratory at the Research Institute, the University of Alabama in Huntsville (UAH), was tasked by the Microgravity Experiment Projects (MEP) Office of the Payload Projects Office (PPO) at Marshall Space Flight Center (MSFC) to conduct research in the current methods of written documentation control and retrieval. The goals of this research were to determine the logical interrelationships within selected NASA documentation, and to expand on a previously developed prototype system to deliver a distributable, electronic knowledge-based system. This computer application would then be used to provide a paperless interface between the appropriate parties for the required NASA document.
The National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) is implementing an Automated Procurement System (APS) to streamline its business activities that are used to procure goods and services. This Project Management Plan (PMP) is the governing document throughout the implementation process and is identified as the APS Project Management Plan (DS-03). At this point in time, the project plan includes the schedules and tasks necessary to proceed through implementation. Since the basis of APS is an existing COTS system, the implementation process is revised from the standard SDLC. The purpose of the PMP is to provide the framework for the implementation process. It discusses the roles and responsibilities of the NASA project staff, the functions to be performed by the APS Development Contractor (PAI), and the support required of the NASA computer support contractor (CSC). To be successful, these three organizations must work together as a team, working towards the goals established in this Project Plan. The Project Plan includes a description of the proposed system, describes the work to be done, establishes a schedule of deliverables, and discusses the major standards and procedures to be followed.
The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system was developed as a prototype for intelligent tutoring systems with the intention of seeing PD/ICAT evolve and produce a general ICAT architecture and development environment that can be adapted by a wide variety of training tasks. The proposed architecture is composed of a user interface, a domain expert, a training session manager, a trainee model and a training scenario generator. The PD/ICAT prototype was developed in the LISP environment. Although it has been well received by its peers and users, it could not be delivered toe its end users for practical use because of specific hardware and software constraints. To facilitate delivery of PD/ICAT to its users and to prepare for a more widely accepted development and delivery environment for future ICAT applications, we have ported this training system to a UNIX workstation and adopted use of a conventional language, C, and a C-based rule-based language, CLIPS. A rapid conversion of the PD/ICAT expert system to CLIPS was possible because the knowledge was basically represented as a forward chaining rule base. The resulting CLIPS rule base has been tested successfully in other ICATs as well. Therefore, the porting effort has proven to be a positive step toward our ultimate goal of building a general purpose ICAT development environment.
Autorotation is a maneuver that permits a safe helicopter landing when the engine loses power. A catastrophe may occur if the pilot's control inputs are incorrect, insufficient, excessive, or poorly timed. Due to the danger involved, full-touchdown autorotations are very rarely practiced. Because in-flight autorotation training is risky, time-consuming, and expensive, the objective of the project was to develop the first helicopter flight simulator expressly designed to train students in this critical maneuver. A central feature of the project was the inclusion of an enhanced version of the Pilot-Rotorcraft Intelligent Symbology Management Simulator (PRISMS), a virtual-reality system developed by Anacapa Sciences and Thought Wave. A task analysis was performed to identify the procedural steps in the autorotation, to inventory the information needed to support student task performance, to identify typical errors, and to structure the simulator's practice environment. The system provides immediate knowledge of results, extensive practice of perceptual-motor skills, part-task training, and augmented cueing in a realistic cockpit environment. Additional work, described in this report, extended the capabilities of the simulator in three areas: 1. Incorporation of visual training aids to assist the student in learning the proper appearance of the visual scene when the maneuver is being properly performed; 2. Introduction of the requirement to land at a particular spot, as opposed to the wide, flat open field initially used, and development of appropriate metrics of success; and 3. Inclusion of wind speed and wind direction settings (and random variability settings) to add a more realistic challenge in "hitting the spot."
A JPL-created set of standard processes is to be used throughout the lifecycle of software development. These SDSPs cover a range of activities, from management and engineering activities, to assurance and support activities. These processes must be applied to software tasks per a prescribed set of procedures. JPL s Software Quality Improvement Project is currently working at the behest of the JPL Software Process Owner to ensure that all applicable software tasks follow these procedures. The SDSPs are captured as a set of 22 standards in JPL s software process domain. They were developed in-house at JPL by a number of Subject Matter Experts (SMEs) residing primarily within the Engineering and Science Directorate, but also from the Business Operations Directorate and Safety and Mission Success Directorate. These practices include not only currently performed best practices, but also JPL-desired future practices in key thrust areas like software architecting and software reuse analysis. Additionally, these SDSPs conform to many standards and requirements to which JPL projects are beholden.
Effective space systems engineering (SSE) is conducted in a fully electronic manner. Competitive hardware, software, and system designs are created in a totally digital environment that enables rapid product design and manufacturing cycles, as well as a multitude of techniques such as modeling, simulation, and lean manufacturing that significantly reduce the lifecycle cost of systems. Because the SSE lifecycle depends on the digital environment, managing the enormous volumes of technical data needed to describe, build, deploy, and operate systems is a critical factor in the success of a project. This chapter presents the key aspects of Technical Data Management (TDM) within the SSE process. It is written from the perspective of the System Engineer tasked with establishing the TDM process and infrastructure for a major project. Additional perspectives are reflected from the point of view of the engineers on the project who work within the digital engineering environment established by the TDM toolset and infrastructure, and from the point of view of the contactors who interface via the TDM infrastructure. Table 17.1 lists the TDM process as it relates to SSE.
The ultimate goal of this project is to develop a photovoltaic system high conversion efficiency (>20%) using high quality III-V compound-based three-dimensional micro-structures on silicon and poly-silicon. Such a PV-system could be of very low cost due to minimum usages of III-V materials. This project will address the barriers that currently hamper the performance of solar cells based on three-dimensional micro-structures. To accomplish this goal the project is divided into 4 tasks, each dealing with a different aspect of the project: materials quality, micropillar growth control, light management, and pillar based solar cells. Materials Quality: the internal quantum efficiency (IQE) - by which is meant here the internal fluorescence yield - of the micro-pillars has to be increased. We aim at achieving an IQE of 45% by the end of the first year. By the end of the second year there will be a go-no-go milestone of 65% IQE. By the end of year 3 and 4 we aim to achieve 75% and 90% IQE, respectively. Micropillar growth control: dense forests of micropillars with high fill ratios need to be grown. Pillars within forests should show minimum variations in size. We aim at achieving fill ratios of 2%, 10%, >15%, >20% in years 1, 2, 3, and 4, respectively. Variations in dimension should be minimized by site-controlled growth of pillars. By the end of year 1 we will aim at achieving site-controlled growth with > 15% yield. By end of year 2 the variation of critical pillar dimensions should be less than 25%. Light management: high light absorption in the spectral range of the sun has been to be demonstrated for the micropillar forests. By the end of year 1 we will employ FDTD simulation techniques to demonstrate that pillar forests with fill ratios <20% can achieve 99% light absorption. By end of year 2 our original goal was to demonstrate >85% absorption. By end of year 3 > 90% absorption should be demonstrated. Pillar based solar cells: devices will be studied to explore ways to achieve high open-circuit voltages which will lead to high efficiency micropillar-based solar cells. We will start on single pillar devices and the findings in these studies should pave the way for devices based on forests/ arrays of pillars. By the end of the second year we aim to demonstrate a single pillar device with an open-circuit voltage of 0.7 V, as well as a pillar-forest based device with 8% conversion efficiency. By the end of year 3 these numbers should be improved to 0.9 V open-circuit voltage for single pillar devices and >15% efficiency for forest/array-based devices. We will aim to realize a device with 20% efficiency by the end of the project period.
Multiagent Cyber-Physical-Human (CPH) systems in realistic environments operate under uncertain conditions. Communication among agents, aimed at reducing the uncertainty, is itself subject to uncertainty. We propose to manage uncertainties in autonomous, long-duration operations of multiagent systems via a modified Honeybee Foraging (HBF) behavioral scheme. The resulting system, Autonomous Persistent Intelligent Swarm (APIS),incorporates two new behaviors to ameliorate informational uncertainty. When “scouting”, agents are tasked based on informational quality and reliability rather than solely on priorities. When “dancing”, agents are tasked to rendezvous with other dancing agents to exchange information at close range, where successful communication is guaranteed. When coupled with uncertainty-aware modeling across agents, these behaviors improve situational awareness and resilience of the system, enabling it to function under more uncertain conditions arising during long-duration missions.
Multiagent Cyber-Physical-Human (CPH) systems in realistic environments operate under uncertain conditions. Communication among agents, aimed at reducing the uncertainty, is itself subject to uncertainty. We propose to manage uncertainties in autonomous, long-duration operations of multiagent systems via a modified Honeybee Foraging (HBF) behavioral scheme. The resulting system, Autonomous Persistent Intelligent Swarm (APIS),incorporates two new behaviors to ameliorate informational uncertainty. When “scouting”, agents are tasked based on informational quality and reliability rather than solely on priorities. When “dancing”, agents are tasked to rendezvous with other dancing agents to exchange information at close range, where successful communication is guaranteed. When coupled with uncertainty-aware modeling across agents, these behaviors improve situational awareness and resilience of the system, enabling it to function under more uncertain conditions arising during long-duration missions.
The Mars Observer team was, until the untimely loss of the spacecraft on August 21, 1993, performing flight operations with greater efficiency and speed than any previous JPL mission of its size. This level of through-put was made possible by a Mission Operations System which was composed of skilled personnel using sophisticated sequencing and commanding tools. During cruise flight operations, however, it was realized by the project that this commanding level was not going to be sufficient to support the activities planned for the mapping operations. The project had committed to providing the science instrument principle investigators with a much higher level of commanding during mapping. Thus, the project began taking steps to enhance the capabilities of the flight team. One mechanism used by project management was a tool available from Total Quality Management (TQM). This tool is known as a Process Action Team (PAT). The Mars Observer PAT was tasked to increase the capacity of the flight team's non-stored commanding process by fifty percent with no increase in staffing and a minimal increase in risk. The outcome of this effort was to, in fact, increase the capacity by a factor of 2.5 rather than the desired fifty percent and actually reduce risk. The majority of these improvements came from the automation of the existing command process. The results required very few changes to the existing mission operations system. Rather, the PAT was able to take advantage of automation capabilities inherent in the existing system and make changes to the existing flight team procedures. This paper will describe in detail the enhancements recommended by the PAT for the non-stored command generation process on Mars Observer. This will be contrasted with the process used by the flight team prior to implementation of these improvements. Finally, there will be a discussion of the applicability of the techniques devised by the PAT for enhancement of the non-stored command process to present and future projects.
An overview of the executive system design task is presented. The flight software executive system, software verification, phase B baseline avionics system review, higher order languages and compilers, and computer hardware features are also discussed.
The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.