Engineering topics
O'Neil, Daniel A.
Publications and source records attributed to O'Neil, Daniel A..
Three Dimensional Computer Graphics Federates for the 2012 Smackdown Simulation
The Simulation Interoperability Standards Organization (SISO) Smackdown is a two-year old annual event held at the 2012 Spring Simulation Interoperability Workshop (SIW). A primary objective of the Smackdown event is to provide college students with hands-on experience in developing distributed simulations using High Level Architecture (HLA). Participating for the second time, the University of Alabama in Huntsville (UAHuntsville) deployed four federates, two federates simulated a communications server and a lunar communications satellite with a radio. The other two federates generated 3D computer graphics displays for the communication satellite constellation and for the surface based lunar resupply mission. Using the Light-Weight Java Graphics Library, the satellite display federate presented a lunar-texture mapped sphere of the moon and four Telemetry Data Relay Satellites (TDRS), which received object attributes from the lunar communications satellite federate to drive their motion. The surface mission display federate was an enhanced version of the federate developed by ForwardSim, Inc. for the 2011 Smackdown simulation. Enhancements included a dead-reckoning algorithm and a visual indication of which communication satellite was in line of sight of Hadley Rille. This paper concentrates on these two federates by describing the functions, algorithms, HLA object attributes received from other federates, development experiences and recommendations for future, participating Smackdown teams.
Managing Large Scale Project Analysis Teams through a Web Accessible Database
Large scale space programs analyze thousands of requirements while mitigating safety, performance, schedule, and cost risks. These efforts involve a variety of roles with interdependent use cases and goals. For example, study managers and facilitators identify ground-rules and assumptions for a collection of studies required for a program or project milestone. Task leaders derive product requirements from the ground rules and assumptions and describe activities to produce needed analytical products. Disciplined specialists produce the specified products and load results into a file management system. Organizational and project managers provide the personnel and funds to conduct the tasks. Each role has responsibilities to establish information linkages and provide status reports to management. Projects conduct design and analysis cycles to refine designs to meet the requirements and implement risk mitigation plans. At the program level, integrated design and analysis cycles studies are conducted to eliminate every 'to-be-determined' and develop plans to mitigate every risk. At the agency level, strategic studies analyze different approaches to exploration architectures and campaigns. This paper describes a web-accessible database developed by NASA to coordinate and manage tasks at three organizational levels. Other topics in this paper cover integration technologies and techniques for process modeling and enterprise architectures.
Lessons Learned from Deploying an Analytical Task Management Database
Defining requirements, missions, technologies, and concepts for space exploration involves multiple levels of organizations, teams of people with complementary skills, and analytical models and simulations. Analytical activities range from filling a To-Be-Determined (TBD) in a requirement to creating animations and simulations of exploration missions. In a program as large as returning to the Moon, there are hundreds of simultaneous analysis activities. A way to manage and integrate efforts of this magnitude is to deploy a centralized database that provides the capability to define tasks, identify resources, describe products, schedule deliveries, and generate a variety of reports. This paper describes a web-accessible task management system and explains the lessons learned during the development and deployment of the database. Through the database, managers and team leaders can define tasks, establish review schedules, assign teams, link tasks to specific requirements, identify products, and link the task data records to external repositories that contain the products. Data filters and spreadsheet export utilities provide a powerful capability to create custom reports. Import utilities provide a means to populate the database from previously filled form files. Within a four month period, a small team analyzed requirements, developed a prototype, conducted multiple system demonstrations, and deployed a working system supporting hundreds of users across the aeros pace community. Open-source technologies and agile software development techniques, applied by a skilled team enabled this impressive achievement. Topics in the paper cover the web application technologies, agile software development, an overview of the system's functions and features, dealing with increasing scope, and deploying new versions of the system.
System Architecture Modeling for Technology Portfolio Management using ATLAS
Strategic planners and technology portfolio managers have traditionally relied on consensus-based tools, such as Analytical Hierarchy Process (AHP) and Quality Function Deployment (QFD) in planning the funding of technology development. While useful to a certain extent, these tools are limited in the ability to fully quantify the impact of a technology choice on system mass, system reliability, project schedule, and lifecycle cost. The Advanced Technology Lifecycle Analysis System (ATLAS) aims to provide strategic planners a decision support tool for analyzing technology selections within a Space Exploration Architecture (SEA). Using ATLAS, strategic planners can select physics-based system models from a library, configure the systems with technologies and performance parameters, and plan the deployment of a SEA. Key parameters for current and future technologies have been collected from subject-matter experts and other documented sources in the Technology Tool Box (TTB). ATLAS can be used to compare the technical feasibility and economic viability of a set of technology choices for one SEA, and compare it against another set of technology choices or another SEA. System architecture modeling in ATLAS is a multi-step process. First, the modeler defines the system level requirements. Second, the modeler identifies technologies of interest whose impact on an SEA. Third, the system modeling team creates models of architecture elements (e.g. launch vehicles, in-space transfer vehicles, crew vehicles) if they are not already in the model library. Finally, the architecture modeler develops a script for the ATLAS tool to run, and the results for comparison are generated.
Advanced Technology Lifecycle Analysis System (ATLAS)
Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is satisfied with the system configurations, technology portfolios, and deployment strategies, he or she can present the concepts to a team, which will conduct a detailed, discipline-oriented analysis within a CEE. An analog to this approach is the music industry where a songwriter creates the lyrics and music before entering a recording studio.