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This paper describes a hierarchical scheduling, planning, control, and execution monitoring architecture for automating operations of a worldwide network of communications antennas. The purpose of this paper is to describe an architecture for automating the process of capturing spacecraft data.
Integration of planning and execution for single-agent systems has received considerable attention and numerous interesting approaches have been proposed.
This paper describes the application of Artificial Intelligence techniques for plan generation, plan execution, and plan monitoring to automate a Deep Space Communication Station. This automation allows a Communication station to respond to a set of tracking goals by appropriately reconfiguring the communications hardware and software to provide the requested communications services.
The Spitzer Space Telescope is an 85-cm telescope with three cryogenically cooled instruments. Following launch, the observatory was initialized and commissioned for science operations during the in-orbit checkout (IOC) and science verification (SV) phases, carried out over a total of 98.3 days. The execution of the IOC/SV mission plan progressively established Spitzer capabilities taking into consideration thermal, cryogenic, optical, pointing, communications, and operational designs and constraints. The plan was carried out with high efficiency, making effective use of cryogen-limited flight time. One key component to the success of the plan was the pre-launch allocation of schedule reserve in the timeline of IOC/SV activities, and how it was used in flight both to cover activity redesign and growth due to continually improving spacecraft and instrument knowledge, and to recover from anomalies. This paper describes the adaptive system design and evolution, implementation, and lessons learned from IOC/SV operations. It is hoped that this information will provide guidance to future missions with similar engineering challenges
International Space Station is a joint venture. Because of this, ISS execution planning- planning within the week for the ISS requires coordination across multiple partner, and the associated processes and tools to allow this coordination to occur. These processes and tools are currently defined and are extensively used. This paper summarizes these processes, and documents the current data trends associated with these processes and tools, with a focus on the metrics provided from the ISS Planning Product Change Request (PPCR) tool. As NASA's Vision for Space Exploration and general Human spaceflight trends are implemented, the probability of joint venture long duration programs such as ISS, with varying levels of intergovernmental and/or corporate partnership, will increase. Therefore, the results of this PPCR analysis serve as current Lessons learned for the ISS and for further similar ventures.
Computationally complex primitive operations of an algorithm are executed concurrently in a plurality of functional units under the control of an assignment manager. The algorithm is preferably defined as a computationally marked graph contianing data status edges (paths) corresponding to each of the data flow edges. The assignment manager assigns primitive operations to the functional units and monitors completion of the primitive operations to determine data availability using the computational marked graph of the algorithm. All data accessing of the primitive operations is performed by the functional units independently of the assignment manager.
The ROSE framework was designed to facilitate complex system analyses. It completely divorces the model execution process from the model itself. By doing so ROSE frees the modeler to develop a library of standard modeling processes such as Design of Experiments, optimizers, parameter studies, and sensitivity studies which can then be applied to any of their available models. The ROSE framework accomplishes this by means of a well defined API and object structure. Both the API and object structure are presented here with enough detail to implement ROSE in any object-oriented language or modeling tool.
This paper discusses the successful implementation of a highly visible company-wide management system and its potential to change managerial and accounting policies, processes and practices in support of organizational goals. Applying the conceptual framework of innovation in organizations, this paper describes the development and deployment process of the NASA Budget Execution Dashboard and the first two fiscal years of its use. It discusses the positive organizational changes triggered by the dashboard, like higher visibility of financial goals and variances between plans and actuals, increased involvement of all management levels in tracking and correcting of plan deviations, establishing comparable data standards across a strongly diversified organization, and enhanced communication between line organizations (NASA Centers) and product organizations (Mission Directorates). The paper also discusses the critical success factors experienced in this project: Strong leadership and division of management roles, rapid and responsive technology development, and frequent communication among stakeholders.
The SCaN Program has defined an integrated network architecture that fully meets the Administrator s mandate to the Program, and will result in a NASA infrastructure capable of providing the needed and enabling communications services to future space missions. The integrated network architecture will increase SCaN operational efficiency and interoperability through standardization, commonality and technology infusion. It will enable NASA missions requiring advanced communication and tracking capabilities such as: a. Optical communication b. Antenna arraying c. Lunar and Mars Relays d. Integrated network management (service management and network control) and integrated service execution e. Enhanced tracking for navigation f. Space internetworking with DTN and IP g. End-to-end security h. Enhanced security services Moreover, the SCaN Program has created an Integrated Network Roadmap that depicts an orchestrated and coherent evolution path toward the target architecture, encompassing all aspects that concern network assets (i.e., operations and maintenance, sustaining engineering, upgrade efforts, and major development). This roadmap identifies major NASA ADPs, and shows dependencies and drivers among the various planned undertakings and timelines. The roadmap is scalable to accommodate timely adjustments in response to Agency needs, goals, objectives and funding. Future challenges to implementing this architecture include balancing user mission needs, technology development, and the availability of funding within NASA s priorities. Strategies for addressing these challenges are to: define a flexible architecture, update the architecture periodically, use ADPs to evaluate options and determine when to make decisions, and to engage the stakeholders in these evaluations. In addition, the SCaN Program will evaluate and respond to mission need dates for technical and operational capabilities to be provided by the SCaN integrated network. In that regard, the architecture defined in this ADD is scalable to accommodate programmatic and technical changes.
The Aerial Onboard Autonomous Science Investigation System (AerOASIS) system provides autonomous planning and execution capabilities for aerial vehicles (see figure). The system is capable of generating high-quality operations plans that integrate observation requests from ground planning teams, as well as opportunistic science events detected onboard the vehicle while respecting mission and resource constraints. AerOASIS allows an airborne planetary exploration vehicle to summarize and prioritize the most scientifically relevant data; identify and select high-value science sites for additional investigation; and dynamically plan, schedule, and monitor the various science activities being performed, even during extended communications blackout periods with Earth.
Although over forty years have passed since first landing on the Moon, there is not yet a comprehensive, quantitative assessment of Apollo extravehicular activities (EVAs). Quantitatively evaluating lunar EVAs will provide a better understanding of the challenges involved with surface operations. This first evaluation of a surface EVA centers on comparing the planned and the as-ran timeline, specifically collecting data on discrepancies between durations that were estimated versus executed. Differences were summarized by task categories in order to gain insight as to the type of surface operation activities that were most challenging. One Apollo 14 EVA was assessed utilizing the described methodology. Selected metrics and task categorizations were effective, and limitations to this process were identified.
This paper examines uncertainty in the maneuver execution delay for data linked conflict resolution maneuvers. This uncertainty could cause the previously cleared primary conflict to reoccur or a secondary conflict to appear. Results show that the likelihood of a primary conflict reoccurring during a horizontal conflict resolution maneuver increases with larger initial turn-out angles and with shorter times until loss of separation. There is also a significant increase in the probability of a primary conflict reoccurring when the time until loss falls under three minutes. Increasing horizontal separation by an additional 1.5 nmi lowers the risk, but does not completely eliminate it. Secondary conflicts were shown to have a small probability of occurring in all tested configurations.
This document (Volume I) provides an executive summary of the lessons learned from the Constellation Program. A companion Volume II provides more detailed analyses for those seeking further insight and information. In this volume, Section 1.0 introduces the approach in preparing and organizing the content to enable rapid assimilation of the lessons. Section 2.0 describes the contextual framework in which the Constellation Program was formulated and functioned that is necessary to understand most of the lessons. Context of a former program may seem irrelevant in the heady days of new program formulation. However, readers should take some time to understand the context. Many of the lessons would be different in a different context, so the reader should reflect on the similarities and differences in his or her current circumstances. Section 3.0 summarizes key findings developed from the significant lessons learned at the program level that appear in Section 4.0. Readers can use the key findings in Section 3.0 to peruse for particular topics, and will find more supporting detail and analyses in Section 4.0 in a topical format. Appendix A contains a white paper describing the Constellation Program formulation that may be of use to readers wanting more context or background information. The reader will no doubt recognize some very similar themes from previous lessons learned, blue-ribbon committee reviews, National Academy reviews, and advisory panel reviews for this and other large-scale human spaceflight programs; including Apollo, Space Shuttle, Shuttle/Mir, and the ISS. This could represent an inability to learn lessons from previous generations; however, it is more likely that similar challenges persist in the Agency structure and approach to program formulation, budget advocacy, and management. Perhaps the greatest value of these Constellation lessons learned can be found in viewing them in context with these previous efforts to guide and advise the Agency and its stakeholders.
Dryden has embarked on implementing Critical Chain Project Management (CCPM) philosophies and tools to reduce workforce stress and increase the centers work throughput. This effort has been under way for over one year and represents a fundamental state change in how various projects are planned and executed at the center. The implementation of CCPM philosophies and the required cultural changes represent the most difficult aspects of the implementation.
Overview of the US UAS Executive Committee, its progress at integrating government owned UAS in the US airspace, and committee plans
Successful execution of the flight phase of the Superboom Caustic Analysis and Measurement Project (SCAMP) required accurate placement of focused sonic booms on an array of prepositioned ground sensors. While the array was spread over a 10,000-ft-long area, this is a relatively small region when considering the speed of a supersonic aircraft and sonic boom ray path variability due to shifting atmospheric conditions and aircraft trajectories. Another requirement of the project was to determine the proper position for a microphone-equipped motorized glider to intercept the sonic boom caustic, adding critical timing to the constraints. Variability in several inputs to these calculations caused some shifts of the focus away from the optimal location. Reports of the sonic booms heard by persons positioned amongst the array were used to shift the focus closer to the optimal location for subsequent passes. This paper describes the methods and computations used to place the focused sonic boom on the SCAMP array and gives recommendations for their accurate placement by future quiet supersonic aircraft. For the SCAMP flights, 67% of the foci were placed on the ground array with measured positions within a few thousand feet of computed positions. Among those foci with large caustic elevation angles, 96% of foci were placed on the array, and measured positions were within a few hundred feet of computed positions. The motorized glider captured sonic booms on 59% of the passes when the instrumentation was operating properly.
Automating the coupling of data assimilation (DA) and modeling systems is a unique challenge in the numerical weather prediction (NWP) research community. In recent years, the Development Testbed Center (DTC) has released well-documented tools such as the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolation (GSI) DA system that can be easily downloaded, installed, and run by researchers on their local systems. However, developing a coupled system in which the various preprocessing, DA, model, and postprocessing capabilities are all integrated can be labor-intensive if one has little experience with any of these individual systems. Additionally, operational modeling entities generally have specific coupling methodologies that can take time to understand and develop code to implement properly. To better enable collaborating researchers to perform modeling and DA experiments with GSI, the Short-term Prediction Research and Transition (SPoRT) Center has developed a set of Perl scripts that couple GSI and WRF in a cycling methodology consistent with the use of real-time, regional observation data from the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC). Because Perl is open source, the code can be easily downloaded and executed regardless of the user's native shell environment. This paper will provide a description of this open-source code and descriptions of a number of the use cases that have been performed by SPoRT collaborators using the scripts on different computing systems.
We describe the design and execution of the BORTAS (Quantifying the impact of BOReal forest fires on Tropospheric oxidants using Aircraft and Satellites) experiment, which has the overarching objective of understanding the chemical aging of airmasses that contain the emission products from seasonal boreal wildfires and how these airmasses subsequently impact downwind atmospheric composition. The central focus of the experiment was a two-week deployment of the UK BAe-146-301 Atmospheric Research Aircraft (ARA) over eastern Canada. The planned July 2010 deployment of the ARA was postponed by 12 months because of activities related to the dispersal of material emitted by the Eyjafjallaj¨okull volcano. However, most other planned model and measurement activities, including ground-based measurements at the Dalhousie University Ground Station (DGS), enhanced ozonesonde launches, and measurements at the Pico Atmospheric Observatory in the Azores, went ahead and constituted phase A of the experiment. Phase B of BORTAS in July 2011 included the same measurements, but included the ARA, special satellite observations and a more comprehensive measurement suite at the DGS. Integrating these data helped us to describe pyrogenic plumes from wildfires on a wide spectrum of temporal and spatial scales. We interpret these data using a range of chemistry models, from a near-explicit gas-phase chemical mechanism to regional and global models of atmospheric transport and lumped chemistry. We also present an overview of some of the new science that has originated from this project.