SpaceCube v3.0 Mini: NASA Next-Generation Data-Processing System for Advanced CubeSat Applications
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The paper presents the hardware implementation and initial tests from a low-power, high-speed reconfigurable sensor fusion processor.
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Research project reports pertaining to physics, space sciences, computer systems, information processing, and control systems
Building upon the purpose, theoretical approach, and use of a Goal-Function Tree (GFT) being presented by Dr. Stephen B. Johnson, described in a related Infotech 2013 ISHM abstract titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management", this paper will describe the core framework used to implement the GFTbased systems engineering process using the Systems Modeling Language (SysML). These two papers are ideally accepted and presented together in the same Infotech session. Statement of problem: SysML, as a tool, is currently not capable of implementing the theoretical approach described within the "Goal-Function Tree Modeling for Systems Engineering and Fault Management" paper cited above. More generally, SysML's current capabilities to model functional decompositions in the rigorous manner required in the GFT approach are limited. The GFT is a new Model-Based Systems Engineering (MBSE) approach to the development of goals and requirements, functions, and its linkage to design. As a growing standard for systems engineering, it is important to develop methods to implement GFT in SysML. Proposed Method of Solution: Many of the central concepts of the SysML language are needed to implement a GFT for large complex systems. In the implementation of those central concepts, the following will be described in detail: changes to the nominal SysML process, model view definitions and examples, diagram definitions and examples, and detailed SysML construct and stereotype definitions.
Building upon the purpose, theoretical approach, and use of a Goal-Function Tree (GFT) being presented by Dr. Stephen B. Johnson, described in a related Infotech 2013 ISHM abstract titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management", this paper will describe the core framework used to implement the GFTbased systems engineering process using the Systems Modeling Language (SysML). These two papers are ideally accepted and presented together in the same Infotech session. Statement of problem: SysML, as a tool, is currently not capable of implementing the theoretical approach described within the "Goal-Function Tree Modeling for Systems Engineering and Fault Management" paper cited above. More generally, SysML's current capabilities to model functional decompositions in the rigorous manner required in the GFT approach are limited. The GFT is a new Model-Based Systems Engineering (MBSE) approach to the development of goals and requirements, functions, and its linkage to design. As a growing standard for systems engineering, it is important to develop methods to implement GFT in SysML. Proposed Method of Solution: Many of the central concepts of the SysML language are needed to implement a GFT for large complex systems. In the implementation of those central concepts, the following will be described in detail: changes to the nominal SysML process, model view definitions and examples, diagram definitions and examples, and detailed SysML construct and stereotype definitions.
This paper describes the core framework used to implement a Goal-Function Tree (GFT) based systems engineering process using the Systems Modeling Language. It defines a set of principles built upon by the theoretical approach described in the InfoTech 2013 ISHM paper titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management" presented by Dr. Stephen B. Johnson. Using the SysML language, the principles in this paper describe the expansion of the SysML language as a baseline in order to: hierarchically describe a system, describe that system functionally within success space, and allocate detection mechanisms to success functions for system protection.
LANDSAT digital multispectral scanner data, in conjunction with supporting ground truth, were investigated to determine their utility in delineation of urban-rural boundaries. The digital data for the metropolitan areas of Washington, D. C.; Austin, Texas; and Seattle, Washingtion; were processed using an interactive image processing system. Processing focused on identification of major land cover types typical of the zone of transition from urban to rural landscape, and definition of their spectral signatures. Census tract boundaries were input into the interactive image processing system along with the LANDSAT single and overlayed multiple date MSS data. Results of this investigation indicate that satellite collected information has a practical application to the problem of urban area delineation and to change detection.
Systems engineering is examined in terms of functional activities that are performed in the conduct of a system definition/design, and system development is described in a parametric analysis that combines functions, performance, and design variables. Emphasis is placed on identification of activities performed by design organizations, design specialty groups, as well as a central systems engineering organizational element. Identification of specific roles and responsibilities for doing functions, and monitoring and controlling activities within the system development operation are also emphasized.
The Mod II Site Data Acquisition Subsystem (SDAS) is designed to collect data from sensors located on residential or commercial buildings using a solar heating and/or cooling system. The SDAS takes the data obtained from sensors located on the solar heating and/or cooling system, processes the data into a suitable format, stores the data for a period of time, and provides the capability for both telephone retrieval by the Central Data Processing System (CDPS) and manual retrieval of the data for transfer to the central site. The unit is designed so it will not degrade the operation of the solar heating/cooling system which it is monitoring.
The Site Data Acquisition Subsystem (SDAS) designed to collect data from sensors located on residential or commercial buildings using a solar heating and/or cooling system is described. It takes the data obtained from sensors located on the solar system, processes the data into suitable format, stores the data for a period of time, and provides the capability for either telephone retrieval by the central data processing system or manual retrieval of the data for transfer to a central site. The SDAS is also designed so that it will not degrade the operation of the solar heating/cooling system which it is monitoring.
A multitude of locations exist for acquiring satellite-derived precipitation rate data. Because the volume of data exceeds what can reasonably be analyzed manually, online tools have been developed to help researchers make more informed data acquisition decisions. Some interfaces provide sample images generated from prioritized variables to enable efficient visual inspection, while others include the ability to subset geographically to reduce the volume of the data to the area of interest. Building upon such value-added services is the STORM (the NASA Precipitation Processing System (PPS) data product ordering system) Swath-Based Analysis Tool (https://storm.pps.eosdis.nasa.gov/storm/Analysis.jsp). With it, users can compare overflights of multiple precipitation satellites simultaneously and from this make determinations about which swaths will best serve their research. They can preview these overflights with two distinct visualization tools. Finally, they can then download geographically subset swaths that have precipitation rate characteristics matching their research needs. A user starts by making up to six selections. They then select their date range of interest going back to 1997. Finally, they select a geographical region either by inputting latitude-longitude corners of a rectangle or drawing that rectangle on an interactive map. The system processes each file, determining aggregate statistics about the precipitation rates within the selected region as observed by each instrument. These statistical values are added to a time series graph as a "time remaining" counter is continuously updated. The chart is fully interactive, with detailed values displayed upon mouseover, and numerous options available upon clicking each point. Since the user is likely to need the relevant files for their own research, they can generate an order from their request. All files are geographically subset to the region of interest, and the user can use the statistical values to limit which files are added to the order. This flexibility helps to ensure researchers are only downloading the files they need for their work, making for a more efficient process both from a time-consumption and a storage perspective. This paper will introduce the Swath-Based Analysis Tool and explore its numerous features. It will discuss several use cases for precipitation scientists.
The processing of trash and waste is a welcome and valuable addition to humans living and working in space. Besides the obvious desire to have a pleasant and productive habitation environment, trash management has many practicalbenefits for crew health, resource recovery, and volume reclamation through garbage compaction. The Trash Compaction and Processing System (TCPS), which is a NASA project to develop a trash processing system for long-duration spaceflight, is currently undergoing concept development with engineering prototype validation through two contracted efforts. The development efforts are being supported with activities associated with the NASA Generation 2 Heat Melt Compactor (HMC). The HMC is a facility that compacts trash, recovers water, heats the trash to eliminate biological activity, and manages gas and vapor effluents. The resulting residual processed trash is a compact tile that is free of biological growth and that can be used for augmenting radiation shields. The work being conducted with the HMC focuses on high risk technical areas with respect to operations, subsystem performance, and ISS effluent management interface requirements. This paper gives an overview of the technical risks and the current use of the HMC as a facility for reducing risk.
An experimental data processing system has been developed to demonstrate the feasibility of processing high speed, multispectral image data on board the spacecraft. The design incorporates real-time processing with adaptable operation in an expandable architecture. The experimental hardware is coupled to test support and computing equipment to provide a laboratory tool for evaluating and demonstrating each of the processing functions as well as the overall system operation. An evaluation of the high speed processor was conducted to ensure that the desired system throughput was achieved without sacrificing processing accuracy. A description of the system is presented along with the results of the test and evaluation activity.