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At least 991 records · Page 55

Adding a Verification View for Autonomous Real-Time Architecture

Spacecraft software systems continue to increase in complexity and must frequently operate autonomously for extended periods. Thus, the consequences of software flaws are increasing and it is necessary to improve development methods to minimize the risk of latent flaws in the operational software. Traditional software architectures place verification as one element in the development architectural view and treat verification as a later lifecycle activity that is considered complete when the system is certified for flight. The Gateway Vehicle System Manager team, recognizing the importance of verification throughout the system lifecycle, is treating verification as an additional architectural view that receives continuous attention from the requirements analysis phase and continuing for the life of the operational system. The verification view consists of two viewpoints: development and operational. We present background on the verification view and discuss the approaches the Vehicle System Manager team is taking.

James B Dabney↗

What can formal methods offer to digital flight control systems design

Formal methods research begins to produce methods which will enable mathematic modeling of the physical behavior of digital hardware and software systems. The development of these methods directly supports the NASA mission of increasing the scope and effectiveness of flight system modeling capabilities. The conventional, continuous mathematics that is used extensively in modeling flight systems is not adequate for accurate modeling of digital systems. Therefore, the current practice of digital flight control system design has not had the benefits of extensive mathematical modeling which are common in other parts of flight system engineering. Formal methods research shows that by using discrete mathematics, very accurate modeling of digital systems is possible. These discrete modeling methods will bring the traditional benefits of modeling to digital hardware and hardware design. Sound reasoning about accurate mathematical models of flight control systems can be an important part of reducing risk of unsafe flight control.

Good, Donald I.↗

An Introduction to Message-Bus Architectures for Space Systems

This course presents technical and programmatic information on the development of message-based architectures for space mission ground and flight software systems. Message-based architecture approaches provide many significant advantages over the more traditional socket-based one-of-a-kind integrated system development approaches. The course provides an overview of publish/subscribe concepts, the use of common isolation layer API's, approaches to message standardization, and other technical topics. Several examples of currently operational systems are discussed and possible changes to the system discussed and time for questions and answers will be provided.

Smith, Danford↗

Introduction to Message-Bus Architectures for Space Systems

This course presents technical and programmatic information on the development of message-based architectures for space mission ground and flight software systems. Message-based architecture approaches provide many significant advantages over the more traditional socket-based one-of-a-kind integrated system development approaches. The course provides an overview of publish/subscribe concepts, the use of common isolation layer API's, approaches to message standardization, and other technical topics. Several examples of currently operational systems are discussed and possible changes to the system development process are presented. Benefits and lessons learned will be discussed and time for questions and answers will be provided.

Smith, Dan↗

Impact of knowledge-based software engineering on aerospace systems

The emergence of knowledge engineering as a software technology will dramatically alter the use of software by expanding application areas across a wide spectrum of industries. The engineering and management of large aerospace software systems could benefit from a knowledge engineering approach. An understanding of this technology can potentially make significant improvements to the current practice of software engineering, and provide new insights into future development and support practices.

Peyton, Liem↗

U.S. Space Shuttle GPS navigation capability for all mission phases

Incorporating a GPS capability on the Space Shuttle presented unique system integration design considerations and has led to an integration concept that has minimum impact on the existing Shuttle hardware and software systems. This paper presents the Space Shuttle GPS integrated design and the concepts used in implementing this GPS capability. The major focus of the paper is on the modifications that will be made to the navigation systems in the Space Shuttle General Purpose Computers (GPC) and on the Operational Requirements of the integrated GPS/GPC system. Shuttle navigation system architecture, functions and operations are discussed for the current system and with the GPS integrated navigation capability. The GPS system integration design presented in this paper has been formally submitted to the Shuttle Avionics Software Control Board for implementation in the on-board GPC software.

Kachmar, Peter↗

Digital image analysis of Landsat data

The paper defines some basic processing functions than can be performed digitally, discusses a variety of computer peripherals including hard copy output devices and television terminals, compares the characteristics of stand-alone image analysis systems, and briefly describes the important features of image processing and geographic information systems software. Several examples are discussed to demonstrate the efficient use of computers through implementation of hard copy image recorders and television display terminals. The commercially available stand-alone image analysis systems include a computer, appropriate peripherals, and sufficient software to perform analysis without other computational support.

Alford, W. L.↗

Ground data systems resource allocation process

The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.

Berner, Carol A.↗

Decomposing Systems Into Subsystems For Design

Interactions among systems displayed in concise format. DeMAID (Design Manager's Aide for Intelligent Decomposition) is knowledge based software system for automating sequencing of subprocesses in design process and identifying possible multilevel structure for synthesis problem. Reorders and groups modules of equipment being designed on basis of links among modules, helping design manager make design decisions early in design cycle. Written in FORTRAN 77.

Rogers, James L., Jr.↗

Generic architectures for future flight systems

Generic architecture for future flight systems must be based on open system architectures (OSA). This provides the developer and integrator the flexibility to optimize the hardware and software systems to match diverse and unique applications requirements. When developed properly OSA provides interoperability, commonality, graceful upgradability, survivability and hardware/software transportability to greatly minimize life cycle costs and supportability. Architecture flexibility can be achieved to take advantage of commercial developments by basing these developments on vendor-neutral commercially accepted standards and protocols. Rome Laboratory presently has a program that addresses requirements for OSA.

Wood, Richard J.↗

Reusable Software Technology

The objective of the Reusable Software System (RSS) is to provide NASA Langley Research Center and its contractor personnel with a reusable software technology through the Internet. The RSS is easily accessible, provides information that is extractable, and the capability to submit information or data for the purpose of scientific research at NASA Langley Research Center within the Atmospheric Science Division.

Morgan, Timothy E.↗

A Multiprocessor Operating System Simulator

This paper describes a multiprocessor operating system simulator that was developed by the authors in the Fall semester of 1987. The simulator was built in response to the need to provide students with an environment in which to build and test operating system concepts as part of the coursework of a third-year undergraduate operating systems course. Written in C++, the simulator uses the co-routine style task package that is distributed with the AT&T C++ Translator to provide a hierarchy of classes that represents a broad range of operating system software and hardware components. The class hierarchy closely follows that of the 'Choices' family of operating systems for loosely- and tightly-coupled multiprocessors. During an operating system course, these classes are refined and specialized by students in homework assignments to facilitate experimentation with different aspects of operating system design and policy decisions. The current implementation runs on the IBM RT PC under 4.3bsd UNIX.

Johnston, Gary M.↗

Memory-Efficient Onboard Rock Segmentation

Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering operations were re-coded to operate on horizontal data stripes across the image. Data types were reduced to smaller sizes where possible. Binary- valued intermediate results were squeezed into a more compact, one-bit-per-pixel representation through bit packing and bit manipulation macros. An estimated 16-fold reduction in memory footprint relative to the original Rockster algorithm was achieved. The resulting memory footprint is less than four times the base image size. Also, memory allocation calls were modified to draw from a static pool and consolidated to reduce memory management overhead and fragmentation. Rockster-MER has now been run onboard Opportunity numerous times as part of AEGIS with exceptional performance. Sample results are available on the AEGIS website at http://aegis.jpl.nasa.gov.

Burl, Michael C.↗

Big Software for SmallSats: Adapting CFS to CubeSat Missions

Expanding capabilities and mission objectives for SmallSats and CubeSats is driving the need for reliable, reusable, and robust flight software. While missions are becoming more complicated and the scientific goals more ambitious, the level of acceptable risk has decreased. Design challenges are further compounded by budget and schedule constraints that have not kept pace. NASA's Core Flight Software System (cFS) is an open source solution which enables teams to build flagship satellite level flight software within a CubeSat schedule and budget. NASA originally developed cFS to reduce mission and schedule risk for flagship satellite missions by increasing code reuse and reliability. The Lunar Reconnaissance Orbiter, which launched in 2009, was the first of a growing list of Class B rated missions to use cFS. Large parts of cFS are now open source, which has spurred adoption outside of NASA. This paper reports on the experiences of two teams using cFS for current CubeSat missions. The performance overheads of cFS are quantified, and the reusability of code between missions is discussed. The analysis shows that cFS is well suited to use on CubeSats and demonstrates the portability and modularity of cFS code.

Open Source↗

Big Software for SmallSats: Adapting cFS to CubeSat Missions

Expanding capabilities and mission objectives for SmallSats and CubeSats is driving the need for reliable, reusable, and robust flight software. While missions are becoming more complicated and the scientific goals more ambitious, the level of acceptable risk has decreased. Design challenges are further compounded by budget and schedule constraints that have not kept pace. NASA's Core Flight Software System (cFS) is an open source solution which enables teams to build flagship satellite level flight software within a CubeSat schedule and budget. NASA originally developed cFS to reduce mission and schedule risk for flagship satellite missions by increasing code reuse and reliability. The Lunar Reconnaissance Orbiter, which launched in 2009, was the first of a growing list of Class B rated missions to use cFS.

Flight Software↗

The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and its intuitive graphics capabilities is providing a concurrent engineering environment for rapid prototyping and development. Operational schematics of the MSRR-1 electrical, thermal control, vacuum access, and gas supply systems, and furnace inserts are represented graphically in the environment. Logic to represent first order engineering calculations is coded into the knowledge base to simulate the operational behavior of the MSRR-1 systems. An example of engineering data provided includes electrical currents, voltages, operational power, temperatures, thermal fluid flow rates. pressures, and component status indications. These type of data are calculated and displayed at appropriate instrumentation points, and the schematics are animated to reflect the simulated operational status of the MSRR-1. The software control functions are also simulated to represent appropriate operational behavior based on automated control and response to commands received by the crew or ground controllers. The first benefit of this simulation environment is being realized in the high fidelity engineering analysis results from the electrical power system G2 model. Secondly, the MSRR-1 simulation model will be embedded with a hardware mock-up of the MSRR-1 to provide crew training on MSRR-1 integrated payload operations. G2 gateway code will output the simulated instrumentation values, termed as telemetry, in a flight-like data stream so that the crew has realistic and accurate simulated MSRR-1 data on the flight displays which will be designed for crew use. The simulation will also respond appropriately to crew or ground initiated commands, which will be part of normal facility operations. A third use of the G2 model is being planned; the MSRR-1 simulation will be integrated with additional software code as part of the test configuration of the primary onboard computer, or Master Controller, for MSRR-1. We will take advantage of the G2 capability to simulate the flight like data stream to test flight software responses and behavior. A fourth use of the G2 model will be to train the Ground Support Personnel that will monitor the MSRR-1 systems and payloads while they are operating aboard the ISS. The intuitive, schematic based environment will provide an excellent foundation for personnel to understand the integrated configuration and operation of the MSRR-1, and the anticipated telemetry feedback based on operational modes of the equipment. Expert monitoring features will be enhanced to provide a smart monitoring environment for the operators. These features include: (1) Animated, intuitive schematic-based displays which reflect telemetry values, (1) Real-time plotting of simulated or incoming sensor values, (3) High/Low exception monitoring for analog data, (4) Expected state monitoring for discrete data, (5) Data trending, (6) Automated malfunction procedure execution to diagnose problems, (7) Look ahead capability to planned MSRR-1 activities in the onboard timeline. And finally, the logic to calculate telemetry values will be deactivated, and the same environment will interface to the incoming data for the real-time telemetry stream to schematically represent the onboard hardware configuration. G2 will be the foundation for the real-time monitoring and control environment. In summary, our MSRR-1 simulation model spans many elements of the life cycle development of this project: Engineering Analysis, Test and Checkout, Training of Crew and Ground Personnel, and Real-time monitoring and control. By utilizing the unique features afforded by an expert system development environment, we have been able to synergize a powerful tool capable of addressing our project needs at every phase of project development.

Rice, Amanda↗