2,824,136 research outputs found

    A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

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    The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes

    Software Design Guidelines for Usability

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    For years, the Human Computer Interaction (HCI) community has crafted usability guidelines that clearly define what
characteristics a software system should have in order to be easy to use. However, in the Software Engineering (SE)
community keep falling short of successfully incorporating these recommendations into software projects. From a SE
perspective, the process of incorporating usability features into software is not always straightforward, as a large number
of these features have heavy implications in the underlying software architecture. For example, successfully including an
“undo” feature in an application requires the design and implementation of many complex interrelated data structures and
functionalities. Our work is focused upon providing developers with a set of software design patterns to assist them in the
process of designing more usable software. This would contribute to the proper inclusion of specific usability features
with high impact on the software design. Preliminary validation data show that usage of the guidelines also has positive
effects on development time and overall software design quality

    Software Design for Empowering Scientists

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    Scientific research is increasingly digital. Some activities, such as data analysis, search, and simulation, can be accelerated by letting scientists write workflows and scripts that automate routine activities. These capture pieces of the scientific method that scientists can share. The averna Workbench, a widely deployed scientific-workflow-management system, together with the myExperiment social Web site for sharing scientific experiments, follow six principles of designing software for adoption by scientists and six principles of user engagement

    Software, architecture, and participatory design

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    Much work in software architecture has been inspired by work in physical architecture, in particular Alexander's work on `design patterns'. By contrast, Alexander's work is little-used in town planning and architecture. In this paper, we examine some of the reasons that this is so, describe some parallels and differences between the fields of physical and software architecture, and identify areas in which future collaboration may be fruitful. The notion of `participatory design' is important in software engineering and in urban regeneration, but the participatory mechanisms in each field are quite different

    Altimeter waveform software design

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    Techniques are described for preprocessing raw return waveform data from the GEOS-3 radar altimeter. Topics discussed include: (1) general altimeter data preprocessing to be done at the GEOS-3 Data Processing Center to correct altimeter waveform data for temperature calibrations, to convert between engineering and final data units and to convert telemetered parameter quantities to more appropriate final data distribution values: (2) time "tagging" of altimeter return waveform data quantities to compensate for various delays, misalignments and calculational intervals; (3) data processing procedures for use in estimating spacecraft attitude from altimeter waveform sampling gates; and (4) feasibility of use of a ground-based reflector or transponder to obtain in-flight calibration information on GEOS-3 altimeter performance
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