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Cloud-based orchestration of a model-based power and data analysis toolchain

机译:基于模型的电源和数据分析工具链的基于云的编排

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The proposed Europa Mission concept contains many engineering and scientific instruments that consume varying amounts of power and produce varying amounts of data throughout the mission. System-level power and data usage must be well understood and analyzed to verify design requirements. Numerous cross-disciplinary tools and analysis models are used to simulate the system-level spacecraft power and data behavior. This paper addresses the problem of orchestrating a consistent set of models, tools, and data in a unified analysis toolchain when ownership is distributed among numerous domain experts. An analysis and simulation environment was developed as a way to manage the complexity of the power and data analysis toolchain and to reduce the simulation turnaround time. A system model data repository is used as the trusted store of high-level inputs and results while other remote servers are used for archival of larger data sets and for analysis tool execution. Simulation data passes through numerous domain-specific analysis tools and end-to-end simulation execution is enabled through a web-based tool. The use of a cloud-based service facilitates coordination among distributed developers and enables scalable computation and storage needs, and ensures a consistent execution environment. Configuration management is emphasized to maintain traceability between current and historical simulation runs and their corresponding versions of models, tools and data.
机译:拟议的欧罗巴飞行任务概念包含许多工程和科学仪器,它们在整个飞行过程中消耗不同量的能量并产生不同量的数据。必须很好地理解和分析系统级电源和数据使用情况,以验证设计要求。大量的跨学科工具和分析模型用于模拟系统级航天器的动力和数据行为。本文讨论了在所有权分配给众多领域专家的情况下,在统一的分析工具链中协调一致的模型,工具和数据的问题。开发了一种分析和仿真环境,作为管理电源和数据分析工具链的复杂性并减少仿真周转时间的一种方式。系统模型数据存储库用作高级输入和结果的可信存储,而其他远程服务器则用于较大数据集的归档和分析工具的执行。仿真数据通过众多领域特定的分析工具传递,并且通过基于Web的工具启用端到端仿真执行。基于云的服务的使用促进了分布式开发人员之间的协调,并实现了可伸缩的计算和存储需求,并确保了一致的执行环境。强调配置管理以保持当前和历史模拟运行及其模型,工具和数据的相应版本之间的可追溯性。

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