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GAMME, a meta-model to unify data needs in simulation modeling (WIP)

机译:GAMME,一种用于在仿真建模(WIP)中统一数据需求的元模型

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摘要

Complex system studies, especially in the aerospace context, where systems are too expensive and too critical to allow real experimentation, make extensive use of simulation. A drawback of the simulation approach is that, in general, aerospace systems studied are so large that their simulations are quite difficult to develop. Indeed, such a simulation will generally involve simulation components coming from various sources and sharing information. There, one may see two opposite constraints. On the one hand, the simulation components are developed independently from each other (or potentially preexist) and hence need to manage on their own the data that they need. On the other hand, overall data consistency has to be ensured in the simulation, especially for shared data. An interesting way to solve this issue consists in structuring the data, i.e. defining a datamodel that will be used as a support to specify all operations relevant to data (access, storage,...): one may see this approach as the application of model-driven methods to the central point of data in a simulation. This paper presents GAMME, a home-made data-centered framework for the development of large-scale simulations, as well as uses of this framework in an ONERA simulation example.
机译:复杂的系统研究(尤其是在航空航天环境中,因为系统过于昂贵且过于苛刻而无法进行实际实验)广泛使用了模拟。仿真方法的一个缺点是,通常来说,所研究的航空航天系统是如此之大,以至于很难进行仿真。实际上,这种模拟通常会涉及来自各种来源并共享信息的模拟组件。在那里,可能会看到两个相反的约束。一方面,仿真组件彼此独立(或潜在地存在)开发,因此需要自己管理所需的数据。另一方面,在仿真中必须确保总体数据一致性,尤其是对于共享数据。解决此问题的一种有趣方法是构造数据,即定义一个数据模型,该模型将用作支持指定与数据相关的所有操作(访问,存储等)的方法:模型驱动的方法来模拟仿真中的数据中心点。本文介绍了GAMME,这是一个用于大规模仿真开发的自制数据中心框架,以及该框架在ONERA仿真示例中的使用。

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