KEYWORDS: Data modeling, Computer simulations, Systems modeling, Computer architecture, Associative arrays, Data conversion, Chemical elements, Standards development, Human-machine interfaces, Data integration
This paper will discuss automated scenario generation (Sgen) techniques to support the development of simulation scenarios. Current techniques for scenario generation are extremely labor intensive, often requiring manual adjustments to data from numerous sources to support increasingly complex simulations. Due to time constraints this process often prevents the simulation of a large numbers of data sets and the preferred level of “what if analysis”. The simulation demands of future mission planning approaches, like Effects Based Operations (EBO), require the rapid development of simulation inputs and multiple simulation runs for those approaches to be effective. This paper will discuss an innovative approach to the automated creation of complete scenarios for mission planning simulation. We will discuss the results of our successful Phase I SBIR effort that validated our approach to scenario generation and refined how scenario generation technology can be directly applied to the types of problems facing EBO and mission planning. The current stovepipe architecture marries a scenario creation capability with each of the simulation tools. The EBO-Scenario generation toolset breaks that connection through an approach centered on a robust data model and the ability to tie mission-planning tools and data resources directly to an open Course Of Action (COA) analysis framework supporting a number of simulation tools. In this approach data sources are accessed through XML tools, proprietary DB structures or legacy tools using SQL and stored as an instance of Sgen Meta Data. The Sgen Meta Data can be mapped to a wide range of simulation tools using a Meta Data to simulation tools mapping editor that generates an XSLT template describing the required data translation. Once the mapping is created, Sgen will automatically convert the Meta Data instance, using XSLT, to the formats required by specific simulation tools. The research results presented in this paper will show how the complex demands of mission planning can be met with current simulation tools and technology.
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