Integrating External Simulations Within the Model-Based Systems Engineering Approach Using Statistical Metamodels

Abstract

The Model-Based Systems Engineering (MBSE) approach uses the Systems Modeling Language (SysML) to express the architectural information of a system throughout different stages of its lifecycle. Within the approach, the system's structure, behavior, requirements, and parametrics are defined as elements within an integrated model. System Engineers use nine SysML diagrams to display unique views of these system elements. A significant limitation of SysML is that it is only descriptive in nature and cannot produce analytical results to inform system effectiveness. In order to achieve the full benefit of the MBSE approach the systems engineering community must also rely on external models that capture more sophisticated analysis across a wide variety of domains. These domain models include simulations that measure operational effectiveness, life cycle costing models, physics-based computational simulations, manufacturing models, and many more. The purpose of this paper is to propose an approach that integrates these external simulation models with the MBSE integrated model using statistical metamodels that act as surrogates to the simulations. We demonstrate the approach using a simple system design problem and an agent-based simulation.