There's no ‘I’ in SEAM—An Interim Report on the ‘Spacecraft Early Analysis Model’

摘要

Model-Based Systems Engineering (MBSE) represents a move away from the traditional approach of Document-Based Systems Engineering (DBSE), and is used to promote consistency, communication, clarity and maintainability within systems engineering projects. In previous work, industry focus groups have indicated that one way this can be achieved is by performing early functional validation of elements of the spacecraft avionics. This paper presents an extended approach, introduced in a case study previously published by the authors, to enable early functional analysis of a spacecraft. The approach uses the ‘Spacecraft Early Analysis Model’ (SEAM), a SysML-based model framework for the definition, development and analysis of a space-based mission and corresponding space system. This formal model-based representation of the system enables the high-level simulation of the design during Phase B of the spacecraft system lifecycle. The SEAM pulls together different, traditionally disparate, analysis tools and enables them to work together, producing an integrated system model spanning multiple tools. It facilitates the simulation of the mission using dedicated orbit modelling software, analysis of the completeness and accuracy of the system behaviour, and provides an indication of the appropriate logical architecture. The SEAM has been developed iteratively by applying it to Earth-observation case studies from the Biomass mission, refining the capabilities of the template accordingly, and subsequently generalising the model. The resulting interim version of the Spacecraft Early Analysis Model contains a series of MBSE patterns that will ultimately provide users with a comprehensive and consistent SysML-based structure that enables early functional definition and analysis of spacecraft. Next steps in the development of the SEAM include its application to a wider variety of use cases to develop and demonstrate its versatility, and the development of metrics to measure its perceived value among practitioners.