Beartooth: Nuclear material testbed with MBSE and digital twin

Abstract

AbstractDigital engineering can fundamentally change the construction and operation of complex projects. Traditional engineering teams operate in siloed tools and disparate teams. Throughout a project lifecycle, data is translated manually or over brittle point‐to‐point connections, which increases the risk of silent errors. These potential errors can cascade across the effort, resulting in significant project delays and cost overruns. Furthermore, traditional engineering projects are not designed for the rapid digitization that allows for advanced analytic tools. Digital engineering can create a cohesive data “source of truth” to ensure a project is designed for the digital future. There is a need for a standard toolset to normalize and integrate project datasets. Idaho National Laboratory (INL) has developed DeepLynx, a crucial tool to mitigate this data management problem. This paper introduces INL's digital engineering approach and provides a concrete example of a digital engineering design effort currently taking place with Beartooth, a new nuclear material processing testbed project. This paper will provide the benefits, challenges, and lessons learned in using digital engineering on this complex system. The digital engineering approach is utilizing model‐based systems engineering, extended reality, and a digital twin. Finally, this paper will discuss the new possibilities provided by using a digital thread and twin during future operation of a nuclear fuel cycle testbed.