Abstract

AbstractDigital engineering is the practice of creating repeatable frameworks to bring the power of automation and information technologies to complex systems. Model‐based systems engineering (MBSE) is an essential part of digital engineering by providing a roadmap for digitalization. Digital engineering and MBSE can be applied in a myriad of situations, one of which is for the development of digital twins for autonomous and remote control. Autonomous and remote operation of physical assets can provide numerous benefits to organizations and industries that deal with complex and distributed systems. The automation of the operation of a physical asset can be achieved through a digital twin, connected to the inputs and outputs of the asset and using machine learning (ML) and artificial intelligence (AI). Development of the digital twin requires understanding of systems interfaces and incorporating this understanding in digital systems. The effort described herein aims to determine the feasibility and benefit of such a process through the development and evaluation of a digital twin connected to a heat‐pipe test‐bed environment. Many challenges need to ultimately be addressed by a digital twin including data quality, infrastructure, privacy and security, and more. However, the focus of this paper will be on the application and use of digital engineering for the development of autonomous digital twins through a repeatable framework that can be applied across various domains and assets.

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