Chapter 2 Historical Perspective of the Development of Digital Twins Matthew S. Bonney and David Wagg Abstract With modern advances in high-performance computing, design engineers have put a large focus on digital testing and simulations to inform new systems. In addition, recent market tendencies show a desire to reduce waste and for longer designed life. One major strategy used to meet these trends is the utilization of a digital twin. Digital twins are numerical analogues to physical systems such as aircraft, auto-mobiles, and power generation systems. With the wide applicability of the digital twin, an understanding of their development can give insight into the impact and direction of recent research. Understanding these advancements can also give confidence in both the technique of using a digital twin and the simulated predictions to various loading conditions. This chapter focuses on detailing the historical development of digital twins to the state-of-the-art research being done and specifically how it is relevant to the structural dynamics community. 2.1 Background Using computational models to simulate physical phenomena is by no means novel. Recently, however, there has been an increase in desire to integrate the computational models into the design process. Additionally, there is an increased need to expand the models to be accurate for the life cycle of a system. This is where the concept of twinning, especially digital twins, originates and the main motivation of recent research. The discussion of integrating a twin into designs dates back to NASA’s Apollo mission [1]. The twin for the NASA Apollo mission incorporated a physical cockpit to use during training and diagnostic testing. The nomenclature of digital twin is based on the work in product life-cycle management [2]. This was first published in the ASME Standard for Verification and Validation (V&V) in Computational Solid Mechanics (ASME V&V 10) [3]. In the ASME standard, a digital twin is defined as “Digital Twin is an integrated multiphysics, multiscale simulation of a vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin.” A common generalization of this definition is the use of the term physical twin instead of flying twin to incorporate non-aerospace systems. From this definition, there are a few main aspects, first being the multiphysics and multiscale simulations. The majority of the digital twins incorporate multiphysics, such as structural and fluid dynamics (such as aerodynamic pressures on an aircraft during flight). Using multiscale simulations, however, seems to be more flexible depending on the physical twin. For industrial systems, the multiscale aspects are typically included; however, academic systems do not tend to have multiscale since they can be designed to only contain a single length scale of importance. A second aspect of this definition is the incorporation of “physical models, sensor updates and fleet history.” This included model updating, grey-box modeling (combination of computational models and sensor data), and pure sensor-based models. The last aspect is the ability to “mirror the life of the flying twin.” Around the same time as the ASME standard was published, several other terms have been used to describe identical or similar ideas. For example, Digital Counterpart [4], Virtual Engine [5], Intelligent Prognostic Tools [6], and Mirrors [7] to mention a few. Many of these alternative names tend to focus on either a specific type of physics (electrical or hydraulic, for example), scale, or specifying computational/sensor-based models only. The term digital twin captures the underlying meaning for these systems and allows for a better understanding for a general audience. This chapter discusses some usages of the digital twins and describes different types of digital twins. Section 2.2.1 discusses how digital twins are used in the design of a new system, and Sect. 2.2.2 discusses the utilization during the M. S. Bonney ( ) · D.Wagg Dynamics Research Group, Department of Mechanical Engineering, University of Sheffield, Sheffield, UK e-mail: david.wagg@sheffield.ac.uk © The Society for Experimental Mechanics, Inc. 2022 D. S. Epp (ed.), Special Topics in Structural Dynamics & Experimental Techniques, Volume 5, Conference Proceedings of the Society for Experimental Mechanics Series, https://doi.org/10.1007/978-3-030-75914-8_2 15
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