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A digital twin (DT) is an interactive, real-time digital representation of a system or a service utilizing onboard sensor data and Internet of Things (IoT) technology to gain a better insight into the physical world. With the increasing complexity of systems and products across many sectors, there is an increasing demand for complex systems optimization. Digital twins vary in complexity and are used for managing the performance, health, and status of a physical system by virtualizing it. The creation of digital twins enabled by Modelbased Systems Engineering (MBSE) has aided in increasing system interconnectivity and simplifying the system optimization process. More specifically, the combination of MBSE languages, tools, and methods has served as a starting point in developing digital twins. This article discusses how MBSE has previously facilitated the development of digital twins across various domains, emphasizing both the benefits and disadvantages of adopting an MBSE enabled digital twin creation. Further, the article expands on how various levels of digital twins were generated via the use of MBSE. An MBSE enabled conceptual framework for developing digital twins is identified that can be used as a research testbed for developing digital twins and optimizing systems and system of systems. Keywords—MBSE, Digital Twin, Digital Shadow, Digital Model, SysML
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Digital Twin Modelling of Cascaded Amplifiers in the COSMOS Testbed
Digital twins provide a cost-effective means of evaluating performance, predicting network changes, and enhancing network administration and decision-making processes. However, acquiring detailed data for digital twin development remains a challenge due to commercial system constraints. City-scale testbeds, like COSMOS, offer practical solutions, aiding in data collection for modelling of digital twins. In this paper, we utilize data from experiments on the COSMOS testbed to design a digital twin model for the accumulation of gain ripple in cascaded Erbium-doped fiber amplifiers (EDFAs). We quantify the gain ripple in terms of its peak-to-valley ratios and identify optimal EDFA combinations. Moreover, we explore the impact of system parameters, and validate the proposed digital model through comparison with experimental results. We show that the differences between the digital twin predictions and experimental results are <0.1 dB.
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- PAR ID:
- 10546532
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-0767-2
- Page Range / eLocation ID:
- 1 to 6
- Subject(s) / Keyword(s):
- Digital twins EDFA gain ripple COSMOS testbed
- Format(s):
- Medium: X
- Location:
- Jaipur, India
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ANTS59832.2023.10468684
