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research article

Co-simulation of complex engineered systems enabled by a cognitive twin architecture

Li, Yuanfu
•
Chen, Jinwei
•
Hu, Zhenchao
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2022
International Journal Of Production Research

Since the complex engineered system involves multi-disciplinary, co-simulation is the key technique to the performance analysis. However, the co-simulation is hindered by heterogeneous sub-systems and ununified environments. In this paper, a Cognitive Twin (CT) to support the co-simulation of the complex engineered system is introduced. It is a generic approach that can be applied in many complex engineered systems such as the aerospace field, automotive system, the Internet of Things, manufacturing systems, etc. CT adopts an ontology model to develop cognition capability based on CT architecture. Then, a unified ontology modelling approach based on GOPPRR (graph, object, point, property, role, relationship) is presented to support an accurate semantic description of the topology between digital entities that use FMI 2.0 as the interconnection standard. Besides, four types of information are included in the ontology model to form the knowledge in co-simulation. Finally, the co-simulation is automatically executed using the cognition capability. Furthermore, a master-slave algorithm is deployed to establish a unified co-simulation environment. The flexibility of CT is evaluated using a gas turbine case. The results demonstrate that the complication in the co-simulation of complex engineered systems is solved by the unified ontology modelling approach and the architecture of CT.

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Type
research article
DOI
10.1080/00207543.2021.1971318
Web of Science ID

WOS:000695313300001

Author(s)
Li, Yuanfu
Chen, Jinwei
Hu, Zhenchao
Zhang, Huisheng
Lu, Jinzhi
Kiritsis, Dimitris  
Date Issued

2022

Publisher

TAYLOR & FRANCIS LTD

Published in
International Journal Of Production Research
Volume

60

Issue

24

Start page

7588

End page

7609

Subjects

Engineering, Industrial

•

Engineering, Manufacturing

•

Operations Research & Management Science

•

Engineering

•

co-simulation

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cognitive twin

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ontology model

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model based systems engineering

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semantic modeling

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knowledge management

•

ontology

•

framework

•

design

•

hla

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LICP  
Available on Infoscience
September 25, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/181643
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