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Data-Driven Non-intrusive Reduced-Order Modeling Framework for Multiphysics Digital Twin Models of Large-Scale Electronic Devices
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DOI：10.23919/cje.2025.00.110.png)
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Abstract
En 中文
This paper proposes a novel non-intrusive reduced-order modeling framework to implement the multiphysics digital twin modeling of large-scale electronic devices. In this framework, a non-intrusive model order reduction technique is used to project the full-order model onto a low-dimensional subspace to obtain a non-intrusive predictive reduced-order model, namely the digital twin model. To efficiently decompose the large-scale matrices, an improved singular value decomposition approach is adopted to achieve an acceleration of 2 to 3 orders of magnitude. Meanwhile, a dynamic model correction approach is proposed to improve the long-term prediction of digital twin models, by combining a proper orthogonal decomposition basis update approach with operator inference method. The proposed modeling framework is first used to build a thermomechanical digital twin model of a 2.5-dimensional integrated packaging. Compared with the full-order model, the simulation efficiency of the digital twin model is improved by more than 3 orders of magnitude while keeping the relative mean square error (RMSE) of temperature and stress prediction less than 0.5% and 4%, respectively. Further, compared with traditional model order reduction techniques, digital twin models built using the proposed ones have higher prediction accuracy, especially in long-term prediction applications. At last, a thermal test module is designed, and its thermal digital model and online monitoring system prototype are built. The RMSE of predicted real-time temperature of the thermal digital twin model is smaller than 0.4% compared with the online monitoring results at the test points.
Keywords:
Central Processing Unit
Circuits
Circuits and systems
Integrated circuits
MIMICs
Power dissipation
Chiplets
Diodes
Printed circuits
Kalman filters
Non-intrusive reduced-order model
Dynamic model correction approach
Operator inference
Multiphysics digital twin model
Online monitoring
Journal
C
IF:
3
Papers:
62
Citations:
1.7K
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