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Keywords = semiconductor bridge (SCB)

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9 pages, 2231 KiB  
Article
Modeling the Heating Dynamics of a Semiconductor Bridge Initiator with Deep Neural Network
by Jianbing Xu, Jimin Tan, Hanshi Li, Yinghua Ye and Di Chen
Micromachines 2022, 13(10), 1611; https://doi.org/10.3390/mi13101611 - 27 Sep 2022
Cited by 1 | Viewed by 2090
Abstract
A semiconductor bridge (SCB) is an ignition device that provides a safe and efficient method widely used in civilian and military fields. The heating process of an SCB under electrical stimulation has a wide range of applications owing to its unique energy release [...] Read more.
A semiconductor bridge (SCB) is an ignition device that provides a safe and efficient method widely used in civilian and military fields. The heating process of an SCB under electrical stimulation has a wide range of applications owing to its unique energy release process. However, the temperature variation of an SCB is challenging to obtain, both experimentally because of the rapid reaction on a microscale and with simulation due to its high demand in nonlinear calculations. In this study, we propose deep learning (DL) approach to study the electrothermal-coupled multi-physical heating process of the SCB initiator. We generated training data with multi-physics simulation (MPS), producing surface temperature distributions of SCBs under different voltages. The model was then trained with partial data in this database and evaluated on a separate test set. A generative adversarial network (GAN) with a customized loss function was used for modeling point-wise temperature dynamics. In the test set, our proposed method can predict the temperature distribution of an SCB under different voltages with high accuracy of over 0.9 during the heating process. We reduced the computation time by several orders of magnitude by replacing MPS with a deep neural network. Full article
(This article belongs to the Special Issue Machine-Learning-Assisted Sensors)
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