Kozanecki Damian, Kowalczyk Izabela, Krasoń Sylwia, Rabenda Martyna, Domagalski Łukasz, Wirowski Artur
Department of Structural Mechanics, Lodz University of Technology, Politechniki 6, 93-590 Lodz, Poland.
Department of Concrete Structures, Lodz University of Technology, Politechniki 6, 93-590 Lodz, Poland.
Materials (Basel). 2023 Jul 17;16(14):5055. doi: 10.3390/ma16145055.
The VIG (Vacuum Insulated Glazing) unit, composite glazing in which the space between glass panes is filled with vacuum, is one of the most advanced technologies. The key elements of the construction of VIG plates are the support pillars. Therefore, an important issue is the analysis of their mechanical properties, such as Young's modulus and their variability over a long period of time. Machine learning (ML) methods are undergoing tremendous development these days. Among the many different techniques included in AI, neural networks (NN) and extreme gradient boosting (XGB) algorithms deserve special attention. In this study, to train selected methods of machine learning, numerical data developed in the VIG plate modelling process using Abaqus program were used. The test method proposed in this article is based on the VIG plate subjected to forced vibrations of specific frequencies and then the reading of the dynamic response of the composite plate. Such collected and pre-developed experimental data were used to obtain the mechanical parameters of the steel elements located inside the analysed vacuum glazing. In the future, the proposed research methods can be used to analyse the mechanical properties of other types of composite panels.
真空隔热玻璃（VIG）单元，即玻璃面板之间的空间填充有真空的复合玻璃，是最先进的技术之一。VIG板结构的关键要素是支撑柱。因此，一个重要问题是分析它们的力学性能，如杨氏模量及其在长时间内的变化情况。如今，机器学习（ML）方法正在经历巨大的发展。在人工智能所包含的众多不同技术中，神经网络（NN）和极端梯度提升（XGB）算法值得特别关注。在本研究中，为了训练选定的机器学习方法，使用了在使用Abaqus程序进行VIG板建模过程中生成的数值数据。本文提出的测试方法基于对VIG板施加特定频率的强迫振动，然后读取复合板的动态响应。这样收集并预先开发的实验数据被用于获取分析的真空玻璃内部钢构件的力学参数。未来，所提出的研究方法可用于分析其他类型复合板的力学性能。
