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Effect of an Insulation Layer to Prevent Water Vapor Condensation along the Inside Surface of a Building Wall Using an Artificial Neural Network

机译:隔热层通过人工神经网络防止沿建筑物内壁的水蒸气凝结的作用

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摘要

A theoretical analysis was performed to study the attenuation of a heat wave through two composite walls. Each wall was made of three homogenous layers in addition to an insulation layer, all of which were made of local materials. One way to attenuate this heat wave was to apply insulation inside the wall. In this work, an artificial neural network (ANN) was developed to study the effect of insulation materials on a building wall through a four-layered wall. The layer material type, the layer thickness, and the inside and outside temperature were used in the input layer of the network, whereas the temperature distribution was in the output layer of the network. Data that were obtained from previous experiments were used to train the neural network. It was found that the algorithm used (Levenberg-Marquardt) was very much capable of estimating the temperature distribution within each of the four-layered walls with excellent accuracy.
机译:进行了理论分析以研究通过两个复合壁的热波的衰减。除了绝缘层外,每个壁还由三个均质层制成,所有均由局部材料制成。衰减此热波的一种方法是在墙内施加绝缘。在这项工作中,开发了一个人工神经网络(ANN),以研究隔热材料通过四层墙对建筑物墙壁的影响。在网络的输入层中使用层材料类型,层厚度以及内部和外部温度,而在网络的输出层中使用温度分布。从以前的实验中获得的数据用于训练神经网络。结果发现,所使用的算法(Levenberg-Marquardt)非常有能力以极高的精度估算每层四层墙内的温度分布。

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