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Artificial Neural Network Prediction of Aluminium Metal Matrix Composite with Silicon Carbide Particles Developed Using Stir Casting Method

机译:搅拌铸造法开发的碳化硅颗粒铝基复合材料的人工神经网络预测

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摘要

Aluminium matrix composites (AMCs) are range of advanced engineering materials used for a wide range of applications. AMCs consist of a non-metallic reinforcement incorporated into Aluminium matrix providing advantageous properties over base metal alloys.udIn this paper, artificial neural network (ANN) is used to predict the micro-hardness, yield strength, tensile extension, modulus, ultimate tensile strength and stress, time to fracture, load at maximum extension, tenacity, electrical resistivity and conductivity. Information obtained from ANN model predictions can be used as guidelines during the conceptual design and optimisation of manufacturing processes; thus, reducing time and costs.
机译:铝基复合材料(AMC)是一系列用于各种应用的高级工程材料。 AMC由掺入铝基体的非金属增强材料组成,提供了优于贱金属合金的性能。 ud本文采用人工神经网络(ANN)预测了显微硬度,屈服强度,拉伸强度,模量,极限拉伸强度强度和应力,断裂时间,最大延伸载荷,强度,电阻率和电导率。从ANN模型预测中获得的信息可以在概念设计和制造过程优化过程中用作指导;因此,减少了时间和成本。

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