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首页> 外文期刊>Journal of Engineered Fibers and Fabrics >Improving the Mechanical Properties of Wire-Rope Silk Scaffold by Artificial Neural Network in Tendon and Ligament Tissue Engineering
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Improving the Mechanical Properties of Wire-Rope Silk Scaffold by Artificial Neural Network in Tendon and Ligament Tissue Engineering

机译:用人工神经网络改善肌腱和韧带组织工程中钢丝丝支架的力学性能。

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摘要

Finding an appropriate model to assess and evaluate mechanical properties in tissue engineered scaffolds is a challenging issue. In this research, a structurally based model was applied to analyze the mechanics of engineered tendon and ligament. Major attempts were made to find the optimum mechanical properties of silk wire-rope scaffold by using the back propagation artificial neural network (ANN) method. Different samples of wire-rope scaffolds were fabricated according to Taguchi experimental design. The number of filaments and twist in each layer of the four layered wire-rope silk yarn were considered as the input parameters in the model. The output parameters included the mechanical properties which consisted of UTS, elongation at break, and stiffness. Finally, sensitivity analysis on input data showed that the number of filaments and the number of twists in the fourth layer are less important than other input parameters.
机译:寻找合适的模型来评估和评估组织工程支架的力学性能是一个具有挑战性的问题。在这项研究中,基于结构的模型被用于分析工程肌腱和韧带的力学。通过使用反向传播人工神经网络(ANN)方法,人们进行了重大尝试来寻找丝绳骨架的最佳机械性能。根据田口实验设计制造了不同的钢丝绳支架样品。在模型中,将四层钢丝丝纱线的每一层中的细丝数量和捻度视为输入参数。输出参数包括机械性能,其中包括UTS,断裂伸长率和刚度。最后,对输入数据的敏感性分析表明,第四层中的细丝数量和捻数不如其他输入参数重要。

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