Improving the Mechanical Properties of Wire-Rope Silk Scaffold by Artificial Neural Network in Tendon and Ligament Tissue Engineering

Abstract

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.