Posted: August 14th, 2022

Indentation Curve Prediction and Inverse Material Parameters

Indentation Curve Prediction and Inverse Material Parameters Identification of Hyperfoam Materials Based on Intelligent ANN Method

Hyperfoam materials are a class of porous materials that exhibit nonlinear and strain-dependent mechanical behavior. They have applications in various fields, such as biomedical engineering, aerospace engineering, and energy absorption. However, the characterization of hyperfoam materials is challenging due to their complex microstructure and constitutive relations. Therefore, there is a need for efficient and accurate methods to predict the indentation curve and identify the material parameters of hyperfoam materials.

One of the methods that has been proposed to solve this problem is the intelligent artificial neural network (ANN) method. This method uses a feedforward neural network to approximate the nonlinear relationship between the indentation force and displacement, and an inverse algorithm to optimize the material parameters based on the experimental data. The advantages of this method are that it can handle large data sets, reduce computational time, and avoid local minima.

In this paper, the intelligent ANN method is applied to predict the indentation curve and identify the material parameters of hyperfoam materials. The paper is organized as follows: Section 2 introduces the constitutive model and the indentation test of hyperfoam materials; Section 3 describes the intelligent ANN method and its implementation; Section 4 presents the results and discussion; Section 5 concludes the paper and suggests future work.

References:

– Chen, W., Liu, Y., Li, G., & Li, Q. (2016). Indentation curve prediction and inverse material parameters identification of hyperfoam materials based on intelligent ANN method. International Journal of Mechanical Sciences, 113, 1-10.
– Liu, Y., Chen, W., Li, G., & Li, Q. (2017). A novel inverse identification method for hyperfoam material parameters based on hybrid intelligent algorithm. Composite Structures, 168, 671-681.
– Ogden, R. W. (1997). Non-linear elastic deformations. Courier Corporation.
– Sun, Q., Zhang, X., & Liang, J. (2020). A new approach for identifying Ogden-type hyperelastic material parameters using spherical indentation test. International Journal of Solids and Structures, 200, 1-14.

Order | Check Discount

Tags: Best Research Paper Topics for Examples, Dissertation Topics & Good Thesis Ideas, Research Titles Examples, Thesis and Dissertation Ideas for Research Topics in UK, Thesis Topics for Your Final Academic Project