Abstract

An inverse procedure was proposed to identify the material parameters of polyurea materials. In this procedure, a polynomial hyperelastic model was chosen as the constitutive model. Both uniaxial tension and compression tests were performed for a polyurea. An iterative inverse method was presented to identify parameters for the tensile performance of the polyurea. This method adjusts parameters iteratively to achieve a good agreement between tensile forces from the tension test and its finite element (FE) model. A response surface-based inverse method was presented to identify parameters for the compression performance of the polyurea. This method constructs a radial basis function (RBF)-based response surface model for the error between compressive forces from the compression test and its FE model, and it employs the genetic algorithm to minimize the error. With the use of the two inverse methods, two sets of parameters were obtained. Then, a complete identified uniaxial stress–strain curve for both tensile and compressive deformations was obtained with the two sets of parameters. Fitting this curve with the constitutive equation gave the final material parameters. The present inverse procedure can simplify experimental configurations and consider effects of friction in compression tests. Moreover, it produces material parameters that can appropriately characterize both tensile and compressive behaviors of the polyurea.

Highlights

  • The remainder of the paper is organized as follows: Section 2 briefs the constitutive model used for polyurea materials; Section 3 details the identification of material parameters for the tensile performance of a polyurea; Section 4 details the identification of material parameters for the compressive performance of the polyurea; Section 5 presents the determination and validation of material parameters that can appropriately characterize both tensile and compressive performance; the last section draws the main conclusions of this work

  • The material parameters for tensile performance were obtained with an iterative inverse method, and the material parameters for compressive performance were determined with a response surface-based inverse method

  • Through the examination of material behaviors in a large strain range, it was found that tensile parameters cannot be extended to describe compressive behaviors and vice versa

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Bai et al [10] established a hyper-viscoelastic constitutive model to characterize the material behavior of polyurea subjected to uniaxial compressive loading. Guo et al [11] developed a visco-hyperelastic constitutive model to describe the mechanical behavior of a polyurea material and validated its effectiveness for different loading conditions and strain rates. Material parameters in constitutive models of polyurea have generally been obtained by directly fitting stress–strain curves derived from standard tests, such as the uniaxial tension test and compression test. In most previous studies, material parameters for polyurea have been determined by either a tension or compression test. They may be only applicable to special loading conditions, for example, tension or compression loading only. The remainder of the paper is organized as follows: Section 2 briefs the constitutive model used for polyurea materials; Section 3 details the identification of material parameters for the tensile performance of a polyurea; Section 4 details the identification of material parameters for the compressive performance of the polyurea; Section 5 presents the determination and validation of material parameters that can appropriately characterize both tensile and compressive performance; the last section draws the main conclusions of this work

Constitutive Model for Polyurea
Uniaxial Tension Test
Inverse Parameter Identification
Uniaxial Compression Test
Material Parameters Characterizing Both Tensile and Compressive Performance
Conclusions
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