PERFORMANCE EVALUATION OF HYPERELASTIC MODELS FOR CARBON-BLACK–FILLED SBR VULCANIZATES

A Modified Constitutive Model for Isotropic Hyperelastic Polymeric Materials and Its Parameter Identification

Given the importance of hyperelastic constitutive models in the design of engineering components, researchers have been developing the improved and new constitutive models in search of a more accurate and even universal performance. Here, a modified hyperelastic constitutive model based on the Yeoh model is proposed to improve its prediction performance for multiaxial deformation of hyperelastic polymeric materials while retaining the advantages of the original Yeoh model. The modified constitutive model has one more correction term than the original model. The specific form of the correction term is a composite function based on a power function represented by the principal stretches, which is derived from the corresponding residual strain energy when the Yeoh model predicts the equibiaxial mode of deformation. In addition, a parameter identification method based on the cyclic genetic-pattern search algorithm is introduced to accurately obtain the parameters of the constitutive model. By applying the modified model to the experimental datasets of various rubber or rubber-like materials (including natural unfilled or filled rubber, silicone rubber, extremely soft hydrogel and human brain cortex tissue), it is confirmed that the modified model not only possesses a significantly improved ability to predict multiaxial deformation, but also has a wider range of material applicability. Meanwhile, the advantages of the modified model over most existing models in the literatures are also demonstrated. For example, when characterizing human brain tissue, which is difficult for most existing models in the literature, the modified model has comparable predictive accuracy with the third-order Ogden model, while maintaining convexity in the corresponding deformation domain. Moreover, the effective prediction ability of the modified model for untested equi-biaxial deformation of different materials has also been confirmed using only the data of uniaxial tension and pure shear from various datasets. The effective prediction for the untested equibiaxial deformation makes it more suitable for the practice situation where the equibiaxial deformation of certain polymeric materials is unavailable. Finally, compared with other parameter identification methods, the introduced parameter identification method significantly improves the predicted accuracy of the constitutive models; meanwhile, the uniform convergence of introduced parameter identification method is also better.

A comparative study of invariant-based hyperelastic models for silicone elastomers under biaxial deformation with the virtual fields method

Silicone elastomers have been widely used for biomedical applications. A variety of hyperelastic models have been proposed to describe this type of materials in the past few decades. The assessment of the quality of the proposed models is mostly based on stress-strain data obtained from uniform deformation, but very little work has been done to investigate model performances with heterogeneous deformation fields and full-field characterization methods. In this study, thirteen hyperelastic models are evaluated using the virtual fields method combined with full-field deformation data obtained from biaxial tests. The quality of these models is assessed by their capabilities to predict the mechanical responses of silicone elastomers, and the influences of the first and second invariants on modeling of elastomers are investigated through comparative studies between models. The results indicate that for elastomers under finite biaxial deformation, Yeoh model performs the best among selected models; the first invariant plays an important role in constitutive modeling; the second invariant does not have obvious influence on improving the fitting performance. This study provides a full-field method to calibrate and compare hyperelastic models of silicone elastomers under biaxial loading conditions.

Construction of a thermoreversible chemical crosslinking network – a new exploration for the efficient reusability of commercial rubber

A thermoreversible rubber DSBR was prepared via a reaction between a nitroxide-based crosslinker and commercial styrene–butadiene rubber. Impressive recoveries of mechanical properties of DSBR were achieved for the alkoxyamine crosslinking network.

ENTANGLED NETWORK INFLUENCED BY CARBON BLACK IN SOLUTION SBR VULCANIZATES REVEALED BY THEORY AND EXPERIMENT

The contribution of carbon black (CB) on changes in cross-link density (n) and physical entanglement has been quantified by swelling and uniaxial stress–strain measurements considering Mooney–Rivlin parameters. Solution SBR (SSBR) vulcanizates with varying content of high abrasion furnace (HAF) CB were studied. Rubber–filler networks increase the n values, which were determined by using Flory–Rehner and modified Guth–Gold equations by equilibrium swelling study. The Mooney–Rivlin parameter C1 was quantified using n, whereas parameter C2, representing physical entanglement, was determined for filled rubber by correlating with tensile results. The parameter C2 is monitored to be decreased with increasing CB (HAF) loading. A simple parabolic trend for physical entanglement parameter with increasing CB loading is proposed, and it shows a correlation coefficient (R2) of 0.99595. Atomic force microscopy study confirms the generation of filler networking in the rubber matrix. The current findings elucidate a way for quantifying physical network changes due to fillers in an unfilled rubber system.