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一种改进预测精度的新的固体非线性黏弹性模型和数学解法。

A new nonlinear viscoelastic model and mathematical solution of solids for improving prediction accuracy.

机构信息

School of Civil Engineering, Yango University, Fuzhou, 350015, China.

Oden Institute for Computational Engineering and Sciences, the University of Texas at Austin, Austin, TX, 78712, USA.

出版信息

Sci Rep. 2020 Feb 10;10(1):2202. doi: 10.1038/s41598-020-58240-y.

Abstract

We developed an innovative material nonlinear viscoelastic model with physical mechanism and mathematical solution to improve existing ones. The relaxation modulus transits from the glassy stage to the rubbery stage through a time-dependent viscosity in a continuous spectrum considering the nonlinear strain hardening. Experimental results of differential solid materials including asphalt concrete, agarose gel, vaginal tissue, polymer, agar, bone, spider silk, and hydrogel demonstrate that the developed model is superior to generalized Maxwell model or Prony series for more accurate prediction outside of the range for data fitting while using much less model parameters. Numerical simulation results indicate that the new model has improved accuracy. It is stable numerically, and does not reduce computation speed. Therefore, the model may be used to simulate a broad range of viscoelastic solids for predicting experimental data and responses with improved accuracy.

摘要

我们开发了一种具有物理机制和数学解的创新材料非线性黏弹性模型,以改进现有模型。考虑到非线性应变硬化,通过连续谱中的时变粘度,使松弛模量从玻璃态转变为橡胶态。包括沥青混凝土、琼脂糖凝胶、阴道组织、聚合物、琼脂、骨、蜘蛛丝和水凝胶在内的微分固体材料的实验结果表明,与广义 Maxwell 模型或 Prony 级数相比,该模型在数据拟合范围之外具有更准确的预测能力,同时使用的模型参数更少。数值模拟结果表明,新模型具有更高的准确性。它在数值上是稳定的,不会降低计算速度。因此,该模型可用于模拟广泛的黏弹性固体,以提高准确性来预测实验数据和响应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/faba/7010732/819438930661/41598_2020_58240_Fig1_HTML.jpg

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