Íñiguez-Macedo Saúl, Lostado-Lorza Rubén, Escribano-García Rubén, Martínez-Calvo María Ángeles
Department of Mechanical Engineering, University of La Rioja, 26004 Logroño, La Rioja, Spain.
IK4-LORTEK, 20240 Ordizia, 20240 Guipuzcoa, Spain.
Materials (Basel). 2019 Mar 27;12(7):1019. doi: 10.3390/ma12071019.
The experimental stress-strain curves from the standardized tests of Tensile, Plane Stress, Compression, Volumetric Compression, and Shear, are normally used to obtain the invariant λi and constants of material C that will define the behavior elastomers. Obtaining these experimental curves requires the use of expensive and complex experimental equipment. For years, a direct method called model updating, which is based on the combination of parameterized finite element (FE) models and experimental force-displacement curves, which are simpler and more economical than stress-strain curves, has been used to obtain the C constants. Model updating has the disadvantage of requiring a high computational cost when it is used without the support of any known optimization method or when the number of standardized tests and required C constants is high. This paper proposes a methodology that combines the model updating method, the mentioned standardized tests and the multi-response surface method (MRS) with desirability functions to automatically determine the most appropriate C constants for modeling the behavior of a group of elastomers. For each standardized test, quadratic regression models were generated for modeling the error functions (ER), which represent the distance between the force-displacement curves that were obtained experimentally and those that were obtained by means of the parameterized FE models. The process of adjusting each C constant was carried out with desirability functions, considering the same value of importance for all of the standardized tests. As a practical example, the proposed methodology was validated with the following elastomers: nitrile butadiene rubber (NBR), ethylene-vinyl acetate (EVA), styrene butadiene rubber (SBR) and polyurethane (PUR). Mooney⁻Rivlin, Ogden, Arruda⁻Boyce and Gent were considered as the hyper-elastic models for modeling the mechanical behavior of the mentioned elastomers. The validation results, after the C parameters were adjusted, showed that the Mooney⁻Rivlin model was the hyper-elastic model that has the least error of all materials studied (MAEnorm = 0.054 for NBR, MAEnorm = 0.127 for NBR, MAEnorm = 0.116 for EVA and MAEnorm = 0.061 for NBR). The small error obtained in the adjustment of the C constants, as well as the computational cost of new materials, suggests that the methodology that this paper proposes could be a simpler and more economical alternative to use to obtain the optimal C constants of any type of elastomer than other more sophisticated methods.
拉伸、平面应力、压缩、体积压缩和剪切等标准化试验的实验应力-应变曲线通常用于获取不变量λi和材料常数C,这些将定义弹性体的行为。获取这些实验曲线需要使用昂贵且复杂的实验设备。多年来,一种称为模型更新的直接方法,它基于参数化有限元(FE)模型与实验力-位移曲线的结合,比应力-应变曲线更简单且更经济,已被用于获取C常数。当模型更新在没有任何已知优化方法支持的情况下使用,或者标准化试验的数量和所需的C常数数量很多时,它具有计算成本高的缺点。本文提出了一种方法,该方法将模型更新方法、上述标准化试验和具有合意函数的多响应面方法(MRS)相结合,以自动确定用于对一组弹性体的行为进行建模的最合适的C常数。对于每个标准化试验,生成二次回归模型以对误差函数(ER)进行建模,误差函数表示实验获得的力-位移曲线与通过参数化有限元模型获得的力-位移曲线之间的距离。使用合意函数进行每个C常数的调整过程,对所有标准化试验考虑相同的重要性值。作为一个实际例子,用以下弹性体对所提出的方法进行了验证:丁腈橡胶(NBR)、乙烯-醋酸乙烯酯(EVA)、丁苯橡胶(SBR)和聚氨酯(PUR)。将穆尼-里夫林、奥格登、阿鲁达-博伊斯和根特模型视为用于对上述弹性体的力学行为进行建模的超弹性模型。在调整C参数后,验证结果表明,穆尼-里夫林模型是所有研究材料中误差最小的超弹性模型(NBR的MAEnorm = 0.054,EVA的MAEnorm = 0.127,EVA的MAEnorm = 0.116,NBR的MAEnorm = 0.061)。在调整C常数时获得的小误差以及新材料的计算成本表明,本文提出的方法可能是一种比其他更复杂的方法更简单、更经济的替代方法,用于获得任何类型弹性体的最佳C常数。