首页> 美国卫生研究院文献>Materials >Finite Element Model Updating Combined with Multi-Response Optimization for Hyper-Elastic Materials Characterization
【2h】

Finite Element Model Updating Combined with Multi-Response Optimization for Hyper-Elastic Materials Characterization

机译:有限元模型更新与多响应优化相结合的超弹性材料表征

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

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 Ci 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 Ci 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 Ci 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 Ci 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 Ci 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 Ci 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 Ci 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 Ci constants of any type of elastomer than other more sophisticated methods.
机译:通常使用来自拉伸,平面应力,压缩,体积压缩和剪切的标准化测试的实验应力-应变曲线来获得材料Ci的不变λi和常数,以定义行为弹性体。获得这些实验曲线需要使用昂贵且复杂的实验设备。多年来,一直使用一种称为模型更新的直接方法,该方法基于参数化有限元(FE)模型和实验力-位移曲线的组合,该方法比应力-应变曲线更简单且更经济,用于获得Ci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当标准化测试的数量和所需的Ci常数很高时,模型更新具有需要高计算成本的缺点。本文提出了一种方法,该方法将模型更新方法,上述标准化测试以及具有期望功能的多响应表面方法(MRS)结合在一起,可以自动确定最合适的Ci常数,以对一组弹性体的行为进行建模。对于每个标准化测试,均生成二次回归模型以对误差函数(ER)进行建模,该误差函数表示通过实验获得的力-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。考虑到所有标准化测试的重要性相同,使用期望函数执行调整每个Ci常数的过程。作为一个实际的例子,使用以下弹性体对提出的方法进行了验证:丁腈橡胶(NBR),乙烯乙酸乙烯酯(EVA),丁苯橡胶(SBR)和聚氨酯(PUR)。 Mooney–Rivlin,Ogden,Arruda–Boyce和Gent被认为是用于建模上述弹性体力学行为的超弹性模型。调整Ci参数后,验证结果表明Mooney-Rivlin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,NBR的MAEnorm = 0.127,MEnorm = 0.116)。 EVA和MAEnorm = 0.061(对于NBR)。在Ci常数的调整中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更简单,更经济的替代方法,可用于获取任何类型的最佳Ci常数。弹性体比其他更复杂的方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号