如何使聚合物压力放松实验更具信息性
Anna Stankiewicz1, Sławomir Juściński2
1Department of Technology Fundamentals, Faculty of Production Engineering, University of Life Sciences in Lublin, 20-612 Lublin, Poland.
Polymers
|January 17, 2024
概括
这项研究引入了一种强大的方法,用于从应力松数据中识别聚合物粘弹性模型. 它可以独立于采样时间进行准确的模型选择,即使在噪音较大的测量中也是如此.
科学领域:
- 聚合物科学 聚合物科学
- 材料科学 材料科学 材料科学
- 类风病学 类风病学 类风病学
背景情况:
- 聚合物的机械性能是由粘弹性模型描述的,例如麦克斯韦和科尔劳施-威廉姆斯-瓦茨模型.
- 从实验数据中准确识别这些模型至关重要,但由于数据依赖性和噪音而具有挑战性.
研究的目的:
- 开发一种独立于采样时刻的方法来识别聚合物放松模量模型.
- 确保从噪声损坏的风湿学数据中识别模型的稳定性和准确性.
主要方法:
- 放松模块的加权最小平方近似值.
- 提霍诺夫规范化的应用,以解决错误的识别问题.
- 随机收分析和使用随机抽样实时的数值研究.
主要成果:
- 开发了一种识别算法,该算法产生了近似的最佳模型参数.
- 该方法在噪声损坏的数据中显示出强大的一致性和指数趋同率.
- 数字研究证实了非对称的时间即时独立模型的恢复.
结论:
- 拟议的识别方法,包括随机化和规范化,准确确定聚合物粘弹性模型.
- 这种方法提供了对测量噪声的稳定性和独立于采样策略的独立性.
- 它推进了聚合物机械行为的可靠表征.
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