A new algorithm for uncertainty quantification for thermal conductivity measurement on polymers with the Haakvoort method using differential scanning calorimetry considering specimen height and real contact area

被引:0
作者
Harutyun Yagdjian
Simon Rommelfanger
Martin Gurka
机构
[1] Leibniz-Institut für Verbundwerkstoffe GmbH,
来源
SN Applied Sciences | 2023年 / 5卷
关键词
Differential scanning calorimetry (DSC); Thermal conductivity; Infrared thermography (IRT); Composite materials; Uncertainty quantification;
D O I
暂无
中图分类号
学科分类号
摘要
A new algorithm for the quantification of uncertainty in thermal conductivity measurements on polymers according to the Haakvort method is presented. This fast and convenient method using differential scanning calorimetry has been established as DIN EN ISO Standard 11357–8 with an error margin of 5–10%, which is a rather large value when considering that this is an important material parameter for many applications and is often used in combined quantities, such as thermal diffusivity or thermal effusivity. Unfortunately, the DIN EN ISO standard does not provide useful information on the dependence of the error range on the number of specimens or important parameters, such as the height of the specimens or their real contact area. Applying a rigorous statistical approach, based on the law of large numbers (LLN) and different techniques which are also used in well-known methods, such as Monte-Carlo- or Markov chain Monte Carlo (MCMC) algorithms, we establish and investigate a method to optimize the experimental effort to a specific target, especially the number of specimens, the aspect ratio and the real contact surface of the specimen.
引用
收藏
相关论文
共 20 条
  • [1] Hakvoort G(1985)Measurement of the thermal conductivity of solid substances by DSC Thermochim Acta 93 317-320
  • [2] Van Reijen LL(2009)Numerical simulation of thermal processes proceeding in a multi-layered film subjected to ultrafast laser heating J Theor Appl Mech 47 383-396
  • [3] Aartsen AJ(1966)Contact of nominally flat surfaces Proc R Soc Lond Ser A Math Phys Sci 295 300-319
  • [4] Majchrzak E(2013)How to determine the number of asperity peaks, their radii and their heights for engineering surfaces: a critical appraisal Wear 300 143-154
  • [5] Mochnacki B(2022)Optimal sparse polynomial chaos expansion for arbitrary probability distribution and its application on global sensitivity analysis Comput Methods Appl Mech Eng 399 115368-undefined
  • [6] Suchy JS(2021)Non-probabilistic uncertain inverse problem method considering correlations for structural parameter identification Struct Multidiscip Optim undefined undefined-undefined
  • [7] Greenwood JA(undefined)undefined undefined undefined undefined-undefined
  • [8] Williamson JBP(undefined)undefined undefined undefined undefined-undefined
  • [9] Pogačnik A(undefined)undefined undefined undefined undefined-undefined
  • [10] Kalin M(undefined)undefined undefined undefined undefined-undefined