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.

提出了一种根据 Haakvort 方法量化聚合物热导率测量不确定性的新算法。这种使用差示扫描量热法的快速方便的方法已被确定为 DIN EN ISO 标准 11357-8，误差范围为 5-10%，考虑到这是许多应用的重要材料参数，这是一个相当大的值，并且是通常以组合量使用，例如热扩散率或热流出率。不幸的是，DIN EN ISO 标准没有提供有关误差范围对样本数量或重要参数（例如样本高度或其实际接触面积）的依赖性的有用信息。应用严格的统计方法，