This work presents a new application of decay heat measurement based on the calibration and inverse uncertainty quantification (IUQ) of modeling parameters of pressurized water reactor (PWR) fuel assemblies. This work (i) solves the problem encountered in forward UQ i.e., the lack of fuel vendor proprietary information (manufacturing tolerances of fuel assembly design) and operating condition uncertainties which are based on ad-hoc expert judgement or personal opinion (ii) calibrates the parameters of a fuel assembly model for improved code calculation-to-experiment agreement. The IUQ is conducted under the Bayesian framework and finds the fuel assembly model parameters that are consistent with decay heat measurements. The forward model implements a polynomial chaos expansion (PCE) based surrogate model for a computationally efficient inverse analysis. The approach introduced is then tested with the decay heat calculations of the deterministic code STREAM. Eight input parameters: fuel density, enrichment, pellet radius, clad outer radius, fuel temperature, power density, moderator temperature and boron concentration, are considered. The outcomes of this work include quantification of uncertainties and determination of probability distribution function (PDF) of these parameters, in addition to reducing code calculation-to-experiment discrepancies. These outcomes are important for future studies on the forward propagation of model parameters uncertainties.

这项工作提出了基于压水堆（PWR）燃料组件建模参数的校准和逆不确定性量化（IUQ）的衰减热测量的新应用。这项工作（i）解决了前向UQ i中遇到的问题。（e）缺乏基于临时专家判断或个人意见的燃料供应商专有信息（燃料组件设计的制造公差）和操作条件不确定性（ii）校准燃料组件模型的参数，以改善代码计算与实验的一致性。IUQ在贝叶斯框架下进行，并找到与衰变热测量值一致的燃料组件模型参数。前向模型实现了基于多项式混沌扩展（PCE）的替代模型，以实现高效计算的逆分析。然后使用确定性代码STREAM的衰减热计算对引入的方法进行测试。考虑了八个输入参数：燃料密度，富集度，颗粒半径，包层外半径，燃料温度，功率密度，调节剂温度和硼浓度。这项工作的结果包括量化不确定性和确定这些参数的概率分布函数（PDF），除了减少代码计算与实验的差异。这些结果对于模型参数不确定性的正向传播的未来研究很重要。