Quantifying uncertainty in thermophysical properties of walls by means of Bayesian inversion
Quantifying uncertainty in thermophysical properties of walls by means of Bayesian inversion
复制标题
通过贝叶斯反演量化墙体热物理特性的不确定性
DOI：
10.1016/j.enbuild.2018.06.045
复制
发表时间：
2017
影响因子：
6.7
通讯作者：
C. Wood
中科院分区：
文献类型：
--
作者：
Lia De Simon;M. Iglesias;B. Jones;C. Wood
我们引入了一个计算框架，从现场测量的空气温度和表面热通量的统计推断任何给定的墙壁的热物理性质。所提出的框架使用这些测量，在贝叶斯校准方法，顺序推断输入参数的一维热扩散模型，描述了热性能的墙壁。这些输入包括空间可变的函数，其表征壁的热导率和体积热容。我们编码我们的计算框架中的算法，顺序更新我们的概率知识的热物理性质的新的测量变得可用，从而使这些属性的动态不确定性量化。此外，所提出的算法使我们能够调查的影响的离散化的基本热扩散模型的热物理性质和相应的预测分布的热通量的估计的准确性。通过虚拟/合成和真实的实验，我们展示了所提出的方法的能力：（i）分析与未知腔和绝缘体相关的非均匀热物理性质;（ii）获得有效热性质的快速准确的不确定性估计（例如热透射率）;以及（iii）精确地计算壁的热性能的统计描述，反过来，在评估可能的改造措施方面至关重要。
We introduce a computational framework to statistically infer thermophysical properties of any given wall from in-situ measurements of air temperature and surface heat fluxes. The proposed framework uses these measurements, within a Bayesian calibration approach, to sequentially infer input parameters of a one-dimensional heat diffusion model that describes the thermal performance of the wall. These inputs include spatially-variable functions that characterise the thermal conductivity and the volumetric heat capacity of the wall. We encode our computational framework in an algorithm that sequentially updates our probabilistic knowledge of the thermophysical properties as new measurements become available, and thus enables an on-the-fly uncertainty quantification of these properties. In addition, the proposed algorithm enables us to investigate the effect of the discretisation of the underlying heat diffusion model on the accuracy of estimates of thermophysical properties and the corresponding predictive distributions of heat flux. By means of virtual/synthetic and real experiments we show the capabilities of the proposed approach to (i) characterise heterogenous thermophysical properties associated with, for example, unknown cavities and insulators; (ii) obtain rapid and accurate uncertainty estimates of effective thermal properties (e.g. thermal transmittance); and (iii) accurately compute an statistical description of the thermal performance of the wall which is, in turn, crucial in evaluating possible retrofit measures.
树脂传递模塑中的贝叶斯反演
影响因子：
2.1
作者：
Iglesias M
通讯作者：
Iglesias M
英国实墙住宅的改造解决方案：不确定性对能源性能差距的影响
影响因子：
1.7
作者：
Loucari C
通讯作者：
Loucari C