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Characterisation of an airflow network model by sensitivity analysis : Parameter screening, fixing, prioritising and mapping

机译:通过敏感性分析表征气流网络模型:参数筛选,确定,确定优先级和映射

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摘要

Due to the over-parameterised models in detailed thermal simulation programs, modellers undertaking validation or calibration studies, where the model output is compared against field measurements, face dficulties in determining those parameters which are primarily responsible for observed diferences. Where sensitivity studies are undertaken, the Morris Method is commonly applied to identify the most influential parameters. They are often accompanied by uncertainty analysis using Monte Carlo simulations to generate confidence bounds around the predictions. This paper sets out a more rigorous approach to sensitivity analysis based on a global sensitivity analysis method with three stages: factor screening, factor prioritising and fixing, and factor mapping. The method is applied to a detailed empirical validation dataset obtained within IEA ECB Annex 58, with the focus of the study on the air flow network, a simulation program sub-model which is subject to large uncertainties in its inputs.
机译:由于详细的热仿真程序中的模型参数过大,建模人员进行了验证或校准研究,在此过程中将模型输出与现场测量结果进行比较,因此很难确定那些主要负责观察差异的参数。在进行敏感性研究的地方,通常使用莫里斯方法来确定最具影响力的参数。它们通常伴随着使用蒙特卡洛模拟的不确定性分析,以围绕预测生成置信区间。本文基于全局敏感性分析方法,通过三个阶段:因子筛选,因子优先级和固定以及因子映射,提出了一种更为严格的敏感性分析方法。该方法应用于在IEA ECB附件58中获得的详细的经验验证数据集,重点是气流网络的研究,该气流网络是一个模拟程序子模型,其输入数据存在较大不确定性。

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