CFD results calibration from sparse sensor observations with a case study for indoor thermal map

Current CFD calibration work has mainly focused on the CFD model calibration. However no known work has considered the calibration of the CFD results. In this paper, we take inspiration from the image editing problem to develop a methodology to calibrate CFD simulation results based on sparse sensor...

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Bibliographic Details
Published inarXiv.org
Main Authors Jiang, Chaoyang, Yeng Chai Soh, Li, Hua, Masood, Mustafa K, Wei, Zhe, Zhou, Xiaoli, Zhai, Deqing
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 13.12.2016
Subjects
Air conditioners
Calibration
Computer simulation
Data points
Optimization
Sensors
Simulation
Thermal mapping
Thermal simulation
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Summary:Current CFD calibration work has mainly focused on the CFD model calibration. However no known work has considered the calibration of the CFD results. In this paper, we take inspiration from the image editing problem to develop a methodology to calibrate CFD simulation results based on sparse sensor observations. We formulate the calibration of CFD results as an optimization problem. The cost function consists of two terms. One term guarantees a good local adjustment of the simulation results based on the sparse sensor observations. The other term transmits the adjustment from local regions around sensing locations to the global domain. The proposed method can enhance the CFD simulation results while preserving the overall original profile. An experiment in an air-conditioned room was implemented to verify the effectiveness of the proposed method. In the experiment, four sensor observations were used to calibrate a simulated thermal map with 167x365 data points. The experimental results show that the proposed method is effective and practical.
ISSN:2331-8422