Dataset for Validating Complex Ventilation Flow Simulations: Postprocessing and Analysis using Bootstrapping

Eugene Mamulova, Douaa Al Assaad-Merema, Twan van Hooff

Research output: Contribution to conferencePaperAcademic

Abstract

There are almost no datasets available to individuals who seek to validate numerical simulations of complex ventilation flows. This research constitutes a preliminary step towards the creation of such a dataset. In this study, several air temperature datapoints, measured in a classroom equipped with displacement ventilation, are processed with the aim of obtaining a time-averaged value for every measurement point. Using the mean temperature values, the resultant temperature field is analysed. The study showcases the use of bootstrapping as a means of estimating the uncertainty of the mean temperature. In addition, the study identifies flow phenomena that are characteristic of displacement ventilation, such as thermal stratification. The temperature values obtained can be used to validate time-averaged numerical simulations, such as Reynolds-averaged Navier–Stokes simulations, of complex displacement ventilation cases involving multiple heat and carbon dioxide sources. The results show that bootstrapping with replacement is a useful method for estimating the uncertainty of the mean temperature. Work on the dataset is currently ongoing and will be extended using air velocity and carbon dioxide concentration measurements, in the interest of compiling a large dataset for simulating complex indoor phenomena.
Original languageEnglish
Number of pages8
Publication statusPublished - 11 Jun 2023

Keywords

  • validation data, displacement ventilation, indoor flows, field measurements, bootstrapping

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