Study On Transition Season’s Window-opening Behaviorin Chongqing Based On Montecarlo Method

Ventilation is a most common way to change the indoor environment. Ventilationby opening windows can take advantage of the outdoor cooler fresh air to improveindoor thermal and humidityenvironment and air quality.And ventilation can reducebuilding energy consumptiontosomeextent. Therefore, knowing the regularpattern ofthewindow-openingis of great significance to understand the indoor air quality, thermalcomfort and energy conservation effect assessment.However, the window-opening behavior is associated with many factors, not onlythe objective factors, such as human thermal comfort, indoor air quality, but also mentaland physical subjective feelings. Giventheabove reason, the window-openingbehaviorisvery randomand accompanied with considerable uncertainty. This is a great challengeas it is difficult to obtain a confirmed solution of random problem, as well as anapproximate solution with deterministic method.In the beginning of the issue, the author invented adevice to automaticallyrecordthe switching state of the windows. The device can provide data to supportfollow-upstudy. Firstly,the author made a two-month test in the fall of2012, which includesmonitoring records about Chongqing window-opening behavior inside an officebuilding intransient seasons and factors that may have a direct impact on the window-opening behavior,such as human thermal comfort and indoor air quality.By usingstatistical analysis software SPSS to process the test data, it was found that inChongqing transient season, window-opining behavior of the staff in the office buildingis directly related to the changes of outdoor temperature, butthe influences of otherfactors such as indoor temperature and humidity, indoor carbon dioxide concentration,outdoor relative humidity are not significant.Secondly, on the basis of the main factors determining the window-openingbehavior, a probability logistic regression model is established.This model describes amathematical relationship between the window-opening probability and outdoortemperature, which shows a certain trend of window-opening probability along with thechange of outdoor temperature.Finally, based on the window-opening probabilitylogistic regression model, Monte Carlo simulationmethodis introduced in the thesis.Arandom sequence generated by theprobability logistic regression model can describethe window-opening behavior factors. Through repeatedly Monte Carlo simulation of these random sequence, it is able toanalysis and forecast window-opining probability, tofinditsdistributingcharacteristics. And in the future, the window-opening probabilitymodelcan be used for the study ofbuildingenergyefficiency,indoorairquality,naturalventilationand thermalcomfort. Withcontinuous improvement of window-opening probability model, itcan achieve energysaving and comfortable indoor environment by combining with the automatic controlsystem in the future research. Inaddition, the model can be used in the simulationsoftware to revise the results,in order to obtain a more realistic simulation resulation.