Numerical Simulation Of The Effect Of Air Conditioning On The Diffusion Of Indoor Gas Pollutants

As people spend more time indoors,the indoor environment and the degree of comfort are correspondingly increased,and the influence of indoor pollutants under air conditioning has also received more attention.However,current researchers are only concerned about the impact of single factors on indoor pollutant diffusion.However,there are still gaps in the study of the combination of temperature and humidity and air flow.The current air conditioning also includes the regulation of air flow,temperature and humidity,in order to improve the effect of air conditioning on the control of indoor pollutant diffusion.In this paper,numerical simulations were used to study the effects of temperature,humidity,and air flow on the diffusion of pollutants.Through analysis and comparison of the advantages and disadvantages of various simulations,and access to relevant data and previous research content,a two-equation model was finally used to simulate the study of the air pollutant diffusion under the air conditioning in this office.Use GAMBIT to create a physical model,import FLUENT,set boundary conditions,and perform calculations.Single-factor analysis of the results and visual analysis of the results and establishment of effect plots through orthogonal simulation tables.Through the single factor analysis of the pollutant distribution map,it is concluded that the higher the temperature and humidity,the higher the overall average concentration of pollutants.The influential factors are finally determined by the intuitive analysis of the typical points and the effect curve: airflow organization> temperature> humidity.The optimal combination of air conditioning was determined: air flow was selected on the same side and sent back and forth,with a temperature of 22? and a relative humidity of 46.9%.At the end of the article,we look forward to the next step.For example,adding more factors to the single-factor analysis,and focusing on the non-steady-state model and increasing the test verification in the following studies.