Localization and characterization of intermittent pollutant source in buildings with ventilation systems:Development and validation of an inverse model
断断续续的污染物质的本地化和描述与通风系统在大楼里采购原料: 逆的开发和确认当模特儿作者机构：College of Environmental Science and EngineeringTongji UniversityShanghai200092China School of Mechanical EngineeringTongji UniversityShanghai 200092China Department of Civil and Mineral EngineeringUniversity of TorontoTorontoCanada
出 版 物：《Building Simulation》 (建筑模拟（英文）)
年 卷 期：2021年第14卷第3期
页 面：841-855页
核心收录：
学科分类：08[工学] 081404[工学-供热、供燃气、通风及空调工程] 0814[工学-土木工程]
基 金：supported by the China National Key R&D Program during the 13th Five-year Plan Period(No.2018YFC0705300) the National Natural Science Foundation of China(No.51278370 and No.51778440) The fund from Science and Technology Commission Shanghai Municipality(19DZ1208100)was also gratefully acknowledged
主 题：intermittent source inverse identification Markov chain regularization parameter ventilation system
摘 要：Terrorist attacks through building ventilation systems are becoming an increasing *** case pollutants are intentionally released in a building with mechanical ventilation systems,it is critical to localize the source and characterize its releasing *** inverse modeling studies have adopted the adjoint probability method to identify the source location and used the Tikhonov regularization method to determine the source releasing profile,but the selection of the prediction model and determination of the regularization parameter remain *** limitations can affect the identification accuracy and prolong the computational time *** address the difficulties in solving the inverse problems,this work proposed a Markov-chain-oriented inverse approach to identify the temporal release rate and location of a pollutant source in buildings with ventilation systems and validated it in an experimental *** the modified Markov chain,the source term was discrete by each time step,and the pollutant distribution was directly calculated with no *** forward Markov chain was reversed to characterize the intermittently releasing profile by introducing the Tikhonov regularization method,while the regularized parameter was determined by an automatic iterative discrepancy *** source location was further estimated by adopting the Bayes *** chamber experiments,the effectiveness of the proposed inverse model was validated,and the impact of the sensor performance,quantity and placement,as well as pollutant releasing curves on the identification accuracy of the source intensity was explicitly *** showed that the inverse model can identify the intermittent releasing rate efficiently and promptly,and the identification error for pollutant releasing curves with complex waveforms is about 20%.
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