张腾飞

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:美国普渡大学

学位:博士

所在单位:土木工程系

学科:供热、供燃气、通风及空调工程

办公地点:综合实验四号楼425-1室

联系方式:0411-84706279

电子邮箱:tzhang@dlut.edu.cn

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Inversely tracking indoor airborne particles to locate their release sources

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论文类型:期刊论文

发表时间:2012-08-01

发表刊物:ATMOSPHERIC ENVIRONMENT

收录刊物:SCIE、EI

卷号:55

页面范围:328-338

ISSN号:1352-2310

关键字:Airborne particles; Inverse modeling; Source prescription; Quasi-reversibility; Lagrangian-reversibility; Indoor air pollution

摘要:Airborne particles can have numerous adverse effects on human health. Knowing the release locations of airborne particulate sources is helpful in minimizing pollutant exposure. This paper describes a proposal to locate indoor particulate sources by two inverse models: the quasi-reversibility (QR) model and the zone prescription of contaminant sources with the Lagrangian-reversibility (LR) model. The QR model reverses the time marching direction of the Eulerian governing equation and replaces the second-order diffusion term with a fourth-order stabilization term. The zone prescription LR model traces individual particulate motion in a Lagrangian reference frame after reversing the flow field. The particle trajectories are solved backward to the initial release once the conservative forces acting on particles are reversed. The tracked particles are proposed to be placed at the zone boundary of the largest concentration contour within the domain at a given time, which is provided as the initially known information. By connecting all particles at t = 0, a zone is formed that can prescribe the actual contaminant source. This study finds that both models can accurately locate particulate sources released instantaneously at a spot. The QR model performs slightly better than the LR model but is much more computationally demanding. (C) 2012 Elsevier Ltd. All rights reserved.