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Issue title: Special Section: Fuzzy theoretical model analysis for signal processing
Guest editors: Valentina E. Balas, Jer Lang Hong, Jason Gu and Tsung-Chih Lin
Article type: Research Article
Authors: Liu, Lindonga | Dai, Jingwenb; * | Yang, Junweia | Jin, Miaoa | Jiang, Weia; c | Lu, Xingyua
Affiliations: [a] School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, China | [b] School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing, China | [c] KTH Research School, University of Gävle, Gävle, Sweden
Correspondence: [*] Corresponding author. Jingwen Dai, School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China. E-mail: [email protected]
Abstract: The occupational health and safety problems caused by indoor dust and toxic gases in industrial plants are becoming increasingly serious. Vertical push-pull ventilation can effectively control dust and toxic gases and avoid indoor environmental pollution. The velocity of the air supply hood and exhaust hood in the push-pull ventilation intelligent device directly affects the control effect of the dust and toxic gases. However, no scholar has given a reasonable ratio of the air supply and exhaust velocity of the vertical push-pull ventilation device. Therefore, this paper uses the combination of Fluent numerical simulation technology and smoke visualization experiment to explore the best ratio of the air supply and exhaust velocity in the push-pull ventilation flow field. The research shows that the traces of the wind flow obtained by numerical analysis under different k which is the ratio of the air supply and exhaust velocity is consistent with the traces of visualized smoke in the actual experiment; The optimal ratio of air supply and exhaust is k = 1.75, which can effectively guarantee the indoor environment, occupational health and work efficiency of the operators.
Keywords: Dust and toxic gases, push-pull ventilation, ratio of the air supply, exhaust velocity, smoke visualization, intelligent
DOI: 10.3233/JIFS-179318
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4819-4826, 2019
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