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6篇 您的检索式：作者名="Lo Siuming"

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		题名	作者	年代	出处	被引量
	1	An agent-based microscopic pedestrian flow sinmlation model for pedestrian traffic problems 显示文摘	Liu Shaobo Lo Siuming Ma Jian et el	2014	IEEE Zrans on Intelligent Transportation Systems2014，15，3：	1
	2	Effect of ignition condition on typical polymer’s melt flow flammability显示文摘	Xuegui Wang Xudong Cheng Liming Li Siuming Lo Heping Zhang	2011	Journal of Hazardous Materials2011，，1：	1
	3	An Evacuation Model: The SGEM Package显示文摘	Lo Siuming Fang Zheng Lin Peng	2004	Fire Safety Journal2004，39，3：	1
	4	A Spatial-grid Evacuation Model for Buildings显示文摘	Lo Siuming Fang Zheng	2000	Journal of Fire Science2000，18，5：	1
	5	Correlation of rate of gas temperature rise with mass loss rate in a ceiling vented compartment显示文摘n-heptane pool fire and industrial alcohol pool fire in a ceiling vented compartment were studied experimentally. The parameters including mass loss rate and rate of gas temperature rise were investigated. The results suggest that the rate of gas temperature rise, whose variations were highly coincident with those of the mass loss rate, minimized at the moment of extinction. The correlation of the rate of average nondimensional temperature rise with mass loss rate was established. It was found that the rate of average nondimensional temperature rise may be correlated with mass loss rate via the gas heat absorption coefficient which was found to be a quadratic function of the nondimensional heat release rate for the ceiling vented compartment under study. The present study may be of practical use for estimation of the time-dependent changes in mass loss rate from the gas temperature curves.	Ruiyu Chen Shouxiang Lu Bosi Zhang Changhai Li Siuming Lo	2014	Chinese Science Bulletin2014，59，33：	0
	6	Observations of Passenger Flow and Verification of a Crowd Dynamics Model显示文摘This paper reports observations of passenger flow in the Wuchang railway station in Wuhan,China during the Chinese Traditional Spring Festival in 2006.The data collected are used to verify a crowd dynamics model previously developed.The crowd dynamics model is based on simulating the global movement of each individual under the influence of the surrounding crowd,and the good agreement between the predictions and observations validates the prediction model.The crowd dynamics model suggests that the crowd movement speed is dominated by two factors: the front-back inter-person effect,and the pedestrian’s self-motive.The first effect gives logarithmic relationship between the crowd speed and crowd density.The second factor depends on the individual motive driven with which people try to divorce themselves from the control of the crowd movement.The prediction model are helpful to guide the design of public traffic systems for effective crowd dispersal.	YUAN Jianping FANG Zheng LO Siuming XIE Lilin HUANG Danguang	2008	Wuhan University Journal of Natural Sciences2008，13，2：	0

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