常用疏散软件

2023年消防设施操作员之消防设备基础知识综合练习试卷A卷附答案单选题（共40题）1、《消防法》规定，（）领导全国的消防工作。

A.公安部消防局B.国务院C.地方各级人民政府D.国务院应急管理部门【答案】 B2、油锅起火，不正确的扑救方法是（）。

A.迅速关闭气源B.用灭火毯覆盖C.用水泼灭D.用锅盖闷灭【答案】 C3、（）是火灾中致死的主要燃烧产物之一，其毒性在于对血液中血红蛋白的高亲和力。

A.二氧化碳B.一氧化碳C.水蒸气D.二氧化硫【答案】 B4、《消防法》规定，火灾扑灭后，发生火灾单位和相关人员应当按照（）要求保护现场，接受事故调查，如实提供与火灾有关情况。

A.所在地公安机关B.消防救援机构C.所在地政府机关D.主管部门【答案】 B5、按可燃物类型和燃烧特性不同，下列物质发生火灾属于C类火灾是（）。

A.二甲苯B.铜粉C.丙烷D.中草药材【答案】 C6、应将喷淋消防泵控制柜的启动、停止按钮专用线路直接连接至设置在消防控制室内消防联动控制器的（）。

A.总线控制盘B.总线回路C.手动控制盘D.警报输出端口【答案】 C7、本题那项不符合建筑消防设施巡查要点的内容：A.应急广播扬声外观完好情况;B.防火门、防火卷帘开户是否处开正常状态，外观完好情况，有无遮挡;C.消防电梯的紧急按钮和电梯轿箱内电话的外观;D.发电机是否正在运转。

【答案】 D8、微型消防站灭火器材配置时，错误的是（）A.应设置人员值守、器材存放等用房且必须单独设置。

B.应根据扑救初起火灾需要，配备一定数量的灭火器、水枪、水带等灭火器材，配置外线电话、手持对讲机等通信器材C.应在建筑物内部和避难层设置消防器材存放点，可根据需要在建筑之间分区域设置消防器材存放点D.有条件的微型消防站可根据实际选配消防车辆【答案】 A9、当湿式报警阀进口水压大于0．14MPa、放水流量大于（）L/s时，报警阀应及时启动。

A.1B.1.5C.2D.2.5【答案】 A10、防火的基本原理为限制燃烧必要条件和充分条件的形成。

Modeling the pedestrian’s movement and simulating evacuation dynamics onstairsYunchao Qu,Ziyou Gao ⇑,Yao Xiao,Xingang LiSchool of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,Chinaa r t i c l e i n f o Article history:Received 23December 2013Received in revised form 15May 2014Accepted 22May 2014Available online 26June 2014Keywords:Pedestrian flowStaircase movement Dynamic characteristics Social force modela b s t r a c tThis paper presents an enhanced social force model to describe the pedestrian’s movement and evacua-tion dynamics on pared with original models that described the pedestrian’s planar motion,our model introduces some mechanisms of the staircase movement,such as the influence of staircase geometry,the restriction of the step size and the optimal velocity selection.The body shape of each pedestrian is regarded as a set of three circles to precisely quantify the movement.In addition,the rotation dynamics are included into the model to describe the congestion effect.The improved model can obtain individual velocity under different staircase geometries and the flow characteristics of the evacuation dynamics.Some empirical data and a series of observations captured in two subway stations in Beijing are applied to study the characteristics and further validate the model.The results show that our model performs well consistent with the observed data.At last,simulations are implemented to find the solutions of estimating the evacuation time and evaluating the capacity of stair.Ó2014Elsevier Ltd.All rights reserved.1.IntroductionStairs are widely used in all kinds of buildings,especially in large scale public places,i.e.,subway stations,shopping malls and office buildings.Walking on stairs is very common and important in our daily lives,and scientific design and effective utilization of stairs are urgently needed for designers and managers (Peacock et al.,2009).In emergency,such as power failure,fire,earthquake or other hazards,the elevators may be out of commission,and the stairs become the primary escape routes.If there are too many peo-ple crowded on stairs,they will pack closer together or even lead to some dangerous situations (Shields and Boyce,2009).Knowing the flow characteristics and predicting the egress time are the key points to grasp the evacuation dynamics and make emergency response plans on stairs (Graat et al.,1999;Oven and Cakici,2009).The characteristics of pedestrian staircase movement are deter-mined by organizational,constructional and behavioral factors:the organizational factors,i.e.,preparation for emergencies;the constructional factors,i.e.,the staircase geometry including riser height,tread depth and step width (Graat et al.,1999;Fujiyama and Tyler,2010);the behavioral factors,i.e.,responses and move-ment characteristics of pedestrians (Yang et al.,2012;Ma et al.,2012).The study of the staircase movement is an interdisciplinaryfield with different focuses,such as biomechanics,physics,physiol-ogy,phycology,computer science,safety science (i.e.,Hankin and Wright,1958;Fruin,1971;Predtechenskii and Milinskii,1978;Templer,1992;Batty,1997;Helbing et al.,2000;Hase and Yamazaki,2002;Nelson et al.,2002;Hoskin,2004;Pauls,2005;Trew,2005;Casburn et al.,2007;Hostikka et al.,2007;Galea et al.,2008;Kretz et al.,2008;Seer,2008;Xu and Song,2009;Fujiyama and Tyler,2010;Galea et al.,2010;Hoskins,2011;Halsey et al.,2012;Yang et al.,2012;Peacock et al.,2012;Burghardt et al.,2013).To make quantitative analyses and detailed descriptions of staircase movement,many researches have carried out a lot of sur-veys,experiments and evacuation drills on stairs,and have collected large amounts of experimental and observational data of staircase movement (please see Table 1for details).In these studies,the flow characteristics of staircase movement are described in individual level and collective level.Pedestrian flow in low densities reflects the characteristics in the individual level,and walking speed is influ-enced by physiological feature and body function,such as gender,age,height,weight,heart rate,rate of oxygen consumption and rate of energy expenditure (Irvine et al.,1990;Teh and Aziz,2002;Halsey et al.,2012).It is also influenced by stairway geometries and movement direction.Pedestrian flow in high densities reflects the characteristics in the collective level.The collective behaviors include pedestrians’self-organized behaviors and optimal route choice behaviors (i.e.,Helbing et al.,2000,2005;Moussaid et al.,2011).The researches of pedestrian flow in the collective level focus on three aspects,(1)evaluating evacuation time,(2)reproducing/10.1016/j.ssci.2014.05.0160925-7535/Ó2014Elsevier Ltd.All rights reserved.⇑Corresponding author.Tel.:+861051688193.E-mail address:zygao@ (Z.Gao).fundamental diagram,and(3)describingflow characteristics,i.e., inflow,outflow,capacity.Staircase movement is a complicated three-dimensional move-ment,and modeling the movement is a quite challenging work. Nowadays,researches have integrated behavioral and construc-tional factors,and have established many models to analyze the flow characteristics and simulate evacuation processes in both sin-gle-story and multi-story buildings(Table1).In our work,we mainly focus on the case of single-story staircases.These models are classified into two categories:macroscopic model and micro-scopic model(Zheng et al.,2009).The macroscopic models regard the crowd as a single entity,and focus onfitting the expression of fundamental diagram.Linear,piecewise linear and non-linear functions(i.e.,Fruin,1971;Warren,1984;Tanaboriboon et al., 1986;Weidmann,1993;Lam and Cheung,2000;Proulx,2002; Peacock et al.,2012;Hoskins and Milke,2012)have been applied to describe relationship between velocity and density under differ-ent stair geometries.Compared with macroscopic models,the microscopic models are able to precisely describe the individual behavior,qualitatively explain the evacuation dynamics and reproduce some self-orga-nized phenomena(Helbing et al.,2000).These microscopic models are spatial-discrete models(cellular automation model,i.e., Kirchner et al.,2004;Huang and Guo,2008;Schadschneider and Seyfried,2009)and spatial-continuous models(social force model, i.e.,Helbing et al.,2000).These models have been applied to reveal two-dimensional planar movement,but few of them have described the three-dimensional staircase movement(Song et al., 2006;Pelechano and Malkawi,2008;Xu and Song,2009;Ma et al.,2012).In addition,the spatial-discrete models are some restricted to describe the staircase movement,such as grid size,fatigue factor,route selection,and uneven use of stairs (Pelechano and Malkawi,2008).Although the spatial-continuous models are advantageous to solve most of the aforementioned problems,these models are quite rare.Social force model(Helbing and Molnar,1995)is a well-known spatial-continuous model in thefield of pedestrianflow.The model can reproduce several self-organized phenomena,such as lane forming,arching queue,shock waves and clogging effects (Helbing et al.,2005,2007).Moussaid et al.(2011)have proposed a heuristics-based model to replace the social force with a heuris-tics intelligent optimum function.Based on the heuristic social force model,this paper introduced some special rules and estab-lished an enhanced model to describe the mechanisms of pedes-trian movement and evacuation dynamics on stairs.Firstly,the body shape of each pedestrian is regarded as a set of three circles (Thompson and Marchant,1995).Compared with traditional sin-gle-circle shape(i.e.,Helbing et al.,2000),the three-circle shape precisely represents the projection of human body and describes the rotation movement when two pedestrians collide with others. Secondly,pedestrians usually walk more carefully on stairs than on planar,so two‘safety rules’are proposed to describe staircase movement behavior.Thefirst rule is that a pedestrian wants to walk upstairs/downstairs with integral steps at a time,and the step-size is restricted by the staircase geometry,such as tread depth,riser height and step width.The second rule is that a pedes-trian tends to walk along the sides,i.e.,holding handrails,propping up against walls.Thirdly,the relaxation time is extended to a var-iable in our model.The relaxation time is defined that a pedestrian tends to correspondingly adapt his/her actual velocity to desired velocity with a certain characteristic time s(i.e.,Helbing et al., 2000;Moussaid et al.,2011).The relaxation time is mostlyTable1The state-of-the-art of staircase movement.Author(s)Year Method Model EvacuationprocessWalking speed NoteDynamics FD Geometry Direction Hankin and Wright1958Data analysis–s d s d–Fruin1971Data analysis–s d s s Planning methodPredtechenskii and Milinskii1978Data analysis Planning model s d s s Planning methodTanaboriboon et al.1986Macro Linear function s d s s Fundamental diagram Weidmann1993Macro Non-linear function s d d d–Frantzich1996Data analysis–s d d d–Graat et al.1999Data analysis–s d s s Capacity estimation Lam and Cheung2000Macro BPR function s d d d Fundamental diagram,capacityestimation Proulx et al.2002Data analysis Non-linear function d d s s SFPENelson and Mowrer2002Data analysis Non-linear function d d s s SFPEHoskin2004Softwaresimulation Coordinate-basedmodeld d d d Simulex32Pauls2005Data analysis–d s s s–Hostikka et al.2007Data analysis–d d s s–Kretz et al.2008Data analysis–s d d d Pedestrian movement on long stairs Seer et al.2008Data analysis–d d s s Flow characteristicsPelechano and Malkawi2008SoftwaresimulationGrid based model d s s s Literature review(STEPS,EXODUS)Galea et al.2008Software Evacuation model d s s s Merging behavior at interactions Xu and Song2009Micro Multi-grid model d s s s Flow characteristics,such as in and outflow Fujiyama and Tyler2010Macro Linear function s s d d Individual walking speed Galea et al.2010Data analysis–d d s s Evacuation softwareHoskins2011Macro Linear function d d d d Fundamental diagramYang et al.2012Data analysis–d d d s Evacuation drillLei et al.2012Softwaresimulation–d s s s Software(FDS,EVAC) Hoskins and Milke2012Data analysis–s d s s NISTPeacock2012Data analysis–d d d s NIST,different measurement methods Ma et al.2012Data analysis CA d s s s SimulationBurghardt et al.2013Data analysis–s d s s Fundamental diagramd Represents the factor is included and s represents the factor is not included.190Y.Qu et al./Safety Science70(2014)189–201assumed to be a constant in previous models,but it is not inade-quate to describe the staircase movement.As mentioned before, the individual walking speed on stairs is influenced by many fac-tors,such as staircase size,movement direction,and physical char-acteristics.For example,pedestrians spend more energy on walking upstairs than downstairs,spend more time on walking steep stairs than gentle stairs.Pedestrians with different age, weight or gender may require different relaxation times when walking on different stairs.Considering the influence factors,the relaxation time is formulated as a linear function of individual weight,moving height,and the slope of stairs.The linear function is similar to the model(Fujiyama and Tyler,2010),and some parameters are introduced to distinguish the upstairs and down-stairs movement.In this paper,some empirical data in literatures are collected and new observations from subway stations are conducted.In Sec-tion2,the characteristics of pedestrianflow on the stairs are dis-cussed.Based on the data and analysis,the constructional and behavioral factors are introduced to the social force model to pre-cisely describe the individual staircase moment in Section3.To validate the model,a series of simulations are implemented,and the simulation results are compared with the observational and empirical data in Section4.Simulations are implemented to ana-lyze theflow characteristics and the evacuation process in subway stations in Section5.Finally,the conclusions and the further work are given in Section6.2.Data collection andflow characteristics on stairs2.1.Empirical data of pedestrian speedOccupant speed is a very important element of pedestrianflow, and pedestrian speed on stairs is mainly affected by the slope of stairway,depth of tread,height of riser,and presence and location of handrails(Gwynne et al.,2009).Graat et al.(1999)had found that speed and capacity on stairs were higher with a normal (30°)slope than a steep(38°)slope.Kretz et al.(2008)had found that some pedestrian accelerate when walking upward a short stairway,and the mean upward walking speed on the short stair-way was found to be roughly twice as large as the one on the long stairway.Fujiyama and Tyler(2010)had proposed a model to pre-dict the walking speed based on the weight,leg power and the gra-dient of the stairs.The evacuation process of a large number of people is another major concern for researchers and designers. During the evacuation,the evacuation process something likes a queuing system that contains the processes of congestion forming, propagation and dissipation(Ma et al.,2012).Besides,the stair width and capacity will affect the route/exit choice behaviors and the evacuation efficiency(Lei et al.,2012).Researches have obtained many observational and experimen-tal data of staircase movement.However,this study here is not intended to be an exhaustive review of all researches.The refer-ences which mentioned both staircase geometry and individual speed are taken into consideration.Ten instances of staircase are included in our paper,and more detailed data can be found in the literatures(i.e.,Weidmann,1993;Frantzich,1996;Fujiyama and Tyler,2010;Hoskins,2011;Peacock et al.,2012).From Table2, it is found that walking speeds listed in the studies are different. This may be caused by natural variation of individual capability, staircase geometry,density of crowd and other factors.Besides, different measurement methods of calculating travel distances and areas on stairs may lead to different results(Hoskins and Milke,2012).Fujiyama and Tyler(2010)have made some experi-ments and found that average upstairs and downstairs speeds were0.58m/s and0.67m/s,respectively.Peacock et al.(2012) have mentioned that average downstairs speeds in their study of 0.48±0.16m/s were observed to be quite similar to the range of literature values.Kretz et al.(2008)have pointed that the density also affected the individual speed.Ma et al.(2012)have made a series of evacuation drills to obtain the average downstairs speed of0.547m/s.Even though different researchers have come up with different values for movement on stairs,most give a maximum for density of4.5–5.5pedestrians/m2,a maximum for speed of0.7–1.2m/s,and maximum for capacity of0.8–1.5pedestrians/(m s).2.2.Observations in subway stationsSomefire drill evacuations of office buildings have been imple-mented by National Institute of Standards and Technology(NIST), and the collected staircase movement data have included a range of stair geometries and occupant densities(Peacock et al.,2012; Hoskins and Milke,2012).However,in those studies,the local speed and the density were inaccurately estimated according to the collected data.It was because the cameras did not fully record the whole of staircase movement.In the drills,cameras were set every twofloors to record an overhead view of occupant move-ment.The view of each camera only covered the main landing area plus tread depth area for about4–6steps of one story.Between every two cameras,there was a mid-landing,where pedestrian movement was a planar movement,but not a staircase movement. It was impossible to dissociate the planar movement on mid-land-ing from the video,so the calculations of the travel distance and travel time of staircase movement were inaccurate.To precisely investigate the pedestrian movement characteristics on stairs,we improved the method of video recording,and conducted observa-tions of whole staircase movement in two stations of Beijing sub-way Line1.The two stations are Sihui East Station(ascendingflow)and Xidan Station(descendingflow).The Sihui East Station is a termi-nal station and all the passengers should get off the train and go to the transfer hall;therefore,the pedestrianflow on the observed stair is an ascendingflow.The Xidan Station is also a transferTable2Individual horizontal speeds in ten instances of staircases with different geometries.ID Riser height(mm)Tread depth(mm)Gradient(°)Horizontal speed(m/s)Source Note#H120021043.60.361("),0.509(;)a Frantzich(1996)Narrow stair #H215030519.00.427("),0.601(;)Lam(2000)MTR #H316327131.00.417("),0.569(;)Lam(2000)KCR #H419027035.10.423(")Kretz(2008)Long stairs #H515029027.30.538("),0.581(;)Fujiyama(2010)Elder people #H615726730.50.590("),0.721(;)Fujiyama(2010)Young people #H718623838.00.488(;)a Peacock(2012)11-Floors #H819125436.90.440(;)a Peacock(2012)18-Floors #H915028028.20.547(;)Ma(2012)SWFC #H1014028026.50.53(;)Yang(2012)Stair No.2#a The speeds were converted to horizontal speeds.Y.Qu et al./Safety Science70(2014)189–201191station and the passengers can get on or off the train by the stair, and there is an escalator on one side of the stair to relieve the coun-tering passengerflows.Therefore,the pedestrianflow is a descend-ingflow.The schematic diagram of the observation stations is shown in Fig.1,and the information of the stairs is shown in Table3.A HD camera was set on the transfer hall to record the trail of each passenger.The observations in the subway stations were made during the afternoon rush hours of weekend(17:30–18:30,Sunday)on May 12,2013.In our observations,383pedestrians(216males,167 females)were collected at the selected staircases in Xidan Station, and221pedestrians(129males,92females)were collected in Sihui East Station.Most of the pedestrians were young and mid-dle-aged people,and their ages mostly ranged from25to55years old.The proportion of children and elderly was very low.In our observations,most of the pedestrians carried light bags and walked in a normal speed on staircases.Because the camera was not right above on the observed region, the passengers were sometimes overlapped in the video.Each pedestrian was recorded by individual characteristics,such as gen-der,age,body size,hair,shirt and pants.Then,the pedestrians were recognized by their features,entering and leaving time.The speed of each pedestrian was calculated by the travel time(leaving time minus entering time)dividing the travel distance on the stairs.The video recordings were processed semi-manually,and the dynamic evacuation characteristics,such as average density,speed andflow,were analyzed.Take Xidan station for example,the evac-uation dynamic characteristics and a snapshot were illustrated in Fig.2a–c).It was found that the curve of time-varying density was divided into several segments,and each segment represented a stream of pedestrians entering and leaving the stairs.During the observation,some measures,such asflow restriction and guidance, had been adopted to avoid crowdedness,so the density of pedestri-ans on stairs was in a normal(low)level.There were eight local maximum points exceeding1.0pedestrians/m2,and the maximal density was about1.6(1/m2).Velocity showed an opposite trend of density.The velocityfluc-tuated between0.4m/s and1.0m/s,and the average velocity was about0.57m/s.The volatility of individual velocities might be caused by different individual capability and desired velocity.In a low density,the pedestrians who walked fast would overtake front pedestrians who walked slowly and blocked them.When the density became larger,the pedestrians began to slow down and follow with others,and then queues might form on stairs.In Fig.2d),the acquainted or familiar people might walk abreast, which is regarded as‘subgroup behavior’(Yang et al.,2012).If they walked slower than the surrounding people,they would form a dynamic bottleneck.Additionally,lane-forming phenomenon was also found.In Fig.3a),the distributions of the speeds during the observa-tions followed normal distributions,which were similar with the reference(Peacock et al.,2012).The average velocities of walking upstairs and downstairs were0.55m/s and0.63m/s,respectively. Affected by gravity,going upstairs was slower than going down-stairs.By gathering the observed data of unidirectionalflow,the relationships between the velocity and the density were shown in Fig.3(b).The velocity decreased as the density increased.It should be noted that,in a low density,the velocity of going upstairs was a little higher than downstairs.It was because some of the pedestrians were hurried out of station and ran more than one steps at one time.3.Modeling the pedestrian’s movement on stairs3.1.Body shapesIn the existing models,the projection of a pedestrian’s body shape is usually regarded as a square(i.e.,Kirchner et al.,2004), a rectangular(i.e.,Song et al.,2006;Weng et al.,2007),a circle (i.e.,Helbing et al.,2000),an ellipse(i.e.,Chraibi et al.,2010)or a set of three circles(Thompson and Marchant,1995).In these geo-metrical shapes,the three-circle shape has some geometrical and computational advantages on modeling the staircase movement. First of all,the three-circle shape is a better alternative to describe the pedestrian’s body shape.It is because the occupied space of one pedestrian is restricted by the stairs,and the shoulder width of the pedestrian is larger than lateral width(Xu and Song,2009).In addi-tion,a pedestrian walks with a relative slow speed on stairs,and his/her space requirement keeps almost constant.Secondly,in social force model,the distance of closest approach of two pedes-trians is a key parameter when calculating the self-driven force, the repulsive force and the contact force.The closet distance between two single-circle or three-circle shapes can be easily cal-culated(Thompson and Marchant,1995);however,the calculation of the closest distance of two ellipses is surprisingly difficult (Zheng and Palffy-Muhoray,2007).For the convenience of calcula-tion,the three-circle shape is a better alternative than ellipse shape.Therefore,the three-circle shape is chosen to describe pedestrian’s body shape,and the schematic diagram is shown in Fig.4.3.2.Modified social force modelThe well-known social force model(Helbing and Molnar,1995; Helbing et al.,2000)is a microscopic force-based model that can reproduce several self-organized phenomena,such as lane form-ing,arching queue,shock waves and clogging effects(Helbing et al.,2005,2007;Moussaid et al.,2011).The model describes pedestrians’movement behavior by introducing the self-driven force~f Di,the contact force with pedestrians~f Cijand walls(obstacles) ~f Ciw.The self-driven force can be calculated by Eq.(1),and the total force~f exerted on pedestrian i can be formulated as Eq.(2).192Y.Qu et al./Safety Science70(2014)189–201~f D i ¼m ~m desiÀ~m isð1Þ~f i ¼~f D i þXj~f C ij þXw~f C iwð2ÞMoussaid et al.(2011)have proposed a heuristics-based modelto replace the social force with a heuristics intelligent optimum function,which can be regarded as a so-called collision prediction process.The model can overcome some difficulties in the original versions.Based on the model,we use the three-circle shape,intro-duce some special rules and establish an enhanced model todescribe the staircase movement.In our model,the modifications are concentrated on the calculations of optimal direction selection,self-driven force and contact force.3.2.1.Selecting optimal direction In Eq.(1),the desired velocity ~m des i can be obtained by the mag-nitude m des i multiplies by the direction ~e des iof desired velocity.The calculation of ~e desi is called ‘optimal direction selection’,which isTable 3Detailed step sizes.ID StationStep number Width (mm)Depth (mm)Height (mm)Gradient (°)Flow direction#O1Xidan Station 16240030014025.0Descending flow #O2Sihui East Station15190033015726.1Ascending flow(b) Change of pedestrian density with time inthe observation of staircase #O1(c) Change of pedestrian speed with time inthe observation of staircase #O1(d) A snapshot of the observations in staircase #O2(a) Change of pedestrian flow with time inthe observation of staircase #O1 Fig.2.Processed data and a snapshot.Y.Qu et al./Safety Science 70(2014)189–201193an important component of the model(Moussaid et al.,2011).In our work,the body shape is extended to three-circle shape,and the calculation becomes a little complex.To make a clear state-ment,some notation and definitions are given as follow:for pedes-trian i,the large circle’s radius is r i1,the small circle’s radius is r i2, the mass is M i,the maximum velocity is v0i,the location is~l i,the velocity is~m i and the desired destination is~D i.Assume that pedestrian i moves at the velocity v0i along the direction of direction a,and will contact with pedestrian j after D t time.The i0and j0represent the locations of i and j at time t+D t.Then,fðaÞ¼v0iÁD t is the distance to thefirst collision with other pedestrian or obstacle in the direction a.If no collision is expected to occur,f(a)is set to a default value d max,which repre-sents the‘maximum horizon distance’of pedestrian i.The calcula-tion of furthest distance without collision f(a)can be improved as follows:l ixm ðtþD tÞ¼l ixmðtÞþv ix D t;l iy mðtþD tÞ¼l iy mðtÞþv iy D tðm;n2f1;2;3gÞl jxn ðtþD tÞ¼l jxnðtÞþv jx D t;l jy nðtþD tÞ¼l jy nðtÞþv jy D tðl ixm ðtþD tÞÀl jxnðtþD tÞÞ2þðl iymðtþD tÞÀl jynðtþD tÞÞ2¼ðr imþr jnÞ2ð3ÞPut thefirst two items into the third item,we can get a qua-dratic equation with moving time D t.Given the locations and velocities of pedestrians i and j,the D t can be easily solved.Then, the value fða i m j nÞand dðaÞcan be calculated asfða i m j nÞ¼min f v i Deltat;d max g;fðaÞ¼min f fða i m j nÞg;aüargmin f dðaÞg dðaÞ¼d2maxþfðaÞÀ2d max fðaÞcosða0ÀaÞð4ÞThe optimal velocity direction~e¼ðcos aÃ;sin aÃÞ;here,aüargmin f dðaÞg is the optimal direction.Fig.5illustrates the calculation.3.2.2.Self-driven forces and contact forcesThe pedestrian’s staircase movement is a three-dimensional motion,which contains horizontal and vertical motion.Pedestrian should change his/her center of gravity to ascend or descend the stairs,which are shown in Fig.6(a)and(b).The complicated move-ment includes the pedestrian’s physiological activity and energy transformation.In our work,we mainly focus on the pedestrians’horizontal optimal choice and crowding behaviors,so the vertical motion is approximately regarded as a linear motion,which is shown in Fig.6(c).In horizontal motion,pedestrians not only over-take front people with slower speeds but also have to notice the steps and prevent themselves from falling down from stairs.To mathematically depict horizontal movement,some assumptions and rules are introduced to simplify the movement,which is illus-trated in Fig.6(d).Thefirst assumption is that a pedestrian wants to move forward within n steps(n is integer).And the pedestrian’s desired destina-tion of next footstep is the center of the forward step.For example, in Fig.6d),pedestrian often moves forward with integer steps,i.e., one step(point A)or two steps(point B).When he/she moves for-ward with non-integer step,i.e.,2.5steps(point C),he/she will move to the edge of the step,and may feel unstable,unsafe or even fall down from the stairs.Therefore,point C is not considered in our model.The pedestrian’s horizontal footstep length is defined as d h¼nDcos b,and is restricted by the tread depths D and riser heights H of the step.Here,b is the included angle between the optimal direction aÃand the x-coordinate.If the pedestrian is obstructed by other pedestrians or obstacles,he/she will slow down and avoid collision,and the footstep length does not exceed the maximal dis-tance fðaÃÞ(Eq.(4))in the optimal direction aÃ.Finally,the footstep length is expressed as:d h¼minnDcos b;fðaÃÞ&'ð5ÞAccording to the model(Moussaid et al.,2011),a pedestrian maintains a distance from thefirst obstacle in the chosen walking direction that ensures a time to collision of at least a relaxation time s.In other words,desired velocity of pedestrian i is formu-lated as v des i¼d h s.Additionally,pedestrian’s speed is assumed to not exceed a maximum velocity v max.Then,the horizontal maxi-mum velocity is v max cos h,and the angle h represents the slope of the stair tan h¼HÀÁ.The horizontal desired velocity v des i can be formulated as Eq.(6):v desi¼mind hs;vmaxcos hð6Þ(a) Probability distribution(b) Fundamental diagramFig.3.Speed and fundamental diagram of theobservations.194Y.Qu et al./Safety Science70(2014)189–201。

环境安全应急监测信息化平台软件系统平台设计方案1设计原则1.1业务横向、纵向一体化业务横向一体化是指在环保部门之间，系统通过面向服务的设计能同时支持总量控制、监察、执法、项目审批等任务。

纵向一体化是在基地环保局、市局、省厅之间支持业务连续的办理，如区县建设项目审批后，可把业务传递到市局的业务总线上，驱动市局领导审批。

通过横向、纵向一体化的支持，打破原有的条块化的非连续的处理，提供了业务人员的办事效率。

1.2全生命周期管理以业务单元为生命周期为主线，实现对业务单元从产生到销毁的全过程闭环管理。

1.3流程可配置、业务平台化由于传统的信息系统建设是以单个应用为单位开发的，部分软件基础功能存在重复，无法实现共享。

建设的一体化业务平台应支持业务流程的可配置、可维护、可管理，为应用系统开发提供高效开发、配置、部署手段。

1.4面向服务的架构紧紧围绕以面向服务为目的，充分分析用户需求，设计出稳定高效的应用服务足见。

在设计中按照可持续性发展的原则，采用正确的策略、适当的技术和有效的措施确保系统的可伸缩性。

1.5统计设计、个性应用实现对环境保护领域的统一管理和全网共享以及与部级信息的纵向连接，这样一些物理上分散的系统，必须坚持统一性原则。

统一性表现在：➢统一规范➢统一标准➢统一接口➢统一的体系结构区县应用、面向角色的服务要有个性化，个性化表现在：➢流程可定制、可配置➢角色可授权➢页面可配置1.6开放性环保信息化是一个长期的工作，因此项目所建系统能在数据、软件开发和相关借口方面应支持符合国际标准和业界标准的相关接口。

在应用开发中，要使用相应国家标准。

1.7易于维护、便于管理系统涉及在市区多级部门中运行，考虑区县的运行维护技术能力，系统要支持易于管理、便于维护；应支持信息中心管理人员远程配置、调试、升级等工作。

1.8安全可靠环境保护业务中涉及多项机密信息，需要构建全方位的安全防护体系；此外还需要实现完善的运维管理，以确保系统安全稳定运行。

基于事件树和ALOHA软件的CNG加气站储气井泄漏燃烧爆炸事故后果分析姜峰;胥朝波【摘要】通过定性和定量相结合的方法,研究了CNG加气站储气井泄漏所产生的燃烧爆炸事故后果影响.先采用事件树分析法定性分析出CNG加气站储气井天然气发生泄漏时可能发生的事故后果;再运ALDHA软件建立数学模型,并重点针对燃烧爆炸事故危害后果进行数值模拟定量分析,得出直观图表;最后通过图表分析,可得出危害半径.该方法可以对CNG加气站的安全管理、事故应急救援以及新建加气站提供技术支持.【期刊名称】《安全与环境工程》【年(卷),期】2018(025)003【总页数】4页(P141-144)【关键词】CNG加气站;储气井泄漏;燃烧爆炸事故后果;事件树分析;ALOHA软件【作者】姜峰;胥朝波【作者单位】兰州理工大学石油化工学院,甘肃兰州730050;兰州理工大学石油化工学院,甘肃兰州730050【正文语种】中文【中图分类】X928.7;TE88随着人们对天然气资源的有效利用，压缩天然气(Compessed Natural Gas,CNG)加气站开始大量建设并不断投入使用，但由于近年来我国各地不断发生的CNG加气站爆炸事故，其安全问题也逐渐引起人们的重视。

CNG加气站是一个复杂的系统，主要包括天然气预处理系统、调压计量系统、天然气压缩系统、储气系统、售气系统等。

陈杰等[1]通过统计分析 2004 年10月至2007年12 月CNG加气站发生的的百起事故，发现风险最高的是储气系统和售气系统。

储气系统的储气方式主要有储气钢瓶、储气罐、储气井三种，目前国内主要采用储气井的方式储气，因此分析CNG加气站储气井泄漏所产生的燃烧爆炸事故危害后果具有必要性。

目前虽然有各种安全评价方法(HAZOP分析法、事故树分析法、道化学指数评价法、检查表法等)，但都各具优缺点，只能基于已知事故现状做出定性或定量分析，不能对未发生的事故做出相对准确的数值模拟分析与预测，无法满足当前针对事故后果评价提供指导意义的要求；同时，虽然有FLACS、PHAST、SAFETI等安全分析软件，但这些数值模拟软件一般为离线模拟，过程比较复杂且计算耗时，不能在事故发生后实时地得出模拟结果，不利于应急人员及时做出疏散决策。

应急照明控制器使用说明书HWYE-C450应急照明控制器使用说明书第一章系统概述该控制器执行国家标准:GB17945-2010《消防应急照明和疏散指示系统》1.1 系统特点控制器挂接本公司生产的各种类型灯具，如：标志灯具、照明灯具、地埋灯具等。

1.1.1总线无极性，采用固定地址编码技术。

整个系统通讯控制只用两根线，建筑物布线极其简单，提高了布线可靠性，也便于穿线施工和线路维修，并可大大降低工程造价。

1.1.2液晶中文触摸屏幕界面，采用图形与汉字相结合的显示模式。

各种操作以菜单形式给出提示。

并且可以通过本公司专门配套研发的专用软件对于现场操作或改动等功能。

1.1.3 人性化键盘设计。

可以通过面板按键直接进行修改。

显示出故障或应急照明的具体设备，使显示内容一目了然，操作起来便捷、清楚、直观，实现了良好的人机对话。

1.1.4 所接现场设备内嵌微处理器。

灯具检测的是模拟量信号，微处理器通过软件对所测的模拟量信号进行监视及分析，从而实现对灯具状态变化进行监视和测验的控制。

1.1.5 黑匣子功能（用户操作日志）。

控制器可以永久保存控制器开机、关机、应急照明、各种故障、强制启动及停止等。

1.1.6 极强的抗干扰能力。

控制器无论是硬件还是软件都有极好的抗干扰措施。

1.1.7系统容量大。

单台控制器最大容量256（节点）, 组网后系统容量更大。

基本能满足用户各种需求。

1.1.8现场预案火警联动。

采用串口协议接口与火灾探头探测系统联动，根据现场火灾区域自动进入预案，智能选择最佳逃生路线。

预案编辑简单方便。

1.1.9 自定义节点应急维护时间，使节点更真实、可靠。

大大的降低了现场维护的成本。

1.2 技术特性线制：两总线，无极性；部件容量：每回路256节点；结点控制网络距离：通讯距离远最大可达到3000米；通过中继器可支持10KM的距离甚至更远，布线无极性，线缆任意布置，线缆兼容性好环境温度 : 0℃～50℃；环境湿度 : ≤95%外接电源 : AC220V 50HZ备用电源：DC12V 17Ah 铅酸电池外型尺寸：600x600x1800mm第二章功能2.1基本功能2.1.1前置面板介面介绍2.1.1.1启动指示系统发出对某个防火门模块的联动请求时，此指示灯被点亮2.1.1.2市电指示在控制器投入使用时，应将电源断路器开关打开。