大型公共建筑火灾逃生环境风险测度与导航路径优化
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摘要
我们生活在一个不平凡的世界。人类社会几千年的发展创造了丰硕的物质文明和精神文明。同时,我们也生活在一个不平静的世界。每年发生的大量的自然灾害、事故灾难、公共安全突发事件以及日益增多的恐怖袭击在给社会造成巨大损失的同时也带走了千千万万个宝贵的生命。因此,安全问题受到各个国家的普遍重视。突发事件应急管理研究也是各国学者共同关注的问题。
建筑是人类文明的象征,也是现代人们进行大多数行为活动的主要空间。大型公共建筑与普通建筑物相比较,具有结构复杂、人员密集、财富集中的特点。发生在大型公共建筑内的突发事件无疑会带来更严重、更广泛的经济、环境、社会影响。相对比于其他类型的突发事件,火灾的爆发频率比较高,在大型公共建筑突发事件中比较具有代表性。而相对于物质财富和文化成果而言,人的生命更加宝贵。如何在极端复杂的大型公共建筑火灾条件下,保障逃生者安全、快速地逃离灾害现场是本文的主要研究内容。
建筑火灾是一个动态的破坏过程,逃生者所处的环境瞬息万变,火灾及其蔓延产物所带来的环境风险时刻威胁着逃生者的生命安全。在这样复杂多变而又极度危险的环境下寻找到正确的逃生道路、迅速撤离火灾现场,对每一位逃生者都是极大的生存挑战。
本文从对大型公共建筑火灾环境与逃生互动行为分析入手,讨论了建筑火灾特性与建筑火灾主动、被动防御系统在火灾环境下的作用。通过对建筑火灾逃生安全分析,归纳了建筑火灾环境下存在的主要风险类型(高温、毒气、浓烟、坍塌),并应用微效用积累作用模型将其对逃生者的影响作用定量化表达。通过建筑火灾环境下逃生者心理与互动行为分析逃生者选择路径的过程与机理,为大型公共建筑火灾逃生导航提供必要的理论依据。
建筑火灾破坏性的复杂动态过程会产生多种危及逃生者生命安全的环境风险。为了能对逃生路径上的火灾环境风险客观、准确地评价,首先需要明确火灾环境风险的种类及其相互之间的关联。本文应用空间数据挖掘方法构建适用于建筑火灾环境风险挖掘的多层次空间聚类模型,实现大型公共建筑火灾应急逃生智能导航系统IENS Fire Guide在GIS数据库中的火灾环境风险挖掘的功能。
建筑火灾逃生路径存在的多种风险在一定程度上会共同影响逃生者的生命安全。本文采用ESDA技术发掘空间数据中隐藏的不同类型风险之间以及风险与逃生者动态网络流之间的关联关系。为了客观地评价建筑火灾这种极度复杂环境下不同类型风险对逃生者的影响作用,正确评价不同类别的风险之间以及风险与逃生者动态网络流之间的关联关系,本文通过构建单变量空间依赖性判别模型和双变量空间相关性评价模型,实现不同类别风险之间以及风险与逃生者动态网络流之间的相关性评价。并在此基础上,建立大型公共建筑逃生O-D路径环境风险评价模型,描述出建筑火灾逃生网络中每一条路段上的逃生概率P和在该路段上消耗的逃生时间T,为基于逃生概率的最短逃生时间消耗网络优化,寻找最佳逃生路径,实现智能逃生导航提供必要的数据基础和算法保障。
在对建筑逃生路网评价的基础上,本文应用有条件的最小资源消耗网络优化技术,构建基于逃生概率的最短逃生时间消耗网络优化模型,用以在建筑火灾环境下的逃生者动态流网络中寻找最安全且最快速的逃生道路。基于逃生概率的最短逃生时间消耗网络优化模型不仅能够为个体逃生者提供双路径优化方案,并且能够为群体逃生者提供n级动态逃生路径优化策略,以满足群体安全快速逃生的需求。
为了满足逃生者又安全又快的逃生需求,实现大型公共建筑火灾群体应急逃生策略最优的目标,本文基于大型公共建筑智能逃生空间理论讨论如何构建大型公共建筑火灾应急逃生智能导航系统IENS Fire Guide。IENS Fire Guide基于网络地理信息系统平台和无线传感器网络,通过对逃生者移动设备发射出的信号实现对逃生者的定位,并通过火灾空间风险挖掘与分析功能对逃生者所能够选择的路网进行空间风险关联与评价,在此基础上应用系统的逃生路网的优化功能确定基于最低逃生概率的n级动态逃生方案以辅助逃生者的路径选择及应急指挥人员的决策分析。最后,本文通过对某会展中心火灾场景的模拟,对IENS Fire Guide辅助决策能力进行实例分析。
We are living in a marvelous world. Thousands of years of human society development created abuandence of substantial civilization and spiritual civilization. And we are living in an unpeaceful world. Numerous of natural disasters, technological accidents, public security emergencies and increasing terrorist attacks bring huge lost and take away tens of thousands of precious lives every year. Public security problems and emergency managment have been generally regarded serious by both governments and scholars.
Buildings are symbols of human civilization, and they are also the majority space for modern activities. Compared with normal buildings, large-scale public buildings are characterized by complex structure, dense of population and wealth concentration. So emergencies happen in large scale-public undoubtedly buildings broad and seriously economical, environmental, and social influence. Fire accidents are much more common compared with other types of public security events, and they are the typical and majority dangerous emergencies happened in large-scale public buildings. And human lives are much more precious than any other treasures and wealth. How to help occupants safely and quickly evacuate from the complex large-scacle public building fire environment is the main content of this research.
Building fire is a dynamic ruinous process, which threats the evacuees so much with its environmental risks caused by fire propagation. In such changeable and dangerous condition, it would be challenge for all occupants to chose a safe and quick way to escape out.
In this paper, large-scale public building fir dynamic environment and evacuees’interaction performance has been analysed first. In chapter two, general building fire features and interaction performance of active and passive building fire defence systems in large-scale public buildings has been expatiated. By building fire evacuation safety analysis, the majority types of building fire environmental risks (heat, toxic gas, smoke, and structure collapse) have been summarized with Fractional Effective Dose models expression. Evacuees’psychology analysis and interaction performance understanding in building fire environment provides necessary theoretical basis for path choice and evacuation navigation study.
In order to objectively and accurately evaluate environmental risks caused by the dynamic ruinous process of building fire propagation, relationships and associations among types of risks should be confirmed. Spatial cluster algorithm has been modeled based on spatial data mining theories in chapter three to fulfil building fire environmental risks mining function of large-scale public building fire navigation intelligence navigation system: IENS Fire Guide.
Exploratory Spatial Data Analysis (ESDA) technology has been employed in chapter four to discover hidden relationships among types of risks and associations between risks and evacuees dynamic flow. Univariate spatial risks independence evaluation model and bivariate risks association evaluation model has been proposed to estimate relativities of those relations and associations. In chapter four, large-scale public building evacuation origin-determination (O-D) path environmental risks evaluation has been also proposed to calculate escape probability P and time cost T of each section on the O-D paths.
In chapter five, optional minimal cost network optimization technology has been employed to model up an escape probability based shortest time cost network optimization models to find out the most reliable and fast way to escape out. These models can not only be able to provide optimal scheme for individual evacuation, but also could provide n-level dynamic evacuation optimal strategies for group evacuation.
To realized large-scale public building fire evacuation navigation, chapter six illustrates how to build up an intelligent space and evacuation navigation system for large-scale public building fire safe and quick evacuation. Finally, a fire scenario case study has been proposed to validate intelligent large-scale public building fire evacuation navigation system IENS Fire Guide use.
建筑是人类文明的象征,也是现代人们进行大多数行为活动的主要空间。大型公共建筑与普通建筑物相比较,具有结构复杂、人员密集、财富集中的特点。发生在大型公共建筑内的突发事件无疑会带来更严重、更广泛的经济、环境、社会影响。相对比于其他类型的突发事件,火灾的爆发频率比较高,在大型公共建筑突发事件中比较具有代表性。而相对于物质财富和文化成果而言,人的生命更加宝贵。如何在极端复杂的大型公共建筑火灾条件下,保障逃生者安全、快速地逃离灾害现场是本文的主要研究内容。
建筑火灾是一个动态的破坏过程,逃生者所处的环境瞬息万变,火灾及其蔓延产物所带来的环境风险时刻威胁着逃生者的生命安全。在这样复杂多变而又极度危险的环境下寻找到正确的逃生道路、迅速撤离火灾现场,对每一位逃生者都是极大的生存挑战。
本文从对大型公共建筑火灾环境与逃生互动行为分析入手,讨论了建筑火灾特性与建筑火灾主动、被动防御系统在火灾环境下的作用。通过对建筑火灾逃生安全分析,归纳了建筑火灾环境下存在的主要风险类型(高温、毒气、浓烟、坍塌),并应用微效用积累作用模型将其对逃生者的影响作用定量化表达。通过建筑火灾环境下逃生者心理与互动行为分析逃生者选择路径的过程与机理,为大型公共建筑火灾逃生导航提供必要的理论依据。
建筑火灾破坏性的复杂动态过程会产生多种危及逃生者生命安全的环境风险。为了能对逃生路径上的火灾环境风险客观、准确地评价,首先需要明确火灾环境风险的种类及其相互之间的关联。本文应用空间数据挖掘方法构建适用于建筑火灾环境风险挖掘的多层次空间聚类模型,实现大型公共建筑火灾应急逃生智能导航系统IENS Fire Guide在GIS数据库中的火灾环境风险挖掘的功能。
建筑火灾逃生路径存在的多种风险在一定程度上会共同影响逃生者的生命安全。本文采用ESDA技术发掘空间数据中隐藏的不同类型风险之间以及风险与逃生者动态网络流之间的关联关系。为了客观地评价建筑火灾这种极度复杂环境下不同类型风险对逃生者的影响作用,正确评价不同类别的风险之间以及风险与逃生者动态网络流之间的关联关系,本文通过构建单变量空间依赖性判别模型和双变量空间相关性评价模型,实现不同类别风险之间以及风险与逃生者动态网络流之间的相关性评价。并在此基础上,建立大型公共建筑逃生O-D路径环境风险评价模型,描述出建筑火灾逃生网络中每一条路段上的逃生概率P和在该路段上消耗的逃生时间T,为基于逃生概率的最短逃生时间消耗网络优化,寻找最佳逃生路径,实现智能逃生导航提供必要的数据基础和算法保障。
在对建筑逃生路网评价的基础上,本文应用有条件的最小资源消耗网络优化技术,构建基于逃生概率的最短逃生时间消耗网络优化模型,用以在建筑火灾环境下的逃生者动态流网络中寻找最安全且最快速的逃生道路。基于逃生概率的最短逃生时间消耗网络优化模型不仅能够为个体逃生者提供双路径优化方案,并且能够为群体逃生者提供n级动态逃生路径优化策略,以满足群体安全快速逃生的需求。
为了满足逃生者又安全又快的逃生需求,实现大型公共建筑火灾群体应急逃生策略最优的目标,本文基于大型公共建筑智能逃生空间理论讨论如何构建大型公共建筑火灾应急逃生智能导航系统IENS Fire Guide。IENS Fire Guide基于网络地理信息系统平台和无线传感器网络,通过对逃生者移动设备发射出的信号实现对逃生者的定位,并通过火灾空间风险挖掘与分析功能对逃生者所能够选择的路网进行空间风险关联与评价,在此基础上应用系统的逃生路网的优化功能确定基于最低逃生概率的n级动态逃生方案以辅助逃生者的路径选择及应急指挥人员的决策分析。最后,本文通过对某会展中心火灾场景的模拟,对IENS Fire Guide辅助决策能力进行实例分析。
We are living in a marvelous world. Thousands of years of human society development created abuandence of substantial civilization and spiritual civilization. And we are living in an unpeaceful world. Numerous of natural disasters, technological accidents, public security emergencies and increasing terrorist attacks bring huge lost and take away tens of thousands of precious lives every year. Public security problems and emergency managment have been generally regarded serious by both governments and scholars.
Buildings are symbols of human civilization, and they are also the majority space for modern activities. Compared with normal buildings, large-scale public buildings are characterized by complex structure, dense of population and wealth concentration. So emergencies happen in large scale-public undoubtedly buildings broad and seriously economical, environmental, and social influence. Fire accidents are much more common compared with other types of public security events, and they are the typical and majority dangerous emergencies happened in large-scale public buildings. And human lives are much more precious than any other treasures and wealth. How to help occupants safely and quickly evacuate from the complex large-scacle public building fire environment is the main content of this research.
Building fire is a dynamic ruinous process, which threats the evacuees so much with its environmental risks caused by fire propagation. In such changeable and dangerous condition, it would be challenge for all occupants to chose a safe and quick way to escape out.
In this paper, large-scale public building fir dynamic environment and evacuees’interaction performance has been analysed first. In chapter two, general building fire features and interaction performance of active and passive building fire defence systems in large-scale public buildings has been expatiated. By building fire evacuation safety analysis, the majority types of building fire environmental risks (heat, toxic gas, smoke, and structure collapse) have been summarized with Fractional Effective Dose models expression. Evacuees’psychology analysis and interaction performance understanding in building fire environment provides necessary theoretical basis for path choice and evacuation navigation study.
In order to objectively and accurately evaluate environmental risks caused by the dynamic ruinous process of building fire propagation, relationships and associations among types of risks should be confirmed. Spatial cluster algorithm has been modeled based on spatial data mining theories in chapter three to fulfil building fire environmental risks mining function of large-scale public building fire navigation intelligence navigation system: IENS Fire Guide.
Exploratory Spatial Data Analysis (ESDA) technology has been employed in chapter four to discover hidden relationships among types of risks and associations between risks and evacuees dynamic flow. Univariate spatial risks independence evaluation model and bivariate risks association evaluation model has been proposed to estimate relativities of those relations and associations. In chapter four, large-scale public building evacuation origin-determination (O-D) path environmental risks evaluation has been also proposed to calculate escape probability P and time cost T of each section on the O-D paths.
In chapter five, optional minimal cost network optimization technology has been employed to model up an escape probability based shortest time cost network optimization models to find out the most reliable and fast way to escape out. These models can not only be able to provide optimal scheme for individual evacuation, but also could provide n-level dynamic evacuation optimal strategies for group evacuation.
To realized large-scale public building fire evacuation navigation, chapter six illustrates how to build up an intelligent space and evacuation navigation system for large-scale public building fire safe and quick evacuation. Finally, a fire scenario case study has been proposed to validate intelligent large-scale public building fire evacuation navigation system IENS Fire Guide use.
引文
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