火灾安全设计中参数不确定性分析及耦合风险的设计方法研究
发布时间：2018-12-13 02:47
【摘要】：在火灾安全设计中,通常利用火灾动力学模型、探测模型和人员疏散模型来计算得到合理的火灾安全设计方案。由于火灾动力学和疏散过程的高度复杂性,这些模型的输入参数往往具有一定的不确定性。对火灾安全设计中的参数不确定性进行科学有效地量化对于保证火灾安全设计结果的科学性、可信性具有重要意义。在目前的火灾安全设计中,经常忽视这些参数的不确定性,将这些参数视为定值或者通过设定安全系数来表示这些不确定性。这样的处理方法很难对参数不确定性进行有效处理,因而所得到设计结果的准确性和可信性缺乏有效验证。针对这一问题,本论文提出了定量分析参数不确定性影响的方法以及考虑参数不确定性的火灾安全设计方法,主要研究工作与成果如下： 基于拉丁超立方抽样(LHS)的Monte Carlo模拟建立了分析热释放速率不确定性对可用安全疏散时间(ASET)影响的方法。根据t2火假设,分析了火灾增长系数和最大热释放速率的不确定性,并采用概率方法来表征其不确定性。在分析了确定性火灾增长系数和最大热释放速率对ASET的影响基础上,利用基于拉丁超立方抽样(Latin Hypercube Sampling, LHS)的Monte Carlo模拟分析了当分别考虑火灾增长系数和最大热释放速率的不确定性时对ASET的影响,最后讨论了二者均为不确定性参数时对ASET的影响。此外,本部分还给出了如何利用概率信息如累积概率函数和补充累积概率函数来帮助火灾安全设计人员设定合理的火灾规模。 提出了RSET相关计算模型的全局参数敏感性分析方法。为减少参数不确定性分析的计算量并保证计算的精度,需要利用参数敏感性分析方法确定各输入参数对结果的影响程度。由于RSET计算所涉及模型的复杂性,模型的输入参数与输出结果之间往往是非线性的且输入参数之间的交互作用也会对模型输出产生影响。因此,传统的局部参数敏感性分析方法不适合RSET相关计算模型的参数敏感性分析。为此,本研究提出了适用于RSET计算模型的全局参数敏感性分析方法,包括输入参数不确定性的表征、基于散点图的初步敏感性分析以及傅里叶谱敏感性测试(Fourier amplitude sensitivity test,FAST)和Sobol指数法的全局参数敏感性分析方法。在给定参数取值范围和分布的情况下,对感温探测模型和人员疏散模型进行了全局参数敏感性分析。首先利用散点图来检验输入参数与输出结果之间是否存在线性关系。基于散点图的分析结果,利用FAST和Sobol一阶指数对感温探测模型和疏散模型进行了全局参数敏感性分析；以Sobol二阶指数为指标定量分析了输入参数的交互作用对探测时间和疏散时间的影响；通过将某一不确定性参数取做定值时的累积概率曲线与考虑所有参数不确定性时的累积概率曲线比较,验证了本研究中参数敏感性分析方法的有效性。 在分析了热释放速率不确定性对ASET影响的基础上,提出了一种火灾安全设计中火灾规模的定量计算方法。该方法将可接受风险水平的概念引入到了目标失效概率的设定中,在考虑热释放速率不确定性的前提下,提出利用可靠性理论和全局优化算法来计算不同火灾场景下所需要设定的火灾规模。工程算例分析结果表明该方法可以用于火灾安全设计中火灾规模的定量计算。 提出了将安全系数与目标失效概率联系起来的计算方法。由于目前安全系数取值依赖设计人员的主观判断且设计人员无法确定所选定的安全系数对应多大的失效概率,在考虑ASET和RSET计算过程中参数不确定性的前提下,将传统的安全系数概念进行了拓展,提出了随机安全系数的概念。基于随机安全系数的概率分布,建立了安全系数与失效概率之间的关系。针对ASET和RSET的概率分布较为复杂,无法得到随机安全系数的概率分布表达式的不足,利用基于LHS的Monte Carlo模拟确定随机安全系数的概率分布。工程算例分析结果表明,本文所提出的方法可以有效地将安全系数与失效概率联系起来,从而使得火灾安全设计人员在选取安全系数时能够充分考虑可接受的火灾风险水平,为安全系数的选取提供科学依据。此外,该方法也能够为设计人员提供现有设计方案的改进建议,使最终的设计结果更为科学可信。
[Abstract]:In the fire safety design, the fire dynamics model, the detection model and the personnel evacuation model are usually used to calculate the reasonable fire safety design scheme. The input parameters of these models often have certain uncertainties due to the high complexity of the fire dynamics and the evacuation process. The scientific and effective quantification of the parameter uncertainty in the fire safety design is of great significance to ensure the scientific and credible of the fire safety design result. In the current fire safety design, the uncertainty of these parameters is often ignored, these parameters are treated as fixed values or these uncertainties are expressed by setting a safety factor. Such a processing method is difficult to effectively handle the uncertainty of the parameters, so that the accuracy and the credibility of the obtained design result are not effectively verified. In order to solve this problem, this paper puts forward a method for quantitatively analyzing the influence of the uncertainty of the parameters and the method of fire safety design considering the uncertainty of the parameters. The main research work and results are as follows: The effect of thermal release rate uncertainty on the available safe evacuation time (ASET) is established based on the Monte Carlo simulation of the Latin hypercube sampling (LHS) Method. According to the hypothesis of t2 fire, the uncertainty of the fire growth factor and the maximum heat release rate is analyzed, and the probability method is used to characterize the uncertainty. Based on the analysis of the effect of the deterministic fire growth factor and the maximum heat release rate on the ASET, the shadow of the ASET is analyzed by the Monte Carlo simulation based on the Latin Hypercube Sampling (LHS). In response, the shadow of the ASET is discussed in the end of the paper. in addition, this section also provide how to use that probability information such as the cumulative probability function and the supplemental cumulative probability function to help the fire safety design personnel to set a reasonable fire gauge The global parameter sensitivity of the RSET-related calculation model is presented. In order to reduce the calculation amount of the parameter uncertainty analysis and to ensure the accuracy of the calculation, it is necessary to use the parameter sensitivity analysis method to determine the shadow of each input parameter to the result In response to the complexity of the model involved in the RSET calculation, the input parameters of the model and the output results are often non-linear and the interaction between the input parameters can also output the model output The traditional local parameter sensitivity analysis method is not suitable for the parameter sensitivity of the RSET-related calculation model. For this purpose, the global parameter sensitivity analysis method for RSET calculation model is proposed, including the characterization of input parameter uncertainty, the preliminary sensitivity analysis based on the scatter diagram, and the Fourier spectrum sensitivity test (Fourier sample sensitivity t Global parameter sensitivity score for the test, FAST, and Sobol index method In the condition of the range and distribution of a given parameter, the temperature-sensitive detection model and the personnel evacuation model are sensitive to global parameters sex analysis. First, use a scatter diagram to verify that there is a line between the input parameter and the output result In this paper, based on the results of the analysis of the scatter diagram, the global parameter sensitivity analysis of the temperature-sensitive detection model and the evacuation model is carried out by using the FAST and Sobel-order indices, and the detection time and the evacuation time of the interaction of the input parameters are quantitatively analyzed with the Sobol second-order index as the index. The influence of the parameter sensitivity analysis method in this study is verified by comparing the cumulative probability curve of a certain uncertainty parameter with the cumulative probability curve when the uncertainty of all parameters is taken into account. Effectiveness. Based on the analysis of the effect of thermal release rate uncertainty on the effect of the ASET, a method for determining the scale of fire in a fire safety design is put forward. In the method, the concept of acceptable risk level is introduced into the setting of the target failure probability. Under the premise of considering the uncertainty of the heat release rate, the reliability theory and the global optimization algorithm are put forward to calculate the required settings in different fire scenarios. The results of the engineering calculation show that the method can be used in the fire safety design The quantitative calculation of the safety factor and the target failure probability is presented. Due to the fact that the current safety factor is dependent on the subjective judgment of the designer and the designer cannot determine the selected safety factor corresponding to the large failure probability, the traditional safety factor is compared under the premise of considering the uncertainty of the parameters in the calculation process of the ASET and the RSET The concept is expanded and random The concept of safety factor. The safety factor and failure are established based on the probability distribution of the random safety factor. The probability distribution of ASET and RSET is complex and the probability distribution expression of the random safety factor cannot be obtained, and the random safety is determined by the Monte Carlo simulation based on the LHS. The results of engineering calculation show that the method proposed in this paper can effectively link the safety factor with the failure probability, so that the fire safety designer can fully consider the acceptable safety factor when selecting the safety factor. The risk level of fire is selected as a factor of safety. in addition, that method can provide the design personnel with the improvement proposal of the existing design scheme to make the final design knot
【学位授予单位】：中国科学技术大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：X932
本文编号：2375733
[Abstract]:In the fire safety design, the fire dynamics model, the detection model and the personnel evacuation model are usually used to calculate the reasonable fire safety design scheme. The input parameters of these models often have certain uncertainties due to the high complexity of the fire dynamics and the evacuation process. The scientific and effective quantification of the parameter uncertainty in the fire safety design is of great significance to ensure the scientific and credible of the fire safety design result. In the current fire safety design, the uncertainty of these parameters is often ignored, these parameters are treated as fixed values or these uncertainties are expressed by setting a safety factor. Such a processing method is difficult to effectively handle the uncertainty of the parameters, so that the accuracy and the credibility of the obtained design result are not effectively verified. In order to solve this problem, this paper puts forward a method for quantitatively analyzing the influence of the uncertainty of the parameters and the method of fire safety design considering the uncertainty of the parameters. The main research work and results are as follows: The effect of thermal release rate uncertainty on the available safe evacuation time (ASET) is established based on the Monte Carlo simulation of the Latin hypercube sampling (LHS) Method. According to the hypothesis of t2 fire, the uncertainty of the fire growth factor and the maximum heat release rate is analyzed, and the probability method is used to characterize the uncertainty. Based on the analysis of the effect of the deterministic fire growth factor and the maximum heat release rate on the ASET, the shadow of the ASET is analyzed by the Monte Carlo simulation based on the Latin Hypercube Sampling (LHS). In response, the shadow of the ASET is discussed in the end of the paper. in addition, this section also provide how to use that probability information such as the cumulative probability function and the supplemental cumulative probability function to help the fire safety design personnel to set a reasonable fire gauge The global parameter sensitivity of the RSET-related calculation model is presented. In order to reduce the calculation amount of the parameter uncertainty analysis and to ensure the accuracy of the calculation, it is necessary to use the parameter sensitivity analysis method to determine the shadow of each input parameter to the result In response to the complexity of the model involved in the RSET calculation, the input parameters of the model and the output results are often non-linear and the interaction between the input parameters can also output the model output The traditional local parameter sensitivity analysis method is not suitable for the parameter sensitivity of the RSET-related calculation model. For this purpose, the global parameter sensitivity analysis method for RSET calculation model is proposed, including the characterization of input parameter uncertainty, the preliminary sensitivity analysis based on the scatter diagram, and the Fourier spectrum sensitivity test (Fourier sample sensitivity t Global parameter sensitivity score for the test, FAST, and Sobol index method In the condition of the range and distribution of a given parameter, the temperature-sensitive detection model and the personnel evacuation model are sensitive to global parameters sex analysis. First, use a scatter diagram to verify that there is a line between the input parameter and the output result In this paper, based on the results of the analysis of the scatter diagram, the global parameter sensitivity analysis of the temperature-sensitive detection model and the evacuation model is carried out by using the FAST and Sobel-order indices, and the detection time and the evacuation time of the interaction of the input parameters are quantitatively analyzed with the Sobol second-order index as the index. The influence of the parameter sensitivity analysis method in this study is verified by comparing the cumulative probability curve of a certain uncertainty parameter with the cumulative probability curve when the uncertainty of all parameters is taken into account. Effectiveness. Based on the analysis of the effect of thermal release rate uncertainty on the effect of the ASET, a method for determining the scale of fire in a fire safety design is put forward. In the method, the concept of acceptable risk level is introduced into the setting of the target failure probability. Under the premise of considering the uncertainty of the heat release rate, the reliability theory and the global optimization algorithm are put forward to calculate the required settings in different fire scenarios. The results of the engineering calculation show that the method can be used in the fire safety design The quantitative calculation of the safety factor and the target failure probability is presented. Due to the fact that the current safety factor is dependent on the subjective judgment of the designer and the designer cannot determine the selected safety factor corresponding to the large failure probability, the traditional safety factor is compared under the premise of considering the uncertainty of the parameters in the calculation process of the ASET and the RSET The concept is expanded and random The concept of safety factor. The safety factor and failure are established based on the probability distribution of the random safety factor. The probability distribution of ASET and RSET is complex and the probability distribution expression of the random safety factor cannot be obtained, and the random safety is determined by the Monte Carlo simulation based on the LHS. The results of engineering calculation show that the method proposed in this paper can effectively link the safety factor with the failure probability, so that the fire safety designer can fully consider the acceptable safety factor when selecting the safety factor. The risk level of fire is selected as a factor of safety. in addition, that method can provide the design personnel with the improvement proposal of the existing design scheme to make the final design knot
【学位授予单位】：中国科学技术大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：X932
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