大尺度障碍物与泄爆面对天然气内爆炸的协同作用规律研究

为阐释民用建筑内部大尺度物品与门窗等泄爆面对天然气爆炸灾害的协同作用机制，基于典型厨房空间布局及内部物品特征，借助计算流体动力学技术研究了不同泄爆面开启压力和不同大尺度障碍物体积阻塞率条件下天然气内爆炸火焰速度、爆炸超压的分布规律。研究结果表明:大尺度障碍物与泄爆面对室内天然气爆炸过程具有显著的协同作用，共同促进火焰速度与爆炸超压的显著增长，并缩短峰值超压到达时间；大尺度障碍物的存在虽然显著降低了室内天然气的体积，但从增加房间内湍流源和相对长径比的角度进一步促进了泄爆效应；大尺度障碍物与泄爆面协同作用下，室内火焰速度呈现明显的阶段性特征，并在泄爆面附近发生波动。研究结论可为民用建筑物内气体爆炸事故调查分析和灾害评估提供科学依据。     

Mitigation performance of the process protection system on the accident consequences of H2S-containing natural gas release and explosion

Toxic loads and explosion overpressure loads pose grave threats to the offshore oil and gas industry. Many safety measures are adopted to prevent and mitigate the adverse impacts caused by toxic loads and explosion overpressure loads. As a general safety barrier, the process protection system has been widely used but rarely evaluated. In order to assess the barrier ability, the mitigation performance of the process protection system is concerned in this study. Firstly, several chain accidents of H₂S-containing natural gas leakage and explosion are simulated by varying the response time of the process protection system with CFD code FLACS. Qualitative assessment is conducted based on the variation of the dangerous load profiles. Furthermore, the quantitative assessment of the mitigation performance is accomplished by considering its ability in reducing the probability of fatality. Emergency evacuation and no emergency evacuation are considered respectively in the quantitative assessment. The results prove that the process protection system takes effect on mitigating the toxic impact and explosion overpressure impact. The results also demonstrate that although the emergency evacuation may result in a severer explosion load to the operator, the process protection system can mitigate the adverse impacts regardless of whether the emergency evacuation is conducted or not.     

障碍物排列方式对海洋平台蒸气云爆炸的影响

为了了解障碍物排列方式对海洋平台蒸气云爆炸的影响,基于CFD方法建立蒸气云爆炸计算模型,选用国外MERGE项目的系列爆炸实验进行模型验证,提出用于衡量障碍物排列不均匀度的量化参数,针对海洋平台典型结构形式,分析障碍物排列方式对爆炸强度的影响。研究结果表明:蒸气云爆炸后果对于结构排列方式比较敏感,结构障碍物间隔均匀排列的形式造成的爆炸冲击作用最大;在爆炸发展初期阶段,障碍物阻塞程度对超压产生和发展影响更加显著。最后,基于研究结果,给出在海洋平台油气泄漏危险区将管线沿甲板非均匀排列布置等防控建议,为海洋平台蒸气云爆炸安全防控提供理论指导。     

开敞空间可燃气云爆炸冲击波超压及灾害动力响应研究评述

为了进一步梳理和分析开敞空间可燃云爆炸冲击波超压传播规律及灾害动力响应方面的各项研究成果,推进可燃气体爆炸安全防控,减少人员伤亡和经济损失。在分析现有研究的基础上,总结开敞空间可燃气云爆炸冲击波超压传播规律及灾害动力响应研究等方面存在的不足,提出开敞空间多元混合气体爆炸冲击波超压传播规律研究、多影响参数下可燃气云爆炸冲击波超压传播规律定量分析、基于可燃气云爆炸冲击波超压作用下的承载体动力响应等未来研究的关键技术问题。     

爆炸冲击荷载对动物杀伤作用距离的试验研究

采用3 kg、5 kg和10 kg装药在自由场中爆炸,观察分析距炸点不同距离的家兔在爆炸冲击波下的伤亡情况.试验同时使用冲击波超压测量仪记录不同位置的冲击波超压.试验结果表明,在超压小于0.08×105 Pa时家兔基本安全,3 kg、5 kg、10 kg炸药爆炸时的安全距离分别为20 m、25 m、30 m.     

基于FLACS的海上钻探平台井喷爆炸事故后果模拟分析*

为研究海上钻探平台井喷燃爆事故后果,运用FLACS软件对某深海钻探平台井喷爆炸事故进行模拟,研究在不同事故场景下气云爆炸发展过程及平台荷载分布规律,讨论井喷速率、风向、点火位置等对爆炸超压的影响。研究结果表明:随泄漏速率增加,爆炸强度和爆炸范围均增大,爆炸严重程度不仅与井喷速率密切相关,同时也受平台结构影响;点火位置会对爆炸超压产生影响,在可燃气体与空气混合气体比例为化学理论当量比处点燃气体,生活区承受的爆炸超压最大;在设施及建构筑物分布较为密集、拥塞度较高的地方产生的爆炸超压更大。研究结果可为可为平台的阻隔防爆性能设计与应急响应提供指导。     

泄爆口参数对氢气火焰传播过程影响的数值模拟*

为了减少管内气体爆炸造成的损失与破坏,基于大涡模拟LES模型和Zimont燃烧模型,研究泄爆尺寸(直径为40,60,80 mm)和泄爆位置(侧方距点火端1,3,5 m)等泄爆条件对受限空间中氢气燃爆特性的影响。研究结果表明:大孔径泄爆口更好的排放效果造成火焰锋面在通过泄爆口时发生严重畸变,而泄爆口与点火端距离的增加则会削弱火焰锋面畸变的程度,且不同尺寸泄爆口产生的泄压效果差异较大。因此,应考虑将合适尺寸的泄爆口设置于靠近易燃点处。通过探索不同泄爆孔径与泄爆口位置对氢气火焰传播的影响规律,可为实际应用中的安全泄爆起到指导性作用。     

一种处理爆炸多能法的新方法

以多能法中距离－超压关系图为例,介绍了一种运用前馈多层感知器网络对现行多能法中查图步骤进行改进的方法。此法从很大程度上解决了多能法在爆炸灾害评估中手工查图误差大且不方便的缺点。模拟结果表明,该处理方法能够很好的逼近多能法中的超压函数P＝f(R0,C),最后提出了人工神经网络方法在爆炸破坏效应评估中进一步应用的设想。     

Prediction of BLEVE mechanical energy by implementation of artificial neural network

In the event of a BLEVE, the overpressure wave can cause important effects over a certain area. Several thermodynamic assumptions have been proposed as the basis for developing methodologies to predict both the mechanical energy associated to such a wave and the peak overpressure. According to a recent comparative analysis, methods based on real gas behavior and adiabatic irreversible expansion assumptions can give a good estimation of this energy. In this communication, the Artificial Neural Network (ANN) approach has been implemented to predict the BLEVE mechanical energy for the case of propane and butane. Temperature and vessel filling degree at failure have been considered as input parameters (plus vessel volume), and the BLEVE blast energy has been estimated as output data by the ANN model. A Bayesian Regularization algorithm was chosen as the three-layer backpropagation training algorithm. Based on the neurons optimization process, the number of neurons at the hidden layer was five in the case of propane and four in the case of butane. The transfer function applied in this layer was a sigmoid, because it had an easy and straightforward differentiation for using in the backpropagation algorithm. For the output layer, the number of neurons had to be one in both cases, and the transfer function was purelin (linear). The model performance has been compared with experimental values, proving that the mechanical energy of a BLEVE explosion can be adequately predicted with the Artificial Neural Network approach.     

压力对镜质组反射率与烃类生成的影响

镜质组反射率是广泛使用的成熟度参数 ,长期以来人们普遍认为温度和时间是控制镜质组反射率的主要因素 ,而压力对反射率的影响人们知之甚少。本文综述了模拟实验和地质实例中压力对镜质组反射率和烃类生成影响的不同观点。介绍了过压造成镜质组反射率延尺的两个动力学模型