煤与瓦斯突出过程中煤体层裂演化特征实验研究

为了探究煤与瓦斯突出过程中煤体层裂演化特征,利用自主研制的煤与瓦斯突出实验模拟系统,研究突出过程中煤体层裂结构特征、煤体裂隙厚度演化特征和煤体质点运动演化特征。研究结果表明：在轴向应力0.9 MPa、瓦斯压力0.4 MPa时,煤体层裂发展时间持续85 ms,煤体共计出现11处裂隙。层裂从煤体后方的弱构面出现并向前方发展,其位置大多集中于突出腔体中后部,煤体层裂形式均为纵向贯通,在第9处出现最大纵向断裂裂隙。煤体裂隙总厚度约为75.6 mm、单处裂隙平均厚度约为8.4 mm,二者均呈现随时间递增的趋势。层裂过程中煤体单处裂隙厚度并不都是沿程递增的,部分煤体中部裂隙厚度呈现先增大后减小的特征。煤体的运动表现为靠近突出口端的运动速度更快、运动距离也更长。研究结果可为揭示煤与瓦斯突出层裂机制提供参考。     

长大区间隧道抽出式串联通风机排烟能力实验研究

为实现有效通风以降低隧道火灾带来的损失和伤亡,依托青岛市地铁8号线大洋站至青岛北站区间隧道,建立线性比尺为1∶15的隧道通风排烟模型实验系统,针对通风机串联单抽,围绕3种通风机频率匹配组合,测定单机的变频频率值、电功消耗、排烟道与行车道的断面平均风速以及右侧行车道静压。研究结果表明：在相同功率消耗下,不同频率匹配的串联通风机排烟效果存在差异;针对此差异,利用气体挡烟墙性能及其计算欧拉数值比较发现,风井近端的通风机频率较大时,下游对污染气流的抵抗力更强,拥有更好的排烟效果。研究结果可为隧道火灾提供更有效率的防灾救灾数据支持,并从欧拉数方面为研究隧道临界风速提供新角度。     

深埋水平岩层隧道开挖稳定性分析及控制*

针对深埋高地应力水平岩层掌子面开挖稳定性及支护结构失效问题,以大峡谷隧道为工程背景,通过现场测试、室内试验、数值模拟等方法,探究深埋高地应力水平岩层失稳机理及控制措施。研究结果表明:坚硬岩体被节理面切割后,在高地应力作用下容易发生挤压破碎,破碎岩体遇水发生软化,导致掌子面发生大范围塌方,初支和超前支护失效;隧道开挖后岩层发生不均匀沉降,浅部岩层最先发生弯折破坏,层内块体错动滑移,继而向上方岩层发展,并伴随层间分离和层内裂隙发育,最终形成宏观破裂面;提出的台阶法、2 m开挖进尺、砼喷层、双层小导管、提高初支强度的整体优化控制措施,可有效提高现场支护效果。     

复杂地下空间交通体系连接匝道烟气控制方案研究

复杂地下空间交通体系作为新型地下交通形式,车流量大且存在多个分合流点,气流组织复杂,防灾排烟难度极大。以杭州某复杂地下空间交通体系连接匝道为研究背景,提出匝道通风排烟设计方法,再选取其中二合一式连接匝道结构,采用FLUENT模拟其两种防灾排烟方案的有效性。模拟结果表明：两个连接匝道末端单独设置排烟口的设计方案可有效保证火源下游车辆和火源上游人员的逃生安全;根据分合流流速分配理论模型,在合流处只设置一个排烟口且排烟量提高40 m³/s时,也可达到同样的防灾排烟效果,从土建成本考虑,推荐此方案,为同类型隧道结构提供借鉴。     

Dynamic risk assessment for underground gas storage facilities based on Bayesian network

Loss of the underground gas storage process can have significant effects, and risk analysis is critical for maintaining the integrity of the underground gas storage process and reducing potential accidents. This paper focuses on the dynamic risk assessment method for the underground gas storage process. First, the underground gas storage process data is combined to create a database, and the fault tree of the underground gas storage facility is built by identifying the risk factors of the underground gas storage facility and mapping them into a Bayesian network. To eliminate the subjectivity in the process of determining the failure probability level of basic events, fuzzy numbers are introduced to determine the prior probability of the Bayesian network. Then, causal and diagnostic reasoning is performed on the Bayesian network to determine the failure level of the underground gas storage facilities. Based on the rate of change of prior and posterior probabilities, sensitivity and impact analysis are combined to determine the significant risk factors and possible failure paths. In addition, the time factor is introduced to build a dynamic Bayesian network to perform dynamic assessment and analysis of underground gas storage facilities. Finally, the dynamic risk assessment method is applied to underground gas storage facilities in depleted oil and gas reservoirs. A dynamic risk evaluation model for underground gas storage facilities is built to simulate and validate the dynamic risk evaluation method based on the Bayesian network. The results show that the proposed method has practical value for improving underground gas storage process safety.     

CFD-based assessment and visualization of the failure consequences of LPG tankers

This paper presents a simulation analysis of the explosions following an LPG leak and visualizes the consequences of the accident to reduce the consequences of the LPG leak explosion. Firstly, this paper proposes a CFD numerical simulation-based method for visualizing the consequences of LPG tanker failure. The method combines satellite maps and CFD numerical simulation data to visualize the consequences of LPG leaks and explosions, taking into account the influence of obstacles on the danger range of leaks and explosions; Secondly, this paper applies the method to a liquefied petroleum gas accident that occurred in the Wenling section of the Shenhai Expressway and performs CFD numerical simulation on the accident process and visualizes the consequences of the accident. Therefore, this method can provide a theoretical reference for the prior prevention of LPG accidents and the analysis of the consequences of accidents, as well as certain practical guidance instructive.     

A disaster scene simulation system in 3D for oil transmission stations: Design and implementation

The disaster scene in three-dimensional (3D) plays a crucial role in disaster emergency management and risk communication of oil transmission stations. However, existing research for the disaster scene mainly focuses on reproducing the disaster environment and rarely predicts the damage state of the disaster-affected object. This paper proposes an object-oriented modeling method that utilizes a multilevel decomposition pattern for disaster scenes. This method combines earthquake vulnerability assessment with 3D visualization technology to predict and characterize the damage state of critical infrastructure in oil transmission stations. To enhance earthquake risk perception, a simulation system is designed and developed, which allows for the construction of virtual scenes and quick simulation of disaster scenes in 3D. The case application shows that the system improves the 3D modeling efficiency of disaster scenes and enhances public awareness of earthquake risks. The simulation system can provide technical support for seismic mitigation planning and emergency management decision-making at oil transmission stations and has good application prospects.     

A data-driven narratives skeleton pattern recognition from accident reports dataset for human-and-organizational-factors analysis

Accidents in the process industry involve several interacting factors, including human and organizational factors (HOFs). A long-standing obstacle to HOFs analysis is lack of data. Accident reports are an essential data source to learn from the past and contain HOFs-related data, but they are usually unstructured text in a not standardized format. Some studies have explored the extraction of information automatically from accident reports based on Natural Language Processing (NLP) techniques. However, they were not dedicated to HOFs. Risk communication is considered an essential pillar in safety and risk science. This research develops a HOFs-focused risk communication framework based on the NLP techniques that can support risk assessment and mitigation. The proposed approach automatically extracts the target groups oriented “Who, When, Where, Why” (4Ws) information from accident reports.This framework was applied to explore the eMARS database. The results show that the “4Ws” skeleton of narratives has appreciated performance in pattern recognition and holistic information analysis. The graphical representation interfaces are designed to display the features of HOFs-related accidents, which can better be communicated to the sharp-end operators and decision-makers.     

Scenario derivation and consequence evaluation of dust explosion accident based on dynamic Bayesian network

In order to clarify the correlation between the evolution path of dust explosion accidents and emergency decision-making, and to accurately predict the disaster damage levels of various disaster bearing bodies. This paper extracts 56 key scenario elements from four aspects, namely state, answer, goal and environment, based on the analysis of typical dust explosion accident cases. At the same time, a general scenario evolution path of dust explosion accident is constructed. Using fuzzy number set theory and dynamic Bayes joint probability model, the accurate solution of scenario state probability was realized. With the help of accident cases and dynamic Bayes approach, the dust explosion consequence prediction index system and evaluation criteria were constructed, covering factors such as dust explosion intensity, casualties, direct economic losses, equipment damage, building damage, environmental damage and other factors. A polyethylene wax dust explosion accident in a city of China was used to verify the dust explosion accident scenario evolution model and consequences prediction model. The predicted results were in good agreement with the actual damage of various carriers of the accident, which indicated that the model could be used for dust explosion accident prediction and disaster loss prediction. The research results provided reference and technical support for the prediction of dust explosion accident evolution direction, emergency aid measures decision and deployment, disaster damage prediction and evaluation.     

Simulation of scenario characteristics of LPG tank explosion accident and its contribution to emergency planning: A case study

Leakage and explosion of hazardous chemicals during road transportation can cause serious building damage and casualties, and adoption of highly-efficient emergency rescue measures plays a critical role in reducing accidental hazards. Considering a liquefied petroleum gas (LPG) transport tanker explosion accident that occurred in Wenling, Zhejiang Province, China on June 13, 2020 as example, this study proposes a risk assessment framework. This framework recreates the leakage and explosion of the accident process using FLACS v10.9, suggests plans for evacuation, describes the rescue areas of different levels, and explores the influence of environmental factors on the evacuation and rescue areas. The results show that simulated and predicted distributions of fuel vapour cloud concentration and explosion overpressure can provide a reference basis for rapid rescue activities; the characterization of the dynamic effects of wind speed, wind direction, and temperature with respect to the evacuation and rescue areas can be used as theoretical support for on-site adjustment of rescue forces. The role of obstacles can prevent the expansion of the evacuation areas under low wind-speed conditions, and the presence of highly congested obstacles determines the level of the rescue area. The results obtained are important for the risk analysis and the development of emergency rescue measures in case of explosion accidents associated with transportation of hazardous chemicals on high-hazard and high-sensitive road sections.