我国煤矿重特大事故统计分析及对策建议

为揭示近年来我国煤矿事故特征,有针对性地提出事故防范对策建议,首先,收集整理2013—2023年全国重特大煤矿事故,分析事故发生的年份、类型、月份、省份和原因等方面;其次,以内蒙古新井煤业“2·22”特别重大坍塌事故为例,基于“2-4”模型(24Model)分析导致事故发生的原因;最后,结合以上分析和研究结果提出符合我国现阶段煤矿安全生产形势的事故预防对策与建议。结果表明:煤矿重特大事故发生起数和死亡人数呈整体下降趋势,且进入“十二五”规划以来,我国煤矿安全生产水平明显提高;瓦斯事故仍是我国煤矿主要事故,占事故总起数的51%;每年第4季度是煤矿事故高发期,占事故总起数的30.43%;受地质条件和赋存情况影响,煤炭主要产区发生事故较多;人的不安全行为导致的事故占比高达74%;当个体层面和组织层面存在隐患且双重预防措施不到位时,易发生事故;从安全监管、科技兴安、队伍建设、安全文化等4个维度提出降低煤矿安全事故的对策建议。

复杂系统视角下洞室施工人员安全认知仿真研究

为制定有效的安全认知提升策略及减少安全事故的发生,需深入探究洞室施工人员安全认知的演化过程和特征。首先,基于复杂社会技术系统和“2-4”模型(24Model)等相关知识,识别安全认知影响因素,构建洞室施工人员安全认知指标体系;然后,通过Super Decisions软件计算指标权重;随后利用系统动力学(SD)理论,明确各因素间的相互关系,建立包含组织安全管理等4个子系统的SD仿真模型,将以安全投入为基础的认知纠偏机制应用到SD仿真模型;最后,结合实际工程算例开展SD仿真以及敏感性分析。研究表明:随着工程进展,通过增加安全投入,并发挥认知纠偏机制作用,施工人员的整体安全认知由下降趋势转变为缓慢上升趋势;组织安全管理对洞室施工人员安全认知影响程度最大,结果与24Model的基本假设一致,从而验证了SD仿真模型的科学性和有效性。

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

Numerical Analysis of Steady Smoldering of Biomass Rods

Understanding the steady mechanism of biomass smoldering plays a great role in the utilization of smoldering technology.In this study numerical analysis of steady smoldering of biomass rods was performed.A two-dimensional(2D)steady model taking into account both char oxidation and pyrolysis was developed on the basis of a calculated propagation velocity according to empirical correlation.The model was validated against the smoldering experiment of biomass rods under natural conditions,and the maximum error was smaller than 31%.Parameter sensitivity analysis found that propagation velocity decreases significantly while oxidation area and pyrolysis zone increase significantly with the increasing diameter of rod fuel.

Calculations and Sensitivity Analysis of Chlorine-,NO_(x)-,and Bromine-Depleting Cycles of Stratospheric Ozone

This paper presents an engineering system approach using a 2D model of conservation of mass to study the dynamics of ozone and concerned chemical species in the stratosphere.By considering all fourteen photolysis,ozone-generating,and-depleting chemical reactions,the model calculated the transient,spatial changes of ozone under different physical-chemical-radiative conditions.Validation against the measured data demonstrated good accuracy,close match of our model with the observed ozone concentrations at both 20°S and 90°N locations.The deviation in the average concentration was less than 1% and in ozone profiles less than 17%.The impacts of various chlorine-(Cl),nitrogen oxides-(NO_(x)),and bromine-(Br)depleting cycles on ozone concentrations and distribution were investigated.The chlorine catalytic depleting cycle was found to exhibit the most significant impact on ozone dynamics,confirming the key role of chlorine in the problem of ozone depletion.Sensitivity analysis was conducted with levels of 25%,50%,100%,200%,and 400% of the baseline value.The combined cycles(Cl+NO_(x)+Br)showed the most significant influence on ozone behavior.The total ozone abundance above the South Pole could decrease by a small 3%,from 281 DU(Dubson Units)to 273 DU for the 25% level,or by a huge thinning of 60%to 114 DU for the 400% concentration level.When the level of chlorine gases increased beyond 200%,it would cause ozone depletion to a level of ozone hole(below 220 DU).The 2D Ozone Model presented in this paper demonstrates robustness,convenience,efficiency,and executability for analyzing complex ozone phenomena in the stratosphere.

3D and 2D topographic correction to estimated geothermal gradient from the base of gas hydrate stability zone in the Andaman Forearc Basin

Methane gas hydrate related bottom-simulating reflectors(BSRs)are imaged based on the in-line and cross-line multi-channel seismic(MCS)data from the Andaman Forearc Basin.The depth of the BSR depends on pressure and temperature and pore water salinity.With these assumptions,the BSR depth can be used to estimate the geothermal gradient(GTG)based on the availability of in-situ temperature measurements.This calculation is done assuming a 1D conductive model based on available in-situ temperature measurement at site NGHP-01-17 in the study area.However,in the presence of seafloor topography,the conductive temperature field in the subsurface is affected by lateral refraction of heat,which focuses heat in topographic lows and away from topographic highs.The 1D estimate of GTG in the Andaman Forearc Basin has been validated by drilling results from the NGHP-01 expedition.2D analytic modeling to estimate the effects of topography is performed earlier along selected seismic profiles in the study area.The study extended to estimate the effect of topography in 3D using a numerical model.The corrected GTG data allow us to determine GTG values free of topographic effect.The difference between the estimated GTG and values corrected for the 3D topographic effect varies up to~5℃/km.These conclude that the topographic correction is relatively small compared to other uncertainties in the 1D model and that apparent GTG determined with the 1D model captures the major features,although the correction is needed prior to interpreting subtle features of the derived GTG maps.

Structural Setting of the South-West Cameroon Using Satellite Potential Field Derived from SGG-UGM-2 Gravity Data

This study aims to improve knowledge of the structure of southwest Cameroon based on the analysis and interpretation of gravity data derived from the SGG-UGM-2 model. A residual anomaly map was first calculated from the Bouguer anomaly map, which is strongly affected by a regional gradient. The residual anomaly map generated provides information on the variation in subsurface density, but does not provide sufficient information, hence the interest in using filtering with the aim of highlighting the structures affecting the area of south-west Cameroon. Three interpretation methods were used: vertical gradient, horizontal gradient coupled with upward continuation and Euler deconvolution. The application of these treatments enabled us to map a large number of gravimetric lineaments materializing density discontinuities. These lineaments are organized along main preferential directions: NW-SE, NNE-SSW, ENE-WSW and secondary directions: NNW-SSE, NE-SW, NS and E-W. Euler solutions indicate depths of up to 7337 m. Thanks to the results of this research, significant information has been acquired, contributing to a deeper understanding of the structural composition of the study area. The resulting structural map vividly illustrates the major tectonic events that shaped the geological framework of the study area. It also serves as a guide for prospecting subsurface resources (water and hydrocarbons). .

2-D Modeling and Calculations of Stratospheric Ozone and Influences of Convection, Diffusion, and Time

An engineering system approach of 2-D cylindrical model of transient mass balance calculations of ozone and other concerned chemicals along with fourteen photolysis, ozone-generating and ozone-depleting chemical reaction equations was developed, validated, and used for studying the ozone concentrations, distribution and peak of the layer, ozone depletion and total ozone abundance in the stratosphere. The calculated ozone concentrations and profile at both the Equator and a 60˚N location were found to follow closely with the measured data. The calculated average ozone concentration was within 1% of the measured average, and the deviation of ozone profiles was within 14%. The monthly evolution of stratospheric ozone concentrations and distribution above the Equator was studied with results discussed in details. The influences of slow air movement in both altitudinal and radial directions on ozone concentrations and profile in the stratosphere were explored and discussed. Parametric studies of the influences of gas diffusivities of ozone DO3 and active atomic oxygen DO on ozone concentrations and distributions were also studied and delineated. Having both influences through physical diffusion and chemical reactions, the diffusivity (and diffusion) of atomic oxygen DO was found to be more sensitive and important than that of ozone DO3 on ozone concentrations and distribution. The 2-D ozone model present in this paper for stratospheric ozone and its layer and depletion is shown to be robust, convenient, efficient, and executable for analyzing the complex ozone phenomena in the stratosphere. .

Prediction of discharge in a tidal river using the LSTM-based sequence-to-sequence models

The complexity of river-tide interaction poses a significant challenge in predicting discharge in tidal rivers.Long short-term memory(LSTM)networks excel in processing and predicting crucial events with extended intervals and time delays in time series data.Additionally,the sequence-to-sequence(Seq2Seq)model,known for handling temporal relationships,adapting to variable-length sequences,effectively capturing historical information,and accommodating various influencing factors,emerges as a robust and flexible tool in discharge forecasting.In this study,we introduce the application of LSTM-based Seq2Seq models for the first time in forecasting the discharge of a tidal reach of the Changjiang River(Yangtze River)Estuary.This study focuses on discharge forecasting using three key input characteristics:flow velocity,water level,and discharge,which means the structure of multiple input and single output is adopted.The experiment used the discharge data of the whole year of 2020,of which the first 80%is used as the training set,and the last 20%is used as the test set.This means that the data covers different tidal cycles,which helps to test the forecasting effect of different models in different tidal cycles and different runoff.The experimental results indicate that the proposed models demonstrate advantages in long-term,mid-term,and short-term discharge forecasting.The Seq2Seq models improved by 6%-60%and 5%-20%of the relative standard deviation compared to the harmonic analysis models and improved back propagation neural network models in discharge prediction,respectively.In addition,the relative accuracy of the Seq2Seq model is 1%to 3%higher than that of the LSTM model.Analytical assessment of the prediction errors shows that the Seq2Seq models are insensitive to the forecast lead time and they can capture characteristic values such as maximum flood tide flow and maximum ebb tide flow in the tidal cycle well.This indicates the significance of the Seq2Seq models.

多因素耦合失效模式下地铁施工安全系统与管理模型

为提升地铁施工安全管理效果,减小地铁坍塌事故的发生,分析地铁施工事故风险因素。首先,分析事故致因中人群-机群的多因素耦合模式;然后,借助事故致因“2-4”模型(24Model)和广义安全模型(GSM),构建地铁施工安全系统管理模型;最后,将人群-机群系统多因素耦合失效模式应用于已有的16起地铁施工坍塌事故,统计得到14个人群与6个机群致因因素,分别给出其多因素耦合模式及作用路径,并计算风险等级。结果表明:地铁施工人群-机群的多因素耦合效应包含6种模式和14条作用路径。地铁施工安全系统管理模型分为目标层与匹配层,其中,匹配层主要是将事故原因与安全防线相匹配,包括微匹配、中匹配和宏匹配3个层面。并基于地铁施工安全系统管理模型,给出地铁坍塌事故预防安全管理“三道防线”。

24 Model在道路运输事故成因中的应用

为预防道路运输事故,基于事故致因“2-4”(24 Model)模型,对2015—2021年发生的215起道路运输事故的行为原因进行研究。从个人层面和组织层面分析导致事故发生的直接原因、间接原因、根本原因及其根源原因。结果表明:发生频次最多的不安全动作是驾驶员超速行驶(占10.67%);22.33%的道路运输事故存在管理者违章安排无资质员工上岗作业;管理者和领导者对57.67%的道路运输事故的发生有重要影响;由人为因素产生的不安全物态占比达71.53%;驾驶员、车辆安全生产管理制度欠缺或执行不到位在根本原因中尤为突出(占20.92%)。基于此,提出道路运输事故预防对策并构建出道路运输系统各因素关系图。

基于“2-4”模型和Apriori算法的商业综合体火灾成因分析

为深入分析商业综合体火灾事故成因,揭示事故致因因素之间的关联规则,运用事故致因“2-4”模型和Apriori算法,对40起商业综合体火灾事故原因进行分析,研究结果表明:在组织文化、管理体系、个体能力和个体动作4个层面中,安全主体责任的认识(100%)、安全管理制度未执行(80%)、无安全培训(70%)等因素是火灾事故的主要原因;通过Apriori算法挖掘出277条关联规则,并从高支持度、高置信度和高提升度3个维度进行深入分析,发现员工参与度与防火意识薄弱、安全管理知识匮乏与报警意识薄弱且应急响应不及时等因素之间存在显著关联。基于分析结果,提出加强安全责任意识、完善管理制度执行、强化安全培训等针对性建议,为商业综合体火灾预防提供理论依据和实践指导。

基层社区应急能力提升对策研究

为解决基层社区应急能力不足、缺乏有效应急对策等问题,选用24Model对社区火灾事故进行分析,明确社区火灾发生的关键节点,构建基层社区火灾情景贝叶斯网络(bayesian network),并结合专家打分法和贝叶斯方法计算得出基层社区火灾在不同情景的发生概率。研究结果表明:采取专人监管、完善消防装备体系及设置第一响应人等一系列应急措施后,社区火灾事故发生概率降低到33.3%,结合24Model与贝叶斯方法分析基层社区火灾,可找到最易导致火灾发生的个体动作,从而提出应急能力提升对策,有效降低基层社区火灾的发生概率,为社区应急管理提供理论依据。

IFAM与24Model的对比研究

为完善和推动事故致因理论的发展,提高事故防控水平,在对信息流事故致因模型(IFAM)和事故致因2-4模型(24Model)理论基础、组成要素和分析过程对比研究的基础上,通过实例分析辨识二者之间的异同。研究结果表明:IFAM与24Model都有较强的理论基础,部分组成要素存在对应关系,但原因类别划分存在差异。IFAM以信息流和组织为研究对象,研究过程相对复杂,更适用于分析单起事故;24Model以组织为研究对象,事故原因模块通用性和逻辑性强,适用于分析单起或某类事故。在实际应用中,IFAM与24Model均可用于事故调查分析和事故分级定责,具有一定的理论和实践价值。IFAM通过信息流表征事故致因,直观描述组织外部原因因素,但对个体能力的深入研究欠缺;而24Model认为组织外部因素需要通过组织内部原因模块的欠缺体现,认为个体能力是引发事故的间接原因并进行细致分析,但对组织间相关关系的探究欠缺。研究结果可为事故预防工作提供新视角和理论支撑。

基于24Model的房屋市政工程事故致因组态研究

为探索房屋市政工程事故的影响因素与关联组态路径,依据案例的完整性、代表性与可靠性选取2018—2022年发生的70起较大及以上规模房屋市政工程生产安全事故作为研究对象,运用定性比较分析方法和“2-4”模型寻找该类事故的致因组态。研究结果表明:组织安全管理体系的执行情况是导致事故发生的重要影响因素;安全文化型和不安全动作型是事故的主要发生机制;事故致因与结果之间存在多重并发的因果关系。房屋市政工程生产安全管理需夯实安全管理体系,利用致因组态强化事故预防措施,以改善工程的经济与社会效益。

基于NLP的煤矿事故原因分类研究

为有效提升分析和处理煤矿事故文本的效率,融合自然语言处理(NLP)技术与事故致因模型,构建一个自动化的事故原因分类框架。首先以事故致因“2-4”模型(24Model)为事故分类依据,分析87份煤矿事故调查报告,得到煤矿事故原因分类框架,构建每类事故原因的语料库;然后利用NLP技术分别处理语料库中各类原因文本,将其用于训练fastText模型,自动识别事故原因文本并分类;最后对比分析fastText模型与TextCNN等其他3种经典模型的分类效果。结果表明:共得到21类事故原因和6684条训练语料,训练后的fastText模型对煤矿事故原因分类的识别正确率能够达到98.92%,综合性能优于其他3种分类模型。基于24Model和NLP技术开发的事故文本挖掘系统,能够快速分析处理事故文本信息,进一步细化事故调查报告中的原因,便于进行事故案例学习和统计分析。

事故致因理论及其发展综述

事故致因理论作为安全工作的理论基础和支撑,明确其概念和发展过程对理解“大安全、大应急”等管理业务具有重要意义。通过文献综述,对事故致因理论的发展过程及其分类进行梳理。结果表明,1984年至今发表的事故致因理论综述文献中,将事故致因理论分为3个主要类别,即线性事故致因理论、多因素事故致因理论和系统论事故致因理论。其中系统论事故致因理论主要包括AcciMap、STAMP、FRAM和HFACS,这几个模型在社会技术系统事故发生机制的定量化描述方面取得很大进展,但也存在较大的主观性和抽象性。动态事故致因“2-4”模型完全具有系统论事故致因模型的特征,它在社会技术系统事故发生机制的描述及预防对策制定上比以往模型有很大优势。

行为追溯安全培训法(ACT)理论构建与应用

为减少作业人员不安全行为,提高现场作业安全绩效,以案例教学和事故致因“2-4”模型(24Model)为指导,结合策划、实施、检查、处理(PDCA)循环理论,构建以事故-原因-培训(ACT)为关系链的行为追溯安全培训法,亦称ACT安全培训法。该方法将事故案例贯穿培训全程,发挥案例教学优势,利用事故致因24Model追溯导致事故的组织层面和个人层面的不安全因素,基于分析结果制定针对性的培训方案,并以有限空间作业课程培训体系设计实施为例,验证ACT安全培训法的实际应用效果。结果表明:在有限空间作业培训课程体系实施过程中,参训人员数量及考核成绩均呈整体上升趋势,受训人员参与积极性及学习效果都得到有效提高,验证了ACT安全培训法具有良好的实用效果。

SST effect on the pre-monsoon intraseasonal oscillation over the South China Sea based on atmospheric-coupled GCM comparison

The role of sea surface temperature(SST)variability in the pre-monsoonal(April to July)intraseasonal oscillation(ISO)over the South China Sea(SCS)is investigated using the Community Earth System Model Version 2(CESM2).An Atmospheric Model Intercomparison Project(AMIP)simulation forced by daily sea surface temperatures(SSTs)derived from a parallel coupled general circulation model(CGCM)run was compared with observations and the mother coupled simulation.In the coupled model,the SST warming leads the peak convection about 1/4 period as in observations.The paralell uncoupled model fails to simulate this phase relationship,implying the importance of air-sea coupling in reproducing realistic ISO.Due to the near-quadrature phase relationship between SST and precipitation ISOs during the ISO events,it is difficult to distinguish the active/passive role of SST from observations alone.Significant correlation in intraseasonal precipitation between the daily SST-forced AMIP and mother CGCM runs indicates that SST plays a role in driving the atmospheric ISO.