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。

Nonlinear Auto-Companding Method for Behavioral Modeling of Switched-Current Circuits

A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.

Fixed-Bed Column Adsorption Modeling of MnO4- Ions from Acidic Aqueous Solutions on Activated Carbons Prepared with the Biomass

Activated carbons calcined at 400˚C and 600˚C (AC-400 and AC-600), prepared using palm nuts, collected in the town of Franceville in Gabon, were used to study the dynamic adsorption of MnO4- ions in acidic media on fixed bed column and on the kinetic modeling of experimental data of breakthrough curves of MnO4- ions obtained. Results on the adsorption of MnO4- ions in fixed-bed dynamics obtained on AC-400 and AC-600 adsorbents beds indicated that the AC-400 bed appears to be the most efficient in removing MnO4- ions in acidic media. Indeed, the adsorbed amounts, the adsorbed capacities at saturation and the elimination percentage of MnO4- ions obtained with AC-400 (31.24 mg;52.06 mg·g-1 and 41.65% respectively) were higher compared to those obtained with AC-600 (9.87 mg;16.45 mg·g-1 and 17.79% respectively). The breakthrough curves kinetic modeling revealed that the Thomas model and the pseudo-first-order kinetic model were the most suitable models to describe the adsorption of MnO4- ions on adsorbents studied in our experimental conditions. The results of the intraparticle diffusion model showed that intraparticle diffusion was involved in the adsorption mechanism of MnO4- ions on investigated adsorbents and was not the limiting step and the only process controlling MnO4- ions adsorption. In contrast to AC-400, the intraparticle diffusion on AC-600 bed plays an important role in the adsorption mechanism of MnO4- ions.

A Study of Wind Statistics Through Auto-Regressive and Moving-Average (ARMA) Modeling

Statistical properties of winds near the Taichung Harbour are investigated. The 26 years'incomplete data of wind speeds, measured on an hourly basis, are used as reference. The possibility of imputation using simulated results of the Auto-Regressive (AR), Moving-Average (MA), and/ or Auto-Regressive and Moving-Average (ARMA) models is studied. Predictions of the 25-year extreme wind speeds based upon the augmented data are compared with the original series. Based upon the results, predictions of the 50- and 100-year extreme wind speeds are then made.

基于迁移学习-元学习的ADS-B攻击分类研究

准确分类通航领域ADS-B攻击类型,采取预防攻击措施,对保障通航运行安全性具有重要意义。针对通航领域ADS-B攻击数据样本少,提出一种基于迁移学习-元学习的ADS-B攻击分类模型。该模型将迁移学习与深度卷积自编码器相结合,建立ADS-B攻击特征提取模型,提取数据样本的攻击有效特征表示,并运用元学习策略在特征空间中实现ADS-B攻击准确分类。实例研究表明,基于迁移学习-元学习的攻击分类模型可有效分类小样本ADS-B攻击,且正确率在95%以上。

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。

Auto machine learning-based modelling and prediction of excavationinduced tunnel displacement

The influence of a deep excavation on existing shield tunnels nearby is a vital issue in tunnelling engineering.Whereas,there lacks robust methods to predict excavation-induced tunnel displacements.In this study,an auto machine learning(AutoML)-based approach is proposed to precisely solve the issue.Seven input parameters are considered in the database covering two physical aspects,namely soil property,and spatial characteristics of the deep excavation.The 10-fold cross-validation method is employed to overcome the scarcity of data,and promote model’s robustness.Six genetic algorithm(GA)-ML models are established as well for comparison.The results indicated that the proposed AutoML model is a comprehensive model that integrates efficiency and robustness.Importance analysis reveals that the ratio of the average shear strength to the vertical effective stress E_(ur)/σ′_(v),the excavation depth H,and the excavation width B are the most influential variables for the displacements.Finally,the AutoML model is further validated by practical engineering.The prediction results are in a good agreement with monitoring data,signifying that our model can be applied in real projects.

基于VAE-LSTM模型的无人机飞行数据异常检测

无人机飞行数据是反映其自身飞行安全的重要状态参数,通过对飞行数据进行异常检测,是提高无人机整体飞行安全性的关键举措。尽管基于数据驱动方法不需专家先验知识和精确的物理模型,但缺乏参数选择且检测网络结构模型单一,使得检测模型由于参数过多导致过拟合以及无法有效捕捉数据异常模式的问题。文中结合变分自编码器和长短期记忆网络的优势,提出了一种基于VAE-LSTM的无人机飞行数据异常检测模型方法。首先,引入肯德尔相关性分析方法用于选择相关依赖的飞行数据参数集;其次,将具有相关性的参数集对所设计的VAE-LSTM深度混合模型进行训练,学习不同数据特征之间的关系映射;最后,以无监督异常检测方式在真实多维无人机飞行数据进行验证。实验结果表明,VAE-LSTM的精密度、检测率、准确率、F1分数及误检率的各项平均性能指标分别达到95.24%、98.71%、98.8%、96.82%、1.31%,相比于KNN、OC-SVM、VAE、LSTM模型,整体上展现出较好异常检测性能。

Periodic Packing Mode for Trickle-Bed Reactors: Experiments and Modeling

A periodic packing mode of trickle-bed reactor (TBR) for the gas limited reaction was proposed. Hy-drogenation of 2-ethylanthraquinone over Pd/Al2O3 in a laboratory-scale TBR was taken as a test reaction for determining whether the periodic packing mode is advantageous. The effects of operating conditions and packing type on TBR performance were experimentally examined to demonstrate the cause-effect relationships. A mathe-matic model of TBR considering axial dispersion and fractional wetting was developed to quantitatively illuminate the reason of performance enhancement.

Roll System and Stock's Multi-parameter Coupling Dynamic Modeling Based on the Shape Control of Steel Strip

The existence of rolling deformation area in the rolling mill system is the main characteristic which dis- tinguishes the other machinery. In order to analyze the dynamic property of roll system＇s flexural deformation, it is necessary to consider the transverse periodic movement of stock in the rolling deformation area which is caused by the flexural deformation movement of roll system simul- taneously. Therefore, the displacement field of roll system and flow of metal in the deformation area is described by kinematic analysis in the dynamic system. Through intro- ducing the lateral displacement function of metal in the deformation area, the dynamic variation of per unit width rolling force can be determined at the same time. Then the coupling law caused by the co-effect of rigid movement and flexural deformation of the system structural elements is determined. Furthermore, a multi-parameter coupling dynamic model of the roll system and stock is established by the principle of virtual work. More explicitly, the cou- pled motion modal analysis was made for the roll system. Meanwhile, the analytical solutions for the flexural defor- mation movement＇s mode shape functions of rolls are discussed. In addition, the dynamic characteristic of the lateral flow of metal in the rolling deformation area has been analyzed at the same time. The establishment ofdynamic lateral displacement function of metal in the deformation area makes the foundation for analyzing the coupling law between roll system and rolling deformation area, and provides a theoretical basis for the realization of the dynamic shape control of steel strip.

Kinetic Modeling the Formation of Low-mature Gases and Analysis of the Possibility to Be Accumulated

At present, shallow gases have received much attention due to low cost in exploration and production. Low-mature gases, as one significant origin to shallow gas, turns to be an important research topic. The present understanding of low-mature gases is confined within some geological cases, and few laboratory studies have been reported. Therefore, the potential and characters of low- mature gases are not clear up to now. Here, two premature samples （one coal and the other shale） were pyrolyzed in a gold confined system. The gaseous components including hydrocarbon gases and non-hydrocarbon gases were analyzed. Based on kinetic modeling, the formation of low-mature gases was modeled. The results showed that during low mature stage, about 178 mL/gTOC gas was generated from the shale and 100 mL/gTOC from the coal. Two third to three fourth of the generated gases are non-hydrocarbon gases such as H2S and CO2. The total yields of C1-5 for the two samples are almost the same, 30-40 mL/gTOC, but individual gaseous hydrocarbon is different. The shale has much lower C1 but higher C2-5, whereas the coal has higher C1 but lower C2-5. Hydrocarbon gases formed during low-mature stage are very wet. The stable carbon isotope ratios of methane range from -40‰ to -50‰ （PDB）, in good consistence with empiric criterion for low-mature gases summed up by the previous researchers. The generation characters suggest that the low-mature gases could be accumulated to form an economic gas reservoir, but most of them occur only as associated gases.

Thermodynamic modeling and phase diagram prediction of salt lake brine systemsⅡ.Aqueous Li^(+)-Na^(+)-K^(+)-SO_(4)^(2-) and its subsystems

It is still a challenging task to accurately and temperature-continuously express the thermodynamic properties and phase equilibrium behaviors of the salt-lake brine with multi-component,multitemperature and high concentration.The essential subsystem of sulfate type brine,aqueous Li^(+)-Na^(+)-K^(+)-SO_(4)^(2-) and its subsystems across a temperature range from 250 K to 643 K are investigated with the improved comprehensive thermodynamic model.Liquid parameters(Δg_(IJ),Δh_(IJ),and ΔC_(p,IJ))associated with the contributions of Gibbs energy,enthalpy,and heat capacity to the binary interaction parameters,i.e.the temperature coefficients of eNRTL parameters formulated with a Gibbs Helmholtz expression,are determined via multi-objective optimization method.The solid constantsΔ_(f)G_(k)°^((298.15))andΔ_(f)H_(k)°^((298.15))of11 solid species occurred in the quaternary system are rebuilt from multi-temperature solubilities.The modeling results show the accurate representation of(1)solution properties and binary phase diagram at temperature ranges from eutectic points to 643 K;(2)isothermal phase diagrams for Li_(2)SO_(4)-Na_(2)SO_(4)-H_(2)O,Li_(2)SO_(4)-K_(2)SO_(4)-H_(2)O and Na_(2)SO_(4)-K_(2)SO_(4)-H_(2)O ternary systems.The predicted results of complete structure and polythermal phase diagram of ternary systems and the isothermal phase diagrams of quaternary system excellently match with the experimental data.

Aeroelastic modeling of wind loading on a cable-net supported glass wall

Wind loading study on a cable-net supported glass wall is conducted by means of wind tunnel tests. An equiva- lent aeroelastic model is designed and constructed. Response of displacements of the wall is measured and analyzed. In order to design a glass wall under wind loading, the ＂wind- vibration factor＂ is estimated and discussed. In fact, the mech- anism of wind acting on the wall is commonly known not only as positive pressure, but also as negative pressure caused by the flow separation on the corners of the building. Due to the diffidence in the mechanism of wind acting, two typi- cal response cases are classified. The results show that the dynamic response of the structure caused by the negative pressure is stronger than that of the positive pressure case. To determine the aerodynamic wind loading on a flexible part of structure on a building, wind tunnel study may be useful and play an important role.

Lumped parameter analytic modeling and behavioral simulation of a 3-DOF MEMS gyro-accelerometer

A new analytical model of a 3-degree-of-freedom （3-DOF） gyro-accelerometer system consisting of a 1-DOF drive and 2-DOF sense modes is presented. The model constructs lumped differential equations associated with each DOFof the system by vector analysis. The coupled differential equations thus established are solved analytically for their responses in both the time and frequency domains. Considering these frequency response equations, novel device design concepts are derived by forcing the sense phase to zero, which leads to a certain relationship between the structural frequencies, thereby causing minimization of the damping effect on the performance of the system. Furthermore, the feasibility of the present gyro-accelerometer structure is studied using a unique discriminatory scheme for the detection of both gyro action and linear acceleration at their events. This scheme combines the formulated settled transient solution of the gyro-accelerometer with the processes of synchronous demodulation and filtration, which leads to the in-phase and quadrature components of the system＇s output signal. These two components can be utilized in the detection of angular motion and linear acceleration. The obtained analytical results are validated by simulation in a MATLAB/Simulink environment, and it is found that the results are in excellent agreement with each other.

Application of Seasonal Auto-regressive Integrated Moving Average Model in Forecasting the Incidence of Hand-foot-mouth Disease in Wuhan,China

Outbreaks of hand-foot-mouth disease（HFMD） have occurred many times and caused serious health burden in China since 2008. Application of modern information technology to prediction and early response can be helpful for efficient HFMD prevention and control. A seasonal auto-regressive integrated moving average（ARIMA） model for time series analysis was designed in this study. Eighty-four-month（from January 2009 to December 2015） retrospective data obtained from the Chinese Information System for Disease Prevention and Control were subjected to ARIMA modeling. The coefficient of determination（R^2）, normalized Bayesian Information Criterion（BIC） and Q-test P value were used to evaluate the goodness-of-fit of constructed models. Subsequently, the best-fitted ARIMA model was applied to predict the expected incidence of HFMD from January 2016 to December 2016. The best-fitted seasonal ARIMA model was identified as（1,0,1）（0,1,1）12, with the largest coefficient of determination（R^2=0.743） and lowest normalized BIC（BIC=3.645） value. The residuals of the model also showed non-significant autocorrelations（P_（Box-Ljung（Q））=0.299）. The predictions by the optimum ARIMA model adequately captured the pattern in the data and exhibited two peaks of activity over the forecast interval, including a major peak during April to June, and again a light peak for September to November. The ARIMA model proposed in this study can forecast HFMD incidence trend effectively, which could provide useful support for future HFMD prevention and control in the study area. Besides, further observations should be added continually into the modeling data set, and parameters of the models should be adjusted accordingly.

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。

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。

Fuzzy Modeling on L - R Fuzzy Number and Its Application

A new fuzzy modeling method, which based on L - R fuzzy number, is discussed in this paper. First, the fuzzy state equation model is constructed based on fuzzy state variable,fuzzy Input variable and fuzzy output variable whkh are represented by L - R fuzzy number. And then, identification of time - varying parameter in this model is discussed further. At the end, a simulated application is given to Indicate the effectiveness of this fuzzy modeling method.

Application of Auto-regressive Linear Model in Understanding the Effect of Climate on Malaria Vectors Dynamics in the Three Gorges Reservoir

It is important to understand the dynamics of malaria vectors in implementing malaria control strategies. Six villages were selected from different sections in the Three Gorges Reservoir fc,r exploring the relationship between the climatic ｜：actors and its malaria vector density from 1997 to 2007 using the auto-regressive linear model regressi^n method. The result indicated that both temperature and precipitation were better modeled as quadratic rather than linearly related to the density of Anopheles sinensis.

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。