基于人工神经网络的二元液体闪点预测

建立了一个基于人工神经网络的理论模型,用于预测二元混合液体的闪点.根据所研究混合液体的物理性质,选择了相关黏度、表面张力等物理参数来表征闪点,以这些参数作为输入参数,二元混合液体的闪点作为输出值,应用反向传播(BP)人工神经网络方法对两者之间的内在定量关系进行模拟.结果表明,闪点预测值与实验值符合良好,优于传统的计算方...     

混合液体火灾爆炸危险性——闪点预测与实验研究

支持向量机应用核函数技术,已经成为当前国际上一个研究的热点,由于支持向量机具有良好的理论基础和泛化性能,可将其引入到混合液体闪点预测的研究之中,以期建立准确、高效的预测模型。本文建立了一个基于支持向量机的理论模型,用于预测二元互溶混合液体的闪点。根据所研究混合液体的物理性质,选择了纯物质的粘度、表面张力、配比、燃烧下限等物理参数来表征闪点,以这些参数作为输入参数,二元混合液体的闪点作为输出值,应用支持向量机方法对两者之间的内在定量关系进行模拟。结果表明,闪点预测值与实验值符合良好。本方法的提出为工程上提出了一种预测二元互溶液体闪点的有效方法,可应用于评估混合溶液的火灾爆炸危害性及本质较安全设计。     

A new method for the prediction of flash points for ternary miscible mixtures

The flash point is one of the most important physicochemical parameters used to characterize the fire and explosion hazard for flammable liquids. The flash points of ternary miscible mixtures with different components and compositions were measured in this study. Four model input parameters, being normal boiling point, the standard enthalpy of vaporization, the average number of carbon atoms and the stoichiometric concentration of the gas phase for mixtures, were employed and calculated based on the theory of vapor–liquid equilibrium. Both multiple linear regression (MLR) and multiple nonlinear regression (MNR) methods were applied to develop prediction models for the flash points of ternary miscible mixtures. The developed predictive models were validated using data measured experimentally as well as taking data on flash points of ternairy mixtures from the literature. Results showed that the obtained average absolute error of both the MLR and the MNR model for all the datasets were within the range of experimental error of flash point measurements. It is shown that the presented models can be effectively used to predict the flash points of ternary mixtures with only some common physicochemical parameters.     

闪速炉废热锅炉安全检修

介绍了江西铜业公司贵溪冶炼厂闪速炉废热锅炉的安全检修方案和方法以及检修中的一些注意事项。通过本次安全检修,减少了锅炉的泄漏,提高了闪速炉的作业率,也为今后同类废热锅炉的检修摸索出一条路子。     

烃类及其衍生物闪点、沸点的定量构效关系

基于定量结构一性质相关性（QSPR）原理,研究了烃类及其衍生物闪点、沸点与其分子结构间的内在定量关系。应用CODESSA软件计算384种烃类及其衍生物的分子结构描述符,建立了闪点和沸点的QSPR模型。用最佳多元线性回归（B．MLR）方法筛选得到的分子描述符建立了线性回归模型。用B-MLR方法所选择的5个描述符作为支持向量机（SVM）的输入建立了非线性模型。所有的化合物被分为训练集和测试集,对每个模型的训练集和测试集的复相关系数、交互验证系数、均方根误差等进行了计算,并用测试集对模型的预测能力进行检验,预测结果表明：预测值与实验值均符合良好,所建立的闪点模型稳健,泛化能力强,预测误差小,预测的效果令人满意,但沸点的模型预测效果有待加强。相比烃类物质的模型,加了衍生物的模型性能均有所下降。     

Correlation between flash points and vapor pressures of organic compounds

Correlations between flash points and vapor pressures at 25 °C for pure organic compounds were investigated. It was found that classification of organic compounds according to their chemical-structural characteristics (e.g., functional groups) was necessary for the correlation study. Under this classification, linearity seems to be the most appropriate correlation to explain the relationship between the inverse of flash points (°K) and the logarithm of vapor pressures (mm Hg) at 25°C for pure organic compounds. A test study to evaluate the validity of a regression line as an estimation of an unknown flash point from a known vapor pressure was carried out with a data set containing 31 alkanes and aromatics; 55% of the flash points were predicted within ±5°Cand89% were within ±10°C. Within limits of ± 5 to 10°C the procedure is useful but should be improved.     

Flash points measurements and prediction for binary miscible mixtures

Flash point is one of the most important parameters used to characterize the potential fire and explosion hazards for flammable liquids. In this study, flash points of twenty eight binary miscible mixtures comprised eighteen flammable pure components with different compositions were measured by using the closed cup apparatus. The obtained experimental data are further employed to develop simple and accurate models for predicting the flash points of binary miscible mixtures. Based on the vapor–liquid equilibrium theory, the normal boiling point, the standard enthalpy of vaporization, the average number of carbon atoms, and the stoichiometric concentration of the gas phase were selected as the dominant physicochemical parameters that were relevant to the overall flash point property of liquids. With these parameters for pure components as well as the compositions of mixtures, the new form of characteristic physicochemical parameters for mixtures were developed and used as the input parameters for the flash point prediction of mixtures. Both the modeling methods of multiple linear regression (MLR) and multiple nonlinear regression (MNR) were employed to model the possible quantitative relationships between the parameters for mixtures and the flash points of binary miscible mixtures. The resulted models showed satisfactory prediction ability, with the average absolute error for the external test set being 2.506 K for the MLR model and 2.537 K for the MNR model, respectively, both of which were within the range of the experimental error of FP measurements. Model validation was also performed to check the stability and predictivity of the presented models, and the results showed that both models were valid and predictive. The models were further compared to other previously published models. The results indicated the superiority of the presented models and revealed which can be effectively used to predict the FP of binary miscible mixtures, requiring only some common physicochemical parameters for the pure components other than any experimental flash point or flammability limit data as well as the use of the Le Chatelier law. This study can provide a simple, yet accurate way for engineering to predict the flash points of binary miscible mixtures as applied in the assessment of fire and explosion hazards and the development of inherently safer designs for chemical processes.     

一种改进的帧差法实现火焰目标分割

针对传统船舶火灾报警系统采用的传感器在远离火灾源时很难探测到初期火灾的特性,提出了利用摄像头模式识别的方法来探测火源的构想,将顶置鱼眼摄像头作为图像传感器,在一个较大的范围内探测初期火灾,提出了一种基于火焰闪点位置的交叉性与聚合性的帧差算法,实现火焰目标分割识别.该方法是在实时视频流中,对连续两帧图像进行帧差,根据闪点位置的交叉性排除运动物体的干扰,再根据闪点的聚合程度排除一部分游离的干扰闪点,最后得到疑似火焰区域.对疑似火焰区域二值化、抽取轮廓、再由种子点位置确定火焰外形.此法能够高效地从视频图像中分割出火焰,从而为火灾的初期预防报警提供高效识别手段.     

Reliable method for prediction of the flash point of various classes of amines on the basis of some molecular moieties for safety measures in industrial processes

This work presents a novel, reliable and simple method of estimating the flash point of various types of flammable amines, which are important for safety measures in industrial processes. Different amines include aliphatic amines such as primary, secondary, tertiary and cyclic amines as well as aromatic amines and hetero arenes containing nitrogen heteroatom. The proposed correlation is based on the contribution of some specific molecular moieties and functional groups, which can easily be used for any types of amines. Intermolecular forces are important in the new method, which are counted by two increasing and decreasing parameters. The root mean square (rms) deviation is 18 K for different classes of amines including 133 diverse compounds. The estimated flash points have been compared with one of the best available predictive methods, which gives much lower value of the rms deviation.     

Flammability hazard analysis of imidazolium-based ionic liquid binary mixtures under high temperatures

Ionic liquid (IL) mixtures are promising because they can optimize the involved properties according to industrial needs. It has already been demonstrated that IL flammability is due mainly to IL decomposition generating flammable substances. Four different ILs, 1-Butylimidazolium tetrafluoroborate ([BIM][BF₄]), 1-butylimidazolium nitrate ([BIM][NO₃]), 1-butyl-3-methylimidazolium tetrafluoroborate([BMIM][BF₄]), and 1-butyl-3-methylimidazolium nitrate ([BMIM][NO₃]), were selected as the parent salts to form the different imidazolium-based IL binary mixtures. These mixtures were tested via isothermal thermogravimetric analyzer (TGA) at different temperatures (120, 150, 180, 210, and 240 °C), then tested by the flash point analyzer after isothermal heating pretreatment at the above temperatures. Results show that the mixtures' flash point values decrease with the heating temperature increase. Vaporization of the IL mixtures’ decomposition products results in a higher concentration of flammable gases and a flash point decrease, which lead to the flammability hazard increasing. Moreover, results show that the flash points of the studied binary imidazolium IL mixtures are more similar to those of the more unstable IL in their parent ILs. Also, the flammability hazard of IL binary mixtures may obviously increase under the high temperature environment for a long time.     

基于QSPR方法的脂肪醇化合物闪点预测

为提高脂肪醇化合物闪点预测精度,提出基于定量结构-性质关系(QSPR)原理的脂肪醇化合物闪点预测方法。应用Dragon软件计算出91种脂肪醇的分子描述符,利用遗传函数算法(GFA)从1 481个描述符中筛选出3个与脂肪醇闪点关系最密切的分子描述符。分别用多元线性回归(MLR)方法和支持向量机(SVM)方法进行建模,并采用内部验证和外部检验的方式对模型的拟合度、预测性等性能进行验证。结果表明:预测集的MLR方法和SVM方法的平均绝对误差(AAE)分别为2.870 K和2.706 K;均方根误差(RMSE)为3.451 K和3.371 K。SVM模型在精度上略优于MLR模型,而MLR模型更为简单和方便。     

锚杆支护巷道安全监测技术

锚杆支护巷道顶板冒落具有突发性和冒落面积大的特点 ,安全监测非常必要。笔者介绍了国内近年来最新研制的CM— 2 0 0型测力锚杆、GYS— 30 0型锚杆 (索 )测力计、LBY— 3型顶板离层指示仪、ZW— 4型遥测多点位移计等监测仪器 ;提出锚杆支护巷道动态信息施工方法 :监测施工、监测信息反馈、检验和修正设计 ,循环往复 ,以达到最佳施工效果。     

基于小波分析的入库径流变化研究

基于桂林市青狮潭水库1958—2011年入库径流资料,采用Morlet小波分析方法对入库径流在不同时间尺度下的变换时频分布特征及丰枯变化的情况进行了分析。结果表明,青狮潭水库入库径流序列具有多时间尺度变化特性,主要存在8,15,22,32 a左右的周期变化。这4个主要周期变化,主导着青狮潭水库入库径流的趋势变化特性,尤其是以32 a的周期变化为主,入库径流大致经历了枯→丰→枯→丰→枯的变化。     

Perceptions of implied hazard for visual and auditory alerting signals

Visual and auditory alerts are increasingly important and have many applications, particularly in the presentation of hazard information in transportation and many industrial systems. This paper is concerned with the factors that govern the relative effectiveness of alerting signals involving various combinations of visual and auditory signals. The visual variables were colour, flash rate, and flash mode, combined with or without an auditory alarm. It was found that the subjects associated different levels of hazard with different alerting light colours, flash rates, flashing modes, and with combinations of auditory and visual alerts. A red flashing light was perceived as the most effective hazard warning colour, with yellow and blue warning lights indicative of less hazardous situations. The faster the flash rate, the greater is the hazard perceived. A flash rate of 60 fpm (flashes per minute) was not as effective as the rates of 180 and 240 fpm, and 240 fpm was the most effective. This implies that hazard warning signal should flash at well above 60 fpm. Having a breakup in the flashing pattern so as to provide a double or triple flash mode also increases the effectiveness of the signal. There were significant interactions between the alert variables used. The difference in perceived hazard levels for the colours blue and yellow were statistically non significant, but blue was more effective in conveying hazard message than yellow at the high flash rates. When accompanied with auditory alarms, blue and yellow were perceived to convey the same perception level of hazard as red without auditory alarms. The effect of colour on perceived hazard was also found to vary with flash mode. As compared to either visual signal alone or a visual signal with other types of acoustic alarms, a siren type of auditory alarm was found more effective for eliciting perception of hazards. There was evidence that presenting alerting signal in triple-flash mode and at high flash rate could be annoying and might not help improving hazard awareness.     

MNLR and ANN structural group contribution methods for predicting the flash point temperature of pure compounds in the transportation fuels range

A QSPR method is presented for predicting the flash point temperature (FPT) of pure compounds in the transportation fuels range. A structural group contribution method is used to determine the flash point temperature using two techniques: multivariable nonlinear regression and artificial neural networks. The method was used to probe the structural groups that have significant contribution to the overall FPT of pure compounds and arrive at the set of 37 atom-type structural groups that can best represent the flash point for about 375 substances. The input parameters to the model are the number of occurrence of each of the 37 structural groups in each molecule. The neural network method was the better of the two techniques and can predict the flash point of pure compounds merely from the knowledge of the molecular structure with an overall correlation coefficient of 0.996 and overall average and maximum errors of 1.12% and 6.62%, respectively. The results are compared to the more traditional approach of the SGC method along with other methods in the literature.     

Micro‐break activities at work to recover from daily work demands

Recovery literature has focused predominantly on recovery processes outside the workplace during nonwork times. Considering a lack of research on momentary recovery at work, we examined four categories of micro‐break activities—relaxation, nutrition‐intake, social, and cognitive activities—as possible recovery mechanisms in the workplace. Using effort recovery and conservation of resources theories, we hypothesized that micro‐break activities attenuate the common stressor–strain relationship between work demands and negative affect. For 10 consecutive workdays, 86 South Korean office workers (842 data points) reported their specific daily work demands right after their lunch hour (Time 1) and then reported their engagement in micro‐break activities during the afternoon and negative affective state at the end of the workday (Time 2). As expected, relaxation and social activities reduced the effects of work demands on end‐of‐workday negative affect. Nutrition intake of beverages and snacks did not have a significant moderating effect. Post hoc analyses, however, revealed that only caffeinated beverages reduced work demands effects on negative affect. Unexpectedly, cognitive activities aggravated the effects of work demands on negative affect. The findings indicate not only the importance of taking micro‐breaks but also which types of break activities are beneficial for recovery. Implications, limitations, and future research directions are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Flash point prediction for the binary mixture of phosphatic solvents and n-dodecane from UNIFAC group contribution model

The flash point temperature of Tri-n-butyl phosphate(TBP) and Tri-iso-amyl phosphate(TiAP) in n-dodecane binary mixture has been measured for the entire concentration range using the continuously closed cup flash point apparatus based on the ASTM D6450 method. The flash point was predicted using the UNIFAC group contribution model. The measured flash point was also compared with the prediction from the NRTL, UNIQUAC and Ideal solution models. The UNIFAC model is able to predict the flash point fairly well for the TBP–dodecane mixture and for TiAP–dodecane mixture no improvements is obtained over the ideal solution assumption. The flash point shows positive deviation from ideal solution behavior for both the binary mixture.     

A mathematical model for predicting the flash point of binary solutions

A mathematical model which may be used for predicting the flash point of binary solutions has been proposed and subsequently verified by experimentally-derived data, such data pertaining to an almost-ideal solution as also to highly non-ideal solutions. The results reveal that the model is able to precisely predict the flash point over the entire composition range of binary solutions for both ideal solutions and non-ideal solutions by way of utilizing the flash point of the individual components. The highly non-ideal solution like octane+ethanol exhibits the minimum flash-point behavior, which leads to the minimum on the flash point vs composition curve.     

关于中国式安全管理模式的探讨

我国目前的安全管理模式大多源于国外,由于文化传统、民族精神等方面的差异,不免会产生水土不服的现象。通过对我国安全管理模式发展的4个阶段和国外安全管理模式的分析,阐述了我国安全管理中存在的问题,结合我国传统文化中注重结果、追求简约、以和为贵、经验为先的特征和中国工人的缺乏民主与法治的思想、重视家庭、负担重、期望实现自我价值和缺乏关爱等群体特征,立足我国国情,提炼出中国安全管理模式应具备的特征以及发展趋势。