危险化学品火灾爆炸事故不安全动作分布规律研究

以我国210起典型危险化学品火灾爆炸事故为样本,对造成事故的不安全动作进行归类统计,应用云模型云发生器算法计算大类不安全动作的云模型参数值并绘制隶属云图,得出了危险化学品火灾爆炸事故中不安全动作类型和发出者分布规律及特点。结果表明:造成火源型火灾爆炸事故的违规型不安全动作平均发生次数最多,分布不均匀且不稳定,其中现场工作缺乏指导或监护发生次数最多,发出对象为监理;蓄热型火灾爆炸事故中技术型不安全动作分布表现出较大的随机性,其中物料添加不当和隐患排查不彻底发生次数最多,发出对象分别为基层人员和监理。     

A new leak location method based on leakage acoustic waves for oil and gas pipelines

In order to study a new leak detection and location method for oil and natural gas pipelines based on acoustic waves, the propagation model is established and modified. Firstly, the propagation law in theory is obtained by analyzing the damping impact factors which cause the attenuation. Then, the dominant-energy frequency bands of leakage acoustic waves are obtained through experiments by wavelet transform analysis. Thirdly, the actual propagation model is modified by the correction factor based on the dominant-energy frequency bands. Then a new leak detection and location method is proposed based on the propagation law which is validated by the experiments for oil pipelines. Finally, the conclusions and the method are applied to the gas pipelines in experiments. The results indicate: the modified propagation model can be established by the experimental method; the new leak location method is effective and can be applied to both oil and gas pipelines and it has advantages over the traditional location method based on the velocity and the time difference. Conclusions can be drawn that the new leak detection and location method can effectively and accurately detect and locate the leakages in oil and natural gas pipelines.     

Ammonium nitrate thermal decomposition with additives

Runaway reactions present a potentially serious threat to the chemical process industry and the community; such reactions occur time and time again often with devastating consequences. The main objective of this research is to study the root causes associated with ammonium nitrate (AN) explosions during storage. The research focuses on AN fertilizers and studies the effects of different types of fertilizer compatible additives on AN thermal decomposition. Reactive Systems Screening Tool (RSST) has been used for reactivity evaluation and to better understand the mechanisms that result in explosion hazards. The results obtained from this tool have been reported in terms of parameters such as “onset” temperature, rate of temperature and pressure rise and maximum temperature. The runaway behavior of AN has been studied as a solid and solution in water. The effect of additives such as sodium sulfate (Na₂SO₄) and potassium chloride (KCl) has also been studied. Multiple tests have been conducted to determine the characteristics of AN decomposition accurately. The results show that the presence of sodium sulfate can increase the “onset” temperature of AN decomposition thus acting as AN thermal decomposition inhibitor, while potassium chloride tends to decrease the “onset” temperature thus acting as AN thermal decomposition promoter.     

PLS-based EWMA fault detection strategy for process monitoring

Fault detection (FD) and diagnosis in industrial processes is essential to ensure process safety and maintain product quality. Partial least squares (PLS) has been used successfully in process monitoring because it can effectively deal with highly correlated process variables. However, the conventional PLS-based detection metrics, such as the Hotelling's T² and the Q statistics are ill suited to detect small faults because they only use information from the most recent observations. Other univariate statistical monitoring methods, such as the exponentially weighted moving average (EWMA) control scheme, has shown better abilities to detect small faults. However, EWMA can only be used to monitor single variables. Therefore, the main objective of this paper is to combine the advantages of the univariate EWMA and PLS methods to enhance their performances and widen their applicability in practice. The performance of the proposed PLS-based EWMA FD method was compared with that of the conventional PLS FD method through two simulated examples, one using synthetic data and the other using simulated distillation column data. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS, especially in the presence of faults with small magnitudes.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

石墨相氮化碳协同UV-H_2O_2光催化降解亚甲基蓝

以三聚氰胺为前驱体,经热解—回流法制备了石墨相氮化碳(g-C3N4),采用XRD、FTIR、SEM、EDS、PL等技术对g-C_3N_4进行了表征。研究了g-C_3N_4在UV-H_2O_2体系中对废水中亚甲基蓝(MB)的光降解效果。实验结果表明,UV+g-C_3N_4催化剂+H_2O_2体系能协同降解MB,在初始MB质量浓度为20 mg/L、初始废水p H为5、废水体积为250 mL、g-C_3N_4加入量为0.10 g、H_2O_2浓度为0.4 mmol/L、反应温度为25℃的优化工艺条件下,紫外光照射70 min时MB脱色率达98.32%。g-C_3N_4催化剂具有较好的重复使用性能,使用5次后MB脱色率仍保持在95.10%。     

高温高压下煤孔隙结构的变化对瓦斯吸附特性的影响

为了研究高温高压条件下煤孔隙结构变化对瓦斯吸附特性的影响，选取九里山矿无烟煤，在压力为7 MPa、温度为40～130℃的条件下进行等温吸附实验和压汞实验。研究结果表明:煤样对甲烷的等温吸附曲线在该压力、温度条件下符合Ⅰ型吸附曲线特性，吸附规律符合Langmuir吸附模型；在压力7 MPa和温度130℃条件下，煤样的孔隙结构发生一定的变化，煤的比表面积增大、累计孔体积降低，可见孔及裂隙的数量比例增高，加强了煤样孔隙之间的连通度，导致原本吸附在煤样表面的甲烷分子大量解吸；在压力不变的情况下，随着温度的不断增高，煤的极限吸附量逐渐减小，其主要原因是样品孔隙结构的破坏和分子间作用力的变化。     

国家生态环境监测“十四五”展望

"十四五"时期,生态文明改革持续深入,生态环境治理将向精准治污、科学治污、依法治污转变,这对加快推进生态环境监测体系与监测能力现代化提出了迫切要求。因此,本文从网络建设、体制机制、服务效能等方面,对生态环境监测所取得的进展与成效进行了系统分析,并对国家生态环境监测面临的机遇与挑战进行了深入剖析。在此基础上,针对支撑评价排名、服务精准治污、有序衔接新职能、建设大数据平台、强化数据应用、深化综合评价、理顺体制机制、推动产学研用、提升基础能力等方面,提出了"十四五"期间国家生态环境监测发展的相关建议。     

德国铁路噪声实时监测系统研究现状

分析了德国铁路噪声在线监测的应用背景，介绍了德国铁路噪声实时监测系统的研究现状，包括测量站点的选取原则、技术结构和具体信息，列车声压级曲线时域连续变化图、单次列车通过声压级曲线图、单次列车通过参数表和等效声压级曲线图/表等测量结果的表达方法，以及无效数据的处理方式等，为我国建立铁路噪声自动监测系统提供参考。