HNO_3在气相及SiO_2表面的紫外光解反应

利用紫外及红外吸收光谱等分析手段对365 nm光照下HNO3在气相与SiO2表面的光解反应进行了研究.考察了HNO3浓度、光照时间、相对湿度等条件对反应的影响.结果表明:随着HNO3浓度及光照时间的增加,光解产生的NO2和NO浓度均呈指数增加;无水汽情况下,400 Pa的HNO3光解45 min后,产生NO2及NO浓度比气相光解产生的分别高约3及1.7倍.HNO3光解产生的HONO的浓度随相对湿度的增加而呈线性增加,在SiO2颗粒物表面光解产生的NO2浓度随着相对湿度的增加而减少,而NO浓度则随之增大.400 Pa的HNO3光照45 min后,SiO2表面光解产生的HONO浓度是气相光解的3倍、SiO2表面暗反应的约30倍.     

基于放射性碳分析的多环芳烃源解析:技术进展和准确性评估

化石燃料燃烧和生物质燃烧是污染物多环芳烃(polycyclic aromatic hydrocarbon,PAHs)的两大来源.放射性碳(14C)分析近年用于评估这两类源对环境中PAHs的相对贡献.此方法基于化石燃料和生物质的14C含量差异,即化石燃料不含14C,而生物质的14C浓度有一个较稳定值.14C的自然丰度极低(约10-12),因此检测PAHs这样的痕量污染物的14C含量一度极具挑战.1990年代中期,加速器质谱的技术突破使得对环境样品PAHs的14C分析具有实用价值.要准确测出PAHs的14C含量,须先从化学成分复杂的环境样品中分离出高纯度的PAHs.制备气相色谱因其出色的分离能力而成为目前环境样品PAHs14C分析必备的工具.本文意在简介基于14C分析的PAHs源解析的基本原理、技术进展,以及评估该方法获得的PAHs源解析结果的准确性.     

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.     

An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

Natural gas pipeline construction is developing rapidly worldwide to meet the needs of international and domestic energy transportation. Meanwhile, leakage accidents occur to natural gas pipelines frequently due to mechanical failure, personal operation errors, etc., and induce huge economic property loss, environmental damages, and even casualties. However, few models have been developed to describe the evolution process of natural gas pipeline leakage accidents (NGPLA) and assess their corresponding consequences and influencing factors quantitatively. Therefore, this study aims to propose a comprehensive risk analysis model, named EDIB (ET-DEMATEL-ISM-BN) model, which can be employed to analyze the accident evolution process of NGPLA and conduct probabilistic risk assessments of NGPLA with the consideration of multiple influencing factors. In the proposed integrated model, event tree analysis (ET) is employed to analyze the evolution process of NGPLA before the influencing factors of accident evolution can be identified with the help of accident reports. Then, the combination of DEMATEL (Decision-making Trial and Evaluation Laboratory) and ISM (Interpretative Structural Modeling) is used to determine the relationship among accident evolution events of NGPLA and obtain a hierarchical network, which can be employed to support the construction of a Bayesian network (BN) model. The prior conditional probabilities of the BN model were determined based on the data analysis of 773 accident reports or expert judgment with the help of the Dempster-Shafer evidence theory. Finally, the developed BN model was used to conduct accident evolution scenario analysis and influencing factor sensitivity analysis with respect to secondary accidents (fire, vapor cloud explosion, and asphyxia or poisoning). The results show that ignition is the most critical influencing factor leading to secondary accidents. The occurrence time and occurrence location of NGPLA mainly affect the efficiency of emergency response and further influence the accident consequence. Meanwhile, the weight ranking of economic loss, environmental influence, and casualties on social influence is determined with respect to NGPLAs.     

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.     

CuSnZr三元催化剂应用于NTP强化催化脱硫过程的特性

为高效地在低温下处理大量低浓度电解铝烟气, 采用浸渍法制备了Sn Zr型金属氧化物并添加Cu作为助剂的催化剂, 并首次测试了它在低温等离子体(NTP)技术上的脱硫效果, 结果表明负载了20wt% Cu老化温度为40℃的催化剂表现出最佳的脱硫性能.并对强化之后的催化剂进行了表征, 与新鲜的催化剂对比, X射线衍射分析(XRD)结果表明放电对催化剂晶型基本不产生影响; 扫描电子显微镜(SEM), 氮吸附和脱吸(BET)表明放电会使催化剂的吸附脱附能力与孔道结构有较大提升; X射线光电子光谱(XPS)也表明放电会使催化剂表面元素价态变化, 从而使其氧化还原性能改变, 反应路径发生偏向; 催化剂性能理论计算表明铜含量的上升会导致催化剂能带结构改变, 更好利用于激发气体.     

碳中和趋势下数学模拟在污水处理系统中的发展与综合应用

数学模拟技术在污水处理方面被广泛应用,为了系统总结相关技术,本文回顾了污水处理系统中数学模拟技术的发展历程;综述了活性污泥模型(ASM)与机器学习(ML)在水质预测及参数工况优化领域中的应用;重点探究了污水处理系统中温室气体排放模型,以及多目标优化模型在污水处理系统中温室气体排放(GHG)、出水质量(EQI)和运行成本(OCI)的权衡问题;归纳了数学模拟技术在实现污水厂能量自给与资源回收的应用发展.研究结果表明数学模拟技术能准确预测出水水质、快速优化工艺参数、权衡温室气体排放、出水水质与运行成本之间的关系、以及提高资源回收效率等.因此,数值模拟技术可有效指导污水处理工艺的运行优化以及管理,为污水处理行业减污降碳协同增效提供技术支撑.     

液化石油气槽车泄漏处置专用接头套组的应用探讨

针对消防救援车辆缺乏专业堵漏和倒罐装备、应急处置受限等问题,研究采用专用注压接头套组与消防车配合,通过向事故槽车阀门注水加压或惰性气体的方式实施辅助堵漏,能够实现因地制宜、快速有效地解决现场液化石油气大量泄漏的问题,降低事故危害。     

民用飞机实验室APU开车高温尾气排放影响因素分析

目的 对民用飞机APU在气候实验室内开展极端气候环境下的起动和工作试验,建立一种APU高温尾气安全排放方法。方法 用CFD仿真手段对采用排气管道将APU高温尾气排出气候实验室的可行性及影响因素(包括管道直径、距离、背压等)进行系统性分析研究。结果 气管道入口距离APU管道出口过近时,将有利于APU排气,引射比ε与排气管道出口压力Pex及排气管道直径D线性相关,排放温度tex与管道直径D成反比。在排气管道入口设置平滑收敛段,利于消除涡流,减轻负压程度,并在一定范围内提高引射比。结论 采用管道被动排气是可行的,合适的排气管道设计为D/d=2.0,L/d=1.5,并在管道入口设置平滑收敛段。     

极端梯度提升与随机森林融合的天然气露点预测方法

目的 解决目前水露点数据多为人工采用测量仪器测得,时效性低且成本高昂的问题。方法 建立一种基于极端梯度提升(XGBoost)和随机森林(RF)的天然气水露点预测方法。采用XGBoost方法对所有监测工艺参数进行分析,筛选出主要影响水露点的关键工艺特征参数,以排除无关特征参数对预测的干扰。建立RF预测模型,输入关键特征集参数,实现对水露点的实时预测。以重庆气矿某脱水监测系统监测数据与生产数据为例,对所提预测方法进行对比分析验证。结果 相较于XGBoost、SVM等预测方法,RF模型具有最佳的预测性能,且经过XGBoost特征选择后,RF预测结果的MAE值降低了0.016 9 ℃,RMSE值降低了0.014 6 ℃。结论 基于极端梯度提升与随机森林融合的水露点预测方法具有更优的预测精度与鲁棒性,对指导脱水现场生产具有积极作用。