Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

珠江口盆地珠一坳陷古近系高自然伽马砂岩形成机制及油气地质意义

运用放射性元素寻找油气是一种非常规油气勘探手段。近年来,在珠江口盆地珠一坳陷富烃凹陷周边古近系钻遇高自然伽马(GR)砂岩,其GR值(100~300 API)甚至大于同区泥岩的GR值(100~200 API)。为了弄清该特殊现象背后的地质意义,对珠江口盆地珠一坳陷古近系高自然伽马砂岩开展了铀(U)、钍(Th)、钾(K)等3种元素含量与GR值的相关趋势线分析,从井震特征、岩性特征及矿物成分特征等入手分析了砂岩GR值增高的主要原因及成因机制,探讨了放射性元素聚集的条件、运移通道、驱动力以及油气意义。结果表明:西江、惠州地区由U含量增高导致砂岩GR值偏高,恩平、番禺地区由K,Th含量增高导致砂岩GR值偏高;砂岩GR值增高有两大成因机制,一是地下流体带来的放射性元素离子U4+在氧化-还原面处富集后导致地层GR值偏高,这种特殊现象说明在具有连通基底大断裂旁的圈闭中,U4+的富集指示了曾经油气的存在,证实了研究区油气运移通道的有效性,对于油气藏的预测有着非常重要的指导性意义,二是地表流体带来的含放射性元素的矿物大量沉积后导致地层GR值偏高,含放射性元素矿物性质不稳定,可指示近源供给的存在,对于判断物源及沉积环境有着非常重要的意义。该研究成果为预测研究区油气成藏有利区带提供了依据。     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

基于Bert预训练模型的虚假新闻文本检测

虚假新闻剥夺了人们获取真相的权利,也给社会和国家带来了许多危害。文中以虚假新闻文本为例,分析和验证了多种预训练语言模型在虚假新闻文本分类上的分类效果。经实验证明,相较于其他语言模型,Bert预训练语言模型取得了较好的结果,预测准确率为86.97%,召回率为88.12%,F1值为87.54%。     

炼油废白土在水泥厂燃煤自备电厂中再利用的实践

本项目主要研究和实现了工业废白土在BAYAH燃煤自备电厂中的再利用,实现变废为宝,减少了环境污染,同时为企业创造了一定的经济效益。针对废白土的特性,对燃料输送系统给煤机、皮带机、煤仓、下料溜子和排渣系统进行了改造。通过修改操作规程消除废白土对锅炉运行的影响。     

自然循环窄矩形通道内过冷沸腾两相摩擦阻力特性

采用去离子水作为实验工质，在低压低流速自然循环工况下开展了单面加热可视化窄矩形通道内的过冷沸腾摩擦阻力特性实验研究。实验中测量了实验段内的压降数据，并通过高速摄影仪拍摄了窄矩形通道内的气液两相图像，提出了过冷沸腾条件下的两相摩擦压降的剥离计算方法。基于本实验中获得摩擦压降数据，对分别基于均相流模型和分液相模型的经典两相摩擦压降计算关系式进行了评估，实验结果表明：采用不同等效黏度计算方法的均相流模型计算结果比实验值明显偏小；而分相流模型中，Sun and Mishiba关系式和Tran关系式均能够较好地预测摩擦阻力，计算值与实验值的平均相对偏差在±15%以内。结合实验数据，以分相流模型方法为基础，考虑全液相Reynolds数、Martinelli参数和Laplace数的影响，获得了计算分液相折算系数的经验关系式，与实验数据符合较好, 平均相对误差在10%范围内。     

干熄焦锅炉炉管失效机理分析

通过对干熄焦锅炉炉管及腐蚀产物开展系统研究，提出炉管失效原因为氧化/硫腐蚀＋高温粉尘冲刷。长寿命炉管仅耐磨层发生了较为严重的氧化及硫腐蚀，而近基体层发生了轻微氧化及硫腐蚀，基体只发生了轻微氧化；短寿命炉管耐磨层、近基体层以及基体裂纹内均发生了较为严重的氧化及硫腐蚀，且存在珠光体球化、内表面产生全脱碳层等缺陷。推测短寿命炉管存在超温现象，而超温可加剧氧化及硫腐蚀反应。此外，短寿命炉管遭受了较为严重的高温粉尘冲刷，不仅可造成炉管减薄，还会导致炉管表面温度升高。因此，减少循环气体中粉尘量尤其是大颗粒，可有效减弱冲刷以及控制炉管表面温度，是提高炉管使用寿命的关键。     

管道清管器运行速度控制技术研究进展

随着对管道安全问题和降本增效理念的逐步重视，管道清管操作已成为全世界油气管道运行中必不可少的作业规程，清管器的运行速度是需要重点控制的参数之一，当其处于合理区间内时（原油管道1~5m/s，天然气管道2~7m/s），清管效果最佳。本文基于对管道清管数学模型的研究，首先论述了不同的被动控制方法，认为该方法较为灵活，应用广泛，对不同入口条件下清管器速度的准确计算是能否控制清管器速度处于合理区间的关键；然后对不同的主动控制方法进行了研究，研究表明：射流清管器速度控制的核心是旁通率的优选，其依赖于压降系数、皮碗与管壁间摩擦力的准确计算，建立简便可靠的摩擦力工程计算模型将有助于射流清管技术应用的进一步推广；最终本文对清管器智能调速技术进行综述和展望，指出发展稳定可靠的国产智能调速技术是未来重点研究方向。