电动态平衡技术在研究单颗粒煤燃烧中的应用

利用电动态平衡技术,将单个带电煤颗粒悬浮在样品池中,可以实现煤颗粒燃烧过程的原位微观研究。本文简要介绍了电动态平衡技术的原理和相关的操作方法,总结了该技术应用于煤燃烧研究的进展,进一步探讨了结合时间分辨光谱技术研究煤燃烧物理化学过程细节的可行性与发展前景。目的在于向国内研究者介绍这一新技术并激发更多的研究兴趣。     

典型煤的近红外反射光谱特征的方向性研究

高光谱遥感是煤矿区探测的有效方法,对于煤炭资源调查、矿区环境监测等具有重要意义,其中煤、矸石、植被、水体等被遥测物各个方向的反射光谱特征是煤矿高光谱遥感的基础,为此有必要针对典型煤的方向反射光谱特征进行研究.从我国不同矿区收集了无烟煤、烟煤、褐煤三大类煤中的4种典型煤样,4种煤样按煤阶由高到低顺序包括无烟煤一号、贫煤、...     

高光谱成像的煤与矸石分类

煤与矸石分选是煤矿生产的必要工序,现有的人工分选与机械分选,存在效率低,易造成资源浪费以及环境污染等问题.鉴于可见/近红外高光谱成像具有分析速度快、样品无需预处理、无污染等诸多优势,旨在探讨基于可见/近红外高光谱成像对黑色背景下块状煤与矸石准确分类的可行性,并基于特征波长筛选算法简化模型,为构建多光谱煤与矸石分选系统提...     

基于随机森林结合地球物理测井资料的煤体结构识别方法及应用

在更加复杂的地质因素影响下,常规测井方法识别煤体结构准确度低,为精确识别煤体结构,研究了煤体结构测井曲线响应机理以及随机森林决策树个数的优选,从而建立煤体结构与测井曲线的随机森林分类模型进行煤体结构识别。结果表明:决策树个数为500时,随机森林分类模型效果最佳;通过袋外误差和模型对测试集样本的预测结果可知,随机森林分类模型的结果稳定且泛化性强,并且适合处理非均衡数据,预测精度较高。可见随机森林算法能有效识别煤体结构,为煤层气开发提供帮助。     

煤炭地下气化注入井压力控制

煤炭地下气化具有煤炭清洁利用和低碳能源保障的优势,是煤炭清洁转化技术创新战略方向。而压力是影响煤炭气化的重要因素,为使煤炭气化在地下高效安全进行,需要对注入井的压力进行控制研究。为了实现对注入井压力的控制,本文建立了气化剂注入的流量压力仿真模型,对水力摩阻的部分影响因素进行分析,并调整生产参数,进行了压力控制研究。研究结果表明:（1）水力摩阻随井筒直径的增大而减小;水力摩阻随连续油管外径的增大而增大;水力摩阻随注水排量的增大而增大。（2）在10 MPa注入压力下调整环空中的注水排量由5.50 L/s改变为5.75 L/s时,井底压力由7.26 MPa降至6.11 MPa。（3）当在8 MPa注入压力下调整连续油管中的注氧量由594.44 L/s改变为629.37 L/s时,井底压力由8.91 MPa降至8.87 MPa。（4）在8 MPa注入压力下调整生产井粗煤气的产出流量由800 L/s改变为900 L/s时,井底压力由8.94 MPa降至8.63 MPa。研究结果可为注入井的压力控制提供一定的指导。     

北皂煤矿煤岩含水热模拟产物地球化学特征

为了模拟地质体中油气生成的过程,了解煤系烃源岩成烃热演化特征及其产物的地球化学特征,对北皂煤矿演化程度较低的煤岩进行了(250~600)℃的10个温阶的加水热模拟实验。对原样和热模拟残余物进行油气生成模拟实验和岩石有机碳、镜质体反射率(Ro)、氯仿沥青"A"、族组分和饱和烃气相色谱等生油岩地化分析测定,对反应产物进行了天然气气体组分分析。结果表明煤系烃源岩在不同热演化阶段表现出的地质地球化学特征具有相当大的差异:在有机质热降解—热裂解阶段,温度较低时(325℃),镜质组反射率增长幅度并不太大,通常Ro1.0%,TOC75%,氯仿沥青"A"逐渐增大。随着温度的升高,热演化进程相对加快,Ro值从0.47%~0.97%迅速增大到1.00%~3.73%,TOC值从64.7%~75.1%增大到75.9%~84.5%,而氯仿沥青"A"逐渐下降,从1.46%减小到0.057%。生物标志化合物中,姥鲛烷跟植烷相比一直处于优势,重烃含量也随着温度的升高增多。此项研究对于揭示北皂煤矿煤阶较低的煤系烃源岩在地质体中经历的物理、化学演化过程,各组分的产出特征及变化规律,了解产物的地球化学特征具有重要的意义。     

压裂中顶底板对缝高控制作用的数值模拟研究

裂缝在缝高方向的延伸会导致裂缝有效长度的降低,影响压裂效果;也可能直接穿过水层,造成压裂施工的失败。因此,基于FEPG有限元平台,利用网格开裂技术,开展了煤层气井压裂数值模拟研究,对垂向裂缝起裂、扩展及穿层的全过程进行分析。数值模拟结果表明:煤层气井压裂过程中,控制裂缝是否向隔层扩展主要取决于作业的净压力与隔层水平地应力差之间的关系;与储集层岩石力学性质相比,储集层的地应力剖面是影响裂缝垂向扩展范围的主要因素;T型缝、工型缝等复杂缝是由储集层的岩石力学性质和地应力共同作用的结果。这对于提高现场煤层气井水力压裂的效果具有重要的指导意义。     

Predicting nitrogen release during coal tar decomposition

This paper develops a detailed phenomenological reaction mechanism for N-species transformations throughout tar decomposition, including tar-N sequestration into soot. It expands the previously validated mechanism for tar decomposition based on FLASHCHAIN^® theory to cover N-transformations during pulverized fuel firing. Tar-N transformations are described by two distinctive features: (1) An elimination reaction that produces HCN governs the decay in the average moles of nitrogen per aromatic nucleus throughout tar decomposition; and (2) Empirical observations determine the fraction of tar-N incorporated into soot. Validation cases represent heating rates of at least several thousand degrees per second; temperatures from 600 to 1100 °C; tar contact times from 75?ms through 2?s; and coal ranks from subbituminous through low volatile bituminous. The predicted partitioning of coal-N into tar-N, HCN, soot-N, and char-N was within measurement uncertainties for all coals for simulated p. f. firing conditions, including the variation in fractional char-N levels from 0.4 to 0.8 across this domain. Since primary tar-N levels are directly proportional to fractional primary tar yields, and since ultimate soot-N levels account for one-third of tar-N with any coal type, the ultimate coal-N partitioning for CFD furnace simulations can be accurately described with two analyses: (1) A primary devolatilization mechanism to predict primary tar yields under rapid heating conditions; and (2) A submechanism to predict HCN release from char throughout devolatilization up to the point of char ignition. Dynamics may be resolved with either global reactions or the full tar decomposition mechanism, depending on the impact of the lag between tar decomposition and soot production in the subject application.     

Predicting particle deposition for flow over a circular cylinder in combustion environments

Particle deposition on heat exchanger tubes is a serious concern in solid fuel combustion and gasification systems, such as power plants and syngas coolers. To predict deposition rates, several detailed computational fluid dynamic (CFD) models have been developed. However, these models are computationally expensive and cannot be used for quick determination of deposition rates and/or slagging tendencies. Particle impaction efficiency correlations, while not as accurate as detailed CFD models, are easier to use and are able to estimate the impaction rate of particles on the heat exchanger tubes. Nonetheless, since deposition and slagging are not just functions of particle impaction rates, but also sticking propensity, which is related to the particle temperature at impact, the impaction efficiency correlations fail to provide sufficient information. To address this shortcoming, similar correlations for particle temperature at impact have been developed in this work, based on a non-dimensional parameter that captures the flow and boundary conditions, as well as particle properties. When used alongside the impaction efficiency correlations, the new correlations developed can provide a reasonable estimate of the deposition and slagging tendencies, at negligible computational expense.     

Investigating particle and volatile evolution during pulverized coal combustion using high-speed digital in-line holography

Devolatilization is an important process in pulverized coal combustion because it affects the ignition, volatile combustion, and subsequent char burning and ash formation. In this study, high-speed digital in-line holography is employed to visualize and quantify the particle and volatile evolution during pulverized coal combustion. China Shanxi bituminous coal particles sieved in the range of 105–154 µm are entrained into a flat flame burner through a central tube for the study. Time-resolved observations show the volatile ejection, accumulation, and detachment in the early stage of coal combustion. Three-dimensional imaging and automatic particle extraction algorithm allow for the size and velocity statistics of the particle and stringy volatile tail. The results demonstrate the smaller particle generation and coal particle swelling in the devolatilization. It is found that the coal particles and volatiles accelerate due to the thermal buoyancy and the volatiles move faster than the coal particles. On average, smaller particles move faster than the larger ones while some can move much slower possibly because of the fragmentation.