颗粒群平衡模拟的随机模型与燃煤可吸入颗粒物高效脱除的研究
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摘要
可吸入颗粒物(空气动力学直径小于10μm的颗粒物,简称为PM或PM10)已经成为大气环境污染的突出问题.由于PM的微观性和其生成、生长和演变所经历的复杂物理化学过程,无论是对其的采样和物理化学特征分析、在燃烧过程中的形成机理和微尺度动力学演变规律,还是在自然条件和外加条件下的非线性和非稳态运动规律、各种高效捕集策略的设计和优化等方面,人们都缺乏足够的认识,特别是缺乏相关的理论描述和定量描述.本文正是在此背景下,为燃煤PM复杂的动力学演变过程(包括碰撞、凝并、破碎、冷凝/蒸发、成核和沉积等动力学事件)构建颗粒群平衡模拟随机模型的完整数值模拟体系结构,并以此为平台对静电除尘器和湿式除尘器的除尘过程、自然环境中PM的干沉降和湿沉降过程进行颗粒群平衡模拟,对这些除尘机理进行深入分析,最终以此为基础对两种高效PM除尘技术(静电增强湿式除尘器和静电布袋混合除尘器)进行可行性分析和运行优化,为其工业化应用提供理论基础和技术指导.本文的研究成果包括:
(1)零维颗粒群平衡模拟的随机算法
本文引入“加权虚拟颗粒”概念而发展了一种全新的零维颗粒群平衡模拟随机算法——多重Monte Carlo (Multi-Monte Carlo, MMC)算法.该算法具有时间驱动Monte Carlo (MC)、常数目法和常体积法的特点,由于跟踪数目较少的虚拟颗粒群而具备适用于工程计算的计算代价,由于保持恒定的虚拟颗粒总数目而具有稳定的计算精度,由于保持恒定的计算区域体积和基于时间驱动技术而具有与两相湍流模型无缝耦合的扩展性.特殊工况下MMC算法结果与相应的理论分析解之间的良好吻合,证明该算法能够以较高计算精度和计算效率描述初始单分散性或多分散性颗粒群工况、单动力学事件或复合动力学事件工况等.
本文首次建立了MC算法对颗粒尺度分布时间演变过程描述精度的定量评判方法.以此为基础,定量比较了时间驱动直接模拟MC、阶梯式常体积法、常数目法和MMC算法对于各种动力学事件的描述精度,并定性分析了各种MC数值误差的来源和计算代价的主要贡献源.针对MMC算法所表现的“常数目误差”,通过建立“异数目权值虚拟颗粒群策略”以及相应的“异数目权值虚拟颗粒凝并准则”、在时间驱动MC中引入接受-拒绝法来数值实现标准Markov过程、发展“常数目方案”和“阶梯式常数目方案”来恢复虚拟颗粒数目等手段,对MMC算法进行改进.多种MC算法之间的定量比较表明,改进的MMC算法已经成为时间驱动MC中计算精度和计算效率最高的算法之一.
基于事件驱动MC对解藕误差的免疫及高计算精度和效率的认识,本文发展了另外一种全新的零维颗粒群平衡模拟随机算法——事件驱动常体积(EDCV)法.该算法仍然引入“加权虚拟颗粒”的概念和保持常体积特征,并把“等数目权值虚拟颗粒群策略”和“异数目权值虚拟颗粒群策略”、累积概率法和接受-拒绝法、“常数目方案”和“阶梯式常数目方案”以及“重整方案”等技术统一在一个框架下.通过对多种主流MC的定量比较,证明EDCV法成为目前零维颗粒群平衡模拟中计算精度和计算效率最高的随机算法之一.
(2)多维颗粒群平衡模拟的随机算法
通过把描述颗粒动力学演变的改进MMC算法与描述两相湍流场的欧拉-拉氏模型的无缝耦合,首次发展了一种多维颗粒群平衡模拟的随机算法——多维MMC算法.该算法引入网格划分技术和设置合适的时间步长,采用随机过程来判断碰撞/凝并等动力学事件的发生、寻找碰撞/凝并伙伴、建立碰撞动力学等.对细微颗粒流和粗重颗粒流中颗粒碰撞和凝并过程进行了数值模拟,模拟结果与直接数值模拟(DNS)结果实现定量上的较好吻合,证明所构建的多维多重Monte Carlo算法为四向耦合的两相湍流模型和多维颗粒群平衡模拟提供一个高精度和高效率的数值描述方案.采用所发展的MC算法考察了轴对称突扩通道有旋气固两相流中颗粒碰撞对于两相流场的影响,发现颗粒之间的相互碰撞使得颗粒速度和雷诺应力重新分配并趋于各向同性,而颗粒湍动能及颗粒-流体脉动速度关联降低.
(3)传统除尘装置和自然环境对PM的除尘机理研究
为了理解外加条件对PM动力学特性的作用机理,采用事件驱动常体积法对典型的静电和湿式除尘器进行了颗粒群平衡模拟.发现静电力与惯性力的相互竞争导致0.1~1μm的细微颗粒难以被静电除尘器捕集,而布朗扩散和惯性碰撞机制对0.1~1μm区间颗粒物影响最小也导致其难以被湿式除尘器的液滴所捕集.对300MW燃煤锅炉配备的静电除尘器进口和出口烟尘颗粒进行现场采样,并进行实际静电除尘器的颗粒群平衡模拟,模拟结果和是试验结果达到定量的吻合.
为了描述从除尘器逃逸出来的PM在自然环境中的沉降过程,并借鉴大自然的自身净化机制,采用多重Monte Carlo算法对自然环境中PM的干沉降和湿沉降过程进行数值模拟.发现大自然对0.3μm附近的中等尺度颗粒物难以自身净化,降雨量的增加有利于各种尺度颗粒物的湿去除,而雨滴几何平均尺度越小、雨滴几何标准偏差越小,越有利于小尺度和中等尺度颗粒物的湿去除,但稍稍不利于大尺度颗粒物的湿去除.
(4)高效PM除尘技术的可行性分析和运行优化
通过对自然条件和外加条件下PM动力学演变规律的认识,采用复合外加条件提高PM的除尘效率.对两种高效PM除尘技术(静电增强湿式除尘器和静电布袋混合除尘器)进行了颗粒群平衡模拟,并以此为基础对这些除尘技术进行了可行性分析.模拟结果表明两种除尘技术均可能达到99%以上的整体质量除尘效率和整体数量除尘效率.对静电增强湿式除尘器的优化运行分析表明,增大含尘气流输运速度或减小液滴喷射速度、增大液气比或液滴荷质比、减小液滴几何平均尺度和几何标准偏差(使得喷雾液滴越细和越均匀),可以提高该种除尘器对PM的除尘效率.
Inhalable particles or particulate matter (PM or PM10), whose aerodynamic diameters are less than 10μm, have been the serious problem of air pollution. Because of the micromechanism of PM and the complicated physicochemical process of its formation, growth and evolution, little information relating with theoretical model and quantitative description was reported, not only about its sampling and analysis of the physicochemical characteristic, or its formation mechanism and micro-scale dynamic evolution during coal combustion, but also about its nonlinear and nonsteady evolution in natural environment or the imposed external force and condition, or even the design and optimization of high-efficiency capture strategy. On this condition, the integrated framework of the stochastic model of population balance modeling is constructed for the numerical simulation of dynamic evolution of PM from coal combustion, including particle collision, coagulation, breakage, condensation/evaporation, nucleation and deposition. Besides, the stochastic model of population balance modeling is used to simulate numerically the dust-removal process of electrostatic precipitator and wet scrubber, the dry deposition and wet scavenging of particles in the natural environment. Those removal mechanisms in those industrial or natural processes are analyzed quantificationally. Based on this, two techniques with high PM-removal efficiency, i.e., the gravitational wet scrubbers with electrostatic enhancement and the electrostatic-bag hybrid precipitator, are proposed. Therefore, feasibility analysis and operation optimization are taken against the two techniques, which will provide theoretical basis and technical guide for their industrial application. The main points are as following:
(1) Stochastic algorithm for zero-dimensional population balance modeling
The concept of“weighted fictitious particle”is instructed and a new multi-Monte Carlo (MMC) method is developed to realize numerically zero-dimensional population balance modeling. The MMC method has characteristics of time-driven Monte Carlo, constant-number and constant-volume method. It has the receivable computational cost in engineering because the fictitious particle population is tracked, whose number is greatly less than that of real particle population; it exhibits the stable and high computation precision because of the constant number of fictitious particles; it also shows the friend expansibility coupling perfectly with two-phase turbulent models due to its constant-volume characteristic and time-driven frame. The MMC method is used to simulate some special cases including initial monodisperse or polydisperse particle population, independent or simultaneous dynamic events, in which complete or partial analytical solutions exist. The good agreement between MMC solutions and the corresponding analytical solutions proves that MMC method has high and stable computational precision and efficiency.
For the first time, the accuracy of MC methods has been quantified on basis of standard deviations in calculation of properties of particle size distribution. This approach is be used for accuracy analysis of time-driven direct simulation Monte Carlo, stepwise constant volume, constant number and MMC method. And then the source of numerical error and the contributor of numerical cost are analyzed qualitatively on the basis of quantitative comparison. With respect to the so-called“constant number error”of MMC method, it is improved by some measures including the establishment of the procedure of“differently weighted fictitious particle population”and the corresponding coagulation rule between“differently weighted fictitious particles”; the introduction of the acceptance-rejection method to realize numerically the standard Markov process in the time-driven MC; the development of“constant number scheme”and“stepwise constant number scheme”to restore the number of fictitious particles. The quantitative comparison among some kinds of MCs shows that the improved MMC method has been one of the most high-precision and high-efficiency methods among time-driven MC techniques.
With the understanding that event-driven MC exhibits the congenital immunity to“uncoupling error”and high precision and efficiency, a new event-driven constant volume (EDCV) method for zero-dimensional population balance modeling is developed. The method still introduces the concept of“weighted fictitious particle”and conserves the characteristic of constant volume. Furthermore, the following different techniques, the procedure of“equally or differently weighted fictitious particle population”, the cumulative probabilities or acceptance-rejection methods,“constant number scheme”or“stepwise constant number scheme”or“resetting scheme”, are unified within the one framework. By the comparison of several popular MCs, it’s concluded that the EDCV method has come into the MC family of the highest precision and efficiency.
(2) Stochastic algorithm for multi-dimensional population balance modeling
The multi-dimensional MMC method for multi-dimensional population balance modeling is founded by means of the perfect coupling of the improved MMC method for the particle dynamic evolution and the Euler-Lagrangian model for two-phase turbulent flows. The method introduces the spatially grid-plotting technique and sets the right time-step. Furthermore, the stochastic process is utilized to judge the occurrence of the dynamic events such as collision/coagulation, to search the collision/coagulation partner, and to establish the collision dynamics. Two standard cases, fine particle flows and heavy particle flows, are chosen to validate the multi-dimensional MMC method for the description of particle collision and coagulation. The simulation results of MMC method are in good agreement with those of direct numerical simulation (DNS), which indicates the proposed multi-dimensional MMC method has constructed a high-efficiency and high-precision numerical platform for four-ways coupling two-phase turbulent models and multi-dimensional population balance modeling. In order to investigate the influence of particle collision on the two-phase flows field, the proposed MC method is used to simulate a swirling gas-particle flows which tack place in an axial symmetry and suddenly expanded pipe. The result shows, the velocity and Reynold stress of particle phase are redistributed and is inclined to isotropy; and turbulence kinetic energy of particle phase and fluctuation velocity correction of particle-gas phase are attenuated.
(3) The research on the PM collection mechanisms in traditional dust control units and natural environment
In order to understand the dynamic mechanism of PM when imposed by external force and condition, the event-driven constant volume method is adopted to simulate the dynamic process of fly ashes in typical electrostatic precipitator and wet scrubber. The simulation results indicate that, the competition between the inertia force and the electric force of fly ash in electrostatic precipitator results in the low collection efficiency of fine particles with size 0.1~1μm; and fine particles with size 0.1~1μm in wet scrubber are scavenged by drops with low efficiency because not only Brownian diffusion mechanism but also inertial impaction mechanism have a weak effect on those intermediate particles. Moreover, low pressure impactor is used to sample locally the fly ashes of the inlet and outlet of electrostatic precipitator in a 300MW coal-fired boiler, and then the collection process is decribed by population balance modeling. The simulation results agree with the experimental results well.
In order to describe quantitatively the sedimentation process of PM from the outlet of dust separator, and to learn the self-purification mechanism of nature, the dry deposition and wet removal process of particles are simulated by the multi-Monte Carlo method. The numerical results show that, it’s difficult for nature to settle the intermediate particles of about 0.3μm by its self-purification mechanism; the increase of rainfall intensity will benefit the wet scavenging of particles with any size; the smaller geometric mean diameter or geometric standard deviation of raindrops can help scavenge small and intermediate particles better, though large particles are prevented from being collected in some ways.
(4) The feasibility analysis and operation optimization of two techniques with high PM-removal efficiency
Owe to the understanding of the dynamic laws of PM in the natural and imposed condition, the hybrid external conditions or forces are adopted to enhance the collection efficiency of PM. Population balance modeling and then feasibility analysis are taken against two PM-removal techniques with high efficiency, saying, the gravitational wet scrubbers with electrostatic enhancement and the electrostatic-bag hybrid precipitator. The simulation results indicate that overall number and mass efficiency reach to 99% in the two techniques. Operation optimization of the gravitational wet scrubbers with electrostatic enhancement shows that, the faster gas velocity or the slower droplet velocity, and the smaller geometric mean diameter or geometric standard deviation of droplets (that is, the finer or evener droplets), and the bigger liquid-to-gas flow ratio or charge-to-mass ratio of droplets, can help remove PM.
(1)零维颗粒群平衡模拟的随机算法
本文引入“加权虚拟颗粒”概念而发展了一种全新的零维颗粒群平衡模拟随机算法——多重Monte Carlo (Multi-Monte Carlo, MMC)算法.该算法具有时间驱动Monte Carlo (MC)、常数目法和常体积法的特点,由于跟踪数目较少的虚拟颗粒群而具备适用于工程计算的计算代价,由于保持恒定的虚拟颗粒总数目而具有稳定的计算精度,由于保持恒定的计算区域体积和基于时间驱动技术而具有与两相湍流模型无缝耦合的扩展性.特殊工况下MMC算法结果与相应的理论分析解之间的良好吻合,证明该算法能够以较高计算精度和计算效率描述初始单分散性或多分散性颗粒群工况、单动力学事件或复合动力学事件工况等.
本文首次建立了MC算法对颗粒尺度分布时间演变过程描述精度的定量评判方法.以此为基础,定量比较了时间驱动直接模拟MC、阶梯式常体积法、常数目法和MMC算法对于各种动力学事件的描述精度,并定性分析了各种MC数值误差的来源和计算代价的主要贡献源.针对MMC算法所表现的“常数目误差”,通过建立“异数目权值虚拟颗粒群策略”以及相应的“异数目权值虚拟颗粒凝并准则”、在时间驱动MC中引入接受-拒绝法来数值实现标准Markov过程、发展“常数目方案”和“阶梯式常数目方案”来恢复虚拟颗粒数目等手段,对MMC算法进行改进.多种MC算法之间的定量比较表明,改进的MMC算法已经成为时间驱动MC中计算精度和计算效率最高的算法之一.
基于事件驱动MC对解藕误差的免疫及高计算精度和效率的认识,本文发展了另外一种全新的零维颗粒群平衡模拟随机算法——事件驱动常体积(EDCV)法.该算法仍然引入“加权虚拟颗粒”的概念和保持常体积特征,并把“等数目权值虚拟颗粒群策略”和“异数目权值虚拟颗粒群策略”、累积概率法和接受-拒绝法、“常数目方案”和“阶梯式常数目方案”以及“重整方案”等技术统一在一个框架下.通过对多种主流MC的定量比较,证明EDCV法成为目前零维颗粒群平衡模拟中计算精度和计算效率最高的随机算法之一.
(2)多维颗粒群平衡模拟的随机算法
通过把描述颗粒动力学演变的改进MMC算法与描述两相湍流场的欧拉-拉氏模型的无缝耦合,首次发展了一种多维颗粒群平衡模拟的随机算法——多维MMC算法.该算法引入网格划分技术和设置合适的时间步长,采用随机过程来判断碰撞/凝并等动力学事件的发生、寻找碰撞/凝并伙伴、建立碰撞动力学等.对细微颗粒流和粗重颗粒流中颗粒碰撞和凝并过程进行了数值模拟,模拟结果与直接数值模拟(DNS)结果实现定量上的较好吻合,证明所构建的多维多重Monte Carlo算法为四向耦合的两相湍流模型和多维颗粒群平衡模拟提供一个高精度和高效率的数值描述方案.采用所发展的MC算法考察了轴对称突扩通道有旋气固两相流中颗粒碰撞对于两相流场的影响,发现颗粒之间的相互碰撞使得颗粒速度和雷诺应力重新分配并趋于各向同性,而颗粒湍动能及颗粒-流体脉动速度关联降低.
(3)传统除尘装置和自然环境对PM的除尘机理研究
为了理解外加条件对PM动力学特性的作用机理,采用事件驱动常体积法对典型的静电和湿式除尘器进行了颗粒群平衡模拟.发现静电力与惯性力的相互竞争导致0.1~1μm的细微颗粒难以被静电除尘器捕集,而布朗扩散和惯性碰撞机制对0.1~1μm区间颗粒物影响最小也导致其难以被湿式除尘器的液滴所捕集.对300MW燃煤锅炉配备的静电除尘器进口和出口烟尘颗粒进行现场采样,并进行实际静电除尘器的颗粒群平衡模拟,模拟结果和是试验结果达到定量的吻合.
为了描述从除尘器逃逸出来的PM在自然环境中的沉降过程,并借鉴大自然的自身净化机制,采用多重Monte Carlo算法对自然环境中PM的干沉降和湿沉降过程进行数值模拟.发现大自然对0.3μm附近的中等尺度颗粒物难以自身净化,降雨量的增加有利于各种尺度颗粒物的湿去除,而雨滴几何平均尺度越小、雨滴几何标准偏差越小,越有利于小尺度和中等尺度颗粒物的湿去除,但稍稍不利于大尺度颗粒物的湿去除.
(4)高效PM除尘技术的可行性分析和运行优化
通过对自然条件和外加条件下PM动力学演变规律的认识,采用复合外加条件提高PM的除尘效率.对两种高效PM除尘技术(静电增强湿式除尘器和静电布袋混合除尘器)进行了颗粒群平衡模拟,并以此为基础对这些除尘技术进行了可行性分析.模拟结果表明两种除尘技术均可能达到99%以上的整体质量除尘效率和整体数量除尘效率.对静电增强湿式除尘器的优化运行分析表明,增大含尘气流输运速度或减小液滴喷射速度、增大液气比或液滴荷质比、减小液滴几何平均尺度和几何标准偏差(使得喷雾液滴越细和越均匀),可以提高该种除尘器对PM的除尘效率.
Inhalable particles or particulate matter (PM or PM10), whose aerodynamic diameters are less than 10μm, have been the serious problem of air pollution. Because of the micromechanism of PM and the complicated physicochemical process of its formation, growth and evolution, little information relating with theoretical model and quantitative description was reported, not only about its sampling and analysis of the physicochemical characteristic, or its formation mechanism and micro-scale dynamic evolution during coal combustion, but also about its nonlinear and nonsteady evolution in natural environment or the imposed external force and condition, or even the design and optimization of high-efficiency capture strategy. On this condition, the integrated framework of the stochastic model of population balance modeling is constructed for the numerical simulation of dynamic evolution of PM from coal combustion, including particle collision, coagulation, breakage, condensation/evaporation, nucleation and deposition. Besides, the stochastic model of population balance modeling is used to simulate numerically the dust-removal process of electrostatic precipitator and wet scrubber, the dry deposition and wet scavenging of particles in the natural environment. Those removal mechanisms in those industrial or natural processes are analyzed quantificationally. Based on this, two techniques with high PM-removal efficiency, i.e., the gravitational wet scrubbers with electrostatic enhancement and the electrostatic-bag hybrid precipitator, are proposed. Therefore, feasibility analysis and operation optimization are taken against the two techniques, which will provide theoretical basis and technical guide for their industrial application. The main points are as following:
(1) Stochastic algorithm for zero-dimensional population balance modeling
The concept of“weighted fictitious particle”is instructed and a new multi-Monte Carlo (MMC) method is developed to realize numerically zero-dimensional population balance modeling. The MMC method has characteristics of time-driven Monte Carlo, constant-number and constant-volume method. It has the receivable computational cost in engineering because the fictitious particle population is tracked, whose number is greatly less than that of real particle population; it exhibits the stable and high computation precision because of the constant number of fictitious particles; it also shows the friend expansibility coupling perfectly with two-phase turbulent models due to its constant-volume characteristic and time-driven frame. The MMC method is used to simulate some special cases including initial monodisperse or polydisperse particle population, independent or simultaneous dynamic events, in which complete or partial analytical solutions exist. The good agreement between MMC solutions and the corresponding analytical solutions proves that MMC method has high and stable computational precision and efficiency.
For the first time, the accuracy of MC methods has been quantified on basis of standard deviations in calculation of properties of particle size distribution. This approach is be used for accuracy analysis of time-driven direct simulation Monte Carlo, stepwise constant volume, constant number and MMC method. And then the source of numerical error and the contributor of numerical cost are analyzed qualitatively on the basis of quantitative comparison. With respect to the so-called“constant number error”of MMC method, it is improved by some measures including the establishment of the procedure of“differently weighted fictitious particle population”and the corresponding coagulation rule between“differently weighted fictitious particles”; the introduction of the acceptance-rejection method to realize numerically the standard Markov process in the time-driven MC; the development of“constant number scheme”and“stepwise constant number scheme”to restore the number of fictitious particles. The quantitative comparison among some kinds of MCs shows that the improved MMC method has been one of the most high-precision and high-efficiency methods among time-driven MC techniques.
With the understanding that event-driven MC exhibits the congenital immunity to“uncoupling error”and high precision and efficiency, a new event-driven constant volume (EDCV) method for zero-dimensional population balance modeling is developed. The method still introduces the concept of“weighted fictitious particle”and conserves the characteristic of constant volume. Furthermore, the following different techniques, the procedure of“equally or differently weighted fictitious particle population”, the cumulative probabilities or acceptance-rejection methods,“constant number scheme”or“stepwise constant number scheme”or“resetting scheme”, are unified within the one framework. By the comparison of several popular MCs, it’s concluded that the EDCV method has come into the MC family of the highest precision and efficiency.
(2) Stochastic algorithm for multi-dimensional population balance modeling
The multi-dimensional MMC method for multi-dimensional population balance modeling is founded by means of the perfect coupling of the improved MMC method for the particle dynamic evolution and the Euler-Lagrangian model for two-phase turbulent flows. The method introduces the spatially grid-plotting technique and sets the right time-step. Furthermore, the stochastic process is utilized to judge the occurrence of the dynamic events such as collision/coagulation, to search the collision/coagulation partner, and to establish the collision dynamics. Two standard cases, fine particle flows and heavy particle flows, are chosen to validate the multi-dimensional MMC method for the description of particle collision and coagulation. The simulation results of MMC method are in good agreement with those of direct numerical simulation (DNS), which indicates the proposed multi-dimensional MMC method has constructed a high-efficiency and high-precision numerical platform for four-ways coupling two-phase turbulent models and multi-dimensional population balance modeling. In order to investigate the influence of particle collision on the two-phase flows field, the proposed MC method is used to simulate a swirling gas-particle flows which tack place in an axial symmetry and suddenly expanded pipe. The result shows, the velocity and Reynold stress of particle phase are redistributed and is inclined to isotropy; and turbulence kinetic energy of particle phase and fluctuation velocity correction of particle-gas phase are attenuated.
(3) The research on the PM collection mechanisms in traditional dust control units and natural environment
In order to understand the dynamic mechanism of PM when imposed by external force and condition, the event-driven constant volume method is adopted to simulate the dynamic process of fly ashes in typical electrostatic precipitator and wet scrubber. The simulation results indicate that, the competition between the inertia force and the electric force of fly ash in electrostatic precipitator results in the low collection efficiency of fine particles with size 0.1~1μm; and fine particles with size 0.1~1μm in wet scrubber are scavenged by drops with low efficiency because not only Brownian diffusion mechanism but also inertial impaction mechanism have a weak effect on those intermediate particles. Moreover, low pressure impactor is used to sample locally the fly ashes of the inlet and outlet of electrostatic precipitator in a 300MW coal-fired boiler, and then the collection process is decribed by population balance modeling. The simulation results agree with the experimental results well.
In order to describe quantitatively the sedimentation process of PM from the outlet of dust separator, and to learn the self-purification mechanism of nature, the dry deposition and wet removal process of particles are simulated by the multi-Monte Carlo method. The numerical results show that, it’s difficult for nature to settle the intermediate particles of about 0.3μm by its self-purification mechanism; the increase of rainfall intensity will benefit the wet scavenging of particles with any size; the smaller geometric mean diameter or geometric standard deviation of raindrops can help scavenge small and intermediate particles better, though large particles are prevented from being collected in some ways.
(4) The feasibility analysis and operation optimization of two techniques with high PM-removal efficiency
Owe to the understanding of the dynamic laws of PM in the natural and imposed condition, the hybrid external conditions or forces are adopted to enhance the collection efficiency of PM. Population balance modeling and then feasibility analysis are taken against two PM-removal techniques with high efficiency, saying, the gravitational wet scrubbers with electrostatic enhancement and the electrostatic-bag hybrid precipitator. The simulation results indicate that overall number and mass efficiency reach to 99% in the two techniques. Operation optimization of the gravitational wet scrubbers with electrostatic enhancement shows that, the faster gas velocity or the slower droplet velocity, and the smaller geometric mean diameter or geometric standard deviation of droplets (that is, the finer or evener droplets), and the bigger liquid-to-gas flow ratio or charge-to-mass ratio of droplets, can help remove PM.
引文
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