Computational Modeling of Tangentially Fired Boiler(I I) NOx Emissions

The paper describes numerical and experimentalstudy on reduction of NOx emissions in a 600 MWtangentially fired boiler furnace under different operating conditions.A simplified NOx formation mechanism model,along with the gas-particle multiphase flow model, is adopted.The prediction yields encouraging results as compared toexperimental data.     

切向燃烧锅炉的计算模型(Ⅱ)NOx排放

The paper describes numerical and experimental study on reduction of NO~ emissions in a 600 MW tangentially fired boiler furnace under different operating conditions. A simplified NOx formation mechanism model,along with the gas-particle multiphase flow model, is adopted. The prediction yields encouraging results as compared to experimental data.     

Monitoring and prediction of fouling in coal-fired utility boilers using neural networks

This paper describes a systematic approach to predict ash deposits in coal-fired boilers by means of artificial neural networks. The approach is of a “grey box” nature, decomposing the problem into logical parts, and avoiding the use of sophisticated data. Although it is relative to the specific fuel and equipment, the prediction is very detailed and can be used on-line; it accounts not only for the deposition rate, but also for short-term cleaning occurrences, thus simulating a complex and chaotic time-evolution. The model is developed with the aid of a case-study, that of the fouling of a furnace, as detected by heat flux meters. Provided that an adequate amount of heat transfer measurements can be gathered, the procedure can be used to simulate the evolution of boiler heat absorption under realistic conditions of deposition. Applications include obviously new possibilities for automatic control of the equipment, as well as the optimization of operating set points to maximize thermal efficiency, such as the sequence and operation of on-load cleaning devices. It is thought that the method developed would be applicable to other instances of fouling or equipment degradation exhibiting similar behavior, specially with respect to on-line corrective measures.     

Modelling of comminution processes in Spex Mixer/Mill

It is well known that mathematical models which simulate comminution processes represent a useful tool in several fields of academic and industrial research, with particular emphasis on nano-material and pharmaceutical production. In the present work a mathematical model which is able to quantitatively describe comminution processes in a ball milling system (i.e., Spex-Mixer/Mill) has been developed. The proposed approach takes into account three different contributions: dynamics of the vial, dynamics of spheres motion and simulation of the comminution process. The vial dynamics has been modelled by taking advantage of an appropriate roto-translation matrix. Model results have been successfully compared with literature experimental data. The spheres motion within the Spex Mixer/Mill has been simulated using a 3D dynamic model based on classical mechanics as well as the so-called discrete element method, which is widely adopted to quantitatively describe multi-body collision behaviour. In particular, existing models of impact with dissipation as well as the classical Hertz impact theory have been taken into account. This part of the global model allows one to obtain, for different operating conditions, the impact specific energy and impact velocity as a function of time. The latter ones represent input parameters for the simulation of comminution processes that is performed through suitable population balances, where different breakage functions as well as appropriate breakage probabilities have been considered. Model results are reported in terms of granulometric distribution of powders within the mixer-mill as a function of time, minimal grain size obtainable and time needed to complete the comminution process for various operating conditions (i.e., mill frequency and charge ratio).     

Chemical reactor network application to predict the emission of nitrogen oxides in an industrial combustion chamber

A new chemical reactor network model is developed to predict the emission of nitrogen oxides in an industrial combustion chamber operating on liquefied petroleum gas. The boundary conditions and operating parameters used for this model are typical operating conditions of an industrial combustion chamber. The global mechanism is developed by GRI-MECH 3.0 in the UW code. The model predictions are compared with experimental data. The chemical reactor network model provides an accurate estimation of nitrogen oxide emission.     

Development of fireside waterwall corrosion correlations using pilot-scale test furnace

Fireside waterwall wastage in a pulverized coal-fired boiler was investigated and the relevant rate correlations were developed for three corrosion mechanisms: gas-phase attack by reduced sulfur species, chlorine-based attack, and unoxidized fuel deposition. Rate correlations were based on the published data and the experiments at a pilot-scale test furnace. The parameters of the correlations include local flue gas composition, flue gas temperature, metal surface temperature, deposition, deposit characteristics, and heat flux. Validation work performed using the same furnace and the different operating conditions provided good agreement between predictions and measurements. The correlations in conjunction with computational fluid dynamics simulation are expected to provide a predictive tool that can optimize the furnace operating conditions to reduce fireside waterwall wastage.     

Systematics and modelling representations of LPG thermal cracking for olefin production

Pyrolysis of hydrocarbons is an important commercial process for the production of ethylene, propylene and 1,3 butadiene. These low molecular weight olefins are among the most important base chemicals for the petrochemical industries for polymer production. A simulation program of the reaction kinetics and coke formation inside the coils of a thermal cracking unit can provide information on the effects of operating conditions on the product distribution. The aim of this study was to develop a mechanistic reaction model for the pyrolysis of LPG that can be used to predict the yields of the major products from a given LPG sample with commercial indices. A complete reaction network, using a rigorous kinetic model, for the decomposition of the LPG feed has been developed, which is used for the simulation of industrial LPG crackers. This model has been adapted using industrial data for the pyrolysis yields of LPG. The present paper attends on the asymptotic coking mechanism and describes the development of a kinetic coking model in the pyrolysis of LPG. Detailed and accurate information about the product distribution, growth of coke layer, the evolution of the tube skin temperatures can be obtained from this simulation. Simulations of this kind can be used to optimize the furnace operation. They can be used as a guide for the adaptation of the operating variables aiming at prolonging the run length of the furnace. The reactor model, as well as kinetic scheme, is tested in an industrial cracking furnace.     

NUMERICAL SIMULATION OF SWIRLING FLOW IN A CYCLONE CHAMBER

The ability to predict the influence of design parameters on the aerodynamics of cyclone chambers flows is of prime concern in furnace engineering and a number of high temperature processes. The two-dimensional Los Alamos SOLA prediction technique has been extended to include the computation of an axisymmetric swirling flow. The transient Navier-Stokes equations of an incompressible fluid are solved via their associated finite difference equations, directly in terms of the primitive pressure-velocity variables. For this, a short simple computer code has been developed, using a laminar flow simulation with 'free slip' wall boundary conditions. Predictions show that a useful characterization of the flowfield is now available. The simplified code represents a basic tool, to which user-oriented complexities and sophistications can be added later as required     

传递过程原理在移动床中的应用——(Ⅰ)高炉煤粉喷吹数学模型

炼铁高炉是移动床工艺用于固相加工的重要特殊例子.根据物料和热的微分平衡,对高炉风口喷吹煤粉时所发生的传递现象和化学反应进行了解析.本文中数学模型的理论计算值和实际高炉的实测结果的一致性证明了模型的可靠性.本文提供的软件具有通用性,只要输入不同高炉的鼓风条件、燃料喷吹量、风口直径等初始参数,就可以预报任一参数的变更对炉内状况(诸如炉内气体组分、温度、诸反应速率、回旋区深度、置换比等)的影响,由此不仅可判断高炉内的燃烧状况,而且为高炉操作选择合适的鼓风参数及喷煤量提供了计算方法,以便控制高炉内气流分布和炉温,使高炉操作正常.     

基于迁移学习工况划分的裂解炉收率PSO-LS-SVM建模

乙烯裂解炉收率的实时预测对于生产的先进控制及节能降耗具有重要意义。实际生产过程中,不同工况的收率具有较大差别,采用单一工况、单一模型无法满足生产需要。考虑到裂解炉不同运行过程中的相似性,同时为了减小建模过程中典型样本的采集成本,有效利用历史数据,辅以迁移学习算法实现工况的高精度划分。不同工况采用泛化能力强、训练速度高的最小二乘支持向量机建模,并利用粒子群算法对LS-SVM的参数寻优,进一步提高模型精度,从而实现了多工况、多模型的高精度收率预测。基于某乙烯厂现场数据的实验结果表明,多工况、多模型的预测效果更准确合理,PSO优化LS-SVM建立的裂解炉收率模型预测精度更高,趋势跟踪性能良好。     

提高加热炉出口温度,增加装置液收

介绍了某公司延迟焦化装置加热炉运行工况,并从焦化反应机理和主要工艺操作参数影响的角度分析,提高加热炉出口操作温度不仅增加装置液收,而且增大了弹丸焦生成的几率,结合该装置实际生产数据和该公司模拟软件数据,提出适合本装置提温增液抑制弹丸焦生成可行性的经验操作方案,使得实际生产取得了较好的经济效益。     

NUMERICAL SIMULATION OF SWIRLING FLOW IN A CYCLONE CHAMBER

The ability to predict the influence of design parameters on the aerodynamics of cyclone chambers flows is of prime concern in furnace engineering and a number of high temperature processes. The two-dimensional Los Alamos SOLA prediction technique has been extended to include the computation of an axisymmetric swirling flow. The transient Navier-Stokes equations of an incompressible fluid are solved via their associated finite difference equations, directly in terms of the primitive pressure-velocity variables. For this, a short simple computer code has been developed, using a laminar flow simulation with ‘free slip’ wall boundary conditions. Predictions show that a useful characterization of the flowfield is now available. The simplified code represents a basic tool, to which user-oriented complexities and sophistications can be added later as required     

On-line batch process monitoring using a consecutively updated multiway principal component analysis model

Batch processes lie at the heart of many industries; hence the effective monitoring and control of batch processes is crucial to the production of high-quality materials. Multiway principal component analysis (MPCA) has been widely used for batch monitoring and has proved to be an effective method for monitoring many industrial batch processes. However, because MPCA is a fixed-model monitoring technique, it gives false alarms when it is used to monitor real processes whose normal operation involves slow changes. In this paper, we propose a simple on-line batch monitoring method that uses a consecutively updated MPCA model. The key to the proposed approach is that whenever a batch successfully remains within the bounds of normal operation, its batch data are added to the historical database of normal data and a new MPCA model is developed based on the revised database. The proposed method was applied to monitoring fed-batch penicillin production, and the results were compared with those obtained using conventional MPCA. The simulation results clearly show that the ability of the proposed method to adapt to new normal operating conditions eliminates the many false alarms generated by the fixed model and provides a reliable monitoring chart.     

基于高斯混合模型与主元分析的多模型切换方法

针对多模型预测控制的模型切换问题,提出了一种基于工况判断的多模型切换方法,利用工业过程中的可测变量综合反映系统的动态特性,根据动态特性的变化进行多模型切换。首先利用高斯混合模型(GMM)将历史数据划分为若干个工况,然后利用不同工况下的历史数据建立负荷向量矩阵和预测模型,最后根据主元模型的平方预报误差(SPE)选择预测模型。以乙烯裂解炉的反应管出口温度(COT)的控制为例进行仿真,仿真结果表明:提出的方法实现了多个反应管出口温度的稳定均衡控制,当系统的工况发生改变时,通过不同主元模型的SPE统计量的比较,可以很容易地找到匹配的工况,并切换为相应的预测模型,解决了当系统动态特性发生改变时,预测模型切换滞后的问题。     

A comparative study of models for molten carbonate fuel cell (MCFC) processes

The necessity of this work arose from the need for identification of a comprehensive plant model that can be used in the model-based control of the MCFC plant. Various models for molten carbonate fuel cell (MCFC) processes are presented and evaluated in this paper. Both a rigorous model based on mass and energy balances and implicit models based on operation data were investigated and analyzed. In particular, auto-regressive moving average (ARMA) model, least-squares support vector machine (LSSVM) model, artificial neural network (ANN) model and partial least squares (PLS) model for a MCFC system were developed based on input-output operating data. Among these models, the ARMA model showed the best agreement with plant operation data.     

Modeling of the Residence Time Distribution and Application of the Continuous Two Impinging Streams Reactor in Liquid‐Liquid Reactions

The two‐phase monosulfonation of toluene, as an example of liquid‐liquid reactions, has been conducted in a continuous two impinging stream reactor (TISR). The extent of reaction under different operating conditions has been determined. A comparison has been made between the performance capability of the TISR and that of continuous stirred tank reactors (CSTR). Under identical conditions, including mean residence time, temperature, feed compositions and phase ratio, the impinging stream reactor has shown a higher efficiency. Finally, a stochastic model, based on Markov chain processes has been developed for the TISR, which describes the flow pattern and the residence time distribution (RTD) within the reaction system. The RTD model, combined with the kinetic expression, has been applied to calculate the conversion of toluene in the reactor. The predicted values for toluene conversion have been compared with those determined experimentally.     

Transport in deformable food materials: A poromechanics approach

A comprehensive poromechanics-based modeling framework that can be used to model transport and deformation in food materials under a variety of processing conditions and states (rubbery or glassy) has been developed. Simplifications to the model equations have been developed, based on driving forces for deformation (moisture change and gas pressure development) and on the state of food material for transport. The framework is applied to two completely different food processes (contact heating of hamburger patties and drying of potatoes). The modeling framework is implemented using total Lagrangian mesh for solid momentum balance and Eulerian mesh for transport equations, and validated using experimental data. Transport in liquid phase dominates for both the processes, with hamburger patty shrinking with moisture loss for all moisture contents, while shrinkage in potato stops below a critical moisture content.     

基于高斯混合模型的MWPCA高炉异常监测算法

大型高炉是钢铁制造过程中的重要装备,由于高炉运行过程复杂,干扰因素繁多,经常会有异常炉况发生。为及时监测异常炉况、保证高炉顺行,本文利用高炉运行数据,开发了一种基于MWPCA和高斯混合模型的算法对高炉异常过程进行监测。由于高炉运行数据存在非高斯分布和时变的特点,利用高斯混合模型改进了传统PCA监测模型的T²统计量,使算法可以适应高炉数据的独特分布特征,并加入了滑窗机制,使算法具有实时更新的能力。随后,将算法应用在华南某大型钢铁集团的真实高炉数据上,检测了算法的有效性,并将其与基础算法进行了对比分析,证明了算法在高炉异常监测能力上有所提高。