从KCl-NaCl浸出液中分离提纯氯化钾的多效蒸发结晶能耗分析研究

建立了从烧结电除尘灰浸出液中分离提纯氯化钾的多效蒸发结晶模型,采用数学拟合的方法拟合得到KCl-NaCl溶液的xKCl-xNaCl-t和p-xNaCl-t的数学方程,避免了手工逐步逼近计算的繁琐,也实现了计算机编程对烧结电除尘提纯分离氯化钾的多效蒸发结晶过程的模拟求解。优化计算得到了KClNaCl溶液的四效蒸发过程的能量消耗,同时研究了冷凝水闪蒸、额外蒸汽引出预热原料液及冷凝水闪蒸额外蒸汽预热联合措施对四效蒸发系统生蒸汽用量的影响,结果表明,有冷凝水闪蒸可以节省生蒸汽5.59%,有额外蒸汽引出预热原料液可以节省生蒸汽11.86%,额外蒸汽引出预热原料液比冷凝水闪蒸更能合理利用额外蒸汽的潜热,节能生蒸汽的用量。2种节能措施联用可以节省生蒸汽18.17%,比单个节能措施的节能效果简单加和更具有节能优势。     

高效节能热泵错流多效蒸发复杂系统

为了大幅降低错流多效蒸发过程的能耗,首次将蒸汽喷射式热泵技术、冷凝水闪蒸和溶液闪蒸等3种节能措施同时运用到错流多效蒸发系统中,并建立了用矩阵方程描述的该系统的数学模型。模型具有很强的通用性,可实现热泵在任意效抽汽的功能,可简化为只有其中若干种节能措施组合或无上述节能措施的错流、并流、逆流多效蒸发系统的模型。在满足约束条件的前提下,模型存在最佳的热泵喷射系数和抽汽位置,同时采用上述3种节能措施且在最佳条件下模型是高效节能的。浓缩氢氧化钠溶液的热泵错流五效蒸发系统的模拟结果表明,当热泵的喷射系数为0.15、抽汽位置在第2效,采用冷凝水闪蒸和溶液闪蒸时系统节省的生蒸汽消耗量高达32.51%。     

选择热泵多效蒸发系统最佳流程的新方法

为了能从众多多效蒸发流程中快速准确地筛选出能耗最低的最佳流程,建立了筛选多效蒸发最佳流程的新方法——矩阵法。新方法将多效蒸发系统中的物料衡算和热量衡算非线性方程组描述成矩阵方程,当流程或节能措施改变时,无需重新推导数学模型,只需将矩阵方程中的若干参数重新赋值,模型就能模拟并流、逆流、各种形式的错流、平流和平错流,还能模拟上述流程有或无蒸汽喷射式热泵技术、引出额外蒸汽预热原料液、冷凝水闪蒸和溶液闪蒸的各种情况,从而快速准确地筛选出最佳流程。浓缩菠萝汁的三效蒸发系统的模拟筛选结果表明:不采用任何节能措施或仅采用冷凝水闪蒸或仅采用蒸汽喷射式热泵技术时,最佳流程是逆流;同时采用蒸汽喷射式热泵技术、引出额外蒸汽预热原料液和冷凝水闪蒸的并流流程最佳,其节省的生蒸汽消耗量高达42.77%。矩阵法是筛选多效蒸发最佳流程的新方法,具有通用性强、效率高、速度快且准确等突出优点。     

高效节能海水淡化热泵并流多效蒸发系统研究

为了降低海水淡化过程的能耗,首次建立了同时包含蒸汽喷射式热泵技术、引出额外蒸汽预热海水和冷凝水闪蒸等3种节能措施的海水淡化热泵并流多效蒸发系统的数学模型,并用矩阵方程的形式描述该模型,具有很强的通用性,可简化为具有不同节能措施组合或无节能措施的并流多效蒸发模型,还可实现热泵在任意效抽汽的功能。用收敛速度快的迭代法结合矩阵法模拟求解海水淡化热泵并流9效蒸发系统,结果表明同时采用上述3种节能措施,且在满足相关约束条件下,使海水的预热温度尽可能高,使热泵的喷射系数和抽汽位置均为最佳值时该蒸发系统是高效节能的,节省的生蒸汽消耗量最高可达16.72%左右。     

复杂逆流多效蒸发系统的模拟

建立有冷凝水、完成液预热符效进料,或冷凝水、完成液闪蒸,闪蒸蒸汽加入对应压力的蒸发器中,作加热蒸汽的复杂逆流多效蒸发系统的数学模型,提出了一种采用常规迭代法求解的计算方法,用面向对象的Pascal语言,编制计算程序,可模拟计算二至七效常规和复杂逆流蒸发系统,并以碱液为例,计算和比较三效逆流的5种流程.     

复杂平流多效精馏系统能量集成模型及过程模拟

为了更合理利用能量,将平流多效精馏系统中各效塔底产品、第1效至第n-1效塔顶产品及首效再沸器中加热生蒸汽的冷凝液用于预热原料液,建立由多效精馏及多级预热2个子系统构成的复杂平流多效精馏系统的能量集成模型。用于模拟具有切点系统的高度非理想溶液的平流多效精馏过程,用迭代法结合矩阵法求解。结果表明:用系统余热预热原料液可节省加热生蒸汽消耗量25%～35%,是1种非常有效的节能措施;各效精馏塔回流比及再沸器的有效传热温差、首效塔底再沸器中加热生蒸汽压力(或温度)、末效塔顶压力(或温度)、原料液的预热温度等参数,对平流多效精馏系统的操作费用及设备费用影响很大。     

氧化铝蒸发系统的模拟

在氧化铝蒸发工序中,生蒸汽流量和母液出口浓度是重要的能耗指标和出口质量指标;目前,在实际生产中由于采用离线浓度检测,以致对蒸汽流量和出口浓度的控制严重滞后;因此,针对蒸汽流量控制和浓度检测滞后的现状,建立了氧化铝四效蒸发系统的数学模型;采用Newton-Raphson算法求解四效蒸发系统模型,并对实际氧化铝四效蒸发系统进行了模拟计算,进而绘出母液出口浓度和总蒸发水量的误差曲线图;结果表明该模型准确、高效,对蒸发系统节能降耗有现实的指导意义。     

间歇精馏常规设计和优化设计的模型及算法

建立了板式间歇精馏塔在恒馏出液组成操作状况下常规设计及优化设计的数学模型。常规设计模型用数值方法编程求解，对二元理想及非理想溶液均适用。优化设计模型以间歇精馏系统年效益最大为优化目标，用菲波那契法求解单变量优化问题，用复合形法求解多变量优化问题。模型同时考虑对整个间歇精馏系统(包括塔主体、塔顶冷凝器及塔底再沸器)进行优化，更符合工程实际情况。求解模型可得到间歇精馏过程最优的一系列设计和操作参数(如理论板数，塔径，操作回流比，塔釜蒸发量，釜残液组成，冷凝器传热面积及冷却水出口温度，再沸器传热面积及加热蒸汽温度等)。算例表明，对恒馏出液组成间歇精馏单变量及多变量优化设计比常规设计分别提高年效益2．6％和18．9％。     

基于子流程图的氧化铝蒸发过程模拟系统

为了便于分析并优化氧化铝蒸发过程中蒸汽消耗的分布,设计一种基于子流程图的氧化铝蒸发过程模拟系统。介绍氧化铝蒸发的工艺流程,针对氧化铝多效蒸发流程中各效内部单元模型基本相同的特点,在创建流程图时引入子流程图来管理单元模块和相关变量,以简化整体流程图、提高求解效率。采用Lee-Rudd环路分解法切割流程图中的环路,寻找最佳收敛模块。该系统提高了蒸发模拟系统建模的可重用性。     

基于火用分析的真空精馏系统操作优化

提出了真空精馏系统操作优化方案,对流程进行稳态模拟计算,并进行(?)分析,建立以处理单位质量原料的成本最低目标的优化设计模型。进而调整精馏塔塔顶压力、进料负荷、塔顶冷凝器出口副产蒸汽压力、再沸器导热油温度等操作参数,以达到优化流程参数的目的。结果表明,当塔顶压力达到10 kPa,精馏塔进料量可以增大到3750kg·h~(-1),此时处理单位质量原料的费用最低,优化流程的成本比原工况减少17.0%。     

Control of a two-pressure distillation column

A recent paper explored the separation of the close-boiling mixture 1,2 propanediol (PDO) and ethylene glycol (EG). The optimum operating pressure using a traditional single vessel was 282 kPa with a reboiler duty of 399 kW. However, the vapor–liquid equilibrium shifts with pressure such that higher pressure is favorable in the PDO-rich region. An interesting steady-state design was developed that splits the column into a high-pressure rectifier (4.9 bar) and a low-pressure stripper (2.38 bar). A compressor (32 kW) moves vapor from the top of the stripper into the bottom of the rectifier. The hot vapor leaving the top of the rectifier at 244 °C provides all the heat required in the reboiler at the base of the stripper (234 °C). This novel design reduces energy cost by 85%.An effective control structure for this complex process is developed in this paper. A small auxiliary reboiler and condenser are used to stabilize the system and to handle large disturbances in throughput and feed composition.     

板式吸收塔优化设计研究与软件开发

以板式吸收塔系统的年总费用为目标函数，建立了优化设计数学模型，以吸收塔的液气比为决策变量，用单变量优化算法(菲波拿契法)求得最优解。用Visual Basic6．0开发出板式吸收塔优化设计软件。软件运行于Windows 9x系统，界面友好，操作方便。算列表明优化设计比常规设计节省生产成本。     

具有废气循环的并流回转干燥器优化设计研究

建立了以具有废气循环的并流回转干燥系统年总费用为目标函数的优化设计数学模型,用遗传算法与菲波那契法求解数学模型,实现湿空气出口温度与废气循环比的优化设计。结果表明：采用部分废气循环并进行优化设计是干燥系统节能中非常重要的措施。对湿空气出口温度和废气循环比进行优化设计,比无废气循环的常规设计节省年总费用20．8%,比循环比为0．2时的常规设计节省年总费用14．3%。     

An application of stochastic geometric programming to heat exchanger design

This article presents an application of stochastic geometric programming to heat exchanger design. The design problem has been formulated based on the geometry and heat transfer characteristics of a horizontal shell-and-tube condenser for industrial refrigeration plants. Solutions of various stochastic geometric programming models indicate a range of estimates of the optimum life cycle cost and the values of the corresponding design parameters such as physical dimensions of the heat exchanger. The method presented here can be applied to other engineering design problems by appropriately modifying the problem formulation.     

Soft computing based multi-objective optimization of steam cycle power plant using NSGA-II and ANN

In this paper a steam turbine power plant is thermo-economically modeled and optimized. For this purpose, the data for actual running power plant are used for modeling, verifying the results and optimization. Turbine inlet temperature, boiler pressure, turbines extraction pressures, turbines and pumps isentropic efficiency, reheat pressure as well as condenser pressure are selected as fifteen design variables. Then, the fast and elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) is applied to maximize the thermal efficiency and minimize the total cost rate (sum of investment cost, fuel cost, and maintenance cost) simultaneously. The results of the optimal design are a set of multiple optimum solutions, called ‘Pareto optimal solutions’. The optimization results in some points show 3.76% increase in efficiency and 3.84% decrease in total cost rate simultaneously, when it compared with the actual data of the running power plant. Finally as a short cut to choose the system optimal design parameters a correlation between two objectives and fifteen decision variables with acceptable precision are presented using Artificial Neural Network (ANN).     

含盐量对土壤的水汽吸附及土壤水能量状态的影响

以甘肃景电灌区盐化土壤为对象用水汽平衡吸附法就盐分对土壤的水汽吸附和土壤水能量状态的影响进行了研究 .结果表明盐分显著增加了土壤水汽吸附量 ,水汽饱和度为 98%的情况下 ,含盐量为 1 0 .772 g/kg和 1 2 .887g/kg的两个土壤的水汽吸附量分别达到了 1 9.4 5 %和 2 5 .34 % .水汽饱和度大于65 %左右时水汽吸附有一个明显的转折点 ,.水汽饱和度大于 65 %时水汽吸附量主要受含盐量影响 ,而当饱和度小于 65 %时则主要受物理性粘粒含量的影响 .盐分非常显著地降低了土壤的水势 ,可以用盐化土样的水势与脱盐处理土样的水势估算盐化土样的渗透势 .估算结果表明在低水势段以及在相当大含水量范围内盐化土壤因盐分浓度所产生的渗透势的绝对值远大于基质势的绝对值     

Data-driven,using design of dynamic experiments,versus model-driven optimization of batch crystallization processes

A new data-driven experimental design methodology, design of dynamic experiments (DoDE), is proposed as a means of developing a response surface model that can be used to effectively optimize batch crystallization processes. This data-driven approach is especially useful for complex processes for which it is difficult or impossible to develop a knowledge-driven model in a timely fashion for the optimization of an industrial process. Design of dynamic experiments [1] generalizes the formulation of time-invariant design variables from design of experiments, allowing for consideration of time-variant design variables in the experimental design. When combined with response surface modeling and an appropriate optimization algorithm, a data-driven optimization methodology is produced, which we call DoDE optimization. The method is used here to determine the optimal cooling rate profile, which integrates to give the optimum temperature profile, for a batch crystallization process. To examine the effectiveness of the DoDE optimization method, the data-driven optimum temperature profile is compared to the optimum temperature profile obtained using a model-based optimization technique for the potassium nitrate–water batch crystallization model developed by Miller and Rawlings [2]. The temperature profiles calculated using DoDE optimization yield response values within a few percent of the true model-based optimum values. A sensitivity analysis is performed on one case study to evaluate the distribution of the response variable from each method in the presence of parameter and initial seed distribution variability. It is demonstrated that there is partial overlap in the distributions when only variability in the model parameters is evaluated and there is substantial overlap when variability is included in both the model and initial seed distribution parameters. From this evidence, it can be concluded that the DoDE optimization method has the potential to be a useful data-driven optimization tool for batch crystallization processes where a first-principles model is not available or cannot be developed due to time and/or cost constraints.