己内酰胺装置用能分析与节能改造

对己内酰胺装置用能状况进行了分析评价,找出过程用能的薄弱环节,指出用能改进的方向;利用“三环节”能量系统集成优化技术对装置进行用能改造和经济调优,得出优化的用能改造方案。     

己内酰胺回收系统的改造

在锦纶 6聚合生产过程中 ,增加二次精馏 ,从而提高了己内酰胺的回收率。分别介绍了温度、真空度、排渣浓度及排渣的清洗对二次精馏操作的影响。     

己内酰胺装置蒸汽系统节能优化

对100 kt/年的己内酰胺精制装置的用能状况进行了分析,找出了己内酰胺精制过程可节能的潜力环节。有针对性地从节能技术改造和管理措施入手,提出了对热水系统进行改造、对汽提、苯蒸馏、凝液系统等进行技术改造等措施。工业应用效果表明：采取上述措施后,100 kt/a己内酰胺精制装置的蒸汽消耗降低了2.6 t/h,每年节省的低压蒸汽和中压蒸汽所创造的效益约为312万元/年。     

己内酰胺水解聚合过程数学模型化与优化研究进展

综述了己内酰胺水解聚合反应动力学模型,并系统论述了ＰＡ６工业聚合反应器包括高压间歇釜反应器（ＢＳＴＲ）、活塞流反应器（ＰＦＲ）、连续搅拌釜反应器（ＣＳＴＲ）和ＣＳＴＲ与ＰＦＲ组合反应器模型化与优化研究,对数值计算方法也作了简要评价,同时就ＰＡ６聚合过程有待进一步研究的问题提出了几点建议。     

己内酰胺氨肟化装置的节能优化设计

阐述了在己内酰胺氨肟化装置工艺设计中,将叔丁醇回收塔顶气相作为氨肟化废水蒸发浓缩的热源进行设计,此工艺的改进,既节省了废水浓缩所需的蒸汽,又节省了回收塔顶冷凝器所需的冷却水量,从而达到节能降耗的目的。该优化工艺既可以应用在己内酰胺新建装置的设计中,也可以在已建成的己内酰胺装置上进行改造,在己内酰胺行业具有很好的推广应用价值。     

己内酰胺联合装置能源优化利用探讨

己内酰胺联合装置是高能耗化工生产装置,能耗成本占比大,对装置运行过程中产生的部分热能损失进行回收利用,将其转化成电能,可降低装置能耗成本。介绍了余热发电技术,并参考该项技术在国内相似企业成功应用的案例,探讨了这项技术在己内酰胺联合装置能源优化中的应用。利用余热发电技术代替装置现有的循环水冷却及高压蒸汽降温减压等技术,安装螺杆膨胀发电机组利用蒸汽压差发电,采用有机朗肯循环膨胀发电机对装置蒸汽冷凝液及反应热回收发电,是行之有效的装置节能方法。     

SNIA甲苯法制备己内酰胺水溶液加氢工艺优化

从己内酰胺水溶液加氢反应机理出发,建立了一个加氢反应模型。通过加氢反应模型给出的加氢工序优化条件来指导生产。     

己内酰胺装置废气废液焚烧系统工艺流程设计

根据己内酰胺生产装置产生的废气废液特性,设计了一套废气废液焚烧系统,并进行了工业化试运行。DSM-HPO工艺生产己内酰胺产生的废气废液主要为羟胺反应器尾气、甲苯分离器不凝气和苯分离器不凝气、苯蒸馏塔残液等。设计的废气废液焚烧系统主要包括焚烧装置、废热锅炉、文丘里除尘器和烟囱。该焚烧系统焚烧废气废液,去除率高达99.99%,排放烟气指标达到GB 18484—2001《危险废物焚烧污染控制标准》要求,经过6个月的工业化运行,运行良好,具有节能环保、安全稳定、可靠高效等特点。     

己内酰胺装置重排反应热的回收利用

阐述了在己内酰胺装置工艺设计中,将重排反应释放出的热量用于装置内苯蒸馏及苯残液蒸馏系统的热源进行回收利用,重点对该回收利用方案设计作详细介绍。此工艺的改进,既节省了蒸馏系统所需的蒸汽,又节省了反应热移走所需的循环冷却水,从而达到节能降耗的目的。该优化工艺在己内酰胺行业具有很好的推广应用价值。     

己内酰胺的生产能力与市场分析

介绍了国内外己内酰胺的生产能力及供需情况。对国内存在的问题作了分析 ,并提出了相应的对策     

己内酰胺生产技术及进展

概述了世界己内酰胺工业化生产现状 ,详述了几种典型工艺的生产特点 ,并介绍了己内酰胺技术的最新进展     

己内酰胺生产中贝克曼转位工艺的改进

通过对己内酰胺生产中贝克曼转位反应机理的研究 ,改进了工艺流程中贝克曼转位反应系统 ,将原设计中的一步转位反应改造成为两步转位反应。改造后工艺数据稳定 ,产品质量提高 ,消耗降低 ,取得了显著的经济效益     

己内酰胺装置制硝酸工艺中NO_x气体冷却冷凝器腐蚀探讨

针对制硝工艺中NOx 气体冷却冷凝器腐蚀问题进行了原因分析探讨 ,并提出相应的改进措施 ,取得明显效果     

Effects of sodium and zinc neutralization on large deformation hysteresis of an ethylene methacrylic acid butyl acrylate copolymer

The mechanical hysteresis and recovery behaviors of an elastomeric ethylene methacrylic acid butyl acrylate (EMAABA) copolymer, its sodium-neutralized (EMAABA_Na) and zinc-neutralized (EMAABA_Zn) counterparts are evaluated and compared under large strain loading conditions. Experiments at different rates, under cyclic loading conditions and in relaxation indicate two major hysteresis mechanisms: a characteristic viscoelastic mechanism operative at all strains and a microstructural evolution/breakdown mechanism incurred during large strains. Loading-unloading cycles show large rate-dependent hysteresis loops with significant recovery of strain upon unloading, revealing a highly dissipative yet resilient behavior. The microstructure breakdown mechanism occurs during the initial strain excursion as revealed by subsequent loading cycles showing a significantly more compliant behavior and dramatically reduced hysteresis loops. The neutralized materials are found to be significantly stiffer, stronger and more dissipative compared to the neat material while still retaining the same level of recovery. Therefore the neutralization of this material provides an excellent means to tune stiffness and dissipation while retaining resilience, providing mechanical performance properties attractive for abrasion, impact and puncture resistant applications.     

Experimental simultaneous state and parameter identification of a pH neutralization process based on an extended Kalman Filter

The pH neutralization process is a representative nonlinear process. If a change in feed or buffer streams is introduced, the characteristics of the titration curve are altered and the way of change in titration curve is highly nonlinear. Moreover, if the changes are introduced in the middle of operation, then the nature of the process becomes nonlinear and time-varying. This is the one of the reason why conventional PID controller may fail. Even though the use of buffer solution may alleviate the nonlinearity, the improvement may be limited. A better way to tackle this type of process is to use nonlinear model-based control techniques with online parameter estimation. However, in most cases, the measurements of the process are not adequate enough so that the full state feedback control techniques can be utilized. If the states and crucial parameters are estimated online simultaneously, the effectiveness of the nonlinear state feedback control can be greatly enhanced. Thus, in this study, the capability of simultaneous estimation of states and parameters using Extended Kalman Filter (EKF) are experimentally investigated for a pH neutralization process. The process is modelled using reaction invariants and the concentrations of reaction invariants of the effluent stream (states) and the feed concentrations (parameters) are estimated online. From the comparison of experiments and simulations, it is found that the states and parameters can efficiently be identified simultaneously with EKF so that the estimated information can be exploited by state-feedback control techniques     

Control of pH neutralization process using simulation based dynamic programming

The pH neutralization process has long been taken as a representative benchmark problem of nonlinear chemical process control due to its nonlinearity and time-varying nature. For general nonlinear processes, it is difficult to control with a linear model-based control method so nonlinear controls must be considered. Among the numerous approaches suggested, the most rigorous approach is the dynamic optimization. However, as the size of the problem grows, the dynamic programming approach suffers from the curse of dimensionality. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach was proposed by Bertsekas and Tsitsiklis [1996]. The NDP approach is to utilize all the data collected to generate an approximation of optimal cost-to-go function which was used to find the optimal input movement in real time control. The approximation could be any type of function such as polynomials, neural networks, etc. In this study, an algorithm using NDP approach was applied to a pH neutralization process to investigate the feasibility of the NDP algorithm and to deepen the understanding of the basic characteristics of this algorithm. As the approximator, the neural network which requires training and the k-nearest neighbor method which requires querying instead of training are investigated. The approximator has to use data from the optimal control strategy. If the optimal control strategy is not readily available, a suboptimal control strategy can be used instead. However, the laborious Bellman iterations are necessary in this case. For pH neutralization process it is rather easy to devise an optimal control strategy. Thus, we used an optimal control strategy and did not perform the Bellman iteration. Also, the effects of constraints on control moves are studied. From the simulations, the NDP method outperforms the conventional PID control.     

N-甲基己内酰胺的无溶剂合成

以在无溶剂条件下合成的1-氮杂-2-甲氧基-1-环庚烯为原料,加入的硫酸二甲酯的物质的量为原料1-氮杂-2-甲氧基-1-环庚烯的物质的量的1/10,95℃反应6小时,生成N-甲基己内酰胺的收率为76.3%。     

丙烯制冷系统改造及优化操作

本文简单介绍了丙烯制冷原理及包头煤化工分公司丙烯制冷系统工艺流程,着重讨论了对丙烯制冷系统原设计的改造,开车及运行过程中出现的问题、注意事项及整改措施。经过不断地技术改造、操作优化和经验总结,取得了明显成效,在安全稳定运行的基础上,不但节约大量丙烯,而且还缩短了开车时间。丙烯平均月耗从优化前的24t减少到现在的1t,开车时间也从4h缩短至2h,为公司节约了生产成本,也为以后的安全稳定运行奠定良好基础。