碳二加氢等温反应过程模拟与操作参数优化

以碳二加氢等温管式固定床反应器为研究对象, 利用计算流体力学(CFD)方法建立了与外界有热量交换的二维均相流反应器模型, 通过添加气固能量方程, 建立了多孔介质区内部热交换与气固耦合传热的两温度模型。采用遗传算法对反应的动力学参数进行了拟合, 并以加氢选择性最优为目标函数, 对碳二加氢反应的入口氢炔比与反应器的冷却温度进行优化, 得到最优氢炔比为1.18, 最优的冷却温度为334.66 K。最后根据模拟与优化结果, 分析了氢炔比和冷却温度对加氢反应选择性的影响, 对提高加氢反应器的操作性能具有重要的意义。     

带有精英保留机制的混合差分化学反应算法

传统智能算法在求解复杂的带有多峰特点的优化问题时, 由于其计算量和变异方式的限制很容易陷入局部最优, 并且不具备跳出局部最优进行二次搜索等能力。针对这一问题, 本文提出了混合差分的化学反应算法, 在利用化学反应算法(CRO)良好的全局搜索能力的同时, 使用差分变异策略来加强算法的计算精度。对于优秀分子可能在反应中被消耗掉的现象, 有针对性地加入了精英保留机制来保持种群的优良。本文选取了CEC2005中的测试函数, 特别是几个带有多峰特点的复杂测试函数来分析改进算法的各项性能, 并与几个改进的智能算法进行了对比实验。最终验证改进算法在提高计算精度和全局搜索能力两方面具有良好的效果。     

离子源对磁控溅射制备TiNC膜基结合力的影响

由于膜基附着力不好,膜层脱落问题是工业生产中磁控溅射镀制黑膜最常见的问题.本实验采用 阳极线性离子源和霍尔点源辅助磁控溅射复合技术制备了TiNC薄膜,探讨解决TiNC膜基附着力不好的问题.初步实验结果表明,离子束辅助沉积对于改善膜基附着力的作用并不明显,本文还比较了脉冲偏压清洗对膜基附着力的影响,探讨了其可能影响因素.     

一种改进的混合遗传算法及在化工过程动态优化中的应用(英文)

The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature. Genetic algorithm (GA) has been proved to be a feasible method when the gradient is difficult to calculate. Its advantage is that the control profiles at all time stages are optimized simultaneously, but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum. In this study, a hybrid improved genetic algorithm (HIGA) for solving dynamic optimization problems is proposed to overcome these defects. Simplex method (SM) is used to perform the local search in the neighborhood of the optimal solution. By using SM, the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved. The hybrid algorithm presents some improvements, such as protecting the best individual, accepting immigrations, as well as employing adaptive crossover and Gaussian mutation operators. The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems. At last, HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable.     

基于Aspen Plus的气流床煤气化炉三段平衡模型(英文)

A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiers based on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification temperature. The model is divided into three stages including pyrolysis and combustion stage, char gas reaction stage, and gas phase reaction stage. Part of the water produced in the pyrolysis and combustion stage is assumed to be involved in the second stage to react with the unburned carbon. Carbon conversion is then estimated in the second stage by steam participation ratio expressed as a function of temperature. And the gas product compositions are calculated from gas phase reactions in the third stage. The simulation results are consistent with published experimental data.     

A Hybrid Algorithm Based on Differential Evolution and Group Search Optimization and Its Application on Ethylene Cracking Furnace

To find the optimal operational condition when the properties of feedstock changes in the cracking furnace online, a hybrid algorithm named differential evolution group search optimization (DEGSO) is proposed, which is based on the differential evolution (DE) and the group search optimization (GSO). The DEGSO combines the advantages of the two algorithms: the high computing speed of DE and the good performance of the GSO for preventing the best particle from converging to local optimum. A cooperative method is also proposed for switching between these two algorithms. If the fitness value of one algorithm keeps invariant in several generations and less than the preset threshold, it is considered to fall into the local optimization and the other algorithm is chosen. Experiments on benchmark functions show that the hybrid algorithm outperforms GSO in accuracy, global searching ability and efficiency. The optimization of ethylene and propylene yields is illustrated as a case by DEGSO. After optimization, the yield of ethylene and propylene is increased remarkably, which provides the proper operational condition of the ethylene cracking furnace.     

Modeling and Optimization of the Steam Turbine Network of an Ethylene Plant

In this paper, we developed a hybrid model for the steam turbines of a utility system, which combines an improved neural network model with the thermodynamic model. Then, a nonlinear programming (NLP) model of the steam turbine network is formulated by utilizing the developed steam turbine models to minimize the total steam cost for the whole steam turbine network. Finally, this model is applied to optimize the steam turbine network of an ethylene plant. The obtained results demonstrate that this hybrid model can accurately estimate and evaluate the performance of steam turbines, and the significant cost savings can be made by optimizing the steam turbine network operation at no capital cost.     

基于模糊核聚类的乙烯裂解深度DE-LSSVM多模型建模

乙烯裂解深度的建模与控制对于裂解炉的实时优化具有重要意义。针对石脑油原料组分复杂、油品特性波动大等状况,采用模糊核聚类对石脑油数据库进行最优划分,建立最小二乘支持向量机的多模型,对于最小二乘支持向量机中模型的参数选取,利用差分进化算法进行参数寻优,提高了模型的精度和泛化能力。通过对现场数据的建模实验,结果表明：基于模糊核聚类的乙烯裂解深度最小二乘支持向量机多模型跟踪性能良好,预测精度较高。     

一种基于多模型切换的阶梯式广义预测控制算法

针对一类模型参数突变的系统,提出一种基于多模型切换的阶梯式广义预测控制算法。采用多个固定模型、一个常规自适应模型和一个可重新赋初值的自适应模型并行辨识系统的动态特性。多个固定模型可以提高系统的暂态性能,常规自适应模型可以保证系统的稳定性,可重新赋初值的自适应模型可以进一步提高系统的暂态性能。在每个采样时刻基于性能指标切换到最优的局部模型作为当前模型,设计阶梯式广义预测控制器,从而实现系统全局的控制。最后的仿真结果表明,其控制效果明显优于单一模型的控制器。     

地质勘探套管钻进技术专用套管的研制及应用

地质勘探套管钻进技术中的专用套管是实现套管钻进的关键因素之一。本文介绍了在地质勘探套管钻进过程中,专用套管作为绳索取心钻杆,传递钻压和扭矩,钻进结束后,作为技术套管留在孔内,恢复护壁套管功能。通过室内试验完成专用套管结构、材料及加工工艺等的选型和研制,且经过实际野外应用效果良好。