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。     

改进鲸鱼优化算法及其在渣油加氢参数优化的应用

针对智能优化算法在处理非线性优化问题中存在的容易陷入局部最优和收敛精度差等问题,提出了一种基于结合差分进化和精英反向学习的改进鲸鱼算法（DEOBWOA）。该算法引入对立搜索初始化、精英反向学习,并结合差分进化进行变异修正,显著有效地提高WOA算法的收敛精度和收敛速度,提高其跳出局部最优的能力。之后采用8个标准测试函数进行仿真实验,结果表明：DEOBWOA算法与标准WOA、HCLPSO、DE算法相比,全局搜索能力和收敛速度都有较大提升。最后建立了渣油加氢动力学模型,考虑到渣油加氢过程中存在诸多典型的非线性约束问题,以某炼化厂渣油加氢装置为例,应用DEOBWOA对渣油加氢反应动力学模型参数进行优化,结果表明该算法能较好地处理实际工程优化问题。     

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。     

体育建筑观众席视觉质量评价体系研究与应用

针对现有视线评价参数和设计手段的局限性,提出更优的科学改进方案——Q值视觉质量评价体系,修正了业界沿用多年的视觉质量空间分布图解,揭示出场馆坐席视觉质量空间分布规律。通过引入人工智能启发式搜索工作流程,Q值工具可以智能化自主筛选、生成、快速锁定最优看台形式,极大地提升了当前体育建筑的设计效率。