Couple-based particle swarm optimization for short-term hydrothermal scheduling

A novel couple-based particle swarm optimization (CPSO) is presented in this paper, and applied to solve the short-term hydrothermal scheduling (STHS) problem. In CPSO, three improvements are proposed compared to the canonical particle swarm optimization, aimed at overcoming the premature convergence problem. Dynamic particle couples, a unique sub-group structure in maintaining population diversity, is adopted as the population topology, in which every two particles compose a particle couple randomly in each iteration. Based on this topology, an intersectional learning strategy using the partner learning information of last iteration is employed in every particle couple, which can automatically reveal useful history information and reduce the overly rapid evolution speed. Meanwhile, the coefficients of each particle in a particle couple are set as distinct so that the particle movement patterns can be described and controlled more precisely. In order to demonstrate the effectiveness of our proposed CPSO, the algorithm is firstly tested with four multimodal benchmark functions, and then applied to solve an engineering multimodal problem known as STHS, in which two typical test systems with four different cases are tested, and the results are compared with those of other evolutionary methods published in the literature.     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

On global Hessenberg based methods for solving Sylvester matrix equations

In the first part of this paper, we investigate the use of Hessenberg-based methods for solving the Sylvester matrix equation $AX+XB=C$. To achieve this goal, the Sylvester form of the global generalized Hessenberg process is presented. Using this process, different methods based on a Petrov–Galerkin or on a minimal norm condition are derived. In the second part, we focus on the SGl-CMRH method which is based on the Sylvester form of the Hessenberg process with pivoting strategy combined with a minimal norm condition. In order to accelerate the SGl-CMRH method, a preconditioned framework of this method is also considered. It includes both fixed and flexible variants of the SGl-CMRH method. Moreover, the connection between the flexible preconditioned SGl-CMRH method and the fixed one is studied and some upper bounds for the residual norm are obtained. In particular, application of the obtained theoretical results is investigated for the special case of solving linear systems of equations with several right-hand sides. Finally, some numerical experiments are given in order to evaluate the effectiveness of the proposed methods.     

Decomposition process of bastnaesite concentrate in NaOH-CaO-H_2O system

A novel process of calcification-leaching for bastnaesite concentrate(REFCO_3) was proposed. The prior calcification was carried out in the system of NaOH-CaO-H_2O and the lgC-pH pattern for Ce-F-Ca-C-H_2O system was drawn. The thermodynamics result indicates that decomposition for bastnaesite requires certain alkaline condition, but excessive alkalinity also causes decomposition of CaF_2. XRD and SEM-EDS analyses on the calcification-leaching process reveal that bastnaesite first decomposes into RE(OH)_3 and CaF_2. Then, by HCl leaching rare earths were extracted,while CaF_2 was left in the leaching residue. In addition, effects of temperature, time, NaOH and CaO on the calcification were investigated. The results show that the leaching rate of rare earths(REs)reaches 72.5 wt%, at the same time 99.2 wt% of F is left in leaching residue with 20 wt% NaOH and 38 wt% CaO at 493 K for 180 min.     

高伸长率冷轧双相钢DP980显微组织及性能

摘要：为了进一步提高冷轧双相钢DP980的强塑性，采用低C-Si-Mn-Nb-Cr成分，通过调整连续退火工艺参数，系统研究了工艺组织性能的关系，利用OM、SEM、EBSD分析了不同退火温度条件下各相的比例、尺寸、形貌、分布，同时利用力学拉伸试验手段研究了连退两相区退火温度对强塑性的影响。结果表明，通过优化调整连续退火工艺，不仅可以在冷轧铁素体和马氏体双相钢的组织上获得少量的残余奥氏体，也能细化再结晶晶粒，最终获得ReL/Rm≤0.5、高伸长率A50≥15%的冷轧DP980，提高强塑性的同时改善了成型性能。     

微生物质水热碳锰复合材料对铀的吸附行为研究

以工业啤酒酵母为碳源，采用一步法合成了微生物质水热碳锰复合材料（MHTC），并利用XRD、FT-IR和SEM等对材料进行了表征。在此基础上，系统研究了不同C/Mn原子比、初始pH值、接触时间、初始铀浓度对MHTC吸附铀性能的影响。结果表明：C/Mn原子比为1∶10的碳锰复合材料（MHTC-10）对铀的吸附性能最优。在铀初始浓度为50 mg/L、初始pH=4.5条件下，12 h可达吸附平衡，最大吸附量为371 mg/g。吸附过程符合准二级动力学模型以及Freundlich等温模型。热力学数据表明，铀在MHTC-10上的吸附是一自发、放热的过程。该研究结果可为含铀环境中铀的分离富集提供新的思路。     

Purex流程铀钚分离工艺单元数学模型研究

在铀钚分离工艺单元单级数学模型和混合澄清槽瞬态数学模型的基础上，建立了以U(Ⅳ)-N₂H₄为还原反萃剂、混合澄清槽为萃取设备的Purex流程铀钚分离工艺单元数学模型，开发了计算机模拟程序，并使用台架实验数据对程序的可靠性进行了验证。结果表明，模拟程序的计算值和实验值符合良好。在此基础上，利用模拟软件对铀钚分离工艺单元的工艺参数进行了计算分析，结果表明：1BX₁加入位置、1BS和1BX₂酸度对钚反萃率无太大影响，但1BX₁加入位置和补萃级数对钚中去铀系数SF_U/Pu有一定影响。     

Fe-Si-B非晶带材高温氧化行为及回收工艺

??In order to reduce the oxidative burning loss of Fe78Si9B13 amorphous ribbon in the recovery process?? the oxidation behavior of Fe78Si9B13 amorphous ribbon was studied. The results show that the oxidation of Fe78Si9B13 amorphous ribbon at high temperature is related to the heating rate. The oxidation weight gain of Fe78Si9B13 amorphous ribbon at 5 and 10K/min from room temperature to 1223K are 44% and 31% respectively. There is an oxide layer with loose texture and a small amount of microcrack at the interface between the sample and atmosphere by SEM. The oxide layer contains a large amount of Fe2O3 and a little SiO2 by XRD. Oxidation kinetics curve shows that the oxidation weight gain of the samples follows a linear rule within 5hours at 1073 and 1173K?? then a parabolic rule. At 1273K?? however?? it only follows a linear rule?? meanwhile the oxidation speed is very fast?? with the oxidation weight gain reaches 40% in 12min. The oxidation weight gain in the amorphous ribbon recycling process can be reduced through cutting down the furnace gas temperature?? compressing the waste ribbon and unqualified products in the packaging process and blowing argon to reduce the partial pressure of oxygen in the furnace. Thus the slag decreases to 9-10g when 1kg waste ribbon is recovered?? and the Si content of liquid alloy increases to 8. 9%.