Tributyl phosphate additive enhancing catalytic absorption of NO2 for simultaneous removal of SO2/NOx in wet desulfurization system

Removal of SO₂ and NO emissions from coal-fired power plants have always been the focus in coal's utilization industries for which traditional wet desulfurization system hold the potential to achieve simultaneous removal of SO₂/NO_x. In this work, a novel liquid catalyst (tributyl phosphate, TBP) was investigated for the simultaneous removal of SO₂ and NO_x in a NO pre-oxidation (ozone oxidation) assisted process. The absorption process and reaction mechanism of SO₂ and NO₂ were studied in a small-scale experimental system, and the removal efficiency of pollutant and the key parameters were examined in a pilot-scale system. The results show that the removal efficiency of NO₂ in traditional wet desulfurization system is only 20–40%; however greatly increases to >90% when TBP is added. Moreover, TBP can enhance the NO₂ removal performance in the presence of SO₂ due to the formation of TBP–NO₂–SO₃²⁻ complex. Considering the oily nature of TBP that can be easily separated, such addition strategy hold great potential for industrial SO₂/NO_x simultaneously removal.     

王坡煤矿煤层顶板稳定性主控因素分析

煤炭开采过程中极易发生顶板事故。基于王坡煤矿的地质条件，利用钻孔、井下钻探、物探、生产揭露资料，分别对该矿煤层顶板沉积特征、煤层顶板岩石结构特征进行系统分析研究，通过实验室室内测试，获取了煤层顶板岩石抗压强度、泊松比、坚固性系数、黏聚力等物理力学性质指标，最终确定了影响煤层顶板稳定性相关因素；运用层次分析法确定影响因素的权重值，得出岩石力学性质是影响煤层顶板稳定性的主控因素。研究可为类似煤矿顶板稳定性因素分析提供借鉴。     

Chemical process fault diagnosis based on enchanted machine‐learning approach

In the chemical industry, fault diagnosis is a challenging task due to the complexity of chemical equipment. This paper proposes a machine learning‐based approach to achieve the goal of fault diagnosis. First, in order to reduce the impact of redundant features, support vector machine recursive feature elimination (SVMRFE) is used to select important features. The trained probabilistic neural network (PNN) is then used for fault diagnosis. Considering that the diagnostic performance is affected by its hidden layer element smoothing factor (σ), the modified bat algorithm (MBA) is used to optimize the PNN to obtain optimal global parameter values. The MBA adopts a better optimization mechanism than the basic algorithm and achieves excellent global convergence. It can globally optimize the smoothing factor, which effectively improves the fault diagnosis ability of the PNN. During the testing of the Tennessee Eastman (TE) process data set, we evaluate the performance of the proposed model by comparing the F₁‐score and accuracy of the different methods. The charts provided describe the fault diagnostic results and classification for the different models. The results indicate that the MBA has a better optimization ability than other traditional optimization algorithms. At the same time, the combination method proposed in this paper is also superior to others and can significantly improve the accuracy of TE process fault diagnosis.     

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。     

电阻层析成像技术及其在水合物开采模拟实验中的应用

电阻层析成像是一种可视化的无损测量手段,可以为天然气水合物开采过程室内模拟实验提供有效的监测途径。首先介绍了电阻层析成像技术的工作原理、发展历程与应用现状,重点对电阻层析成像技术在天然气水合物室内模拟实验方面的主要应用进行了综述,并分析了存在的问题,在此基础上给出了解决问题的建议,为下一步开展水合物的电阻层析成像实验提供参考。     

超高强韧油井管合金设计与高强韧机制

 为了揭示1 000 MPa级低碳加铌钒钛微合金钢的高强韧机制,研究了S1(w(C)=0.09%)与S2(w(C)=0.17%)两种合金成分的油井管钢成分-工艺-组织-性能关系。试验表明,两种成分试验钢经水淬后的组织分别为板条贝氏体加少量马氏体和马氏体加少量贝氏体的复相组织。两种成分钢经过450~600 ℃、30 min的中温回火后,组织中均出现碳化物析出,且S1试验钢回火后的屈服强度基本不变,抗拉强度下降了约70 MPa,S2试验钢回火后的屈服强度与抗拉强度迅速升高170 MPa左右。溶度积公式的计算结果表明,两种钢的水淬组织中铌、钛元素析出彻底且析出物的体积分数都很小,因此回火铁素体基体中的VC析出强化对S1试验钢回火后屈服强度保持不变以及S2试验钢回火后屈服、抗拉强度提高起到重要作用。     

A hierarchical simple particle swarm optimization with mean dimensional information

To reduce the negative influence of the overemphasis of gbest the dimensional information of particle is introduced to be a new example. This additional information source is incorporated into simple PSO to establish a simpler position model. Another two simpler position updating models, cognition only model and social only model, based on the simple PSO algorithm are presented as well. Time hierarchy strategy is extended from probability hierarchy, both aiming to make full use of advantages of three models. Three models are used with time or probability hierarchy to update each particle’s position. Thus, two proposed algorithms THSPSO and PHSPSO are finally obtained. Experiments are conducted on fifteen benchmark functions. The results demonstrate the two proposed algorithms both have excellent performances for basic functions compared with other popular PSO variants. Probability hierarchy strategy is more effective than time hierarchy strategy in general.     

基于UG的采煤机防爆盖板三维标注及数控工艺研究

随着三维CAD技术的发展,产品制造信息在三维模型和二维图纸之间的反复传递,严重影响了产品制造信息的正确、快速传递。基于三维产品制造信息技术,以采煤机防爆盖板为例,在UG NX10.0中建立了防爆盖板的三维模型并进行了三维标注,设计了加工工艺路线,规划了数控加工刀具轨迹,进行了加工仿真,验证了数控加工的正确性,在此基础上完成了采煤机防爆盖板的三维工艺式设计。该研究对基于模型定义的数字化设计与制造研究,实现制造业信息化具有重要意义。     

A flexible air separation process: 1. Design and steady-state optimizations

The flexible operation of energy-intensive processes, such as cryogenic air separation, has economic potential due to increasing fluctuations of the electricity markets. Multiproduct air separation processes with high ratios of liquid product are very promising for flexible operation due to storable products. We present a process design with an integrated liquefication cycle and liquid assist operation, that facilitates a high liquid product ratio and a flexible process operation. We use a mechanistic dynamic process model in steady-state process optimizations covering the wide operational range of the proposed process. The optimization results show that the power demand can be varied in a range from 3.5 to 28 MW without violating operational constraints by changing the nitrogen and oxygen production rates. Thus, the proposed process is a promising air separation candidate for flexible operation with respect to fluctuating electricity markets.     

Simultaneous identification of structural stiffness and mass parameters based on Bare-bones Gaussian Tree Seeds Algorithm using time-domain data

This paper mainly illustrates the Tree Seeds Algorithm (TSA) to tackle structural damage identification problem. The damage model is simulated by the alterations of both stiffness and mass parameters. The objective function is introduced by minimizing the differences between the measured and calculated acceleration data. To enhance the performance of the standard TSA, two modifications including the bare-bones Gaussian updated mechanism and the withering process are introduced. The modified algorithm is named after the BGTSA. In the numerical simulation part, the BGTSA is firstly used to make comparisons with several state-of-the-art algorithms on the CEC05. Secondly, the BGTSA is utilized to deal with the structural damage identification problem by optimizing the acceleration-based nonlinear objective function. Numerical experiments involving a simply supported beam and a truss are carried out to verify the effectiveness of the proposed algorithm. The final results show that with low amount of acceleration data, the BGTSA can acquire better identification results compared with other evolutionary algorithms. Therefore the proposed algorithm could be viewed as a potential tool to solve the structural damage identification problem.