准二级压缩空气源热泵系统的变工况试验研究

介绍了准二级涡旋压缩机空气源热泵系统,对研制出的具有蒸汽喷射的涡旋压缩机空气源热泵系统样机进行了大范围变工况试验研究,获得机组在各工况下的输入功率、制热量、COP、排气温度的变化。通过变工况实验,综合考虑制热量、COP和机组工作稳定性,得出准二级压缩热泵系统最佳中间补气压力为1200kPa~1400kPa。研究结果可为准二级压缩系统设计与应用提供参考。     

三效吸收式制冷循环系统性能分析

对12个通用的三效循环系统以及这12个通用循环系统组成的76种可能的密闭循环系统进行了评测。根据通用三效循环系统的压力和溶解度要求,对通用三效循环系统进行了分析,并充分考虑各部件设计中的问题和COPs数值,以及处于高腐蚀环境中部件的数目。通过分析,确定了四个性价比较优的系统:Alkitrate Topping循环系统,Pressure Staged Envelope循环系统,High Overlap循环系统和Dual Loop循环系统。     

不同环境温度下工艺参数对扩散吸收式制冷机的性能影响

外界环境温度对扩散吸收制冷循环有重要影响,以四台相同结构的扩散吸收式制冷机为基础,用实验的手段研究了不同环境温度下,氨水溶液灌装浓度、充注压力、输入功率等工艺参数对扩散吸收式制冷机性能的影响。得出了实验样机在各工况下的最优工艺参数;研究发现随环境温度的升高,样机的最佳灌装浓度下降,而最佳输入功率和最适宜充注压力升高。可为扩散吸收式制冷机根据环境温度选择各工艺参数提供一定的依据。     

高效液相色谱法同时测定化妆品中9种激素

建立了化妆品中9种激素的HPLC测定方法。样品经甲醇超声提取后,经ZORBAXExtend-C18柱分离,以甲醇-水(pH=8.0,0.02mol/L磷酸盐缓冲体系)为流动相,采用紫外检测器检测。9种激素分离良好并排除了样品中杂质峰的干扰,各激素在1—100mg/L范围内呈良好线性关系(r0.999),平均回收率在93.3%—107.2%之间,相对标准偏差为0.79%—2.07%(n=7),检出限为0.05—0.2mg/L。该方法可简便、快捷、准确的同时测定化妆品中9种激素。     

关于光学实验中望远镜与光杠杆的调节探讨

在关于望远镜的光杠杆调节中通常只给出了对光杠杆及望远镜的上下位置的调节,而忽视了望远镜和光杠杆的左右调节。给出了望远镜和光杠杆的调节中左右位置的调节原理和调节操作方法,从而使望远镜和光杠杆的调节更具有目的性,使实验进行的更加快速和准确。     

测量光栅波长中分光计调节过程几个常见问题的解决方法

本文对分光计测量光栅波长的调节过程,包括查找平面镜反射的十字像,调节平行光管主轴和望远镜主轴重合且垂直于仪器主轴,以及判别光栅位于玻璃哪一面几个常见问题,给出了简单解决方法。     

地基多孔径成像系统验证实验设计

基于工程实践中高分辨率目标成像技术的需求,讨论了光学合成孔径成像技术的成像原理以及在提高成像分辨率方面的优越性,阐述了国内外在相关领域取得的科研成果及存在的技术难点。在现有加工工艺及装调检测条件下,设计了基于两个子望远镜的合成孔径成像实验。以斐索型多孔径望远镜为研究对象,从几何光学理论出发,讨论了地基斐索型合成孔径成像系统实验的可行性。分析实验中关键组件的调整精度,提出了合成孔径成像系统精确成像的方案。实验中设计了分辨率±0.03mm的微调机构来保证系统获得清晰的像,并使用分辨率达到0.05μm的压电直线精密驱动器来保证两束光相位同步。分析结果表明,本文设计的地基多孔径成像系统实验切实可行,可得到合成孔径成像系统分辨率的确切值,为进一步研究合成孔径成像系统奠定了基础。     

基于公众偏好大数据分析的重大突发事件应急决策方案动态调整方法

针对在重大突发事件应急过程中如何根据与其相关的公众偏好大数据信息来对事件进行划分以及确定事件风险大小等问题,提出了一种基于公众偏好大数据分析的两阶段聚类算法,将事件现场公众在社交媒体上发布的偏好大数据信息进行聚类分析,识别出多个与事件相关的子事件,并得出每个子事件的客观风险级别。然后,结合专家经验判断,综合得出每个子事件的风险级别,进而选择相对应的方案。在此基础上,根据实际突发事件多阶段演变特点,描述了应急决策中多事件多方案的动态调整过程,考虑方案之间的相关性和不同子事件调整方案对各风险级别子事件的应急处置效果、应对损失以及不同方案之间的转化成本等因素,得出不同情境下的最佳调整方案。通过案例分析说明了该方法的可行性和有效性。     

Numerical investigation of finite-source multiserver systems with different vacation policies

Systems with vacations are usually modeled and analyzed by queueing theory, and almost all works assume that the customer source is infinite and the arrival process is Poisson. This paper aims to present an approach for modeling and analyzing finite-source multiserver systems with single and multiple vacations of servers or all stations, using the Generalized Stochastic Petri nets model. We show how this high level formalism, allows a simple construction of detailed and compact models for such systems and to obtain easily the underlying Markov chains. However, for real vacation systems, the models may have a huge state space. To overcome this problem, we give the algorithms for automatically computing the infinitesimal generator, for the different vacation policies. In addition, we develop the formulas of the main exact stationary performance indices. Through numerical examples, we discuss the effect of server number, vacation rate and vacation policy on the system’s performances.     

Performance appraisal based on distance function methods

Performance appraisal is a process used by some firms to evaluate their employees’ efficiency and productivity in order to plan their promotion policy, salary policy, layoffs policy, etc. Initially this process was just carried out by the executive staff, but recently it has evolved into an evaluation process based on the opinion of different reviewers, supervisors, collaborators, customers and the employees themselves (360-degree method). In such an evaluation process the reviewers evaluate some indicators related to employees performance appraisal. In this paper we propose an evaluation framework where there are different sets of reviewers taking part in the evaluation process. Since reviewers have a different knowledge about the evaluated employee, it seems suitable to offer a flexible framework in which different reviewers can express their assessments in different finite scales according to their knowledge. The final aim is to compute a global evaluation for each employee, that can be used by the management team to make their decisions regarding their human resources policy. In this way, to obtain a global evaluation for each employee, we propose a methodology able to aggregate individual valuation in a metric L_p framework. In this context, the associated optimization problems can be reduced to an Extended Goal Programming formulation that is very easy to compute.