适应能源和环保双重标准的超超临界高参数燃烧技术

简要介绍我国首台百万千瓦超超临界锅炉的高参数以及低NOx燃烧过程。     

超超临界1000MW锅炉选型的几个关键要点

本文分析了超超临界发电技术的发展历程,着重分析了超超临界1000MW锅炉选型的关键要点。     

660MW超超临界汽轮机调试探析

在现代电厂发电中采用超超临界汽轮机,每度电大约可以节约5~7克煤,可以大幅度减少资源。所以,采用发电厂超超临界汽轮机意义重大。本文就660MW超超临界汽轮机在现场安装调试中应注意的问题及调试流程做简要介绍,使相关工作人员明确660MW超超临界汽轮机在安装调试过程中应注意的问题。     

给水加氧技术在超超临界锅炉中的应用

随着中国电力建设技术的发展,大多数新建机组都具有高容量的超超临界机组,这些机组具有高效的循环热传导,低产煤量,节能环保等高参数。基于水将在超临界压力下转变为单向流动的事实,所以锅炉的蒸汽系统只能协助直流运行的方式进行运转。但直流炉在整体的运行工作找那个缺乏废弃物的排放,所以影响到了进入锅炉的水的品质,而水的品质又直接的影响到了轮汽机蒸汽的品质好坏,进而对机组的安全运行起到关键性的直接影响,这关系到电厂的整体经济效益,所以给水加氧技术在超超临界锅炉中放入应用对机组乃至整个电厂都有极其重要的意义。     

超临界流体干燥法制备超微粉体技术的研究

超细微粒,特别是纳米级粒子的研制,在当前的高新技术中已成为一个热门领域,在材料、化工、轻工、冶金、电子、生物医学等领域得到广泛应用。超临界流体干燥技术制备超微粉体是一项新技术。现介绍了近年来开发的一些新方法和新工艺,诸如超临界溶液快速膨胀法,超临界流体抗溶剂法,超临界流体化学反应和超临界干燥法。重点介绍了超临界溶液快速膨胀法、超临界流体抗溶剂法的研究进展及其影响因素。     

关于火电基建财务内控问题的思考

火力发电是我国的主要发电方式之一。随着当代社会的发展,火电行业也在进行转型升级,关闭一系列 低效率、高污染的小型火电机组,新建高效率、高参数的超临界（SC）和超超临界（USC）火电机组,实现资源的优化配 置。在火力发电基本建设项目中,内部控制是提高财务管理工作效率,建立完善企业会计管理制度的重要工作环节, 对降低财务管...     

超超临界锅炉水冷壁壁温异常的原因分析

针对垂直管屏超超临界锅炉的结构特点,结合首台超超临界锅炉的调试,运行经验,分析了超超临界锅炉水冷壁壁温异常的原因,阐述了一些对于水冷壁壁温的影响因素.     

600MW超超临界机组锅炉防爆管技术的研究

从我国国情而言,发展超超临界火电机组有利于提高机组热效率,降低发电煤耗,并且减少二氧化碳和其他大气污染物的排放,因此是我国火电机组发展的必然趋势。本文笔者在阐述600MW超超临界机组锅炉爆管原因的基础上,针对性提出了预防措施,以期确保机组的安全和稳定运行。     

1000MW超超临界汽轮机润滑油系统的特点

在科技发展的带动下，百万等级的超超临界汽轮机已经得到了广泛的应用，其润滑油系统的设计和安装工作对于保证系统性能的充分发挥十分重要。文章以上海汽轮机厂生产的1000MW超超临界汽轮机为例，分析了汽轮机润滑油系统的设计特点以及相应的设备性能，为汽轮机的生产和使用提供相应的参考。     

我国启动700℃超超临界发电技术研发计划

国家能源局6月24日在京组织电力研究机构、发电集团、电工设备制造企业等，召开国家700℃超超临界燃煤发电技术创新联盟第一次理事会和技术委员会会议，此举意味着酝酿已久的700℃超超临界燃煤发电技术研发计划正式启动。     

用“几何画板”软件探讨含参数的函数在区间上的最值

利用"几何画板"软件绘制含参数的函数在区间上的图象,并用参数控制图象,探讨函数的最值。     

基于模型分析的液压伺服系统性能参数预测

为了提高液压伺服系统的控制精度,文章对液压伺服系统中的一些非线性参数进行了预测与估计。参数估计之前,首先对目标液压工作系统进行了建模与参数化描述,抽取了其控制和工作模型,计算并推导了模型中主要的液压参数直接的数学关系,如液压受力分析、受力传递函数、噪声信号过滤函数等。在此基础上,采用最小二乘估计算法对液压伺服系统中的非线性参数进行预测,给出了详细的参数分析过程和预测参数推导过程,建立了主要参数的估计计算公式。最后,对所估计的非线性参数进行了仿真和测试。结果表明,文章所选择的参数预测结果与实际的运行结果基本吻合,预测算法参数估计误差小。     

识别概念的参数关系说质疑

经济计量学联立方程模型识别概念的参数关系说有两种形式的表述。本文利用线性方程组的求解理论，揭示了参数关系说识别概念的内涵。对于其表述1，我们指出了它叙述的不够准确与不够直观，并在文中给出了相应的建议；对于其表述2，则通过反例证明了它概念上的内在矛盾性。     

Have Standard VARS Remained Stable Since the Crisis?

Small vector autoregressions are commonly used in macroeconomics for forecasting and evaluating shock transmission. This requires VAR parameters to be stable over the evaluation and forecast sample or modeled as time‐varying. Prior work has considered whether there were sizable parameter changes in the early 1980s and in the subsequent period until the beginning of the new century. This paper conducts a similar analysis focused on the period since the recent crisis. Using a range of techniques, we provide substantial evidence against parameter stability. The evolution of the unemployment rate seems particularly different relative to its past behavior. We also evaluate alternative methods to handle parameter instability in a forecasting context. Copyright © 2016 John Wiley & Sons, Ltd.     

基桩声波透射法检测各判据精度探讨

声速、声时、声幅、主频这四个声测参数是判断桩基完整性的主要依据。而在实际桩检中,各参数都不能达到足够的精度评判出桩身质量的好坏,必须经过综合比较加以确定,仅评某一参数的异常来作出判定容易得出相左的结论。并且PSD、声速参数可以归为同一参数。     

The effect of parameter uncertainty on forecast variances and confidence intervals for unit root and trend stationary time-series models

In this paper I describe the effect of parameter uncertainty on the way conditional forecast variances grow as the forecast horizon increases. Without parameter uncertainty, forecast variances for the unit root model grow linearly with the forecast horizon while with the trend stationary model they are bounded. With parameter uncertainty, however, I find that for both the unit root and the trend stationary models, forecast variances grow with the square of the forecast horizon so that uncertainty grows at a much faster rate than without parameter uncertainty.     

An extension of the damage model

The damage model was introduced byRao [1963] and is based on the assumption that an original observation is subjected to a destructive process. Rao, examined in detail the case where the distribution of the original observation and the destructive process were Poisson and Binomial respectively with fixed parameters.In this paper we extend the damage model to the case where either the parameter of the Poisson or the parameter of the Binomial is a random variable with a given distribution function (d.f.).     

Anomalies in the Foundations of Ridge Regression: Some Clarifications

Several anomalies in the foundations of ridge regression from the perspective of constrained least-square (LS) problems were pointed out in Jensen & Ramirez. Some of these so-called anomalies, attributed to the non-monotonic behaviour of the norm of unconstrained ridge estimators and the consequent lack of sufficiency of Lagrange's principle, are shown to be incorrect. It is noted in this paper that, for a fixed Y , norms of unconstrained ridge estimators corresponding to the given basis are indeed strictly monotone. Furthermore, the conditions for sufficiency of Lagrange's principle are valid for a suitable range of the constraint parameter. The discrepancy arose in the context of one data set due to confusion between estimates of the parameter vector, β , corresponding to different parametrization (choice of bases) and/or constraint norms. In order to avoid such confusion, it is suggested that the parameter β corresponding to each basis be labelled appropriately.     

Experimental evidence of bank runs as pure coordination failures

We investigate how coordination requirement, measured by the coordination parameter, affects the occurrence of miscoordination-based bank runs in controlled laboratory environments. We identify an indeterminacy region of the coordination parameter such that games with the parameter within the region have varying coordination outcomes and exhibit persistent path dependence. Experimental economies with the parameter above (below) the region stay close or converge to the run (non-run) equilibrium. Switches between the two equilibria occur even with fixed economic fundamentals. The experimental results are well accounted for by a version of the evolutionary algorithm that uses experimentation rates estimated from the experimental data.     

Parameter estimation and bias correction for diffusion processes

This paper considers parameter estimation for continuous-time diffusion processes which are commonly used to model dynamics of financial securities including interest rates. To understand why the drift parameters are more difficult to estimate than the diffusion parameter, as observed in previous studies, we first develop expansions for the bias and variance of parameter estimators for two of the most employed interest rate processes, Vasicek and CIR processes. Then, we study the first order approximate maximum likelihood estimator for linear drift processes. A parametric bootstrap procedure is proposed to correct bias for general diffusion processes with a theoretical justification. Simulation studies confirm the theoretical findings and show that the bootstrap proposal can effectively reduce both the bias and the mean square error of parameter estimates, for both univariate and multivariate processes. The advantages of using more accurate parameter estimators when calculating various option prices in finance are demonstrated by an empirical study.