压力容器声发射信号参数分析方法的探讨

参数分析是声发射技术应用中的重要环节之一,因为它直接关系到能否正确反映被检对象的物理状况。本文集多年检测的经验,提出了参数分析的几种方法以及参数分析中须注意的问题,力求通过参数分析方法来客观、合理地表征检测对象的物理状况。     

Do statistical inferences allowing three alternative decisions give better feedback for environmentally precautionary decision-making?

Environmental policies and guidelines often specify standards for environmental indicators. The first part of this paper argues that, where compliance with these standards is assessed with the help of statistical inference, an inference employing a three-alternatives decision rule can provide more sensible feedback to environmental managers for precautionary decision-making. The second part of the paper shows how a three-alternatives statistical inference about compliance with a percentile standard might be applied to a small number of observations using a non-parametric binomial interval. This interval expression of uncertainty results in the sample size requirements for various percentile ranks becoming explicit.     

Towards automatic and robust adjustment of human behavioral parameters in a pedestrian stream model to measured data

People die or get injured at mass events when the crowd gets out of control. Urbanization and the increasing popularity of mass events, from soccer games to religious celebrations, enforce this trend. Thus, there is a strong need to better control crowd behavior. Here, simulation of pedestrian streams can be very helpful: Simulations allow a user to run through a number of scenarios in a critical situation and thereby to investigate adequate measures to improve security. In order to make realistic, reliable predictions, a model must be able to reproduce the data known from experiments quantitatively. Therefore, automatic and fast calibration methods are needed that can easily adapt model parameters to different scenarios. Also, the model must be robust. Small changes or measurement errors in the crucial input parameters must not lead to disproportionally large changes in the simulation outcome and thus potentially useless results. In this paper we present two methods to automatically calibrate pedestrian simulations to the socio-cultural parameters captured through measured fundamental diagrams. We then introduce a concept of robustness to compare the two methods. In particular, we propose a quantitative estimation of parameter quality and a method of parameter selection based on a criterion for robustness. We discuss the results of our test scenarios and, based on our experience, propose further steps.     

泥石流灾害的动力成因初探

本文从动力学成因角度分析泥石流灾害的形成机理，提出了泥石流起动的动力学临界条件通式和用实测资料分析确定泥石流起动临界判别式的方法。     

A fuzzy expert system for soil characterization

As soil is a natural resource not always renewable, the risk characterization of contaminated soils is an issue of great interest. Artificial Intelligence (AI), based on Decision Support Systems (DSSs), has been developed for a wide range of applications in contaminated soil management. Decision trees have already shown to be easy to interpret and able to treat large scale applications. Fuzzy logic gives an improvement in the perturbations and the variance of the training data, due to the elasticity of fuzzy set formalism. In this study, we have developed a classificatory tool applied to characterize contaminated soil in function of human and environmental risks. Knowledge engineering for constructing the Soil Risk Characterization Decision Support System (SRC-DSS) involves three stages: knowledge acquisition, conceptual design and system implementation. A total of 26 parameters were divided into three groups to facilitate the configuration of the expert system: source attributes, transfer vector attributes, and local properties. Sixteen case studies were evaluated with the SRC-DSS. In comparison with other techniques, the results of the current study have shown that SRC-DDS is an excellent tool to classify and characterize soils according to the associated risk.     

Bayesian entropy for spatial sampling design of environmental data

We develop a spatial statistical methodology to design national air pollution monitoring networks with good predictive capabilities while minimizing the cost of monitoring. The underlying complexity of atmospheric processes and the urgent need to give credible assessments of environmental risk create problems requiring new statistical methodologies to meet these challenges. In this work, we present a new method of ranking various subnetworks taking both the environmental cost and the statistical information into account. A Bayesian algorithm is introduced to obtain an optimal subnetwork using an entropy framework. The final network and accuracy of the spatial predictions is heavily dependent on the underlying model of spatial correlation. Usually the simplifying assumption of stationarity, in the sense that the spatial dependency structure does not change location, is made for spatial prediction. However, it is not uncommon to find spatial data that show strong signs of nonstationary behavior. We build upon an existing approach that creates a nonstationary covariance by a mixture of a family of stationary processes, and we propose a Bayesian method of estimating the associated parameters using the technique of Reversible Jump Markov Chain Monte Carlo. We apply these methods for spatial prediction and network design to ambient ozone data from a monitoring network in the eastern US.     

矩形喷嘴PM2.5惯性冲击采样器的研制

惯性冲击器是最重要的颗粒物采样器之一,被广泛用于大气颗粒物的分级采样。设计了一种中流量的矩形喷嘴PM2.5惯性冲击采样器。根据Marple准则设计了冲击器的结构参数,用CFX软件进行了惯性冲击器内部气固两相流场的CFD模拟,得出了惯性冲击器的最优结构参数。根据得出的最优设计参数,进行了PM2.5惯性冲击器样机的结构设计,并在实验室用APS气溶胶空气动力学粒度仪进行了标定。实验标定和CFD数值模拟的结果基本吻合,当采样流量为100L/min,冲击器的切割粒径dp50=2.55μm,切割锐度σg=1.4,满足设计要求。     

新钢烧结机尾电除尘器的扩容改造

介绍了烧结机尾电除尘改造技术参数的确定方法,改造后各项参数得到提高。     

马斯京根模型参数估计的新方法

提出了马斯京投模型参数估计的一种新方法—加速遗传算法,分析了该算法控制参数的优化特性,总结出了这些参数的简便设置技术．应用实例表明,该方法简便、直观、通用、适应性强,它可广泛应用于各种自然灾害模型的优化问题之中。     

HSY算法在水质模型参数识别中的应用探讨

参数识别是水质模拟中的技术核心，数据稀缺是水质模型经常面临的问题。采用HSY算法可求得模型参数的分布，而不再是一个单一的最优参数，从而在一定程度上避免了由于“最优”参数失真带来的决策风险，本文以南水北调一期工为例，讨论了在稀疏数据条件下如何应用HSY算法识别CSTR水质模型的参数，并对识别的模型参数进行了检验。模型检验采取了2种方法：分别用动态和稳态计算方法得出的参数进行比较；用模拟结果分布于实测值进行比较。结果表明，HSY算法为稀疏数据条件下进行识别、建立数学模型提供了一条有效的途径。