噪声控制材料的性能测试

阻塞、吸收、制止或隔离噪声达到噪声控制的目的。噪声障碍材料的降噪效果与材料的性能有关。本文提供一些常用降噪材料的阻塞和吸音的技术性能     

基于ELPI的南京城区大气可吸入颗粒物现状分析

采用电称低压冲击器(ELPI)对南京城区可吸入颗粒物粒径分布和质量浓度进行连续在线测量,得到了南京城区大气可吸入颗粒物的日变化特征,表明其呈现双峰、双谷分布,夜间高,白天低,上午高,下午低;结合气象参数,研究了大气可吸入颗粒物浓度变化与气象因子的相关性;此外,对可吸入颗粒物粒径分布特征也进行了研究,可以看出,南京地区可吸入颗粒物的主要成分是细颗粒(PM2.5),粒径在0.028～2.31μm的颗粒物占可吸入颗粒物的98%～99%。     

Trap mortality in mark-recapture studies

When animals die in traps in a mark-recapture study, straightforward likelihood inferences are possible in a class of models. The class includes M₀, M_t, and M_b as reported by White et al. (Los Alamos National Laboratory, LA-8787-NERP, pp 235, 1982), those that do not involve heterogeneity. We include three Markov chain “persistence” models and show that they provide good fits in a trapping study of deer mice in the Cascade-Siskiyou National Monument of Southern Oregon where trapping mortality was high.

Source term estimation of natural gas leakage in utility tunnel by combining CFD and Bayesian inference method

As an effective way to construct and maintain various life pipelines in urban areas and industrial parks, the underground utility tunnel has been developed rapidly in China in recent years. However, the natural gas pipeline leakage in a utility tunnel may cause fire, explosion or other coupling disastrous accidents that could result in fatal consequences. The effective source term estimation (STE) of natural gas leakage can provide technical supports for emergency response during natural gas leakage accidents in utility tunnels. In this paper, a STE model with the combination of gas transport model, Bayesian inference and slice sampling method is proposed to estimate the source parameters of natural gas leakage in underground utility tunnels. The observed data can be integrated into the gas transport model and realize the inversion of natural gas leakage location and release rates. The parameter sensitivity analysis is presented to evaluate the robustness of the proposed model with good practicability, and the gas sensor layouts in the utility tunnel are analyzed and optimized. The spatio-temporal distribution of the leaked gas could be well predicted based on the estimation source parameters by the proposed STE model. The results show that the proposed model is an alternative and effective tool to provide technical supports for loss prevention and mitigation for natural gas leakage accidents in urban utility tunnels.     

EFFICIENCY OF HYDROLOGIC DATA COLLECTION SYSTEMS ROLE OF TYPE I AND II ERRORS1

ABSTRACT The efficiency of hydrologic data collection systems is relevant to solution of environmental problems, scientific understanding of hydrologic processes, model-building and management of water resources. Because these goals may be overlapping and non-commensurate, design of data networks is not simple. Identified are four elements of error or risk in such networks: (a) choice of variables and mathematical model for the same process, (b) accuracy of model parameter estimates, (c) acceptance of wrong hypothesis or rejection of correct hypothesis and (d) economic losses associated with error. Of these four, the classical hypothesis testing problem is specifically evaluated in terms of costs of type I and II errors for simple and composite hypotheses; mathematical models for these economic analyses also include costs of sample data and costs of waiting while new data is obtained. An illustrative computational example focuses on the hypothesis that natural recharge might be augmented by a system of pumping wells along an ephemeral channel. The relationship of the hypothesis testing problem to Bayesian decision theory is discussed; it is felt that the latter theory offers a more comprehensive framework for design and use of hydrologic data networks.     

Anthropogenic threats to evolutionary heritage of angiosperms in the Netherlands through an increase in high-competition environments

Present biodiversity comprises the evolutionary heritage of Earth's epochs. Lineages from particular epochs are often found in particular habitats, but whether current habitat decline threatens the heritage from particular epochs is unknown. We hypothesized that within a given region, humans threaten specifically habitats that harbor lineages from a particular geological epoch. We expect so because humans threaten environments that dominated and lineages that diversified during these epochs. We devised a new approach to quantify, per habitat type, diversification of lineages from different epochs. For Netherlands, one of the floristically and ecologically best-studied regions, we quantified the decline of habitat types and species in the past century. We defined habitat types based on vegetation classification and used existing ranking of decline of vegetation classes and species. Currently, most declining habitat types and the group of red-listed species are characterized by increased diversification of lineages dating back to Paleogene, specifically to Paleocene-Eocene and Oligocene. Among vulnerable habitat types with large representation of lineages from these epochs were sublittoral and eulittoral zones of temperate seas and 2 types of nutrient-poor, open habitats. These losses of evolutionary heritage would go unnoticed with classical measures of evolutionary diversity. Loss of heritage from Paleocene-Eocene became unrelated to decline once low competition, shade tolerance, and low proportion of non-Apiaceae were accounted for, suggesting that these variables explain the loss of heritage from Paleocene-Eocene. Losses of heritage from Oligocene were partly explained by decline of habitat types occupied by weak competitors and shade-tolerant species. Our results suggest a so-far unappreciated human threat to evolutionary heritage: habitat decline threatens descendants from particular epochs. If the trends persist into the future uncontrolled, there may be no habitats within the region for many descendants of evolutionary ancient epochs, such as Paleogene.     

Using conditional inference forests to identify the factors affecting crash severity on arterial corridors

Introduction

The study aims at identifying traffic/highway design/driver-vehicle information significantly related with fatal/severe crashes on urban arterials for different crash types. Since the data used in this study are observational (i.e., collected outside the purview of a designed experiment), an information discovery approach is adopted for this study.

Method

Random Forests, which are ensembles of individual trees grown by CART (Classification and Regression Tree) algorithm, are applied in numerous applications for this purpose. Specifically, conditional inference forests have been implemented. In each tree of the conditional inference forest, splits are based on how good the association is. Chi-square test statistics are used to measure the association. Apart from identifying the variables that improve classification accuracy, the methodology also clearly identifies the variables that are neutral to accuracy, and also those that decrease it.

Results

The methodology is quite insightful in identifying the variables of interest in the database (e.g., alcohol/ drug use and higher posted speed limits contribute to severe crashes). Failure to use safety equipment by all passengers and presence of driver/passenger in the vulnerable age group (more than 55 years or less than 3 years) increased the severity of injuries given a crash had occurred. A new variable, ‘element’ has been used in this study, which assigns crashes to segments, intersections, or access points based on the information from site location, traffic control, and presence of signals.

Impact

The authors were able to identify roadway locations where severe crashes tend to occur. For example, segments and access points were found to be riskier for single vehicle crashes. Higher skid resistance and k-factor also contributed toward increased severity of injuries in crashes.     

污染模型中参数订正的集合Kalman滤波扩展状态变量法

污染模型中不确定参数的精确订正对于提高模型的精度有着重要的意义。在集合Kalman滤波（EnKF）同化方法的基础上,提出了对模型中不确定参数进行订正的EnKF扩展状态变量法,将不确定参数看成和模型状态变量一样的量,根据观测资料对不确定变量进行订正,以达到订正参数的目的。采用一个简化的空气质量方程,对模型参数订正方案进行检验,结果证明,提出的方案可行和有效。同时发现,随着观测资料精度的提高,无论是参数还是模型的状态变量,估计分析值的精度也得到相应的提高。     

火灾节流过程参数变化时序及其影响因素的研究

巷道火灾节流过程中各物理参数变化时序是正确模拟非稳态火灾过程和救灾决策的基础。通过实际规模的火灾试验,三维布点,自动采集数据。研究揭示:节流发生的时段为着火初期燃料挥发分的快速释放和燃烧的数分钟以内;此时,烟温小于330℃,升温速率为138℃/min,耗氧速率为3.4%/min,阻力的响应速率为8.5Pa/min;着火分支节流函数的最小值为0.83,其入口风速滞后下降速率为1.67×10-3m/s2;温度峰滞后于氧气浓度谷点、节流函数最小点和阻力峰的时间分别为1.6min,4.2min和5.6min,使用温度峰值计算最大阻力的传统方法是错误的。提出了描述节流度的定量方法,并导出了影响节流效应的因素为系统和风机特性参数、火灾发生的位置、比燃料消耗速率、火风压和热阻的方向及增长速率。     

燃煤电厂袋式除尘专家系统开发研究

开发了一种袋式除尘系统故障专家诊断方法,用于诊断整个袋式除尘系统的故障现象,通过现场数据采集、操作人员与专家系统的人机对话对故障现象进行分析、推理,并做出相应的解决方案指导操作人员排查故障.燃煤电厂袋式除尘专家系统以知识库、推理机为核心,实现整个袋式除尘系统的设备故障诊断功能和维修故障指导功能,辅以解释机构,人机界面来指导用户如何准确无误地操作运行本系统和袋式除尘控制系统.系统被划分为4个模块:专家系统简介模块,在线故障诊断模块,离线故障诊断模块和专家指导模块.