不同类型压力对飞行员安全绩效的影响规律研究

为探究各类型压力对飞行员安全绩效的影响规律,为飞行员日常工作管理提供依据,选取某航空公司200名飞行员进行压力测试,并调取其近6 a的飞机品质(QAR)数据,通过相关性分析和线性回归分析将飞行员压力数据与其QAR数据进行对比分析,探究飞行员压力对飞行安全绩效的影响规律。研究结果表明:工作负荷压力、家庭压力、人际关系压力和组织管理压力会显著负向影响飞行员安全绩效;角色压力和专业发展压力会显著正向影响飞行员安全绩效。     

不同火灾规模下隧道水幕线性喷水强度的研究

为了探究火源功率和水幕线性喷水强度对烟气特征参数和水幕阻烟隔热能力的影响,以全尺寸隧道为研究对象,采用FDS数值模拟方法,还原验证了前人使用的小尺寸模型,研究了20组工况下烟气特征参数变化的规律。研究结果表明:根据相似性原理还原后的全尺寸模型在相同工况下的模拟结果与小尺寸实验基本一致;水幕系统降低遮光率的效果随线性喷水强度增加而增强,当线性喷水强度增至一定程度时,遮光率和隔热效率无明显变化;对于中、大型规模火灾,水幕有效作用时间出现减少的情况;火源功率为5,20,30 MW的小、中、大规模的隧道火灾,综合考虑经济性和水幕效果,建议分别选择水幕的线性喷水强度为8,14,16 L/(s瘙
簚m)。     

油漆挥发分爆炸特性及浓度检测装置设计研究

为了实现对喷涂车间内挥发分浓度的检测,进行20 L球形爆炸特性测试实验,分析了油漆挥发分主成分及爆炸特性,根据油漆挥发分受热易挥发遇冷易凝结的物理特性、采样器采样原理、滤膜增重法测量原理以及基于单机片C++软件程序编写的电路智能控制技术,设计1种喷涂车间挥发分浓度检测装置。研究结果表明:油漆挥发分主成分具有爆炸性,且随着油漆颗粒物浓度增大,爆炸压力也增加。设计的装置对挥发分的采集率都在90%以上,总采集率为93.1%~98.9%,装置能够较为准确地检测挥发分浓度。     

H∞ loop-shaping controller design for a grid-connected single-phase photovoltaic system

This paper presents a H_∞ loop-shaping controller for controlling dc-link voltage by regulating the switching signal of the inverter associated with a grid-connected single-phase photovoltaic system. To facilitate a robust control design, state-space realisation of the system model is made with uncertainties represented by linear fractional transformation. The controller is achieved through H_∞ synthesis followed by obtaining desired loop shapes through the choice of the proper weighting functions. The controller order is reduced by Henkel-norm method for facilitating its practical implementation. Controller performance is evaluated through carrying out simulations on MATLAB/Simulink platform under standard and changing atmospheric conditions, and fault condition.     

以聚己内酯作为生物反硝化固体碳源的研究

为解决水体因低碳氮比而导致脱氮效率差的问题,将颗粒聚己内酯(PCL)重新塑形为阶梯环状,研究其作为反硝化过程的生物膜载体与固相碳源的反硝化性能。结果表明,在静态实验中,平均反硝化速率为8.57 mg NO3-N/(L·h);反硝化过程为零级反应。连续填充床实验中,超过90%的硝酸盐可被去除,出水NO2-N质量浓度低于0.20 mg/L;出水NH3-N质量浓度略有上升;出水溶解性有机碳(DOC)先上升后降低至1 mg/L左右。电子扫描显微镜扫描显示,PCL阶梯环反应表面空隙率较高,表面生物膜以杆菌为主,反应后被明显腐蚀;液相色谱检测显示PCL阶梯环分子量反应前后略有下降,其结构未受到破坏;表明该材料适合作为反硝化反应的碳源的同时,又可以作为载体供微生物附着生长。     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

秦皇岛地热能梯级利用状况与前景分析

在对秦皇岛地热能资源现状和开发利用调查的基础上,对秦皇岛地区的地热资源分布特征进行了分类,通过对相应的地热资源利用现状进行调查,掌握了地热能利用的现状以及存在的种种问题和不足。为了更加合理高效地利用地热能资源,进行开发利用前景分析,制定了地热能综合梯级利用的规划建议。     

阶式生物接触氧化对富营养化太湖水源水中溶解有机物的去除性能研究

构建阶式生物接触氧化反应器处理富营养化太湖水源水,对其净水效能进行研究。结果表明,在优化工况条件下,阶式生物氧化反应器的三阶对太湖水源水中DOC的累积去除率分别为34．4％、40．2％和47．5％,对BDOC的总去除率为68．4％,除生物降解外,填料拦截、生物吸附絮凝等物理、化学作用对去除原水中的DOC仍有重要作用。DOC分子量分级表明,太湖源水中含量最大的是分子量〈500Da的DOC,含量最小的是分子量在5k～500Da间的DOC。阶式生物接触氧化反应器对分子量〈500 Da的DOC的去除率在60％以上,而出水中5k～500 Da区间的DOC含量相比原水增加近1倍。     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.     

Theoretical and Empirical Analysis on Influence Factors of Modern Agricultural Equipment Level in the Processof Agricultural Sustainable Development

To promote modern agricultural equipment level is one characteristic of constructing and developing modern agriculture in China.This paper makes up stepwise linear regression analysis model of influence factors of modern agricultural equipment level,and chooses rural labor,per capita income of rural residents,rural investment,proportion of people at secondary education level and at higher level in per hundred rural labor force and arable land area as independent variables,and total power of machine as induced variable.The major results show that the relativity of modern agricultural equipment level,rural investment and education level of peasants is remarkable,and they are the major influence factors of modern agricultural equipment level.Raising investment level of rural infrastructure construction as well as and research and development and promotion of advanced and applicable modern agricultural equipment,improving quality and education level of peasants can accelerate the development of China’s modern agricultural equipment effectively in the process of agricultural sustainable development.