高速公路汽车防碰撞模型仿真研究

随着高速公路的快速建设,交通事故迅猛增长.保证适当的车辆行驶距离是预防高速公路事故的有效手段.论文根据车辆制动规律和运行状态,得出行车安全距离模型,同时对模型中的参数进行了说明和分析.采用MATLAB软件对高速公路车辆的安全距离模型进行仿真分析,得出安全距离随车速和附着系数的变化规律,寻求既保证车辆安全行驶又不影响道路通行能力的合理的安全距离值,为降低高速事故率提供一定的依据.     

Evaluation of Poly(ethylene-terephthalate) Products of Chemical Recycling by Differential Scanning Calorimetry

Poly (ethylene-terephthalate), (PET) bottles waste was chemically recycled by glycolysis and hydrolysis. The depolymerization processes were carried out in different time intervals from 5 to 360 min, in two different molar ratios of PET/EG, 1:5 and 1:18 and at different temperatures. The PET glycolysis leads to formation of bis(2-hydroxy-ethyl)terephthalate (BHET) monomer and PET oligomers with hydroxyl and carboxyl end groups while PET hydrolysis is followed by formation of monomers terephthalic acid (TPA) and ethylene glycol (EG). Fractions of monomers and oligomers were further characterized by FTIR spectroscopy and by differential scanning calorimetry (DSC). The results show that DSC is successful method to describe the different structures of oligomers formed during chemical recycling of PET.     

Wind power potential assessment for three buoys data collection stations in the Ionian Sea using Weibull distribution function

The present article utilizes wind measurements from three buoys data collection stations in Ionian Sea to study the wind speed and power characteristics using the Weibull shape and scale parameters. Specifically, the site dependent, annual, and monthly mean patterns of mean wind speed, Weibull parameters, frequency distribution, most probable wind speed, maximum energy carrying wind speed, wind power density and wind energy density characteristics have been analyzed. The Weibull distribution was found to represent the wind speed distribution with more than 90% accuracy, in most of the cases. Moreover, the correlation between the percentages of times the wind speed was above cut-in-speed and the measured mean wind speed for the three selected sites, as the correlation between the aforementioned percentages and the scale parameter c were examined and were found linear. At all these sites, no definite increasing or decreasing trends in annual mean wind speed values could be detective over the data reporting period. The mean values of wind speed, scale parameter, most probable wind speed, maximum energy carrying wind speed, wind power and wind energy density values showed higher values during winter time and lower in summer time in Pylos and Zakynthos. Moreover, Pylos and Zakynthos were found to be the best sites from wind power harnessing point of view.     

加药量和水力搅拌速度对雨水混凝效果的影响

为降低分流制雨水中悬浮颗粒物及其他污染物浓度,减轻城市景观河道的水体富营养化程度,对取自泵站的雨水进行混凝沉淀工艺优化实验。以PAC为混凝剂,采用Zeta电位仪、激光粒度仪和iPDA在线监测技术对混凝过程进行监测,考察了混凝剂投加量和水力搅拌速度对絮体形成和分流制雨水处理效果的影响,结果表明,混凝剂投加量和混合水力搅拌速度直接影响絮体Zeta电位和聚沉特性;混合搅拌速度控制混凝反应速率,絮凝速度梯度影响絮体形成粒径。FI曲线特征参数对控制混凝工艺具有指导意义。PAC投加量为35 mg/L,混合阶段搅拌速度800 r/min,搅拌30 s,絮凝阶段采用150、108和60 r/min的转速各自搅拌5 min,沉后水中剩余颗粒总数最少,浊度、COD和总磷去除效果最佳。     

Numerical Modeling of Particulate Matter Dispersion from Kerman Cement Plant, Iran

A three dimensional diffusion model has been developed for computing the concentration of PM10 from Kerman Cement Plant, Iran. This model incorporates source-related factors, meteorological factors, surface roughness, and settling particles to estimate pollutant concentration from continuous sources. The study focused on the local environmental impact of Kerman Cement Plant. The performance of the model was found to be in good agreement with measured data; the average absolute percent deviation is 25.53%. In addition, the result of this modeling shows that the PM10 concentration in the ambient air at distances of about 600–1,400 m from the stacks is higher than the WHO guidelines of an annual average of 260 μg/m³.     

A hybrid model based on smooth transition periodic autoregressive and Elman artificial neural network for wind speed forecasting of the Hebei region in China

Wind energy, one of the most promising renewable and clean energy sources, is becoming increasingly significant for sustainable energy development and environmental protection. Given the relationship between wind power and wind speed, precise prediction of wind speed for wind energy estimation and wind power generation is important. For proper and efficient evaluation of wind speed, a smooth transition periodic autoregressive (STPAR) model is developed to predict the six-hourly wind speeds. In addition, the Elman artificial neural network (EANN)-based error correction technique has also been integrated into the new STPAR model to improve model performance. To verify the developed approach, the six-hourly wind speed series during the period of 2000–2009 in the Hebei region of China is used for model construction and model testing. The proposed EANN-STPAR hybrid model has demonstrated its powerful forecasting capacity for wind speed series with complicated characteristics of linearity, seasonality and nonlinearity, which indicates that the proposed hybrid model is notably efficient and practical for wind speed forecasting, especially for the Hebei wind farms of China.     

Short-term wind speed forecasting: Application of linear and non-linear time series models

This study forecasts day-ahead wind speed at 15 minute intervals at the site of a wind turbine located in Maharashtra, India. Wind speed exhibits non-stationarity, seasonality and time-varying volatility clustering. Univariate linear and non-linear time series techniques namely MSARIMA, MSARIMA-GARCH and MSARIMA-EGARCH have been employed for forecasting wind speed using data span ranging from 3 days to 15 days. Study suggests that mean absolute percentage error (MAPE) values first decrease with the increase in data span, reaches its minima and then start increasing. All models provide superior forecasting performances with 5 days data span. It is further evident that ARIMA-GARCH model generates lowest MAPE with 5 days data span. All these models provide superior forecasts with respect to current industry practices. This study establishes that employing various linear and non-linear time series techniques for forecasting day-ahead wind speed can benefit the industry in terms of better operational management of wind turbines and better integration of wind energy into the power system, which have huge financial implications for wind power generators in India.     

中国高铁建设投资对国民经济和环境的短期效应综合评估

近年来,传统铁路发展远不能满足各行业对综合交通运输体系的需求,中国政府正加大对高铁行业的规划与投资。现有高铁网络与其他铁路共同构成的快速客运网,推动了产业的空间布局,加速了产业结构调整,提高了就业率,提升了区域间劳动力、资本、自然资源等配置效率,促进了区域经济协调发展。在中国政府大力建设高铁网络的当下,综合评估中国高铁建设投资给国民经济和环境带来的影响具有必要性和十分重要的现实意义。本文基于中国2012年投入产出表,利用投入产出技术和计量经济学模型,通过重新刻画投入产出模型中农村居民、城镇居民部门"收入-消费"内生关系,区分高铁与传统铁路在生产结构和投资结构的差异,构建基于居民消费局部内生化的高铁投资投入产出局部闭模型,评估中国高铁建设投资对经济、就业和能源环境的短期效应。结果表明:12012年中国高铁投资每亿元拉动总产出增加3.72亿元,GDP增长1.21亿元,投资总量给国民经济共带来总产出增长19 373.44亿元、GDP增长6 296.04亿元;2在拉动经济增长同时,高铁建设投资对就业拉动显著,每亿元高铁投资创造1 084个就业岗位,2012年因高铁投资新增就业岗位高达565.23万人。这意味着,在短期内,中国高铁建设投资会在发展社会经济、促进居民就业等方面注入强大的动力;3在环境层面,2012年高铁前期基础建设共带来83.42 Mt CO2排放,略大于传统铁路投资,但考虑到建成运营后,高铁具有清洁、稳定、高速等特点,高铁建设投资在环境层面优势会慢慢显现。     

1961-2018年中国风速均值和极端值的时空演变特征

基于1961-2018年中国545个气象观测站点的日值平均风速、最大风速和极大风速数据,采用多种数理统计方法,从气候态特征、长期变化趋势、年际波动特征和1990年前后的差异特征诊断气候变暖背景下近58年来中国风速均值和极端值的时空演变特征.结果表明:①1961-2018年中国平均风速具有南低、北高的空间分异特征,而最大...     

传热子模型对火灾网络模型的求解精度与速度的影响研究

分析半无限大物体的传热过程,提出线性化的传热计算方法并编制了计算子程序,将子程序嵌入传热子模型为有限厚墙体的《高层建筑火灾烟流运动特性预测软件》,利用实例分析比较了两种传热计算方法对火灾网络模型求解精度和求解速度的影响。计算结果表明对3个节点的简单建筑,半无限大传热子模型与有限厚模型的室温计算最大偏差不超过5%,而计算机耗时约减少了1/3。该研究的结论对《高层建筑火灾烟流运动特性预测软件》的进一步完善和成熟及其市场化具有重要的推动作用。