安全工程学科发展与专业办学思路的思考

迎合安全工程教育的蓬勃发展,结合上海应用技术学院安全工程专业建设的历史以及人才培养现状,分析了上海经济形势和学科专业教育教学方向,总结了安全工程学科的探索思路以及办学拓展方向,提出了专业课程模块方向与课程设置,供安全工程教育工作者参考.     

太湖表层沉积物重金属污染评价与来源分析

对太湖湖区表层沉积物中11种重金属的总量进行调查分析,借助地累积指数法和潜在生态风险指数法分析了重金属的污染程度和生态风险,并利用主成分分析-绝对主成分分数-多元线性回归受体模型对重金属来源进行解析.结果显示太湖沉积物中Cd、Sb含量平均值分别为江苏省土壤背景值的4.29倍和3.18倍,地累积指数表明Cd和Sb为偏中度...     

中国企业社会责任财务绩效评价模型研究

2003年,英国政府出台了<我们能源的未来-创建低碳经济>能源白皮书,其中首次引入了"低碳经济"的概念,随后越来越多的学者开始探讨这种经济发展模式及其技术和政策的可行性,并展开了一系列实证研究.而在这种新的经济发展趋势下,作为经济主体的企业所要承担的社会责任也就被赋予了新的内窖.那么在向低碳经济转型的过程中,如何对企业的社会责任进行客观、有效的评价将对于企业更好履行其社会责任起到重要作用.基于我国国情,本文通过对低碳经济发展模式下中国企业社会责任财务绩效进行模型研究,提出了在传统指标分析模型基础上进行数据包络分析(DEA)和可持续计量的双重模型修正,以期弥补传统财务绩效模型在企业有效投入分析和动态性评价方面的缺陷和不足.     

川东平行岭谷区野生春剑伴生植物群落特征研究

为了对春剑野生种群生物多样性保护和再引入生态重建提供理论和技术基础,采用典型样地调查法,对川东平行岭谷区野生春剑伴生植物群落特征进行了研究。结果表明：野生春剑主要分布在松科与壳斗科针阔混交林、壳斗科常绿 落叶阔叶混交林和松树林植物群落,伴生植物有40科58属70种,优势种主要是乔木层的马尾松、青冈、巴山松、油松等,灌木层的杜鹃花、马桑、山茶花等,草本层的蕨类和地被层的苔藓。其中,马尾松、杜鹃花、蕨类、苔藓具有较高的重要值,可作为野生春剑栖息地的指示植物。春剑伴生植物种类具有相对的特异性和选择性,与其它群落相比,群落3、群落4和群落6物种多样性指数H′和均匀度指数E都相对较低,松科和壳斗科植物个体数量较多并占有突出地位,春剑种群的生态密度也相对较高。虽然川东平行岭谷区野生春剑的适生生境条件依然存在,但春剑种群数量总体较小,种群的生态密度在11～60株/hm2,人为破坏性的滥采,是其濒危的直接原因。加强野生春剑资源的就地保护和生境保护,突破春剑种子野生环境共生萌发技术瓶颈,积极开展春剑的“再引入”工作,是春剑保育策略的重要方向     

鄱阳湖克氏原螯虾的分布现状及其群体外部形态聚类分析

克氏原螯虾(Procambarus clarkii)作为外来入侵物种,对淡水水生生物的多样性已构成严重威胁为国内外学者所共识。有鉴于此,本项目通过对环鄱阳湖湖盆地域9县（市）计12个调查点进行样本采集,并对其多个形态学指标进行测量和数据聚类分析,以探讨克氏原螯虾在该地域的地理分布现状。研究结果表明,克氏原螯虾在鄱阳湖湖盆地域已占据一定的生态地位,并呈现全湖广泛分布及泛滥孳生趋势,已形成对其他水生生物多样性和生态系统稳定的潜在威胁;聚类分析结果显示,鄱阳湖克氏原螯虾群体外部形态上分为两个类群,即星子县、永修县、共青城市群体为一类,鄱阳县、新建县、余干县群体聚成一类,两类群似不存在地域上的交叉,但尚不能说明这两类群为完全不同的群体。同时,提出了防控克氏原螯虾的可行性建议     

湖北省土地利用减碳增效系统仿真及结构优化研究

土地利用变化是引起碳排放的重要原因之一,土地经济效益是利用土地的目标之一,如何通过优化土地利用结构实现土地利用减碳增效是值得研究的重要问题。基于系统结构与功能相互作用的视角,梳理复杂系统内变量间的反馈关系,运用系统动力学(SD)进行建模,将约束条件纳入到多目标规划(MOP)中,实现MOP与SD模型整合,进行系统仿真并得出优化后2020年湖北省土地利用结构。结果显示,利用SD-MOP模型能够实现减碳增效目标下土地利用结构优化,与2008年真实值相比,耕地、林地、牧草地及建设用地分别增加了0.33×10~4、30.17×10~4、0.08×10~4和16.37×10~4 hm~2,其他农用地及未利用地分别减少7.23×10~4、33.15×10~4 hm~2;与无约束SD单模型仿真相比,土地利用碳排放量减少了58×10~4 t,经济效益年增长率维持在3.58%,优化方案具有可行性。SD-MOP模型优化的土地利用结构符合区域可持续发展要求,兼顾了土地利用碳减排和经济效益增长的双重目标,能为区域土地资源优化配置提供参考。     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Comparative study on performances of a heat-pipe PV/T system and a heat-pipe solar water heating system

The heat-pipe solar water heating (HP-SWH) system and the heat-pipe photovoltaic/thermal (HP-PV/T) system are two practical solar systems, both of which use heat pipes to transfer heat. By selecting appropriate working fluid of the heat-pipes, these systems can be used in the cold region without being frozen. However, performances of these two solar systems are different because the HP-PV/T system can simultaneously provide electricity and heat, whereas the HP-SWH system provides heat only. In order to understand these two systems, this work presents a mathematical model for each system to study their one-day and annual performances. One-day simulation results showed that the HP-SWH system obtained more thermal energy and total energy than the HP-PV/T system while the HP-PV/T system achieved higher exergy efficiency than the HP-SWH system. Annual simulation results indicated that the HP-SWH system can heat the water to the available temperature (45°C) solely by solar energy for more than 121 days per year in typical climate regions of China, Hong Kong, Lhasa, and Beijing, while the HP-PV/T system can only work for not more than 102 days. The HP-PV/T system, however, can provide an additional electricity output of 73.019 kWh/m², 129.472 kWh/m², and 90.309 kWh/m² per unit collector area in the three regions, respectively.     

Structure optimization and annual performance analysis of the lens-walled compound parabolic concentrator

The primary lens-walled compound parabolic concentrator (lens-walled CPC) has a significant advantage of a larger half acceptance angle as a static solar concentrator, but it also has a drawback of a low optical efficiency. In order to overcome this drawback, in this article, series of structure parameters were investigated and compared to further improve the optical efficiency within the half acceptance angle combined with the material properties. The average optical efficiencies of the improved lens-walled CPCs could achieve more than 82% within the half acceptance angle of 35?. Experiments were adopted to verify the credibility and validity of the simulation. Moreover, annual performance of the lens-walled CPCs comparison with that of the mirror CPC for Nottingham was analyzed. Results show that the improved lens-walled CPC has a higher optical performance for actual building application.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.