纺织废水集中处理厂升级改造关键技术

某纺织废水集中处理厂接纳的主要废水为棉纺织、染整、洗毛、化工等综合性废水。这种废水成分复杂．污染程度高,混合废水CODCr质量浓度高达2000mg／L,pH值达13。为响应江苏省DB32／1072--2007《湖地区城镇地区水处理厂及重点工业行业主要水污染物排放限值》的新标准,研究了老污水厂升级改造的关键技术：首先采用清浊分流,将高浓度的退浆废水与洗毛废水经8d厌氧预处理,使CODCr质量浓度由8000mg／L降至1800mg／L．然后与印染废水混合,使调节池出水CODCr质量浓度从1600mg/L降至800mg／L左右;污泥量减少40％～50％;并深化曝气生物滤池处理工艺,采用气水联合反冲洗,节约80％反冲洗水,并使曝气生物滤池出水CODCr质量浓度稳定在60mg／L以下。     

地震灾后重建中的多元化资金支持研究

本文以汶川地震为背景,针对灾后重建资金需求量大、持续时间长的特点,提出灾后重建资金来源应以财政资金为引导,走多元化的道路;并分别从财政资金支持、信贷资金支持、社会资金支持、国外资金支持、保险资金支持、证券市场资金支持的角度进行分析,提出了在财政资金引导下,切实可行的多元化资金支持建议.     

Multibody model of the human upper extremity for fracture simulation

About 3.8 million people are injured in accidents at work in Europe every year. The resulting high costs are incurred by the victims themselves, their families, employers and society. We have used a numerical simulation to reconstruct accidents at work for several years. To reconstruct these accidents MADYMO R7.5 with a numerical human model (pedestrian model) is used. However, this model is dedicated to the analysis of car-to-pedestrian accidents and thus cannot be fully used for reconstructing accidents at work. Therefore, we started working on the development of a numerical model of the human body for the purpose of simulating accidents at work. Developing a new numerical model which gives an opportunity to simulate fractures of the upper extremity bones is a stage of that work.     

Traffic accident reconstruction and an approach for prediction of fault rates using artificial neural networks: A case study in Turkey

Objective: Currently, in Turkey, fault rates in traffic accidents are determined according to the initiative of accident experts (no speed analyses of vehicles just considering accident type) and there are no specific quantitative instructions on fault rates related to procession of accidents which just represents the type of collision (side impact, head to head, rear end, etc.) in No. 2918 Turkish Highway Traffic Act (THTA 1983). The aim of this study is to introduce a scientific and systematic approach for determination of fault rates in most frequent property damage–only (PDO) traffic accidents in Turkey.

Methods: In this study, data (police reports, skid marks, deformation, crush depth, etc.) collected from the most frequent and controversial accident types (4 sample vehicle–vehicle scenarios) that consist of PDO were inserted into a reconstruction software called vCrash. Sample real-world scenarios were simulated on the software to generate different vehicle deformations that also correspond to energy-equivalent speed data just before the crash. These values were used to train a multilayer feedforward artificial neural network (MFANN), function fitting neural network (FITNET, a specialized version of MFANN), and generalized regression neural network (GRNN) models within 10-fold cross-validation to predict fault rates without using software. The performance of the artificial neural network (ANN) prediction models was evaluated using mean square error (MSE) and multiple correlation coefficient (R).

Results: It was shown that the MFANN model performed better for predicting fault rates (i.e., lower MSE and higher R) than FITNET and GRNN models for accident scenarios 1, 2, and 3, whereas FITNET performed the best for scenario 4. The FITNET model showed the second best results for prediction for the first 3 scenarios. Because there is no training phase in GRNN, the GRNN model produced results much faster than MFANN and FITNET models. However, the GRNN model had the worst prediction results. The R values for prediction of fault rates were close to 1 for all folds and scenarios.

Conclusions: This study focuses on exhibiting new aspects and scientific approaches for determining fault rates of involvement in most frequent PDO accidents occurring in Turkey by discussing some deficiencies in THTA and without regard to initiative and/or experience of experts. This study yields judicious decisions to be made especially on forensic investigations and events involving insurance companies. Referring to this approach, injury/fatal and/or pedestrian-related accidents may be analyzed as future work by developing new scientific models.     

植物微体遗存分析在第四纪环境研究中的应用:综述与展望

以孢粉、植硅体等为代表的植物微体遗存由于其分布广泛,容易保存,可反映母体植物类型的优点,在第四纪环境研究中得到了广泛应用。本文介绍了植物微体遗存的概念、常见类型,以及它们的提取方法和原理,综述了利用植物微体遗存重建古环境的传统方法和近年来发展的几种古植被与古气候定量重建方法,最后简述了植物微体遗存在年代测定、稳定同位素分析研究上的应用进展与实例。文末指出了现有研究方法的问题与不足,并对今后的多代用指标的综合研究提出了展望。     

基于LCA的污水处理厂提标改造环境影响负荷研究

研究旨在评价污水处理厂提标改造工程前后的环境影响,并做出科学的管理决策。以呼和浩特市公主府污水处理厂为例,采用生命周期评价(LCA)的方法,定量研究了污水处理厂改造前后的环境影响负荷,识别和判断出环境影响负荷的变化量。结果表明:该污水处理厂经过改造之后的环境负荷大于改造之前,相比改造前增长约63.5%,其中水质和水体富营养化影响潜能明显减小,而不可再生资源消耗、全球变暖影响潜能的增加量较大,环境负荷增加的根本原因在于电耗的增加。最后根据评价结果提出针对污水处理厂提标改造工程的改善建议。     

大气污染总量控制方案的区域排放当量制定方法

在分析现有的大气污染总量控制方案的制定方法的基础上,本文提出了区域排放当量概念及相应的大气污染物总量控制方法。应用该概念制定总量控制方案,首先是运用线性规划模型求解区域允许排放当量,线性规划模型中的技术系数是以区域内网格为基础的污染物转移函数;其次是分配区域允许当量至各个污染源,从而确定污染源的允许排放量。该方法已在南昌市的大气污染总量控制方案的制定中得到应用。     

混沌理论在水质预测中的应用初探

基于混沌理论、相空间重构思想和嵌入理论分析涟水流域溶解氧的时间序列,计算吸引子维数和最大的Lyapunov指数,研究河流水质系统的复杂性特征。结果表明,河流水质时间序列具有混沌特性,其外在表现为貌似随机的无规则特点;但系统本身内在的、固有的规律(表现在最大的Lyapunov指数),表明短期预测河流水质变化是可行的,并应用混沌相空间模线性回归模型进行了短期预测,其预测结果对涟水流域的水质管理和控制具有一定的参考价值。     

水上交通事故分析研究进展

为更好地开展水上交通事故分析研究,提高我国水上交通安全水平,从船舶风险评估与事故预测、事故分析以及事故及通航安全数据的组织与数据库建立3个方面对国内外的相关研究进行论述和分析。提出以建立水上交通事故时空数据平台为基础,结合数据挖掘和安全工程的理论方法研究事故发生机理,评估事故风险,并将研究事故模拟再现技术作为事故分析的重要技术手段。     

环黄渤海地区土壤介质中PFOS网格排放清单估算及不确定性分析

全氟辛烷磺酸(PFOS)是一种《斯德哥尔摩公约》所列的持久性有机污染物.加强对土壤中PFOS排放的合理认识,并追踪其污染源,对减少和控制土壤中污染物具有重要意义.然而,很少有研究涉及土壤介质中PFOS生命周期排放清单.基于PFOS生命周期评价法构建了 2018年环黄渤海地区各污染源排放到土壤介质中的PFOS排放因子,估...