木薯酒糟沼气发酵污泥生物干燥条件优化

利用生物干燥方法,通过添加微生物菌剂,将木薯酒糟沼气发酵后污泥进行干燥实验.利用响应面法对影响污泥干燥工艺的条件进行优化,确定生物干燥过程中接种量、通风量、温度对物料含水率的影响.最后得到在接种量1.5％、通风量6.5 L/h、温度36℃时,固态发酵96 h物料含水率可降到30％以下.     

柴油机微粒捕集器技术发展现状

颗粒物是柴油机排气主要污染物之一,微粒捕集器能够将排气中的颗粒物过滤,实现90%以上的净化效率,是国际应对未来机动车排放法规的必然选择。文章通过分析近几年国际的研究成果,阐述了颗粒物的组成以及在微粒捕集器中的燃烧过程,并介绍了微粒捕集器的净化机理、材料技术和再生技术。国际研究表明:(1)颗粒物主要由固体碳、可溶性有机成分和硫酸盐三部分组成,在燃烧过程中,可溶性有机物、官能团、高度结晶碳随着温度升高依次燃烧;(2)壁流式微粒捕集器通过扩散、拦截、重力和惯性四种形式将颗粒物拦截过滤;传统的堇青石、碳化硅材料各有优缺点,可能被新型钛酸铝材料取代;过滤体通过增加入口通道体积的方式增加对颗粒物和灰分的容纳能力;(3)微粒捕集器再生技术种类繁多,被动再生技术由于对燃油硫含量由较高要求,因此主要在国外采用;国内主要应采用主动再生技术,同时使用燃油添加剂进行辅助再生。     

水葫芦控制性种养技术研究

利用水葫芦强大的无性繁殖能力和对水体氮磷的吸附能力,可以有效治理水体内源污染。大规模的水葫芦圈养必须解决水葫芦逃逸问题,在满足安全生长的前提下实施经济效益和生态效益高的圈养方式,是水葫芦产业得以推广的必要保证。     

Optimization of process parameters using response surface methodology for bioconversion of activated sludge by Penicillium corylophilum

The optimization of process parameters for the bioconversion of activated sludge by Penicillium corylophilum was investigated using response surface methodology （RSM）. The three parameters namely temperature of 33℃, agitation of 150 r/min, and pH of 5 were chosen as center point from the previous study of fungal treatment. The experimental data on chemical oxygen demand （COD） removal （%） were fitted into a quadratic polynomial model using multiple regression analysis. The optimum process conditions were determined by analyzing response surface three-dimensional surface plot and contour plot and by solving the regression model equation with Design Expert software. Box-Behnken design technique under RSM was used to optimize their interactions, which showed that an incubation temperature of 32.5℃, agitation of 105 r/min, and pH of 5.5 were the best conditions. Under these conditions, the maximum predicted yield of COD removal was 98.43%. These optimum conditions were used to evaluate the trail experiment, and the maximum yield of COD removal was recorded as 98.5%.     

武汉城市圈产业发展的空间优化

武汉城市圈是指以武汉市为中心,包括黄石、鄂州、黄冈、孝感、咸宁、仙桃、潜江和天门等周边8市共同组成的城市密集区。该区域具有悠久的产业发展传统,其历史轨迹可分为3个阶段：第一阶段（1840~1949）为产业发展起步时期,第二阶段（1949~1994）为产业结构强化时期,第三阶段（1994~）为产业体系调整时期;与此相适应,区域产业的部门结构和空间结构均呈现典型的集中特征,以2003年区域制造业的增加值为指标,武汉市的空间集中度为50.5％,前10类制造业的产业集中度为60.6％。据此,目前的武汉城市圈是一个松散的“经济联邦”,但存在区域整合的产业、空间和创新基础。以2001~2004年武汉城市圈9城市的统计资料为基础,以制造业分行业的年均增加值和增长率为指标,计算和分析其区域产业发展潜力,结果表明：以钢铁、汽车和电子及通讯设备制造业等为依托,构建区域集群网络,能够充分发挥武汉市的产业组织和创新扩散功能。武汉城市圈应进一步调整产业发展思路,坚持创新驱动路径,通过完善集群网络规划、强化区域空间关联和引导产业集聚发展等政策措施,有效推动具有区域竞争优势的特色产业发展。     

体育馆中人员安全疏散的仿真分析

针对现今公共活动中的人群踩踏事故频发问题,应用计算机仿真技术研究紧急情况下建筑物中人群逃生规律及设施优化方法。设置人员体质、移动余值、出口逃生条件等因素,扩展元胞自动机(CA)行人流模型。利用Matlab语言实现可视化模拟。对莱阳市某体育馆进行人流疏散模拟,分析得到其安全设施的最佳设定参数,实现优化目的。结果表明:该体育馆仿真疏散完成总时间为103.5 s,可引发踩踏事故的疏散危险期长达49.0 s,疏散危险期长度为判断踩踏事故发生可能性的重要指标;出口宽度、数量均与疏散时间呈负相关,且均存在疏散能力饱和点。据此提出将宽度改建为2.5 m、数量增加到6个的优化方案,此方案疏散危险期为9.0 s,疏散总时间缩短到33.5 s。     

校车儿童安全气囊安全性仿真分析

为提高校车乘员约束系统在正面碰撞中对儿童乘员的保护效果,提出一种新型主动式校车儿童安全气囊。运用多刚体动力学分析软件MADYMO建立包括地板、前后排座椅、安全带与第5百分位女性假人在内的校车乘员正面碰撞仿真模型,通过台车试验结果验证模型的准确性。在此基础上,建立主动式安全气囊模型,研究其对12岁和6岁乘员的保护效果。用正交试验方法,分析气囊设计参数,针对12岁乘员进行气囊优化。结果表明:头部气囊的厚度及排气孔大小对乘员伤害影响最大。与原始约束系统相比,经优化后的气囊使12岁乘员的头部、胸部和颈部伤害分别下降84.5%,19%和84.3%,同时加装气囊对6岁儿童也有一定的保护效果。     

Cost‐Effective Placement of Best Management Practices in a Watershed: Lessons Learned from Conservation Effects Assessment Project

This article reviews the key, cross‐cutting findings concerning watershed‐scale cost‐effective placement of best management practices (BMPs) emerging from the National Institute of Food and Agriculture Conservation Effects Assessment Project (CEAP) competitive grants watershed studies. The synthesis focuses on two fundamental aspects of the cost‐effectiveness problem: (1) how to assess the location‐ and farmer‐specific costs of BMP implementation, and (2) how to decide on which BMPs need to be implemented and where within a given watershed. Major lessons learned are that (1) data availability remains a significant limiting factor in capturing within‐watershed BMP cost variability; (2) strong watershed community connections help overcome the cost estimation challenges; (3) detailing cost components facilitates the transferability of estimates to alternative locations and/or economic conditions; and (4) implicit costs vary significantly across space and farmers. Furthermore, CEAP studies showed that (5) evolutionary algorithms provide workable ways to identify cost‐effective BMP placements; (6) tradeoffs between total conservation costs and watershed‐scale cost‐effective water quality improvements are commonly large; (7) quality baseline information is essential to solving cost‐effectiveness problem; and (8) systemic and modeling uncertainties alter cost‐effective BMP placements considerably.     

Safety-based process plant layout using genetic algorithm

This paper presents a method based on a genetic algorithm for optimizing process plant layout. The relative location of main process units is determined to minimize an annual cost function including the cost of material transfer between process units (piping and pumping costs), land cost, and the expected annual loss resulting from damage to each secondary unit caused by primary accidents occurring in nearby process units. This method is an improvement over previous attempts using genetic algorithms or mathematical programming techniques to optimize plant layout, which neglected pumping costs and included safety issues by evaluating the infringement of predefined safety distances only. In this approach the operating cost of material transfer is included and the likelihood of accidents is taken into account thus providing good practical solutions to the plant layout problem incorporating more realistic cost functions and constraints. In the paper, after discussing the structure of the annual cost function and describing the working logic of the layout generating algorithm, a case study is described to demonstrate the effectiveness of the proposed methodology.     

A hybrid machine learning model for predicting crater width formed by explosions of natural gas pipelines

Despite the existence of industry models for estimating the crater width formed by the explosion of natural gas pipelines, their applicability is still limited since the complex formation mechanisms. In this work, a novel hybrid model was developed to predict crater width formed by explosions of natural gas pipelines, using artificial neural networks (ANN) as the fundamental predictor. Based on the historical accident records, the proposed hybrid model was trained by the pipeline parameter, the operating condition, the installation parameter, and the crater width. A novel nature-inspired optimization algorithm, i.e., the Lévy-Weighted Quantum particle swarm optimization (LWQPSO) algorithm, was proposed to optimize the ANN model's parameters. Three machine learning models were developed for comparative reasons to predict the crater width. The use of precision and error analysis indicators assesses prediction performance. The results show that the proposed hybrid model (LWQPSO-ANN) has high prediction accuracy and stability, which outperforms QPSO-ANN-based benchmark hybrid models and the model without an optimizer (Support Vector Machine, SVM). The parameter sensitivities of the proposed algorithm, including the maximum number of iterations, population size and contraction-expansion coefficient, were determined. The proposed hybrid model is expected to support the quantitative risk assessment (QRA), Right-of-Way (ROW) definition and the inherently safer design of the underground parallel pipelines.