Simulation-based fault propagation analysis—Application on hydrogen production plant

Recently production of hydrogen from water through the Cu–Cl thermochemical cycle is developed as a new technology. The main advantages of this technology over existing ones are higher efficiency, lower costs, lower environmental impact and reduced greenhouse gas emissions. Considering these advantages, the usage of this technology in new industries such as nuclear and oil is increasingly developed. Due to hazards involved in hydrogen production, design and implementation of hydrogen plants require provisions for safety, reliability and risk assessment. However, very little research is done from safety point of view. This paper introduces fault semantic network (FSN) as a novel method for fault diagnosis and fault propagation analysis by using evolutionary techniques like genetic programming (GP) and neural networks (NN), to uncover process variables’ interactions. The effectiveness, feasibility and robustness of the proposed method are demonstrated on simulated data obtained from the simulation of hydrogen production process in Aspen HYSYS^®. The proposed method has successfully achieved reasonable detection and prediction of non-linear interaction patterns among process variables.     

Interaction of selenium and cadmium in wheat at different salinities

Abstract

Interaction of Se up to 8?mg?kg^?1 soil and Cd at 5 and 15?mg?kg^?1 soil in wheat at different salinities was evaluated. Se concentrations in wheat shoots were progressively increased in parallel to Se in soil but decreased by addition of Cd. With increasing salinity, Cd concentrations increased and Se decreased. At low salinity, low addition of Se to the soil reduced Cd accumulation. At moderate and high salinities, only high Se amendment led to decline in Cd uptake, at the expense of reduction in biomass yield. Se at 0.5?mg?kg^?1 soil alleviated the negative effect of Cd on shoot yield.     

水稻基因类型与生长环境对精米中砷积累的影响

砷(As)是动植物非必需的有毒类金属。水稻是对As有较强吸收和富集能力的大宗粮食作物,大米的食用是我国及东南亚地区人体暴露As的最主要途径,严重威胁人体健康。水稻籽粒中As的积累与水稻的基因型及众多环境因子密切相关,而且表现出复杂的交互作用。在浙江省选择了不同土壤砷背景值的5块水稻田,同时在嘉兴市农科院布置了人工添加As的盆栽实验,比较了20个水稻品种在这6个实验点的精米中As含量。结果表明,水稻基因型与环境及其相互作用对水稻籽粒中As的积累均有极显著影响,并且筛选得到了5个精米中As含量较低的基因型:秀水128、秀水09、秀水134、甬粳16和Y-05-8。     

基于Box Behnken设计的煤导热系数分析与预测

为研究分析水分、固定碳及密度3个因素对煤导热系数的影响,选取多个矿井不同煤质的煤作为实验煤样,使用NETZSCH LFA457型激光导热系数测试仪进行测定,并引入二次响应曲面试验设计思想,采用Design Expert软件进行煤质指标的Box Behnken试验设计,按设计表筛选实验数据,构建了导热系数多因素、多水平影响下二次回归响应曲面模型,并对不同采样地点的煤导热系数进行了分析与预测。结果表明:二次回归方程P值小于0.000 1,极显著,失拟项为0.072 4,不显著,回归方程具有统计学意义;当水分在0.9%~10.9%,固定碳在49.3%~83.6%,密度在1.2~1.92 g·cm³之间,对煤的导热系数一次项影响程度为密度>固定碳>水分;二次项影响程度为固定碳和密度>水分和密度>水分和固定碳,且固定碳和密度之间存在交互作用,水分和密度、水分和固定碳之间无交互作用;应用响应曲面模型预测的煤导热系数误差为4.3%,满足精度要求。     

坡度和植被盖度对河岸坡面侵蚀产沙特征的影响

坡度和植被盖度是影响坡面土壤侵蚀的重要因子,探讨坡面土壤侵蚀产沙对坡度和植被盖度的响应,对坡面土壤侵蚀产沙的预测和调控具有重要意义。研究基于野外模拟径流冲刷试验,分析了不同坡度（5°、10°、15°、20°）和植被盖度（0、15%、30%）条件下坡面径流系数、泥沙量、时段径流含沙量和侵蚀泥沙粒径组成的变化过程,并运用双因素方差分析和相对贡献指数阐明黄河下游河岸坡面侵蚀产沙特征对坡度和植被盖度交互作用的响应。结果表明：不同植被盖度下坡面径流系数随冲刷历时增加而增加,在冲刷历时前5 min增幅较快,之后增幅变慢并趋于平缓;坡面径流含沙量随冲刷历时呈逐渐下降趋势,随后趋于平缓。坡度小于15°时,不同植被盖度之间的径流系数和时段径流含沙量差异较为明显,坡度大于15°后差异减小。侵蚀产生的泥沙量随冲刷历时和坡度的增加而增加;在同一坡度上,植被覆盖越低,侵蚀产生泥沙量越大。侵蚀泥沙的主要富集粒级中,Dx(10)以粉粒为主,Dx(50)以粗粉粒和极细砂粒为主,Dx(90)以极细砂粒和细砂粒为主。双因素方差分析表明,坡度对河岸坡面侵蚀产生的径流系数、产沙量和径流含沙量均有极显著影响（P<0.001）,植被盖度对产沙量和径流系数有极显著影响（P<0.001）,而坡度和植被盖度的交互作用仅对径流系数有显著影响（P<0.01）,同时相对贡献指数表明,在坡度和植被盖度对坡面侵蚀产沙的交互作用中,植被盖度的作用随坡度的增加逐渐减弱,而坡度的作用逐渐增强,并成为影响坡面水土流失的主导因素。     

河水-地下水交互带沉积物中抗生素和代谢产物提取方法优化及其分布特征

河水-地下水交互带是污染物发生富集、降解和转化等生物地球化学过程的重要场所.抗生素作为一类广泛关注的有机污染物,探索其在交互带中的分布特征对认识特殊生境下污染物迁移转化过程具有重要意义.由于交互带氧化还原条件变化敏感,沉积物组成特殊,建立了一种有效提取交互带中22种抗生素及4种磺胺类代谢产物的前处理方法,并对样品初始状态、提取温度、提取液pH值以及有机提取溶剂进行了优化.同时对汉江下游河水-地下水交互带沉积物中的抗生素含量进行分析,结果表明,采用pH=3的乙腈/乙二胺四乙酸二钠（Na₂EDTA）-Mcllvaine缓冲液（1 ：1,体积比）对未经氧化的沉积物原样在40℃条件下进行3次微波提取,目标抗生素的回收效果最好.汉江下游交互带沉积物中共检出11种抗生素,其中以土霉素（OTC）和氧氟沙星（OFL）为主,最高检出含量分别为6.77 ng ·g^-1和5.81 ng ·g^-1.不同交互剖面中抗生素含量的垂向分布差异较大,主要与沉积物岩性、抗生素理化性质和地表水-地下水交互作用等影响因素有关.     

How humans shape wolf behavior in Banff and Kootenay National Parks, Canada

This paper describes the conceptualization and implementation of an agent-based model to investigate how varying levels of human presence could affect elements of wolf behavior, including highway crossings; use of areas in proximity to roads and trails; size of home ranges; activities, such as hunting, patrolling, resting, and feeding pups; and survival of individuals in Banff and Kootenay National Parks, Canada. The model consists of a wolf module as the primary component with five packs represented as cognitive agents, and grizzly bear, elk, and human modules that represent dynamic components of the environment. A set of environmental data layers was used to develop a friction model that serves as a base map representing the landscape over which wolves moved. A decision model was built to simulate the sequence of wolf activities. The model was implemented in a Java Programming Language using RePast, an agent-based modeling library. Six months of wolf activities were simulated from April 16 to October 15 (i.e., a season coherent with regard to known wolf behaviors), and calibrated with GPS data from wolf radiocollars (n = 15) deployed from 2002 to 2004. Results showed that the simulated trajectories of wolf movements were correlated with the observed trajectories (Spearman's rho 0.566, P < 0.001); other critical behaviors, such as time spent at the den and not traveling were also correlated. The simulations revealed that wolf movements and behaviors were noticeably affected by the intensity of human presence. The packs’ home ranges shrank and wolves crossed highways less frequently with increased human presence. In an extreme example, a wolf pack whose home range is traversed by a high-traffic-volume highway was extirpated due to inability to hunt successfully under a scenario wherein human presence levels were increased 10-fold. The modeling prototype developed in this study may serve as a tool to test hypotheses about human effects on wolves and on other mammals, and guide decision-makers in designing management strategies that minimize impacts on wolves and on other species functionally related to wolves in the ecosystem.     

Influence of low and decreasing food levels on Daphnia-algal interactions: Numerical experiments with a new dynamic energy budget model

Based on numerical experiments with a new physiologically structured population model we demonstrate that predator physiology under low food and under starving conditions can have substantial implications for population dynamics in predator-prey interactions. We focused on Daphnia-algae interactions as model system and developed a new dynamic energy budget (DEB) model for individual daphnids. This model integrates the κ-rule approach common to net assimilation models into a net-production model, but uses a fixed allocation of net-productive energy in juveniles. The new DEB-model agrees well with the results of life history experiments with Daphnia. Compared to a pure κ-rule model the new allocation scheme leads to significant earlier maturation at low food levels and thus is in better agreement with the data. Incorporation of the new DEB-model into a physiologically structured population model using a box-car elevator technique revealed that the dynamics of Daphnia-algae interactions are highly sensitive to the assumptions on the energy allocation of juveniles under low food conditions. Additionally we show that also other energy allocation rules of our DEB-model concerning decreasing food levels and starving conditions at the individual level have strong implications for Daphnia-algae interactions at the population level. With increasing carrying capacity of algae a stable equilibrium with coexistence of Daphnia occurs and algae shifts to limit cycles. The amplitudes of the limit cycles increase with increasing percentage of sustainable weight loss. If a κ-rule energy allocation is applied to juveniles, the stable equilibrium occurs for a much narrower range of algal carrying capacities, the algal concentration at equilibrium is about 2 times larger, and the range of algae carrying capacities at which daphnids become extinct extends to higher carrying capacities than in the new DEB-model. Because predator-prey dynamics are very sensitive to predator physiology under low food and starving conditions, empirical constraints of predator physiology under these conditions are essential when comparing model results with observations in laboratory experiments or in the field.     

Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain1

Epps, Thomas H., Daniel R. Hitchcock, Anand D. Jayakaran, Drake R. Loflin, Thomas M. Williams, and Devendra M. Amatya, 2012. Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12000 Abstract: Hydrologic monitoring was conducted in two first‐order lower coastal plain watersheds in South Carolina, United States, a region with increasing growth and land use change. Storm events over a three‐year period were analyzed for direct runoff coefficients (ROC) and the total storm response (TSR) as percent rainfall. ROC calculations utilized an empirical hydrograph separation method that partitioned total streamflow into sustained base flow and direct runoff components. ROC ratios ranged from 0 to 0.32 on the Upper Debidue Creek (UDC) watershed and 0 to 0.57 on Watershed 80 (WS80); TSR results ranged from 0 to 0.93 at UDC and 0.01 to 0.74 at WS80. Variability in event runoff generation was attributed to seasonal trends in water table elevation fluctuation as regulated by evapotranspiration. Groundwater elevation breakpoints for each watershed were identified based on antecedent water table elevation, streamflow, ROCs, and TSRs. These thresholds represent the groundwater elevation above which event runoff generation increased sharply in response to rainfall. For effective coastal land use decision making, baseline watershed hydrology must be understood to serve as a benchmark for management goals, based on both seasonal and event‐based surface and groundwater interactions.     

新型氨化菌丝体吸附剂的制备及吸附典型内分泌干扰物的研究

以产黄青霉(Penicillium chrysogenum)菌丝体为原料,通过2步化学反应将含有大量氨基的聚乙烯亚胺(PEI)嫁接到菌丝体表面,优化反应条件,得到最佳的氨化菌丝体吸附剂.该氨化吸附剂的等电点为pH 10.2,是一种表面带正电荷的菌丝体吸附剂,能有效吸附水中的阴离子内分泌干扰物五氯酚钠(PCP)、2,4二氯苯氧乙酸(2,4-D)和全氟辛烷磺酸钾(PFOS).3种污染物的吸附等温线符合Langmuir方程,15℃时最大吸附量分别为342.9、234.1、1725.6 mg/g.热力学计算表明,3种污染物的吸附均是自发发生的,2,4-D和PFOS的吸附是吸热反应,而PCP是放热反应.