湖泊富营养化因子对叶绿素a影响的SEM分析

根据湖泊富营养化成因机理,采用结构方程模型(SEM),引入物理环境、有机物、营养盐和浮游植物4个潜变量,并结合选取的5个影响因子,建立了富营养化结构方程模型,以便模拟各因子对巢湖流域南淝河入巢湖口水体中叶绿素a的影响。结果表明,该模型揭示了富营养化各要素与叶绿素a之间的复杂关系,与其他方法相结合可直接预测叶绿素a的浓度。     

感潮河网区白云湖水系生态环境补水研究

感潮网河区水系交错、城市发达，高强度土地利用开发导致城市景观湖泊水环境污染严重，生态环境功能退化。以典型网河区城市景观湖体—广州市白云湖为例，构建二维水动力水质耦合模型，研究其生态环境需水及其补水方案。结果表明，基于MIKE21的二维网河区水动力水质耦合模型，能较好模拟城市景观湖泊水体水质输移规律，模拟值与实测值相对误差值均小于0.20,纳什效率系数均大于0.75;运用白云湖闸、泵水利工程联合调度补水，白云湖及其连通水系生态环境需水量保证率基本达到100%,TN及TP浓度均达到Ⅳ类水标准。研究成果可为感污河网区城市景观湖泊生态环境治理提供参考。     

基于EFDC模型的天镜湖水动力优化调控方案研究

太仓市天镜湖以长江水为水源,补水量只能维持蒸发渗透水量,湖水基本不动,水体极易处于高度富营养化状态。针对该湖现有问题,利用环境流体力学模型(EFDC模型)建立了天镜湖的三维非稳态水量、水龄、污染物颗粒追踪数学模型,对天镜湖水动力优化调控方案进行了模拟(模拟内容包括水位、流速和水龄)。模拟结果表明,通过浏河闸开启向天镜湖引水能够在一定程度上加强湖入口和中心区域的水体流动性能,且浏河闸开启的时间越长效果越好,但引水对天镜湖内部(远离入口处)区域的水动力无明显的改善作用;在西南风条件下,开启浏河闸引水对湖区的水动力改善效果最好;在现状条件下,湖区中存在多处水体交换差的区域(集中在湖周边和远离入口的地方),可能成为天镜湖潜在的水体富营养化高发区。     

基于灰色关联和ABC-BP神经网络的叶绿素a浓度预测

为预测太湖梅梁湾叶绿素a浓度,建立了基于灰色关联和ABC-BP神经网络的叶绿素a浓度预测模型,即通过灰色关联分析选取总磷、CODMn、水温、pH值、悬浮质为BP神经网络的输入变量,采用人工蜂群(ABC)算法优化网络权值与阈值,构造基于ABC算法优化的BP(ABC-BP)神经网络模型,预测出2014年1月~2015年12月的梅梁湾叶绿素a浓度。结果表明,经ABC算法优化后,BP网络模型预测梅梁湾叶绿素a浓度的最大绝对误差从3.54μg/L减小到1.28μg/L,最大相对误差从41.57%减小到20.62%,平均相对误差从8.83%减小到3.31%,可以提高梅梁湾叶绿素a浓度预测的准确性。     

小型景观湖泊眉湖水质分析及富营养化评价

小型景观湖泊已成为城市生态景观的重要组成部分,但因自身特点决定了其易受人为因素影响而导致水质变差,甚至丧失景观水体的功能,因此有必要研究小型景观湖泊的水质状况及其富营养化程度的影响因素。以郑州大学眉湖为例,进行多次定期水环境监测试验,在分析水质指标的时空分布及变化规律的基础上,分别采用单指标评价法和综合营养状态指数法评价其水体的水质状况及富营养化程度。结果表明,CODCr、BOD5、TP、TN、NH3-N等主要污染物的浓度与禽类、鱼类和水生植物的分布密切相关,在监测时段内眉湖整体水质状况呈恶化趋势,从中营养状态变为轻富营养状态。最后,有针对性地提出了改善策略和保护措施,以期为小型景观湖泊的运行管理提供依据和参考。     

PSO_SVM软测量方法在火电厂煤质发热量测量中的应用

为了对电厂煤质发热量进行简单准确的测量,在煤质发热量理论研究的基础上,提出了利用支持向量机算法进行软测量。对支持向量机的数学原理进行分析后,利用某燃煤电厂的运行数据,构建了支持向量机模型。在构建模型过程中引入了PSO(粒子群优化算法)寻找模型中涉及的惩罚参数c和核函数参数g的最优值,然后利用最优值构建了PSO-SVM软测量模型,模型的测试结果表明:PSO-SCM模型相对误差集中在1%以内,CV(交叉验证法)建立的SVM模型相对误差在1.5%左右,而常用的BP(按误差逆传播算法训练的多层前馈网络)神经网络模型得到的相对误差只能保证在3%以内,可见PSO-SVM款测量模型对煤质发热量的测量更准确。     

基于灰色关联分析-GA-BP模型的叶绿素a含量预测

为提高水体叶绿素a预测精度和收敛速率,提出一种基于灰色关联度分析和遗传算法优化BP神经网络预测水体叶绿素a的方法。即先采用灰色关联度分析法选取合适的水质指标作为输入因子,然后优化网络隐含层的结构参数,引入遗传算法优化BP神经网络的初始权值和阈值,最后以预测太湖叶绿素a为例进行比较分析。结果表明,优化神经网络隐含层数能进一步提高网络的预测精度、缩短训练时间;灰色关联分析-GA-BP模型相较于BP、GA-BP模型具有更高的预测精度和收敛速度,可为控制水环境监测和决策平台提供科学依据。     

大伙房水库水质预测模型研究

水质为水库运行管理的重要因素,水质变量包括溶解氧、总磷、叶绿素a及透明度等,是水库富营养化判定的重要指标。在线性回归法分析的基础上,优化环境因子参数,分别采用多元线性回归模型、径向基函数模型与自适应模糊神经网络推理模型对辽宁省大伙房水库的水质进行预测,并通过平均绝对误差、均方根误差及相关系数判定水质模型的预测效果。结果表明,自适应模糊神经网络推理模型预测效果明显优于多元线性回归模型和径向基神经网络模型,因此自适应模糊神经网络推理模型更适合于大伙房水库的水质预测。     

基于随机森林的变工况下重型燃气轮机压气机特性分析研究

为保证不同工况下重型燃气轮机发电机组的高效、稳定运行,需要对其轴流式压气机性能进行高精度建模分析。本文以某F级重型燃气轮机为研究对象,有效结合实测数据和基元叶栅法理论计算值,采用随机森林方法,建立其压气机高精度特性计算模型,从而分析不同工况下的压气机性能。结果表明:模型计算的总压比和多变效率的平均相对误差分别为-0.13%和0.04%;最大相对误差分别为2.11%和1.90%。现有文献的模型最大相对误差分别为3.1%和4.4%,本文方法得到的最大误差仅分别为其68.06%和43.18%。     

基于PSO-SVR的排汽比焓软测量建模研究

为更好地对汽轮机排汽比焓进行测量,将粒子群优化算法引入支持向量回归SVR模型中,构建与之相匹配的排汽比焓软测量预测模型。根据实例校验方法对该模型展开校验,采用汽轮机15种参数作为输入参数,排汽比焓作为输出参数。对某300 MW机组和200 MW机组数据进行仿真,并将该模型与标准SVR模型和双隐层RBF过程神经网络模型预测结果进行对比,对于300 MW机组,该模型的预测平均相对误差为0.101%,均方根误差为0.110%;对于200 MW机组,该模型的预测平均相对误差为0.057%,均方根误差为0.062%;与其他两种模型相比,PSO-SVR模型的预测平均相对误差和均方根误差均最小。实例证明PSO-SVR的排汽比焓软测量预测模型在精确度以及泛化能力等方面呈现出一定的优势,具有较好的预测能力。     

Ash-forming elements in four Scandinavian wood species. Part 1: Summer harvest

Woody biomass in Finland and Sweden comprises mainly four wood species: spruce, pine, birch and aspen. To study the ash, which may cause problems for the combustion device, one tree of each species were cut down and prepared for comparisons with fuel samples. Well-defined samples of wood, bark and foliage were analyzed on 11 ash-forming elements: Si, Al, Fe, Ca, Mg, Mn, Na, K, P, S and Cl. The ash content in the wood tissues (0.2–0.7%) was low compared to the ash content in the bark tissues (1.9–6.4%) and the foliage (2.4–7.7%). The woods’ content of ash-forming elements was consequently low; the highest contents were of Ca (410–1340 ppm) and K (200–1310), followed by Mg (70–290), Mn (15–240) and P (0–350). Present in the wood was also Si (50–190), S (50–200) and Cl (30–110). The bark tissues showed much higher element contents; Ca (4800–19,100 ppm) and K (1600–6400) were the dominating elements, followed by Mg (210–2400), P (210–1200), Mn (110–1100) and S (310–750), but the Cl contents (40–330) were only moderately higher in the bark than in the wood. The young foliage (shoots and deciduous leaves) had the highest K (7100–25,000 ppm), P (1600–5300) and S (1100–2600) contents of all tissues, while the shoots of spruce had the highest Cl contents (820–1360) and its needles the highest Si content (5000–11,300). This paper presented a new approach in fuel characterization: the method excludes the presence of impurities, and focus on different categories of plant tissues. This made it possible to discuss the contents of ash element in a wide spectrum of fuel-types, which are of large importance for the energy production in Finland and Sweden.     

Contents in Volume 23,2014

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Performance assessment of some ice TES systems

In this paper, a performance assessment of four main types of ice storage techniques for space cooling purposes, namely ice slurry systems, ice-on-coil systems (both internal and external melt), and encapsulated ice systems is conducted. A detailed analysis, coupled with a case study based on the literature data, follows. The ice making techniques are compared on the basis of energy and exergy performance criteria including charging, discharging and storage efficiencies, which make up the ice storage and retrieval process. Losses due to heat leakage and irreversibilities from entropy generation are included. A vapor-compression refrigeration cycle with R134a as the working fluid provides the cooling load, while the analysis is performed in both a full storage and partial storage process, with comparisons between these two. In the case of full storage, the energy efficiencies associated with the charging and discharging processes are well over 98% in all cases, while the exergy efficiencies ranged from 46% to 76% for the charging cycle and 18% to 24% for the discharging cycle. For the partial storage systems, all energy and exergy efficiencies were slightly less than that for full storage, due to the increasing effect wall heat leakage has on the decreased storage volume and load. The results show that energy analyses alone do not provide much useful insight into system behavior, since the vast majority of losses in all processes are a result of entropy generation which results from system irreversibilities.     

NEXT GENERATION ENGINEERED MATERIALS FOR ULTRA SUPERCRITICAL STEAM TURBINES

正1 ABSTRACT To reduce the effect of global warming on our climate,the levels of CO2emissions should be reduced.One way to do this is to increase the efficiency of electricity production from fossil fuels.This will in turn reduce the amount of CO2emissions for a given power output.Using US practice for efficiency calculations,then a move from a typical US plant running at 37%efficiency to a 760℃/38.5 MPa(1 400/5 580 psi)plant running at 48%efficiency would reduce CO2emissions by 170kg/MW.hr or 25%.     

Effect of co-cultivation of Chlamydomonas reinhardtii with Azotobacter chroococcum on hydrogen production

Chlamydomonas reinhardtii cc124 and Azotobacter chroococcum bacteria were co-cultured with a series of volume ratios and under a variety of light densities to determine the optimal culture conditions and to investigate the mechanism by which co-cultivation improves H₂ yield. The results demonstrated that the optimal culture conditions for the highest H₂ production of the combined system were a 1:40 vol ratio of bacterial cultures to algal cultures under 200 μE m^?2 s^?1. Under these conditions, the maximal H₂ yield was 255 μmol mg^?1 Chl, which was approximately 15.9-fold of the control. The reasons for the improvement in H₂ yield included decreased O₂ content, enhanced algal growth, and increased H₂ase activity and starch content of the combined system.     

Aerodynamic performance effects of leading-edge geometry in gas-turbine blades

The purpose of this paper is to illustrate the advantages of the direct surface-curvature distribution blade-design method, originally proposed by Korakianitis, for the leading-edge design of turbine blades, and by extension for other types of airfoil shapes. The leading edge shape is critical in the blade design process, and it is quite difficult to completely control with inverse, semi-inverse or other direct-design methods. The blade-design method is briefly reviewed, and then the effort is concentrated on smoothly blending the leading edge shape (circle or ellipse, etc.) with the main part of the blade surface, in a manner that avoids leading-edge flow-disturbance and flow-separation regions. Specifically in the leading edge region we return to the second-order (parabolic) construction line coupled with a revised smoothing equation between the leading-edge shape and the main part of the blade. The Hodson–Dominy blade has been used as an example to show the ability of this blade-design method to remove leading-edge separation bubbles in gas turbine blades and other airfoil shapes that have very sharp changes in curvature near the leading edge. An additional gas turbine blade example has been used to illustrate the ability of this method to design leading edge shapes that avoid leading-edge separation bubbles at off-design conditions. This gas turbine blade example has inlet flow angle 0°, outlet flow angle −64.3°, and tangential lift coefficient 1.045, in a region of parameters where the leading edge shape is critical for the overall blade performance. Computed results at incidences of −10°,   −5°,   +5°,   +10° are used to illustrate the complete removal of leading edge flow-disturbance regions, thus minimizing the possibility of leading-edge separation bubbles, while concurrently minimizing the stagnation pressure drop from inlet to outlet. These results using two difficult example cases of leading edge geometries illustrate the superiority and utility of this blade-design method when compared with other direct or inverse blade-design methods.     

Exergetic evaluation of 5 biowastes-to-biofuels routes via gasification

This paper presents the exergy analysis results for the production of several biofuels, i.e., SNG (synthetic natural gas), methanol, Fischer–Tropsch fuels, hydrogen, as well as heat and electricity, from several biowastes generated in the Dutch province of Friesland, selected as one of the typical European regions. Biowastes have been classified in 5 virtual streams according to their ultimate and proximate analysis. All production chains have been modeled in Aspen Plus in order to analyze their technical performance. The common steps for all the production chains are: pre-treatment, gasification, gas cleaning, water–gas-shift reactions, catalytic reactors, final gas separation and upgrading. Optionally a gas turbine and steam turbines are used to produce heat and electricity from unconverted gas and heat removal, respectively. The results show that, in terms of mass conversion, methanol production seems to be the most efficient process for all the biowastes. SNG synthesis is preferred when exergetic efficiency is the objective parameter, but hydrogen process is more efficient when the performance is analyzed by means of the 1st Law of Thermodynamics. The main exergy losses account for the gasification section, except in the electricity and heat production chain, where the combined cycle is less efficient.     

Natural-gas fueled spark-ignition (SI) and compression-ignition (CI) engine performance and emissions

Natural gas is a fossil fuel that has been used and investigated extensively for use in spark-ignition (SI) and compression-ignition (CI) engines. Compared with conventional gasoline engines, SI engines using natural gas can run at higher compression ratios, thus producing higher thermal efficiencies but also increased nitrogen oxide (NO_x) emissions, while producing lower emissions of carbon dioxide (CO₂), unburned hydrocarbons (HC) and carbon monoxide (CO). These engines also produce relatively less power than gasoline-fueled engines because of the convergence of one or more of three factors: a reduction in volumetric efficiency due to natural-gas injection in the intake manifold; the lower stoichiometric fuel/air ratio of natural gas compared to gasoline; and the lower equivalence ratio at which these engines may be run in order to reduce NO_x emissions. High NO_x emissions, especially at high loads, reduce with exhaust gas recirculation (EGR). However, EGR rates above a maximum value result in misfire and erratic engine operation. Hydrogen gas addition increases this EGR threshold significantly. In addition, hydrogen increases the flame speed of the natural gas-hydrogen mixture. Power levels can be increased with supercharging or turbocharging and intercooling. Natural gas is used to power CI engines via the dual-fuel mode, where a high-cetane fuel is injected along with the natural gas in order to provide a source of ignition for the charge. Thermal efficiency levels compared with normal diesel-fueled CI-engine operation are generally maintained with dual-fuel operation, and smoke levels are reduced significantly. At the same time, lower NO_x and CO₂ emissions, as well as higher HC and CO emissions compared with normal CI-engine operation at low and intermediate loads are recorded. These trends are caused by the low charge temperature and increased ignition delay, resulting in low combustion temperatures. Another factor is insufficient penetration and distribution of the pilot fuel in the charge, resulting in a lack of ignition centers. EGR admission at low and intermediate loads increases combustion temperatures, lowering unburned HC and CO emissions. Larger pilot fuel quantities at these load levels and hydrogen gas addition can also help increase combustion efficiency. Power output is lower at certain conditions than diesel-fueled engines, for reasons similar to those affecting power output of SI engines. In both cases the power output can be maintained with direct injection. Overall, natural gas can be used in both engine types; however further refinement and optimization of engines and fuel-injection systems is needed.     

Controls on the Karaha–Telaga Bodas geothermal reservoir,Indonesia

Karaha–Telaga Bodas is a partially vapor-dominated, fracture-controlled geothermal system located adjacent to Galunggung Volcano in western Java, Indonesia. The geothermal system consists of: (1) a caprock, ranging from several hundred to 1600 m in thickness, and characterized by a steep, conductive temperature gradient and low permeability; (2) an underlying vapor-dominated zone that extends below sea level; and (3) a deep liquid-dominated zone with measured temperatures up to 353 °C. Heat is provided by a tabular granodiorite stock encountered at about 3 km depth. A structural analysis of the geothermal system shows that the effective base of the reservoir is controlled either by the boundary between brittle and ductile deformational regimes or by the closure and collapse of fractures within volcanic rocks located above the brittle/ductile transition. The base of the caprock is determined by the distribution of initially low-permeability lithologies above the reservoir; the extent of pervasive clay alteration that has significantly reduced primary rock permeabilities; the distribution of secondary minerals deposited by descending waters; and, locally, by a downward change from a strike-slip to an extensional stress regime. Fluid-producing zones are controlled by both matrix and fracture permeabilities. High matrix permeabilities are associated with lacustrine, pyroclastic, and epiclastic deposits. Productive fractures are those showing the greatest tendency to slip and dilate under the present-day stress conditions. Although the reservoir appears to be in pressure communication across its length, fluid, and gas chemistries vary laterally, suggesting the presence of isolated convection cells.     

Hydrogen production by steam-gasification of carbonaceous materials using concentrated solar energy – V. Reactor modeling,optimization, and scale-up

A chemical reactor for the steam-gasification of carbonaceous particles (e.g. coal, coke) is considered for using concentrated solar radiation as the energy source of high-temperature process heat. A two-phase reactor model that couples radiative, convective, and conductive heat transfer to the chemical kinetics is applied to optimize the reactor geometrical configuration and operational parameters (feedstock's initial particle size, feeding rates, and solar power input) for maximum reaction extent and solar-to-chemical energy conversion efficiency of a 5 kW prototype reactor and its scale-up to 300 kW. For the 300 kW reactor, complete reaction extent is predicted for an initial feedstock particle size up to 35 μm at residence times of less than 10 s and peak temperatures of 1818 K, yielding high-quality syngas with a calorific content that has been solar-upgraded by 19% over that of the petcoke gasified.