Stepwise superposition approximation approach for analytical solutions with non-zero initial concentration using existing solutions of zero initial concentration in contaminate transport

Analytical solutions for contaminant transport are widely used for both theoretical and practical purposes. However, many existing solutions are obtained subject to an initial condition of zero concentration, which is often unrealistic in many practical cases. This article proposed a stepwise superposition approximation approach to solve the non-zero initial concentration problem for first-type and third-type boundary conditions by using the existing zero initial concentration solution. Theoretical examples showed that the approach was highly efficient if a proper superposition scheme with relative concentration increments was constructed. The key parameter that controlled the convergence speed was the time increment (Δt) multiplied by the rate constant ( ). The approach served also as an alternative way to make a convenient concentration calculation even if the non-zero initial concentration solution of a problem was known.     

Evolution in physiochemical and cloud condensation nuclei activation properties of crop residue burning particles during photochemical aging

As a main form of biomass burning in agricultural countries, crop residue burning is a significant source of atmospheric fine particles. In this study, the aging of particles emitted from the burning of four major crop residues in China was investigated in a smog chamber.The particle size distribution, chemical composition and cloud condensation nuclei(CCN)activity were simultaneously measured. The properties of crop residue burning particles varied substantially among different fuel types. During aging, the particle size and mass concentration increased substantially, suggesting condensational growth by formation of secondary aerosols. The particle composition was dominated by organics. Aging resulted in considerable enhancement of organics and inorganics, with enhancement ratios of 1.24–1.44 and 1.33–1.76 respectively, as well as a continuous increase in the oxidation level of organics. Elevated CCN activity was observed during aging, with the hygroscopicity parameter κ varying from 0.16 to 0.34 for fresh particles and 0.19 to 0.40 for aged particles.Based on the volume mixing rule, the hygroscopicity parameter of organic components(κorg) was derived. κorgexhibited an increasing tendency with aging, which was generally consistent with the tendency of the O:C ratio, indicating that the oxidation level was related to the hygroscopicity and CCN activity of organic aerosols from crop residue burning. Our results indicated that photochemical aging could significantly impact the CCN activation of crop burning aerosols, not only by the production of secondary aerosols, but also by enhancing the hygroscopicity of organic components, thereby contributing to the aerosol indirect climate forcing.     

Optimizing the operation of the Qingshitan Reservoir in the Lijiang River for multiple human interests and quasi-natural flow maintenance

For reservoir operation, maintaining a quasi-natural flow regime can benefit river ecosystems, but may sacrifice human interests. This study took the Qingshitan Reservoir in the Lijiang River as a case, and developed an optimization model to explore a trade-off solution between social-economic interests and nature flow maintenance on a monthly base. The objective function considered irrigation, cruise navigation and water supply aspects. An index of flow alteration degree was proposed to measure the difference between the regulated discharge and the natural flow. The index was then used as an additional constraint in the model besides the conventional constraints on reservoir safety. During model solving, different criteria were applied to the index, representing various degrees of alteration of the natural flow regime in the river. Through the model, a relationship between social-economic interests and flow alteration degree was established. Finally, a trade-off solution of the reservoir operation was defined that led to a favorable social-economic benefit at an acceptable alteration of the natural flow.     

Rapid adsorption of toxic Pb(Ⅱ) ions from aqueous solution using multiwall carbon nanotubes synthesized by microwave chemical vapor deposition technique

Multiwall carbon nanotubes(MWCNTs) were synthesized using a tubular microwave chemical vapor deposition technique, using acetylene and hydrogen as the precursor gases and ferrocene as catalyst. The novel MWCNT samples were tested for their performance in terms of Pb(Ⅱ)binding. The synthesized MWCNT samples were characterized using Fourier Transform Infrared(FT-IR), Brunauer, Emmett and Teller(BET), Field Emission Scanning Electron Microscopy(FESEM) analysis, and the adsorption of Pb(Ⅱ) was studied as a function of p H,initial Pb(Ⅱ) concentration, MWCNT dosage, agitation speed, and adsorption time, and process parameters were optimized. The adsorption data followed both Freundlich and Langmuir isotherms. On the basis of the Langmuir model, Qmaxwas calculated to be 104.2 mg/g for the microwave-synthesized MWCNTs. In order to investigate the dynamic behavior of MWCNTs as an adsorbent, the kinetic data were modeled using pseudo first-order and pseudo second-order equations. Different thermodynamic parameters, viz., ΔH0, ΔS0and ΔG0were evaluated and it was found that the adsorption was feasible, spontaneous and endothermic in nature. The statistical analysis revealed that the optimum conditions for the highest removal(99.9%) of Pb(Ⅱ) are at p H 5, MWCNT dosage 0.1 g, agitation speed 160 r/min and time of 22.5 min with the initial concentration of 10 mg/L. Our results proved that microwave-synthesized MWCNTs can be used as an effective Pb(Ⅱ) adsorbent due to their high adsorption capacity as well as the short adsorption time needed to achieve equilibrium.     

Direct numerical simulation of the motion of circular pollutant particles in Newtonian fluid

An improved implementation of distributed multiplier/fictitious domain method is presented for the direct numerical simulation of particulate flow. The key improvement is to replace a finite-element triangulation for the velocity and a “twice-coarser“ triangulation for the pressure with a rectangular discretization for the velocity and pressure. For code validation, the sedimentation of a single particle in a twodimensional channel was simulated. The results showed that the simulation is independent of the mesh size as well as the time step. The comparison between experimental data and this simulation showed that our code can give a more accurate simulation on the motion of particlesthan previous DLM code. The code was then applied to simulate the sedimentation of 600 particles in a rectangular box. The falling course ispresented and discussed. At the same time, this simulation also demonstrates that the method presented in this paper can be used for solving the initial problems involving a lager number of particles exaclly with computing durations kept at acceptable levels.     

Settling basin design in a constructed wetland using TSS removal efficiency and hydraulic retention time

Using total suspended solid （TSS） removal efficiency and hydraulic retention time （HRT） as design parameters a design guideline of a settling basin in a constructed wetland （CW） was suggested; as well as management of sediment and particle in the settling basin. The CW was desiEned to treat the piggery wastewater effluent from a wastewater treatment plant during dry days and stonnwater runoff from the surrounding paved area during wet days. The first settling basin （FSB） in the CVV was theoretically designed with a total storage volume （TSV） of 453 ms and HRT of 5.5 hr. The amount of sediment and particles settled at the FSB was high due to the sedimentation and interception of plants in the CVV. Dredging of sediments was performed when the retention rate at the FSB decreased to approximately 80%. Findings showed that the mean flow rate was 21.8 m3/hr less than the designed flow rate of 82.8 m3/hr indicating that the FSB was oversize and operated with longer HRT （20.7 hr） compared to the design HRT. An empirical model to estimate the length of the settling basin in the CW was developed as a function of HRT and desired TSS removal efficiency. Using the minimum tolerable TSS removal efficiency of 30%, the length of the FSB was estimated to be 31.2 m with 11.8 hr HRT.     

Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China

Land surface temperature （LST）, which is heavily influenced by urban surface structures, is a significant parameter in urban environmental analysis. This study examined the effect impervious surfaces （IS） spatial patterns have on LST in Beijing, China. A classification and regression tree model （CART） was adopted to estimate IS as a continuous variable using Landsat images from two seasons combined with QuickBird. LST was retrieved from the Landsat Thematic Mapper （TM） image to examine the relationships between IS and LST. The results revealed that CART was capable of consistently predicting LST with acceptable accuracy （correlation coefficient of 0.94 and the average error of 8.59%）. Spatial patterns of IS exhibited changing gradients across the various urban-rural transects, with LST values showing a concentric shape that increased as you moved from the outskirts towards the downtown areas. Transect analysis also indicated that the changes in both IS and LST patterns were similar at various resolution levels, which suggests a distinct linear relationship between them. Results of correlation analysis further showed that IS tended to be positively correlated with LST, and that the correlation coefficients increased from 0.807 to 0.925 with increases in IS pixel size. The findings identified in this study provide a theoretical basis for improving urban planning efforts to lessen urban temperatures and thus dampen urban heat island effects.     

Sedimentation of short cylindrical pollutants with mechanical contacts

Lattice Boltzmann method and elastic particle collision model were used to investigate the sedimentation of short cylindrical pollutant particles with mechanical contacts for varying bulk number density ε and terminal Reynolds number ReT. The corresponding experiments were performed as a comparison. The clusters of pollutant particles with an inverted “T” structure were observed, the pollutant particles for high ε and large ReT scattered wider than that for low ε and small ReT. The sedimentation velocities increased suddenly at the initial stage, then decreased drastically, after that swayed around and approached to a steady value. The time to steady state did not depend on ε and ReT. The effect of particle interactions was to hinder the average sedimentation velocity, and hindrance was directly proportional to ε. The orientation distributions of pollutant particles depended on ReT and ε, especially on the former. Both the standard deviations of vertical and horizontal velocity, the former was larger than the latter, were nearly independent on ε and ReT.     

Determination of the effective density and fractal dimension of PM emissions from an aircraft auxiliary power unit

Gas turbine particulate matter (PM) emissions contribute to air quality degradation and are dangerous to both human health and the environment. Currently, PM mass concentrations determined from gravimetric measurements are the default parameter for gas turbine emissions compliance with PM regulations. The measurement of particle size however, is of significant interest due to its specific effects on health and climate science. The mass concentration can be determined from the number-size distribution measurement but requires the experimental evaluation of effective density of a number of particles to establish the power-law relationship. In this study, the effective density of PM emissions from an aircraft Auxiliary Power Unit (APU) with petroleum diesel, conventional aviation fuel (Jet A-1) and a multicomponent surrogate fuel (Banner NP 1014) as combusting fuels have been compared. An experimental configuration consisting of a Differential Mobility Analyzer, a Centrifugal Particle Mass Analyzer and a Condensation Particle Counter (DMA-CPMA-CPC) was deployed for this purpose. Overall, a decrease in the effective density (220–1900 km? 3) with an increase in the particle size was observed and found to depend on the engine operating condition and the type of fuel undergoing combustion. There was a change in the trend of the effective densities between the PM emissions generated from the fuels burnt and the engine operating conditions with increasing particle size.     

Three-dimensional unstructured-mesh eutrophication model and its application to the Xiangxi River, China

The Xiangxi River is one of the main tributaries in the Three Gorges reservoir, with the shortest distance to the Three Gorges Project Dam. Severe and frequent algal bloom events have occurred frequently in the Xiangxi River in recent years. Therefore, the current study develops a three-dimensional unstructured-mesh model to investigate the dynamic process of algal bloom. The developed model comprises three modules, namely, hydrodynamics, nutrient cycles, and phytoplankton ecological dynamics. A number of factors, including hydrodynamic condition, nutrient concentration, temperature, and light illumination, that would affect the evolution of phytoplankton were considered. Moreover, the wave equation was used to solve the free surface fluctuations and vertical Z-coordinates with adjustable layered thicknesses. These values, in turn, are suitable for solving the algal bloom problems that occurred in the river style reservoir that has a complex boundary and dramatically changing hydrodynamic conditions. The comparisons between the modeling results and field data of years 2007 and 2008 indicate that the developed model is capable of simulating the algal bloom process in the Xiangxi River with reasonable accuracy. However, hydrodynamic force and external pollution loads affect the concentrations of nutrients, which, along with the underwater light intensity, could consequently affect phytoplankton evolution. Thus, flow velocity cannot be ignored in the analysis of river algal bloom. Based on the modeling results, building an impounding reservoir and increasing the releasing discharge at appropriate times are effective ways for controlling algal bloom.     

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.     

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet(China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.     

改进BFO优化BPNN的自来水混凝加药预测

本文给出一种量子粒子群（QPSO）算法、改进菌群觅食（IBFO）算法优化反向传播神经网络（BPNN）的混凝投药预测模型,利用量子粒子群的个体极值与群体极值更新细菌觅食算法趋化过程中细菌位置;通过细菌协同改进趋化算子提高优化精度,结合差分算法改进繁殖算子解决部分维度退化问题,加入轮盘赌方法作为选择机制改进迁移算子来克服优化过程中优秀解消失的缺陷;进而优化BP神经网络的权值、阈值以此预测混凝剂投药量.对云南某自来水厂的数据进行离线训练和模型测试,结果表明,所提算法预测结果的均方误差（MSE）达0.0116mg/L,平均绝对误差百分比（MAPE）达1.36%,在预测精度和稳定性上优于BFO-BPNN、PSO-BPNN等模型.     

蛙跳算法优化的地下水质评价的参数化组合算子模型

传统的参数化多元组合算子模型在进行对数变换后,采用最小二乘法求解模型参数。在满足构建的优化目标函数条件下,直接用基于群集智能的混合蛙跳算法对参数化组合算子模型中的参数进行优化,避免了传统解法过程中需要进行的对数变换,因而使参数求解变得简化。改进后的参数化组合算子模型被应用于地下水水质评价,其评价结果与用其他多种方法的评价结果基本一致。从而表明:混合蛙跳算法优化得出的地下水水质评价参数化组合算子模型为地下水水质评价提供了一种简便和实用的新方法。     

ABC算法优化SVR的磨损故障预测模型

目的为了提高故障预测的精度,针对支持向量回归SVR(Support vector machine for regression,SVR)参数选择困难的问题,提出一种采用人工蜂群(artificial bee colony,ABC)算法优化支持向量回归(SVR)的故障预测模型(ABC-SVR)。方法该模型先对样本数据进行重构,然后将故障预测误差(适应度)作为优化目标,通过ABC算法寻优找到最优的SVR参数,建立故障预测模型。最后通过实例仿真验证模型的优越性。结果采用ABC算法优化的SVR故障预测模型进行时间序列预测,能够较好地跟踪发动机滑油金属元素浓度的变化过程,并且能够提前2个取样时间预测异常情况的出现。结论 ABC-SVR模型有效解决了SVR参数选择难题,能够更加准确地表现故障变化规律,提高了故障预测精度。     

基于PSO优化逻辑斯蒂曲线的水资源安全评价模型

论文引入“压力-状态-响应”框架模型构建区域水资源安全定量评价的指标体系,采用逻辑斯蒂（Logistic）曲线模拟区域水资源安全评价,公式中的参数采用粒子群算法（PSO）进行优化,并用灵敏度分析的方法对公式进行了可靠性分析。优化好的Logistic指数公式用于安徽省16个地级市水资源安全评价,计算得到各地级市评价指数和相应的评价等级,并对压力层、状态层、响应层子系统进行分析。评价结果表明,基于粒子群算法优化的Logistic指数公式用于区域水资源安全评价,具有合理性和可行性,能为区域水资源规划与管理决策提供科学依据。     

基于气象相似准则的城市空气质量预报模型

为提高城市空气质量预报准确率,文章在传统BP神经网络的基础上提出了基于气象相似准则的样本优化方法,建立了三层样本筛选优化机制,确定了阀值及权重矩阵,从而建立了城市空气质量动态预报模型。将模型应用在广州8个空气质量监测站点的预报上,并与传统的BP神经网络空气质量预报模型进行了对比分析,效果良好。分析结果表明,广州8个空气质量监测站点的SO2、NO2、PM10/2.5的实测值与预报值的平均绝对误差分别为0.016 mg/m3、0.014 mg/m3、0.020 mg/m3,级别预报准确性评分分别为89.6、92.6和84.6,预报准确度综合评分达81.6,并且比传统神经网络模型具有更高的预报精度。     

基于人工免疫算法的离散隐马尔科夫故障诊断模型优化

目的解决离散隐马尔科夫模型在行星齿轮箱故障诊断中的自适应性和泛化性问题。方法建立人工免疫优化模型,将包含易被误判样本的多样本集作为抗原,以其正确识别率为适应度函数,不断对初始观测矩阵进行增殖、变异和选择,获得识别率最高时的初始观测矩阵,利用人工免疫算法对隐马尔科夫故障诊断模型的初始观测矩阵进行优化。结果将该方法应用于行星齿轮箱的故障诊断中,通过不同工况下的对比试验、单样本和多样本优化对比试验,验证了优化后的隐马尔科夫故障诊断模型的诊断效果。结论优化后的隐马尔科夫故障诊断模型具有更好的适应性,诊断精度显著提高。     

基于替代模型的地下水DNAPLs污染源反演识别

应用基于核极限学习机替代模型的模拟-优化理论和方法研究解决了地下水DNAPLs污染源及含水层参数的同步反演识别问题.结果表明：1）核极限学习机替代模型对模拟模型有较高的逼近精度,能够识别并模仿模拟模型的输入-输出关系,绝大部分相对误差小于5%,平均相对误差仅有2.98%;2）以替代模型代替模拟模型,大幅度地减小了模拟-优化过程的计算负荷,将反演识别时间由传统方法的83天减少到3小时,并能够保持较高的计算精度;3）应用基于模拟退火的粒子群优化算法求解优化模型,能够以较快的速度搜寻到全局最优,同时避免搜索过程陷于局部极小解.     

基于粒子群算法的城市垃圾中转站的空间布局研究

随着城市化的进程，垃圾处理设施成为影响城市化质量的重要指标。依据人们实际所关注的垃圾处理设施的总成本和负效应两个因素，在前人研究的基础上，建立了垃圾收运多目标模型，使得总成本和负效应最优化。根据模型设计了粒子群算法，该算法属于智能算法，且精度高，收敛快，在许多领域也得到广泛应用。用设计的粒子群算法并结合案例求出了Pareto最优解，给出三种决策方案，验证了模型和算法的有效性和可行性，为决策者提供了一种理论参考。