一个求解二维Navier—Stokes方程组的数值模型

本文建立和开发了一个用于求解二维Navier-Stokes方程组的数学模型，这个模型采用Chorin提出的Projection1方式来解耦基本方程组的流速和压力，空间离散采用有限单元法，而时间离散则采用semi-implicit格式。为了验证模型的正确性，作者计算了二维空腔流动并与其他一些研究者的结果进行了比较，结果令人满意。     

LATTICE BGK MODEL FOR THE INCOMPRESSIBLE NAVIER-STOKES EQUATION

1 .　INTRODUCTIONInthelastdecadeorso ,theLatticeBoltz mann (LB)methodhasemergedasanewandef fectivenumericaltechniqueofComputationalFluidDynamics (CFD) [1 3] ,especially ,theLBGKmodelhasachieved greatsuccessinsimulationsoffluidflowsandinmodeling physicsinfluids[4 9] .ButLBGKmodelshouldbeviewedasanarticicialcompressibleschemetosimulateincompressiblefluid[10 ] .Inotherwords,throughmultiscalingex pansionandChapman Enskog procedure[11] ,thecompressibleNavier Stokesequationscanberecov …     

Hybrid ANN–GA model for predicting turbidity and chlorophyll-a concentrations

The transport and fate of admixtures at coastal zones are driven, or at least modulated, by currents. In particular, in tide-dominated areas due to higher near-bottom shear stress at strong currents, sediment concentration and turbidity are expected to be at maximum during spring tide, while algal growth rate likely is peaking up at slack currents during neap tide. Varying weather and atmospheric conditions might modulate the said dependencies, but the water quality pattern still is expected to follow the dominant tidal cycle. As tidal cycling could be predicted well ahead, there is a possibility to use water quality and hydrodynamic high-resolution data to learn past dependencies, and then use tidal hydrodynamic model for nowcasting and forecasting of selected water quality parameters.This paper develops data driven models for nowcasting and forecasting turbidity and chlorophyll-a using Artificial Neural Network (ANN) combined with Genetic Algorithm (GA). The use of GA aims to automate and enhance ANN designing process. The training of the ANN model is done by constructing input–output mapping, where hydrodynamic parameters act as an input for the network, while turbidity and chlorophyll-a are the corresponding outputs (desired target). Afterward, the prediction is carried out only by employing computed water surface elevation as an input for the trained ANN model. The proposed data driven model has successfully revealed complex relationships and utilized its experiential knowledge acquired from the training process for facilitating the subsequent use of the data driven model to yield an accurate prediction.     

汉江上游地区大尺度分布式水文模型与气象模型耦合应用试验

汉江发源于陕西省秦岭南麓,在其上游地区,局地性的洪灾或旱灾较易频繁发生。为改进洪水预报精度,构建了用于汉江上游地区的基于大尺度分布式水文模型和气象模型耦合的洪水预报系统,并于2007年6～8月在该流域的出口控制站白河站进行了流量模拟试验。其间,利用LSHM水文模型（5km×5km水平网格）分别基于地面气象观测资料和MM5模型（最内层水平空间尺度9km×9km）的预报产品对白河站进行流量模拟试验：同时,也利用MM5的24h预见期信息进行逐日流量作业预报试验。初步结果表明,将分布式水文模型与气象模型耦合应用进行洪水预报具有较好的发展潜力,值得推广应用。     

Long Term Streamflow Forecasting Using a Hybrid Entropy Model

In this paper, the development and evaluation of an entropy based hybrid data driven model coupled with input selection approach and wavelet transformation is investigated for long-term streamflow forecasting with 10 years lead time. To develop and test the models, data including 45 years of monthly streamflow time series from Taleghan basin, located in northwest of Tehran, are employed. For this purpose, first the performance of a maximum entropy forecasting model is evaluated. To boost the accuracy, an auto-correlation method with %95 confidence levels was carried out to determine the optimum order of the entropy model. Nevertheless, the basic entropy model, as expected, was only able to reach Nash-Sutcliffe efficiency (NSE) index of 0.35 during the test period. On the other hand, data driven models such as artificial neural networks (ANN) have shown to yield good accuracy in modeling complicated and nonlinear systems. Thus, to improve the performance of the maximum entropy model, an entropy-based hybrid model using evolutionary ANN (ENN) was proposed for further investigation. The proposed model with seasonality index substantially improved the test NSE to 0.51 and provided more accurate results than the basic entropy model. Moreover, when wavelet transform was applied to preprocess the input data, the model shows a slight improvement (NSE?=?0.54).     

A PARALLEL NUMERICAL MODEL OF SOLVING N-S EQUATIONS BY USING SEQUENTIAL REGULARIZATION METHOD

1 .　ＩＮＴＲＯＤＵＣＴＩＯＮＴｈｅＮａｖｉｅｒ Ｓｔｏｋｅｓ (Ｎ Ｓ)ｅｑｕａｔｉｏｎｓｈａｖｅｂｅｅｎｗｉｄｅｌｙｕｓｅｄｉｎｉｎｄｕｓｔｒｙ ,ｓｕｃｈａｓｓｈｉｐ ｂｕｉｌｄｉｎｇｉｎ ｄｕｓｔｒｙ ,ａｅｒｏｎａｕｔｉｃｉｎｄｕｓｔｒｙ .Ｆｒｏｍｍ[1] ｓｏｌｖｅｄｔｈｅＮ ＳｅｑｕａｔｉｏｎｓｂｙｕｓｉｎｇｔｈｅＤｕｒｆｏｒｔ Ｆｒａｎｋｅｌｄｉｆｆｅｒ ｅｎｃｅｓｃｈｅｍｅ .Ｈａｒｌｏｗ[2 1] ｄｉｓｃｕｓｓｅｄｔｈｅＭａｒｋｅｒａｎｄＣｅｌｌｍｅｔｈｏｄ (ｏｒＭＡＣ)ｆｏｒｓｏｌｖｉｎｇｔｈｅＮ …     

THE GENERATION, EVOLUTION AND PHYSIOLOGICAL RESPONSES OF INTRACELLUAR CALCIUM OSCILLATIONS AND WAVES

The Atri intracellular calcium oscillations model was extended, and two new models were established. Furtherrnore, a unified model of the protein phosphorylation driven by cytosolic calcium oscillations was constructed. The numerical results obtained verified related experimental conclusions. And the analytical expressions of intracellular calcium spiral and target waves in the Xenopus laevis oocyte were obtained, resulting in velocity and waveforrn of calcium solitary pulse wave were found.     

基于CMADS驱动下SWAT模型的敖江流域径流模拟

目前针对气象、水文资料不足的小尺度流域进行径流模拟的研究相对较少。选取敖江流域为研究区,利用中国大气同化驱动数据集(CMADS)驱动SWAT模型对该流域2008—2016年进行逐月径流模拟,并使用水文比拟法结合邻近的2个传统气象站计算出模拟时段的观测数据以完成模型参数的率定与验证。结果表明:模拟结果与观测值较吻合,率定期(2010—2013年)评价指标决定系数R²和Nash-Suttcliffe系数NS分别为0.84和0.76,验证期(2014—2016年)两者分别为0.85和0.74,均达到了模型的评价要求。研究成果表明CMADS驱动下的SWAT模型适用敖江流域的径流模拟,采用水文比拟法适合在水文资料不足的地区进行径流计算,可为缺少气象与水文资料的小尺度流域进行径流模拟提供参考。     

A combined hydraulic and biological SBR model

A sequencing batch reactor (SBR) model was developed consisting of six continuous stirred tank reactors which describe the hydraulic flow patterns occurring in different SBR phases. The model was developed using the results of computational fluid dynamics (CFD) simulation studies of an SBR reactor under a selection of dynamic operational phases. Based on the CFD results, the model structure was refined and a simplified 'driver' model to allow one to mimic the flow pattern driven by the external operational conditions (influent, aeration, mixing) was derived. The resulting model allows the modeling of biological processes, settlement and hydraulic conditions of cylindrical SBRs.     

PREDICTION OF LOADING DISTRIBUTION AND HYDRODYNAMIC MEASUREMENTS FOR PROPELLER BLADES IN A RIM DRIVEN THRU-STER

This article presents an approach which employs a commercial Reynolds-Averaged Navier-Stokes(RANS)solver to predict the steady wake field and loading distributions for a rim driven thruster.Four different cases of propeller blades are chosen to be calculated with the presented method.The propeller blade radial circulation and chordwise circulation density distributions are analyzed.The maximum radial circulation is found at the blade tip,which is different from conventional shaft driven propeller.The numerical results indicate that there is no tip leakage vortex in rim driven propulors.But there exist the tip joint vortex and the root region vortex.Bollard characteristics are calculated by taking rim surface effect into account.From the predicted results the second case in this paper is selected as the final one to perform hydrodynamic experiment.The calculation results with empirical rim surface corrections are compared with the measurement.It shows that the developed numerical method can well predict hydrodynamic performances of the rim driven thruster.     

A COUPLED MODEL OF HYDRODYNAMICS AND WATER QUALITY FOR YUQIAO RESERVOIR IN HAIHE RIVER BASIN

In order to simulate the characteristics of hydrodynamic field and mass transport processes in the Yuqiao Reservoir （YQR）, a 2-D coupled model of hydrodynamics and water quality was developed, and the water-quality related state variables in this model included CODMn, TN and TP. The hydrodynamic model was driven by employing observed winds and daily measured flow data to simulate the seasonal water cycle of the reservoir. The simulation of the mass transport and transformation processes of CODMn, TN and TP was based on the unsteady diffusion equations, driven by observed meteorological forcing and external loadings, with the fluxes form the bottom of reservoir and the plant photosynthesis and respiration as internal sources and sinks. A finite volume method and Alternating Direction Implicit （ADI） scheme were used to solve these equations. The model was calibrated and verified by using the data observed from YQR in two different years. The results showed that in YQR, the wind-driven current was an important style of lake current, while the concentration of water quality item was decreasing from east to west because of the external pollutant loadings. There was a good agreement between the simulated and measured values, with the minimal calculation error percent of 0.1% and 2.6% and the mean error percent of 44.0% and 51.2% for TN and TP separately. The simulation also showed that, in YQR, the convection was the main process in estuaries of inflow river, and diffusion and biochemical processes dominate in center of reservoir. So it was necessary to build a pre-pond to reduce the external loadings into the reservoir.     

基于数据驱动模型的入海污染源排污削减优化方法研究

陆源污染物排放是影响近岸海域水环境生态质量最重要的因素。建立了数据驱动模型人工神经网络算法和海域水质模型相耦合的入海污染源排污削减优化方法:基于水质模型污染源项设计工况的数值计算,获得海域内部观测点污染物浓度;以数据驱动模型人工神经网络算法建立状态变量(海域内部观测点污染物浓度)同控制变量(污染源项)之间的非线性关系;以海域内部观测点环境目标数据为输入,模拟推算出目标前提下的各污染源项入海允许排放量;最终结合实际排污量,核算获得削减量。以连云港徐圩海域4个入海污染源无机氮的排污削减研究验证方法的有效性,结果表明:数据驱动人工神经网络方法具有非线性、简洁、灵活的优点,可以为近岸海域水污染控制工作提供基础数据支撑;同时研究中采用分区排污削减的方式更能体现兼顾公平的基本原则,优化入海污染源排污削减工作。     

神经网络方法在桩基设计中的应用

根据钻孔桩和打击桩的原型试验观测的数据 ,运用人工智能方法对横向承载桩和轴向承载桩的工作特性进行模拟 ,并利用标准贯入试验 (SPT N)值和桩的几何特性等简单的输入数据 ,开发出相应的优化神经网络模型 ;然后 ,运用反向传播神经网络模型和广义回归神经网络模型分别对某工程的钢筋混凝土桩进行分析 ,并将求得的预测结果与常规设计法的结果进行比较 ,结果表明神经网络方法比传统方法有明显的优越性 ,在实际工程设计中具有重要的参考价值和现实意义。     

太湖风生流及污染物输移扩散数值模拟

建立高精度的太湖三维风生流数值模型和风生流-污染物耦合数值模型,分析了盛行风作用下的太湖风生流特征和风生流驱动下的太湖污染物输移特征。结果表明:稳定后的太湖风生流场,表层流速大于底层流速,表层流向基本上同风向一致,底层流向则与表层大致相反,具有补偿流的特征;风向能显著影响太湖风生流的形态和结构;在垂向扩散作用下,太湖污染物质量浓度沿水深方向上近似均匀分布;在定常风作用下,太湖北部的湖湾区出现多个小尺度闭合环流,不利于污染物的输移扩散,对太湖水环境会产生不利影响。     

A LATTICE BOLTZMANN SUBGRID MODEL FOR LID-DRIVEN CAVITY FLOW

In recent years, the Lattice Boltzmann Method (LBM) has developed into an alternative and promising numerical scheme for simulating fluid flows and modeling physics in fluids. In order to propose LBM for high Reynolds number fluid flow applications, a subgrid turbulence model for LBM was introduced based on standard Smagorinsky subgrid model and Lattice Bhatnagar-Gross-Krook (LBGK) model. The subgrid LBGK model was subsequently used to simulate the twodimensional driven cavity flow at high Reynolds numbers. The simulation results including distribution of stream lines, dimensionless velocities distribution, values of stream function, as well as location of vertex center, were compared with benchmark solutions, with satisfactory agreements.     

SUSPENDED SEDIMENT TRANSPORT IN THE OFFSHORE NEAR YANGTZE ESTUARY

Based on the Estuarine, Coastal and Ocean Modeling System with Sediments （ECOMSED） model, a 3-D hydrodynamic-transport numerical model was established for the offshore area near the Yangtze Estuary in the East China Sea .The hydrodynamic module was driven by tide and wind. Sediment module included sediment resuspension, transport and deposition of cohesive and non-cohesive sediment. The settling of cohesive sediment in the water column was modeled as a fimction of aggregation （flocculation） and deposition. The numerical results were compared with observation data for August, 2006. It shows that the sediment concentration reduces gradually from the seashore to the offshore area. Numerical results of concentration time series in the observation stations show two peaks and two valleys, according with the observation data. It is mainly affected by tidal current. The suspended sediment concentration is related to the tidal current during a tidal cycle, and the maximum concentration appears 1 h-4 h after the current maximum velocity has reached.     

Evaluation of numerical wave model for typhoon wave simulation in South China Sea

The simulating waves nearshore (SWAN) model has typically been designed for wave simulations in near-shore regions. In this study, the model's applicability to the simulation of typhoon waves in the South China Sea (SCS) was evaluated. A blended wind field, consisting of an interior domain based on Fujita's model and an exterior domain based on Takahashi's model, was used as the driving wind field. The waves driven by Typhoon Kai-tak over the SCS that occurred in 2012 were selected for the numerical simulation research. Sensitivity analyses of time step, grid resolution, and angle resolution were performed in order to obtain optimal model settings. Through sensitivity analyses, it can be found that the time step has a large influence on the results, while grid resolution and angle resolution have a little effect on the results.     

THE NUMERICAL CALCULATION FOR THE STERN FLOW OF THREE DIMENSIONAL SURFACE SHIP WITH MULTI-PRO-PELLERS IN OPERATION

In this paper the complex structure and pattern of ship stern flow driven by multi-propellers is simulated numerically by using RANS equations with K-ε turbulence model and propeller lifting surface theory as essential research tool and coupling the computer code of ship stern flow to the computer code of propeller performance prediction through the medium of body force.A ship model with four propellers is selected as the numerical example.Detailed computational results are presented graphically and the qualitative and quantitative analysis is made. Finally,the comparison between the calculated result and the available experimental data is made.The agreement between them is satisfactory.     

基于模糊证据权模型的长汀县水土保持措施适宜性评价

在水土保持措施的适宜性评价中,评价因子的选取和权重的确定是值得探讨的问题。为避免因子选取和权重确定的主观随意性,引入集知识和数据驱动为一体的模糊证据权模型。以福建省长汀县封禁措施为研究对象,选取自然适宜性和社会适宜性2方面共7个因子,综合各因子参数计算后验概率,得到长汀县水土保持措施适宜性分级图。结合2014—2015年封禁措施分布情况进行分析,结果表明:高度适宜占38.5％,中度适宜占43.5％,一般适宜占9.2％,中度适宜级别以上占82%,与实际情况有较高的吻合性。这说明模糊证据权模型能够客观、准确地对水土保持措施进行适宜性评价,可以为政府配置水土保持措施提供决策参考和理论依据。     

神经网络方法在桩基设计中的应用

 根据钻孔桩和打击桩的原型试验观测的数据,运用人工智能方法对横向承载桩和轴向承载桩 的工作特性进行模拟,并利用标准贯入试验(SPT N)值和桩的几何特性等简单的输入数据,开 发出相应的优化神经网络模型;然后,运用反向传播神经网络模型和广义回归神经网络模型分 别对某工程的钢筋混凝土桩进行分析,并将求得的预测结果与常规设计法的结果进行比较, 结果表明神经网络方法比传统方法有明显的优越性,在实际工程设计中具有重要的参考价值 和现实意义。