Interactions of wind and density driven currents in North Sea ROFIs—a model study

Three different versions of a baroclinic three-dimensional circulation model of the North Sea are used to obtain information on the wind and density interactions in the North Sea ROFIs (Regions Of Freshwater Influence): the standard version with fully prognostic treatment of salinity and temperature is compared to a barotropic model run on the same grid on the one hand and to an also fully prognostic model run on a four times coarser grid on the other hand. In order to gain knowledge on the wind and density interactions, two opposing wind directions are chosen for investigation, namely a time of strong north wind, 21st–28th April 1982, and a time of strong southwest wind, 22nd–24th May 1982. In the April case the effect of the salinity gradients on the border of the ROFIs of Rhine, Weser, Ems and Elbe, i.e. along the continental shore, is shown to lead to a clear enhancement of the mean surface currents. In May this result is partly disguised by the additional effect of the thermocline in the deeper parts of the North Sea, i.e. in the classical shelf sea regime region. Nevertheless, the same pattern of enhanced mean surface currents along the coast is detected and is of the same order of magnitude as in the April case. It is thus concluded that although the circulation in the North Sea is reversed by the wind, the density induced component of the general circulation is modified only slightly.     

Sequential data assimilation in an upwelling influenced estuary

We have evaluated the impact of assimilating chlorophyll, nitrate, phosphate, silicate and ammonium into a coupled 1D hydrodynamic ecosystem model (GOTM-ERSEM) in an upwelling influenced estuary. The assimilation method chosen is the Ensemble Kalman Filter (EnKF), which has been demonstrated to improve field estimates of key variables (chlorophyll, nutrients) for bulk algal bloom prediction. The 1D model has been set up for a central station inside the Ría de Vigo (Spain). Data from bi-weekly surveys are used to constrain the model. Temperature and salinity profiles are used to ensure the correct representation of the water structure through a relaxation scheme. Chlorophyll extracts and nutrients at three depths are assimilated sequentially during 1 year simulation (1991). The assimilation period includes episodes of active upwelling and downwelling. All five assimilated variables are successfully constrained and represent a large improvement on the reference simulation (without assimilation). Small divergences can be related to poorly resolved physical processes in the model. The assimilation was further evaluated by comparing observed biomass partitioning with model results. Diatoms accounted for the largest biomass update and the largest improvement in terms of percentage of variance explained (R²). This is particularly significant as they represent the 46% of the yearly integrated observed biomass of the planktonic autotrophs. Nonetheless the R² value was low for all phytoplankton groups. Bacteria and nanoflagellates showed an improvement with respect to their yearly Root Mean Square (RMS), while the other functional groups worsen or remained unaffected. Chlorophyll assimilation was responsible for most of the impact on the phytoplankton biomass with small contributions from the silicate. It had minor impact on the updates of nutrients which in turn corrected the state variables related to the detrital pool. In this current setting, combined assimilation of chlorophyll and nutrients is not sufficient to produce a skillful simulation of the phytoplankton succession.     

铁舾装件快速建模方法研究

通过对不规则铁舾装件模型的分析和概括,提出以特征码串描述具体模型的方法,从而形成标准程序,进行快速建模,并以栏杆扶手的快速建模技术为例,阐述了以标准化设计为基础的铁舾装件快速建模方法的可行性。     

Swimming for survival: A role of phytoplankton motility in a stratified turbulent environment

We investigate a role for vertical migration in stratified coastal water, where the swimming speed is generally significantly less than the typical turbulent fluctuations in a tidally-mixed bottom layer. In our modelling approach we use a k- turbulence model to describe the physical forcing, a Lagrangian random walk model to describe the vertical displacement of individual cells in response to turbulence and due to cell motility, and a phytoplankton growth model to direct the swimming behaviour of the phytoplankton according to their light and nutrient requirements. The model results show how the cells form a stable subsurface chlorophyll maximum (SCM) at the base of the thermocline where episodic tidal turbulence causes erosion of part of the SCM biomass into the bottom mixed layer (BML). We then focus on the question of whether an ability to swim (weakly, compared to typical bottom layer turbulent intensities) provides any advantage by allowing return to the SCM. Our results show that tidal turbulence in the BML helps both motile and neutrally-buoyant cells by periodically pushing them into the base of the thermocline. Motile cells then have the advantage that they can swim further into the thermocline towards higher light which also reduces the likelihood of being re-mixed back into the BML.     

实船数据处理建模及仿真系统

为了使科研人员更方便地使用船舶试验数据,采用VB与Matlab混合编程,开发了一套集数据提取、数据处理、建模、仿真及比较功能于一体的实船数据处理、建模及仿真系统,利用育鲲轮试验数据对本系统进行测试,测试效果令人满意。系统界面美观,简捷易用,功能完备。     

新能源发电系统低电压穿越测试用试验电网数学建模

在新能源发电系统低电压穿越（LVRT）测试时,需要研究试验电网的各种电压跌落故障特性及其对新能源发电系统的影响,因此需对试验电网数学建模并进行相关研究。文章在研究试验电网接线原理基础上,对试验电网数学模型进行了推导：并设计了电压跌落发生器的控制策略。仿真与试验结果验证了该数学模型的正确性和精确性。     

Lane-keeping benefits of practical rear axle steer

The classic two-degree-of-freedom yaw-plane or ‘bicycle’ vehicle model is augmented with two additional states to describe lane-keeping behaviour and further augmented with an additional control input to steer the rear axle. A simple driver model is hypothesised where the driver closes a loop on a projected lateral lane position. The driver can select the preview distance to compensate driver/vehicle dynamics, consistent with the ‘cross-over’ model found in the literature. A rear axle steer control law is found to be a function of the front axle steering input and vehicle speed that exhibits stability similar to a positive-real system, while at the same time improving the ability of the driver/vehicle system to track a complex curved lane and improving steady-state manoeuvrability. The theoretically derived control law bears similarity to practical embodiments allowing a deeper understanding of the functional value of steering a rear axle.     

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本文提出一种用于评价公路－铁路联合运输货运枢纽选址方案的整数模型。模型中的四个主体为：货运枢纽经营者、交通运输网络设施规划者、客户、社会公众。介绍了可使全局目标优化的基于主体建模方法(ABM)在货运枢纽选址中的应用。最后，本文以澳大利亚昆士兰州东南部的货物联合运输枢纽为例，介绍了其原始选址过程、个体目标函数测试及基于主体的模型设计过程。     

A data-driven dynamics simulation framework for railway vehicles

The finite element (FE) method is essential for simulating vehicle dynamics with fine details, especially for train crash simulations. However, factors such as the complexity of meshes and the distortion involved in a large deformation would undermine its calculation efficiency. An alternative method, the multi-body (MB) dynamics simulation provides satisfying time efficiency but limited accuracy when highly nonlinear dynamic process is involved. To maintain the advantages of both methods, this paper proposes a data-driven simulation framework for dynamics simulation of railway vehicles. This framework uses machine learning techniques to extract nonlinear features from training data generated by FE simulations so that specific mesh structures can be formulated by a surrogate element (or surrogate elements) to replace the original mechanical elements, and the dynamics simulation can be implemented by co-simulation with the surrogate element(s) embedded into a MB model. This framework consists of a series of techniques including data collection, feature extraction, training data sampling, surrogate element building, and model evaluation and selection. To verify the feasibility of this framework, we present two case studies, a vertical dynamics simulation and a longitudinal dynamics simulation, based on co-simulation with MATLAB/Simulink and Simpack, and a further comparison with a popular data-driven model (the Kriging model) is provided. The simulation result shows that using the legendre polynomial regression model in building surrogate elements can largely cut down the simulation time without sacrifice in accuracy.     

企业敏捷性评价模型

通过对企业敏捷性影响因素的分析,建立评价指标体系结构图,利用AHM属性层次分析法确定各因素权值,然后利用多级模糊综合评判法进行评价。在单因素评判后,以雷达图的形式表示评判结果。综合评判后,对同一敏捷档次的企业敏捷性排序。另外,通过对企业转换能力的评价,确定企业在敏捷空间中的位置,并以图形表示。