Introduction of parameterized sea ice drag coefficients into ice free-drift modeling

Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient （Ca） and oceanic drag coefficient （Cw）. Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions. In the present study, the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model, and the wind factor a and the deflection angle θ between sea ice drift and wind velocity as well as the ratio of Ca to Cw are studied to investigate their dependence on the impact factors such as local drag coefficients, floe and ridge geometry. The results reveal that in an idealized steady ocean, Ca/Cw increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone, while it remains at a steady level （0.2-0.25） for large floes in the central ice zone. The wind factor a increases rapidly at first and approaches a steady level of 0.018 when A is greater than 20%. And the deflection angle ~ drops rapidly from an initial value of approximate 80° and decreases slowly as A is greater than 20% without a steady level like a. The values of these parameters agree well with the previously reported observations in Arctic. The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient （Cs＇/Cs） and the ratio of ridge form drag coefficient （Cr＇/Cr） to the value of Ca/Cw, a, and 8, because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces. Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.

Temperature Drift Modeling of FOG Based on LS-WSVM

Large temperature drift is an important factor for improving the performance of FOG.A trend term of temperature drift of FOG is obtained using stationary wavelets transform,and an FOG drift algorithm with least squares wavelet support vector machine(LS-WSVM) is developed.The algorithm used Maxihat wavelet as a kernel function of LS-WSVM to establish an FOG drift model.It has better modeling precise than LS-WSVM model with Gauss kernel.Results indicate the efficiency of this algorithm of LS-WSVM.

Mechanistic Drifting Forecast Model for A Small Semi-Submersible Drifter Under Tide–Wind–Wave Conditions

Understanding the drifting motion of a small semi-submersible drifter is of vital importance regarding monitoring surface currents and the floating pollutants in coastal regions. This work addresses this issue by establishing a mechanistic drifting forecast model based on kinetic analysis. Taking tide–wind–wave into consideration, the forecast model is validated against in situ drifting experiment in the Radial Sand Ridges. Model results show good performance with respect to the measured drifting features, characterized by migrating back and forth twice a day with daily downwind displacements. Trajectory models are used to evaluate the influence of the individual hydrodynamic forcing. The tidal current is the fundamental dynamic condition in the Radial Sand Ridges and has the greatest impact on the drifting distance. However, it loses its leading position in the field of the daily displacement of the used drifter. The simulations reveal that different hydrodynamic forces dominate the daily displacement of the used drifter at different wind scales. The wave-induced mass transport has the greatest influence on the daily displacement at Beaufort wind scale 5–6; while wind drag contributes mostly at wind scale 2–4.

A Fractional Drift Diffusion Model for Organic Semiconductor Devices

Because charge carriers of many organic semiconductors(OSCs)exhibit fractional drift diffusion(Fr-DD)transport properties,the need to develop a Fr-DD model solver becomes more apparent.However,the current research on solving the governing equations of the Fr-DD model is practically nonexistent.In this paper,an iterative solver with high precision is developed to solve both the transient and steady-state Fr-DD model for organic semiconductor devices.The Fr-DD model is composed of two fractionalorder carriers(i.e.,electrons and holes)continuity equations coupled with Poisson’s equation.By treating the current density as constants within each pair of consecutive grid nodes,a linear Caputo’s fractional-order ordinary differential equation(FrODE)can be produced,and its analytic solution gives an approximation to the carrier concentration.The convergence of the solver is guaranteed by implementing a successive over-relaxation(SOR)mechanism on each loop of Gummel’s iteration.Based on our derivations,it can be shown that the Scharfetter–Gummel discretization method is essentially a special case of our scheme.In addition,the consistency and convergence of the two core algorithms are proved,with three numerical examples designed to demonstrate the accuracy and computational performance of this solver.Finally,we validate the Fr-DD model for a steady-state organic field effect transistor(OFET)by fitting the simulated transconductance and output curves to the experimental data.

Grey Markov chain and its application in drift prediction model of FOGs

A novel grey Markov chain predictive model is discussed to reduce drift influence on the output of fiber optical gyroscopes (FOGs) and to improve FOGs' measurement precision. The proposed method possesses advantages of grey model and Markov chain. It makes good use of dynamic modeling idea of the grey model to predict general trend of original data. Then according to the trend, states are divided so that it can overcome the disadvantage of high computational cost of state transition probability matrix in Markov chain. Moreover, the presented approach expands the applied scope of the grey model and makes it be fit for prediction of random data with bigger fluctuation. The numerical results of real drift data from a certain type FOG verify the effectiveness of the proposed grey Markov chain model powerfully. The Markov chain is also investigated to provide a comparison with the grey Markov chain model. It is shown that the hybrid grey Markov chain prediction model has higher modeling precision than Markov chain itself, which prove this proposed method is very applicable and effective.

A numerical model with Stokes drift for pollutant transport within the surf zone on a plane beach

This study examines the effects of Stokes drift on pollutant transport within the surf zone on a plane beach both numerically and experimentally. Firstly, the numerical model is described. The wave-induced current is modeled using the concept of the radiation stress. The wave propagation model is based on the wave energy conservation equation. And the advective diffusion model including the Stokes drift is used to describe the pollutant transport in the surf zone. Model validation was achieved in this case versus an analytical solution for an instantaneous point source in a uniform horizontal flow. This study also describes a laboratory experiment on dye release in the surf zone over a plane beach. We examined the final inclination angle required by a continuously released pollutant plume to reach the shoreline under both cases, and transport velocities in the alongshore and cross- shore directions were estimated by linearly fitting the location of a dye-patch front at different time. Results show that this dye patch moved shoreward with an approximate speed of 0.05 m/s (0.017 m/s) between 10 s and 40 s and 0.001 m/s (0.011 m/s) after 40 s for Case 1 (2). This model was then used to simulate pollutant transport in the surf zone on a plane beach as reproduced in the current experiment. Comparisons between our dye transport experiment and numerical results were then also conducted;the data showed that the numerical results including Stokes drift agreed more closely with experimental results than those without it. The data showed that the pollutant was generally transported obviously shoreward in addition to its expected drift along the shore. We also suggest that Stokes drift plays an important role in pollutant movement in the surf zone, especially shoreward.

Exact solutions to drift-flux multiphase flow models through Lie group symmetry analysis

In the present paper, Lie group symmetry method is used to obtain some exact solutions for a hyperbolic system of partial differential equations （PDEs）, which governs an isothermal no-slip drift-flux model for multiphase flow problem. Those sym- metries are used for the governing system of equations to obtain infinitesimal transforma- tions, which consequently reduces the governing system of PDEs to a system of ODEs. Further, the solutions of the system of ODEs which in turn produces some exact solutions for the PDEs are presented. Finally, the evolutionary behavior of weak discontinuity is discussed.

Application of Genetic Algorithm in Estimation of Gyro Drift Error Model

Extended Kalman Filter(EKF)algorithm is widely used in parameter estimation for nonlinear systems.The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix.The grid optimization method is always used to find proper initial matrix for off-line estimation.However,the grid method has the draw back being time consuming hence,coarse grid followed by a fine grid method is adopted.To further improve efficiency without the loss of estimation accuracy,we propose a genetic algorithm for the coarse grid optimization in this paper.It is recognized that the crossover rate and mutation rate are the main influencing factors for the performance of the genetic algorithm,so sensitivity experiments for these two factors are carried out and a set of genetic algorithm parameters with good adaptability were selected by testing with several gyros’experimental data.Experimental results show that the proposed algorithm has higher efficiency and better estimation accuracy than the traversing grid algorithm.

Steady thermal hydraulic characteristics of nuclear steam generators based on the drift flux code model

To investigate the steady thermal hydraulic characteristics of U-tube steam generator(SG), a 1D simulation code based on the four-equation drift flux model is developed. The U-tube channels presumably consist mainly of the primary channel, secondary channel, and tube wall. In the sub-cooling regions of the primary and secondary channels, flow is simulated using the single-phase flow model, whereas that in the boiling regions of the secondary channels is simulated using the four-equation drift flux model. The first-order equations of upwind difference are derived based on the staggered grid. Steady-state thermal hydraulic parameters are obtained with a cross-iteration scheme of heat balance and natural circulation requirement. The developed code is applied to analyze the SG behavior of the Qinshan I Nuclear Power Plant under 100%, 75%, 50%, 30%, and 15% power conditions. Analysis results are then compared with the simulation results obtained using RELAP5.

The in situ observation of modelled sea ice drift characteristics in the Bohai Sea

Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind speed, is of great significance to identify ice drift characteristics. A sea ice substitute, the so-called "modelled ice", which is made by polypropylene material with a density similar to Bohai Sea ice, is used to complete a free drift experiment in the open sea. The trajectories of isolated modelled ice, currents and wind in the Bohai Sea during non-frozen and frozen periods are obtained. The results show that the currents play a major role while the wind plays a minor role in the free drift of isolated modelled ice when the wind is mild in the Bohai Sea. The modelled ice drift is significantly affected by the ocean current and wind based on the ice–current–wind relationship established by a multiple linear regression. The modelled ice velocity calculated by the multiple linear regression is close to that of the in situ observation, the magnitude of the error between the calculated and observed ice velocities is less than12.05%, and the velocity direction error is less than 6.21°. Thus, the ice velocity can be estimated based on the observed current velocity and wind speed when the in situ observed ice velocity is missing. And the modelled ice of same thickness with a smaller density is more sensitive to the current velocity and the wind speed changes. In addition, the modelled ice drift characteristics are shown to be close to those of the real sea ice, which indicates that the modelled ice can be used as a good substitute of real ice for in situ observation of the free ice drift in the open sea, which helps solve time availability, safety and logistics problems related to in situ observation on real ice.

Effect of a two-phase wedge-sliding model on the ingredient drift of a stable mixed fluid and its computing method

A two-phase wedge-sliding model is developed based on the micro-cellular structure and minimum entropy theory of a stable system, and it is used to describe the ingredient distribution of a mixed fluid in a non-uniform stress field and to analyse its phase drift phenomenon. In the model, the drift-inhibition angle and the expansion-inhibition angle are also deduced and used as evaluating indexes to describe the drifting trend of different ingredients among the mixed fluids. For solving above two indexes of the model, a new calculation method is developed and used to compute the phase distributions of multiphase fluid at peak stress and gradient area stress, respectively. As an example, the flow process of grease in a pipe is analysed by simulation method and used to verify the validity of the model.

Combined Electromagnetic and Drift Diffusion Models for Microwave Semiconductor Device

In this work, we present a numerical model to solve the drift diffusion equations coupled with electromagnetic model, where all simulations codes are implemented using MATLAB code software. As first, we present a one-dimensional (1-D) PIN diode structure simulation achieved by solving the drift diffusion model (DDM). Backward Euler algorithm is used for the discretization of the proposed model. The aim is to accomplish time-domain integration. Also, finite different method (FDM) is considered to achieve space-Domain mesh. We introduced an iterative scheme to solve the obtained matrix systems, which combines the Gummel’s iteration with an efficient direct numerical UMFPACK method. The obtained solutions of the proposed algorithm provide the time and space distribution of the unknown functions like electrostatic potential and carrier’s concentration for the PIN diode. As second case, the finite-difference time-domain (FDTD) technique is adopted to analyze the entire 3-D structure of the stripline circuit including the lumped element PIN diode. The microwave circuit is located in an unbounded medium, requiring absorbing boundaries to avoid nonphysical reflections. Active device results were presented and show a good agreement with other reference. Electromagnetic results are qualitatively in agreement with other results obtained using SILVACO-TCAD.

Causes and typical control model of wind-drift sandy lands in abandoned channel of the Yellow River

The historical formation and development of the abandoned channel of the Yellow River is reviewed and its causes of formation and present condition of prevention and control are analyzed in this paper. Based on this analysis, some ideas about control, critical problems and countermeasures in the next period are proposed with two typical control models as examples. We suggest that in preventing and controlling the wind-drift sandy lands in the region, the emphasis should be to develop, with a greatly expanded effort, a recycling economy. This should realize a combination of two ideas, i.e. integrate combating desertification with a structural adjustment of agricultural and an increase in the income of farmers.

Ocean Wave Model and Wave Drift Caused by the Asymmetry of Crest and Trough

It follows from the review on classical wave models that the asymmetry of crest and trough is the direct cause for wave drift. Based on this, a new model of Lagrangian form is constructed. Relative to the Gerstner model, its improvement is reflected in the horizontal motion which includes an explicit drift term. On the one hand, the depth-decay factor for the new drift accords well with that of the particle’s horizontal velocity. It is more rational than that of Stokes drift. On the other hand, the new formula needs no Taylor expansion as for Stokes drift and is applicable for the waves with big slopes. In addition, the new formula can also yield a more rational magnitude for the surface drift than that of Stokes.

A Review on the Study of Continental Drift and Numerical Simulation Associated with the Early Earth Core-Magma Angular Momentum Exchange

According to the drive of planetary-scale upper magma fluid motions associated with the core-magma angular momentum exchange in the early Earth’s interior, this paper reviewed the results of continental drift studied over the last three decades. The theoretical speculation is in good fit to the traces of geological events left on the Earth’s surface. A northeastward drift directionality of the Australian, African, and South American continents relative to the Antarctica Continent in the Southern Hemisphere is reanalyzed according to the slowing down of the early Earth’s rotation. Six traces of significant back-and-forth drifts of the Australian and Asian continents left respectively on the Southwest and Northwest Pacific seafloors are reidentified according to the gradually decreasing amplitude of core-magma angular momentum exchange during early geological evolution. Finally, the thickening and shortening of different continents during the early drift processes are re-simulated by using a simple magma fluid dynamical model.

厦门海域落水集装箱漂移路径的数值模拟

对落水集装箱的受力和进水淹没过程进行分析,细化落水集装箱风致漂移系数与淹没率的线性关系。并以“SITC PYEONGTAEK”轮落水集装箱为例,结合区域海洋模式模拟的海流数据,用拉格朗日法和蒙特卡洛随机扩散相结合的粒子追踪法建立集装箱追踪模型模拟集装箱的漂移轨迹,再利用网格化统计方案对零散分布的粒子进行概率统计,分析掉落集装箱的漂移位置。通过实际案例中集装箱落水后的漂移轨迹对模型进行验证,表明该模型模拟得到的轨迹点与海上发现的漂浮集装箱点位基本吻合,说明该模型有助于快速锁定漂移区域,减少由落水集装箱带来的风险,增加航行单位对落水集装箱漂移轨迹的预测准确性,为集装箱落水港区及周边水域的通航安全提供保障。

基于Delft3D的珠江前航道尸体模型漂移轨迹预测

为预测珠江前航道中尸体的漂移轨迹,帮助当地水警确定溺亡者尸体的具体位置,利用Delft3D构建珠江前航道水动力模型,并使用尸体模型进行了多次现场漂移试验。通过对珠江前航道表层流速进行拟合,建立了尸体模型漂移的预测模型,R^(2)为0.88。研究结果表明,珠江前航道释放的尸体模型受潮汐和径流作用沿河道做往复运动,并呈逐渐漂向下游的趋势;漂移模型验证中尸体模型的漂移速度和方向基本与潮流一致,模拟结果的误差在1 km以内,终点距离误差率小于15%;实例验证中成年女性尸体的模拟结果误差约为300 m;游船所引起的波浪力等外力导致漂移轨迹呈现出南北方向性的偏差,需要进一步提升模拟效果。该漂移模型的推导模式同样适用于其他感潮河段,可使尸体的漂移轨迹变得可测,为尸体打捞工作和警方的案件处理提供了便利和参考。

网络异常检测领域概念漂移问题研究综述

【目的】随着网络技术的快速发展和广泛应用,网络异常检测作为保护网络安全和维护系统正常运行的手段变得越来越重要。然而,网络中异常行为和攻击手段不断变化,给异常检测带来了新的挑战。其中,概念漂移问题是网络异常检测领域中受到广泛关注的难点之一。【方法】本综述旨在对网络异常检测领域中概念漂移问题进行研究分析和总结。与前人的研究相比,本文将专注于网络异常检测领域的流数据。【文献范围】首先,对概念漂移进行详细介绍,包括定义、产生原因和特点。通过对概念漂移的全面理解,可以为后续的检测方法提供指导。其次,系统性地介绍了概念漂移检测方法,主要包括基于统计的方法、机器学习方法和深度学习方法等,并对比了各类方法的优缺点和适用场景。最后,探讨了概念漂移在未来可能的研究方向。【结论】本文聚焦于网络异常检测领域的概念漂移问题,通过详细介绍概念漂移的定义、产生原因和特点,以及深入分析和总结针对流数据概念漂移的检测方法,为未来研究方向提供了有价值的参考和指导。

粉煤灰堆积体大断面连拱隧道失稳破坏模式及施工力学研究

国内目前并无在粉煤灰堆积体中采用暗挖法修建大断面连拱隧道的先例,给隧道的设计和施工带来了巨大挑战。依托盐坪坝隧道工程,开展了室内相似模型试验,探讨了该地层下大断面连拱隧道塌落拱演化规律及开挖施工力学行为。研究结果表明:连拱隧道在粉煤灰堆积体中开挖极易发生失稳,将失稳过程划分为4个演化阶段,破坏模式具有突发性、剧烈性、对称性、同步性特征;塌落拱高度约为隧道开挖跨度的40%。采用单侧壁导坑法开挖时粉煤灰堆积体承载力严重不足,根据相似换算关系左、右洞拱顶沉降分别为16.86,14.91cm,需对地层实施注浆加固;地层沉降呈对称“双峰状”,先行洞相较于后行洞受开挖影响较大,中隔墙的承载作用能够有效降低地层位移,单洞压力拱向双洞压力拱转换过程中,中隔墙受到偏压作用容易向先行洞侧偏转,建议在先行洞开挖时中隔墙添加支撑物。

一种多终端视频流智能识别模型共进演化方法研究

在泛在的智能物联网终端部署深度模型并提供智能应用/服务受到越来越多关注.但是,受限于终端硬件资源,研究人员从模型轻量化技术入手,为深度模型的轻量化、高精度部署提供技术支撑.然而基于轻量化深度模型的视频应用会面临实际场景中的数据漂移问题,导致推理精度急剧下降,并且该问题在移动场景中尤为显著.边缘辅助的模型在线演化是解决数据漂移问题的一种有效方式,可实现自演化的可成长的智能计算系统.然而,模型演化速度会影响终端模型高精度服务时间占比,从而影响模型全生命周期推理性能.为了提升多终端协同的模型演化精度和速度,本文提出基于软硬一体理念的多终端视频流智能识别模型共进演化方法和系统.一方面,本文提出了新颖的多终端互学习共进演化方法,借助终端新场景数据,克服模型数据异构挑战,实现多终端模型和全局模型的高增益协同演化和共进学习;另一方面,结合互学习算法特点,提出基于存内计算的训练加速方法,利用自适应数据压缩和模型训练优化提升系统性能,在保证演化精度增益的同时加速多个终端模型的演化速度.最后,通过不同真实移动场景下的轻量化模型持续演化任务实验验证,并对比六种基准方法证明NestEvo可以有效减少51.98%演化延迟,并提升42.6%终端轻量化模型平均推理精度.