非线性破坏准则下被动土压力的计算

基于采用非线性Mohr-Coulomb破坏准则,提出一个对刚性挡土墙的墙后被动土压力计算方法,分析和确定了滑动面的位置以及此时被动土压力的大小.首先,应用"切线法"引入了变量Ct和φt,然后运用迭代法计算得出对应于不同潜在滑动面上的Ct和φt,再运用广义库仑土压力理论求解被动土压力.其中对应于最大被动土压力的滑动面即为最危险滑动面,此时的被动土压力即为所求.通过与采用线性Mohr-Coulomb破坏准则下的研究比较得出,采用线性Mohr-Coulomb破坏准则计算的被动土压力结果偏大,在实际工程设计中偏于不安全,而采用非线性Mohr-Coulomb破坏准则在确定刚性挡土墙的墙后被动土压力时更加符合实际工程,结果更加准确.     

Data assimilation with the Ensemble Kalman Filter and the SEIK filter applied to a finite element model of the North Atlantic

Currently there are different approaches to filter algorithms based on the Kalman filter. One of the most used filter algorithms is the Ensemble Kalman Filter (EnKF). It uses a Monte Carlo approach to the filtering problem. Another approach is given by the Singular Evolutive Extended Kalman (SEEK) and Singular Evolutive Interpolated Kalman (SEIK) filters. These filters operate explicitly on a low-dimensional error space which is represented by an ensemble of model states. The EnKF and the SEIK filter have been implemented within a parallel data assimilation framework in the Finite Element Ocean Model FEOM. In order to compare the filter performances of the algorithms, several data assimilation experiments are performed. The filter algorithms have been applied with a model configuration of FEOM for the North Atlantic to assimilate the sea surface height in twin experiments. The dependence of the filter estimates on the represented error subspace is discussed. In the experiments the SEIK algorithm provides better estimates than the EnKF. Furthermore, the SEIK filter is much cheaper in terms of computing time.     

Vehicle longitudinal velocity estimation during the braking process using unknown input Kalman filter

In this paper, vehicle longitudinal velocity during the braking process is estimated by measuring the wheels speed. Here, a new algorithm based on the unknown input Kalman filter is developed to estimate the vehicle longitudinal velocity with a minimum mean square error and without using the value of braking torque in the estimation procedure. The stability and convergence of the filter are analysed and proved. Effectiveness of the method is shown by designing a real experiment and comparing the estimation result with actual longitudinal velocity computing from a three-axis accelerometer output.     

Comparative study of vehicle tyre–road friction coefficient estimation with a novel cost-effective method

This paper qualitatively and quantitatively reviews and compares three typical tyre–road friction coefficient estimation methods, which are the slip slope method, individual tyre force estimation method and extended Kalman filter method, and then presents a new cost-effective tyre–road friction coefficient estimation method. Based on the qualitative analysis and the numerical comparisons, it is found that all of the three typical methods can successfully estimate the tyre force and friction coefficient in most of the test conditions, but the estimation performance is compromised for some of the methods during different simulation scenarios. In addition, all of these three methods need global positioning system (GPS) to measure the absolute velocity of a vehicle. To overcome the above-mentioned problem, a novel cost-effective estimation method is proposed in this paper. This method requires only the inputs of wheel angular velocity, traction/brake torque and longitudinal acceleration, which are all easy to be measured using available sensors installed in passenger vehicles. By using this method, the vehicle absolute velocity and slip ratio can be estimated by an improved nonlinear observer without using GPS, and the friction force and tyre–road friction coefficient can be obtained from the estimated vehicle velocity and slip ratio. Simulations are used to validate the effectiveness of the proposed estimation method.     

Application of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: Twin experiments and real in-situ data assimilation

The Singular Evolutive Extended Kalman (SEEK) filter has been implemented to assimilate in-situ data in a 1D coupled physical-ecosystem model of the Ligurian Sea. The biogeochemical model describes the partly decoupled nitrogen and carbon cycles of the pelagic food web. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The data assimilation scheme (SEEK filter) parameterizes the error statistics by means of a set of empirical orthogonal functions (EOFs). Twin experiments are first performed with the aim to choose the suitable experimental protocol (observation and estimation vectors, number of EOFs, frequency of the assimilation,…) and to assess the SEEK filter performances. This protocol is then applied to perform real data assimilation experiments using the DYFAMED data base. By assimilating phytoplankton observations, the method has allowed to improve not only the representation of the phytoplankton community, but also of other variables such as zooplankton and bacteria that evolve with model dynamics and that are not corrected by the data assimilation scheme. The validation of the assimilation method and the improvement of model results are studied by means of suitable error measurements.     

基于数据融合的船舶电网参数测量研究

采用单传感器的传统船舶电气参数测量方法存在很多缺陷，会受到传感器的测量噪声和电网中的电磁干扰等影响，从而影响参数测量的精度和测量结果的稳定性。为此，应用状态估计技术和多传感器数据融合理论，提出了一种新的船舶电气参数测量方法。首先建立电压和电流的状态模型，将其连续的动态方程离散化，用于数字信号处理器（DSP）中。然后采用卡尔曼滤波和无反馈分布式融合来对离散化后的采样数据进行融合，从而得到全局数据融合的最优估计。最后，经过一个周期的采集数据估计值进行有效值计算，在液晶屏中显示出来。与单个传感器的检测方法相比，该检测方法具有更高的精度和更好的稳定性。仿真结果和实验测试结果都证明了本检测方法的有效性和优越性。     

Using GPS with a model-based estimator to estimate critical vehicle states

This paper demonstrates a method to estimate the vehicle states sideslip, yaw rate, and heading using GPS and yaw rate gyroscope measurements in a model-based estimator. The model-based estimator using GPS measurements provides accurate and observable estimates of sideslip, yaw rate, and heading even if the vehicle model is in neutral steer or if the gyro fails. This method also reduces estimation errors introduced by gyroscope errors such as the gyro bias and gyro scale factor. The GPS and Inertial Navigation System measurements are combined using a Kalman filter to generate estimates of the vehicle states. The residuals of the Kalman filter provide insight to determine if the estimator model is correct and therefore providing accurate state estimates. Additionally, a method to predict the estimation error due to errors in the estimator model is presented. The algorithms are tested in simulation with a correct and incorrect model as well as with sensor errors. Finally, the estimation scheme is tested with experimental data using a 2000 Chevrolet Blazer to further validate the algorithms.     

GL03型机车过滤器的性能分析

分析了GL03型过滤器的过滤机理,同时重点介绍了其过滤性能上的优点,并将之与国内长期使用的VV格百叶窗进行对比。     

交流传动地面功率试验及问题探讨

介绍了交流传动地面功率试验的主要结果,并就异步牵引电动机、逆变器、滤波电路及保护中的一些问题进行了探讨,提出交流传动机车应进一步研究解决的问题。     

港珠澳跨海集群工程海底沉管隧道防火设计

港珠澳跨海集群工程海底隧道是目前世界上最长的公路沉管隧道,运营期设置有主动与被动的双重防火系统。结合港珠澳海底沉管隧道的主要技术特点,提出防火设计中热释放率、火灾次数、耐火等级以及采取防护措施后构件的主要耐火指标。依据工程防火的具体实施条件,通过综合比较,沉管结构防火设计采用防火板直接覆面方式,沉管接头防火采用由刚性防火板与柔性防火隔断共同组成的具有自主知识产权的双层防护系统。