北黄海北部海域潮余流的模拟研究

基于二维水动力模型,在仅考虑潮流作用条件下,通过计算欧拉余流和拉格朗日余流并结合粒子追踪方法研究了辽宁大连—朝鲜龙渊郡连线北侧的北黄海北部海域的潮余流结构和粒子运移的趋势。结果表明:欧拉余流和拉格朗日余流流速整体较小,呈现由南向北的流向,但在獐子岛及长山群岛的附近岛屿和朝鲜半岛沿岸的海域欧拉余流和拉格朗日余流流速较大。对比粒子追踪计算的结果与欧拉余流和拉格朗日余流的结果表明,流向与粒子运移路径基本一致。该海湾的余流及粒子运动规律特点对辽东半岛东岸及朝鲜半岛西侧海域的排污及污染控制有重要的借鉴意义。     

基于SPE与SPATT的水体中麻痹性贝类毒素检测方法构建与应用

为实现麻痹性贝类毒素(paralytic shellfish poisoning,PSP)的实时监控与提前预警,本研究构建了基于固相萃取技术(solid phase extraction,SPE)与固相吸附毒素跟踪技术(solid phase adsorption toxin tracking,SPATT)的水体中PSP检测方法,重点优化了吸附材料及前处理方法,评价了回收率、检出限等指标,并将方法应用于2019年春季秦皇岛山海关海域PSP消长过程的监测中,比较评估了两种方法的监控预警效果。结果表明:SPE方法选用ENVI-Carb 500mg/6mL固相萃取柱,过样体积为50mL,13种PSP组分的平均回收率为82.2%±10.0%、检出限为4.0-20.0ng/L;SPATT方法选用SP207大孔吸附树脂,洗脱时间为静置Id最佳,整体回收率约为9.2%;在实际应用中,结合产毒藻密度及贻贝富集毒素含量的变化,发现SPE方法的检测结果可实时表征海域PSP风险状况,对于贻贝中PSP的预警效果也显著优于SAPTT方法,后者不仅因监控方式相对滞后一个监测周期,且灵敏度及准确性均较差。对于秦皇岛海域,当SPE方法检测结果达到100ng STX eq/L时,该海域贻贝中PSP残留将具有潜在的食用安全风险,跟踪过程表明这一阈值可提前两周预警贻贝富集毒素含量超出我国限量标准(800μg STX eq/kg),这对于强化风险警示并制定防范措施具有积极作用。     

基于分布式控制力矩陀螺的水下航行器轨迹跟踪控制

基于控制力矩陀螺群(CMGs)的水下航行器具有低速或零速机动的能力。采用基于分布式CMGs的水下航行器方案,并研究其水平面的轨迹跟踪控制问题。通过全局微分同胚变换将非完全对称的动力学模型解耦成标准欠驱动控制模型,并根据简化的模型构建其轨迹跟踪的误差动力学模型,将轨迹跟踪控制问题转化为误差模型镇定问题。基于一种分流神经元模型和反步法设计了系统的轨迹跟踪控制律,该控制器不需要对任何虚拟控制输入进行求导计算,且能确保跟踪误差的最终一致有界性。仿真结果表明该控制器能够实现在不依赖动力学参数先验知识的情况下对光滑轨迹的有效跟踪。     

Nonlinear adaptive control of an underwater towed vehicle

This paper addresses the problem of simultaneous depth tracking and attitude control of an underwater towed vehicle. The system proposed uses a two-stage towing arrangement that includes a long primary cable, a gravitic depressor, and a secondary cable. The towfish motion induced by wave driven disturbances in both the vertical and horizontal planes is described using an empirical model of the depressor motion and a spring-damper model of the secondary cable. A nonlinear, Lyapunov-based, adaptive output feedback control law is designed and shown to regulate pitch, yaw, and depth tracking errors to zero. The controller is designed to operate in the presence of plant parameter uncertainty. When subjected to bounded external disturbances, the tracking errors converge to a neighbourhood of the origin that can be made arbitrarily small. In the implementation proposed, a nonlinear observer is used to estimate the linear velocities used by the controller thus dispensing with the need for costly sensor suites. The results obtained with computer simulations show that the controlled system exhibits good performance about different operating conditions when subjected to sea-wave driven disturbances and in the presence of sensor noise. The system holds promise for application in oceanographic missions that require depth tracking or bottom-following combined with precise vehicle attitude control.     

A Cascade Approach for Global Trajectory Tracking Control of Underactuated AUVs

A global trajectory tracking controller is presented for underactuated AUVs with only surge force and yaw moment in the horizontal plane. A transformation is introduced to represent the tracking error system into a cascade form. The global and uniform asymptotic stabilization problem of the resulting cascade system is reduced to the stabilization problem of two subsystems by use of the cascade approach. For the stabilization of the subsystem involving the yaw moment, a control law is proposed based on the feedback linearization method. Another subsystem is stabilized by designing a fuzzy sliding mode controller which can offer a systematical means of constructing a set of shrinking-span and dilating-span membership functions. In order to demonstrate the practicability of the proposed controller, control constraints, parameter uncertainties, and external disturbances are considered according to practical situation of AUVs. Simulation results show very good tracking performance and robustness of the proposed control schemes.     

Cloud tracking using satellite data for predicting the probability of heavy rainfall events in the Mediterranean area

The use of cloud tracking techniques and storm identification procedures is proposed in this paper with the aim of predicting the evolution of cloud entities associated with the highest rainfall probability within a given meteorological scenario. Suitable algorithms for this kind of analysis are based on the processing of digital images in the thermal infrared (IR) band from geostationary satellites: a selection of such algorithms is described in some detail together with a few real case applications. Three heavy rainfall events have been selected for this purpose with reference to the extreme meteorological situation observed during Fall 1992 and 1993 over the Mediterranean area. A window from 30 to 60 °N and from 20 °W to 30 °E has been identified for the analysis of data from the radiometer on board the ESA Meteosat platform. In conclusion, the suitability of cloud tracking techniques for predicting the probability of heavy rainfall events is discussed provided that the former are associated with proper modeling of small scale rainfall distribution.     

一种求解旅行商问题的改进蚁群算法

蚁群算法作为一种新型的优化算法,具有很强的适应性和鲁棒性,已广泛的应用于系统控制、人工智能、模式识别等工程领域。由于蚁群算法在搜索过程中易于陷入局部最优解,存在着加速收敛和早熟停滞现象的矛盾。文章针对这些问题,在基本蚁群算法的基础上,从参数的动态调整、信息量的更新规则、局部搜索策略进行相应的改进,引入信息素平滑机制,以求在加快收敛和防止早熟停滞之间取得较好的平衡。旅行商问题的仿真表明:改进后的蚁群算法具有较好的收敛性和稳定性,能够克服算法中早熟和停滞现象的过早出现。     

Integral inversion of SST data of type GRACE

Satellite missions CHAMP and GRACE dedicated to global mapping of the Earth’s gravity field yield accurate satellite-to-satellite tracking (SST) data used for recovery of global geopotential models usually in a form of a finite set of Stokes’s coefficients. The US-German Gravity Recovery And Climate Experiment (GRACE) yields SST data in both the high-low and low-low mode. Observed satellite positions and changes in the intersatellite range can be inverted through the Newtonian equation of motion into values of the unknown geopotential. The geopotential is usually approximated in observation equations by a truncated harmonic series with unknown coefficients. An alternative approach based on integral inversion of the SST data of type GRACE into discrete values of the geopotential at a geocentric sphere is discussed in this article. In this approach, observation equations have a form of Green’s surface integrals with scalar-valued integral kernels. Despite their higher complexity, the kernel functions exhibit features typical for other integral kernels used in geodesy for inversion of gravity field data. The two approaches are discussed and compared based on their relative advantages and intended applications. The combination of heterogeneous gravity data through integral equations is also outlined in the article. panovak@kma.zcu.cz     

Approaches for modeling longitudinal dispersion in pore-networks

The purpose of this study is to quantify the dispersivity in the longitudinal direction by upscaling pore scale mixing over a network domain and to verify the dispersivity with that obtained through the more rigorous upscaling technique, the Brownian particle tracking model (BPTM). We model a porous medium with a network of pore-units that are comprised of pore bodies and bonds of finite volume. Such a pore-unit is assumed to be a mixing cell with the steady state flow condition for a single fluid. Dispersivity can be obtained by solving the mixing cell model (MCM) for the concentration in each pore-unit and by averaging the concentrations for a large number of pore units (as a function of time and space). A minimal size of network that ascertains an asymptotic value of dispersivity was determined and verified with large size pore networks. This numerically computed dispersivity is compared with the results from the BPTM for the same porous medium and flow conditions. We show that the dispersivity obtained from the MCM is equally reliable for the heterogeneous pore-networks and can be estimated as a function of pore size heterogeneity. For homogeneous networks with the MCM, the iteration time step plays an important role. On the other hand, for networks with the BPTM, the assumption of intra-bond velocity profile affects the results.