Numerical Study of Finite Element Method Based Solutions for Propagation of Wetting Fronts in Unsaturated Soil

The accurate prediction of the propagation of a wetting front in an unsaturated soil subjected to surficial infiltration is of practical importance to many geotechnical and geoenvironmental problems. The finite element method is the most common solution technique as the hydraulic soil properties are highly nonlinear. Two important issues are often found to create difficulties in such analyses. First, numerical oscillations are usually observed in the calculated pore pressures at the wetting front. Second, when a reasonable mesh size and time step are used, the elevation of the wetting front may be seriously overpredicted. This paper is focused on the second issue. The under-relaxation (UR) technique used in the iterative process within each time step is found to have a serious impact on rate of convergence with refinement in mesh size and time step. Two different techniques are typically used; the first evaluates the hydraulic conductivity using an average of heads calculated from the preceding time node and the most recent iteration of the current time node (UR1), and the second evaluates the hydraulic conductivity using the average of heads calculated from the two most recent iterations of the current time nodes (UR2). The study shows that UR1, which is adopted in programs such as SEEP/W, ensures that the solution converges rapidly to a stable solution within a time step, but may converge to the wrong wetting front at a given elapsed time unless a sufficiently refined mesh is used. UR2 converges much more slowly within a time step, but the error in the wetting front is smaller than that generated by UR1.     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

利用地理信息系统ARC/INFO计算地物面积的方法

详细介绍利用地理信息系统工具ARC/lNFO来计算地物分布专题图中各种不同地物面积的方法，并给出海南省大边河库区地物面积的计算实例。     

锗γ能谱测量中的符合相加修正

本文介绍了锗γ能谱测量中符合相加修正的原理和方法,给出了修正公式。分别计算了不同几何条件下两个锗探测器对一些放射性核素的符合相加修正因子,估计了符合相加修正因子对活度测量结果的误差贡献。     

Sequential tripping strategy for a transmission network back-upprotection expert system

This paper describes a sequential tripping strategy used in a wide area back-up protection expert system (BPES) to combat situations in which protection relays have maloperated or information is missing. The BPES is an innovative back-up protection scheme designed to prevent the occurrence of widespread blackouts. The BPES evaluates the certainty that transmission lines are likely to be affected by the fault and uses a sequential tripping strategy to isolate the fault if a firm decision is not available due to maloperated relays and/or missing information. The mode of analysis and the sequential tripping strategy ensures that the BPES will clear a fault at minimum risk to the network. An example is included to demonstrate how the certainty factor based sequential tripping strategy is employed by the BPES to clear a fault which occurred on the South Western part of the UK National Grid System     

地球物理与中国的可持续发展

在20世纪中国的发展历程中,地球物理在资源探查、环境保护和减轻自然灾害服务等诸多方面发挥了举足轻重的作用。21世纪,中国走可持续发展之路已成为必然选择。随着可持续发展思想及内涵的逐渐丰富,地球物理必将为中国的可持续发展起到更大作用。     

Parameters evaluation of SOLA algorithm for time scale modification

Successful operation of the Synchronous Overlap and Add (SOLA) algorithm for Time Scale Modification (TSM) of speech is closely tied to the proper choice of parameters. This paper investigates the quality of time scale modified speech under different values of primary parameters. Based on Mean Opinion Score (MOS) tests and Bark Spectral Distortion (BSD) measure, the proper choices of synthesis shift (Ss) and the duration of the shift search interval (K _max?) are given experimentally. The conclusions can be helpful for operating the SOLA algorithm for time scale modification of speech.     

ADI-FDTD Method With Fourth Order Accuracy in Time

This letter presents an unconditionally stable alternating direction implicit finite-difference time-domain (ADI-FDTD) method with fourth order accuracy in time. Analytical proof of unconditional stability and detailed analysis of numerical dispersion are presented. Compared to second order ADI-FDTD and six-steps SS-FDTD, the fourth order ADI-FDTD generally achieves lower phase velocity error for sufficiently fine mesh. Using finer mesh gridding also reduces the phase velocity error floor, which dictates the accuracy limit due to spatial discretization errors when the time step size is reduced further.