应用网格走时的射线路径计算方法

子射线法（Raylet method）基于走时场的互易性,可用于多路径射线的计算。针对子射线法在拾取总走时（源点到给定点走时与接收点到给定点走时之和）场极值中存在的困难与稳定性问题,提出利用反插值求取总走时场中走时横向或纵向一阶导数为零的点来构成射线路径。此外,结合多级次计算策略,利用上述算法得到了全部的续至射线。在均匀介质和垂向梯度介质中,通过与解析结果的数值对比,发现计算网格尺度与导数算子长度对上述算法的精度有一定影响;在横向变速介质中,数值试验表明该算法相对于常规运动学射线追踪只有很小的计算偏差,其对横向变速具有很强的适应能力。低速体模型和Marmousi模型试算结果表明,本文算法对复杂模型具有令人满意的计算精度和计算效率。     

基于向下延拓Milne法的重力归一化总梯度法

重力归一化总梯度法需进行向下延拓和垂向导数的计算,这两个过程都会放大高波数成分,影响计算结果的稳定性。为此,将向下延拓Milne法及积分垂向二阶导数法引入重力归一化总梯度的计算。将该方法应用于估算无限长水平圆柱体模型的中心位置,计算结果准确。然后针对实测重力数据,利用本方法得到的矿洞中心埋深较基于泰勒级数展开的重力归一化总梯度法更准确,因此本文方法具有一定的实用性。     

pH sensor based on deposited film of lead oxide on aluminum substrate electrode

Two modified electrodes were fabricated by deposition of thin films of α-PbO₂ and β-PbO₂ on aluminum substrate electrodes. Both electrodes exhibit potentiometric response to the hydrogen ion concentration and, consequently, can be used as pH sensors. The potentiometric responses of the modified electrodes were close to the theoretical slope of Nerustian response and comparable with glass electrodes. The electrochemical properties and stability of the constructed electrode were investigated. The possibility of the pH sensor for using in flow injection analysis (FIA) was also studied, and the optimum conditions were obtained.     

Effect of thermal noise on random lasers in diffusion regime

In this paper, we study the effects of thermal noise on the time evolution of a weak light pulse (probe) in the presence of a strong light pulse (pump) within a gain medium which includes random scatterer particles. Suitable thermal noise term is added to a set of four coupled equations including three diffusion equations for energy densities and a rate equation for the upper level population in a four-level gain medium. These equations have been solved simultaneously by Crank–Nicholson numerical method. The main result is that the back-scattered output probe light is increased as the thermal noise strength is increased and simultaneously, with the same rate, the amplified spontaneous emission is decreased. Therefore, the amplified response of the random laser in diffusion regime for the input probe pulse is enhanced due to effect of the thermal noise.     

Coupled particle swarm optimization method with genetic algorithm for the static–dynamic performance of the magneto-electro-elastic nanosystem

As a first attempt, Fourier series expansion (FSE), particle swarm optimization (PSO), and genetic algorithm (GA) methods are coupled for analysis of the static–dynamic performance and propagated waves in the magneto-electro-elastic (MEE) nanoplate. The FSE method is presented for solving the motion equations of the MEE nanoplate. For increasing the performance of genetic algorithms for solving the problem, the particle swarm optimization technique is added as an operator of the GA. Accuracy, convergence, and applicability of the proposed mixed approach are shown in the results section. Also, we prove that for obtaining the convergence results of the PSO and GA, we should consider more than 16 iterations. Finally, it is shown that if designers consider the presented algorithm in their model, the results of phase velocity of the nanosystem will be increased by 27%. A useful suggestion is that there is a region the same as a trapezium in which there are no effects from magnetic and electric potential of the MEE face sheet on the phase velocity of the smart nanoplate, and the region will be bigger by increasing the wavenumber.

     

Multi-objective optimization of shield construction parameters based on random forests and NSGA-II

Metro shield construction will inevitably cause changes in the stress and strain state of the surrounding soil, resulting in stratum deformation and surface settlement (SS), which will seriously endanger the safety of nearby buildings, roads and underground pipe networks. Therefore, in the design and construction stage, optimizing the shield construction parameters (SCP) is the key to reducing the SS rate and increasing the safe driving speed (DS). However, optimization of existing SCP are challenged by the need to construct a unified multiobjective model for optimization that are efficient, convenient, and widely applicable. This paper innovatively proposes a hybrid intelligence framework that combines random forest (RF) and non-dominant classification genetic algorithm II (NSGA-II), which overcomes the shortcomings of time-consuming and high cost for the establishment and verification of traditional prediction models. First, RF is used to rank the importance of 10 influencing factors, and the nonlinear mapping relationship between the main SCP and the two objectives is constructed as the fitness function of the NSGA-II algorithm. Second, a multiobjective optimization framework for RF-NSGA-II is established, based on which the optimal Pareto front is calculated, and reasonable optimized control ranges for the SCP are obtained. Finally, a case study in the Wuhan Rail Transit Line 6 project is examined. The results show that the SS is reduced by 12.5% and the DS is increased by 2.5% with the proposed framework. Meanwhile, the prediction results are compared with the back-propagation neural network (BPNN), support vector machine (SVM), and gradient boosting decision tree (GBDT). The findings indicate that the RF-NSGA-II framework can not only meet the requirements of SS and DS calculation, but also used as a support tool for real-time optimization and control of SCP.     

Ground roll attenuation using real and complex DWT based methods

This paper deals with ground roll attenuation using double density and dual-tree complex discrete wavelet transforms. These transforms use a new denoising method instead of well-known hard and soft thresholdings and Wavelet Domain Ground roll Analysis (WDGA) applied in finding and attenuating the ground roll energy in the wavelet domain. The dual-tree complex wavelet transform (DTCWT), and double density discrete wavelet transform (DDDWT) have two wavelets and one scaling function and are nearly shift-invariant. Also they have redundancy factors of 2, and their wavelets are smoother than other orthogonal wavelets. Based on this fact, they can be considered as replacement methods for such aims. Recognizing the performance of each method is required to show which method is more suitable and efficient. In the present study, distinct wavelets and scaling function of each method have been applied to the data, and also the data are denoised by Wavelet Domain Ground roll Analysis technique. Additionally, for the inverse transform, the coefficients of the noise are removed. And finally for concluding, the results of all methods are compared with the f-k method and band-pass filtering, and critically sampled Discrete Wavelet Transforms. Final results showed that the DTCWT is reliable in comparison with other methods for ground roll attenuation.     

“电力系统分析”课程可持续发展的建设与实践

本文探索了新工科背景下“电力系统分析”课程建设情况,摸索工程教育的新理念,以学生发展为中心,尝试翻转课堂的互动式教学模式,实现了创新人才的培养目标。编著《电力系统分析》教材,实现了内容的继承和创新、重要知识点的交叉和融合。建设数字仿真及物理模拟实验室,解决高校人才培养与社会需求脱节的问题。以“注重学习过程,加强平时考核,淡化期末考试”的方式进行综合考评,提高了教学效果与教学质量。经过几年的教学探索与实践,证明了本课程建设效果良好。