近似完全匹配层边界条件吸收效果分析及衰减函数的改进

完全匹配层边界条件存在两个问题，一是如何减少实际应用带来的额外存储量以及提升计算速度，另一个是如何提升匹配层的吸收效果。对于第一个问题发展了多种非分裂形式，本文采用一种直接对波场进行变换的新型非分裂方法，相比卷积完全匹配层具有不改变方程的形式以及易于实现等优势。对于如何进一步提升完全匹配层吸收效果，没有太大的进展。这是因为离散差异使匹配层的吸收问题更为复杂，一般采取增加匹配层层数的措施缩小离散差，但是又会导致计算量和存储量的增加。本文以在不增加匹配层层数以及不减小理论误差的情况下减小离散差异所带来的虚假反射为目的，分析传统的衰减因子，研究匹配层的吸收机理，设计新的衰减因子，以提高完全匹配层的吸收性能。新衰减因子能够进一步削弱虚假反射振幅，在匹配层层数为5~20层时，对应的边界反射振幅只有改进前的40%~80%。     

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.     

岩体节理产状极点分布的分形维

40多年来人们一直关注岩体节理产状分布的研究,但由于岩体节理产状呈现出双变量参数的复杂分布,因此准确地描述节理产状的特征及在实际岩石工程中的应用都很不成熟。据此,采用传统的下半球Schmidt等面积投影网与分形几何知识及计算机编程技能结合的方法,研究岩体节理产状空间分布的几何特征,给出岩体节理极点在下半球Schmidt等面积投影网中的分形维,总结出岩体节理极点分形维分布的基本规律,即节理极点较多的优势组其分形维值一般也较高。但节理极点产状的分形维还与该组节理产状分布的范围有关,产状分布范围越大,分散性越高,其所对应的分形维也越高。提出了节理产状在分布上存在分散度的概念,认为岩体节理极点分布分形维可表示与产状分布分散度的特征,并通过一个实例来讨论和分析上述研究成果。     

南方某路基(2#路)软基处理工程监测分析

以南方某港2#路软基处理工程为例,着重阐述了软土地基在堆载预压下土体的变形、固结过程,并进行了计算与试验对比分析.     

深层黏性土渗透释水规律的探讨

从宏观和微观两方面对海口深层坚硬黏性土渗透释水变形规律进行了探讨 ;阐明开采深层承压水有水位降产生就会导致压缩层土的复合沉降 ,认为深层坚硬黏性土变形是不可忽略的 ;并结合渗透规律提出允许开采水位和单位沉降量随水力梯度、时间等变化关系式 ,更方便准确地预测地面沉降。     

CAST工艺的低温活性污泥培养与调试运行

以长春市双阳污水处理厂为例,介绍了CAST工艺在冬季低温条件下活性污泥培养与调试运行的控制方法.针对运行管理过程中存在的问题,提出了有效的解决措施.     

Effects of Bi and rare earth metal on the microstructure and properties of Zn-based high-temperature solder

A novel Zn-based high-temperature solder was developed to join copper/steel at moderate temperature. The effects of Bi and rare earth metal on the microstructures, wettability of solders as well as the mechanical properties of solder joints were investigated. The results indicated that with the addition of Bi into Zn-Cu-Sn (ZCS) alloy, significant improvement in wettability is realized. When the content of Bi element is 1.5 wt. % in the solder, the spreading area researched over 200 mm². Further more, with the addition of RE, refined primary ε-CuZn₅ phases were formed and the shear strength of the solder joint was largely improved.