一类混杂动态系统的能控性(Ⅲ)——含多时滞的情形

首次将时滞现象引入到线性切换系统的模型中,研究含有时滞线性切换系统的能控性及其判定条件。全部工作由三部分组成。第Ⅲ部分,主要研究含多时滞的线性切换系统的能控性及其判定规则。首先给出周期型系统的单周能控性和多周期能控性的定义和充要条件,其次给出非周期系统的能控性的定义和充要条件。最后,研究时滞大小不一致的情形,指出能控性与时滞大小无关。     

人颅骨结构的动力参数

为了深入探讨人头部受撞击时颅脑损伤的力学计算模型,本文对颅骨结构的功力参数连行了测试和有限元分析。结果表明,人颅骨结构属于小阻尼结构,进行动力分析时可以抽象成弹性阻尼薄壳结构。     

Numerical simulation of the flow field in a reactor for titanium dioxide production

A physicochemical and fluid dynamic model is formulated for the numerical simulation of the flow field in a reactor for titanium dioxide production, the turbulence motion is described by theKε equation, the governing equations are solved by the SIMPLER algorithm devised by Partankar and Spalding. The velocity, tmperature and concentration fields are obtained for three cases: A) with chemical reaction and thermal insulation on the walls; B) with chemical reaction and wall temperature is 450K; C) without chemical reaction and thermal insulation on the walls, and the physicochemical numerical simulation for the titanium dioxide production has been done. The results of the paper can be used as a theoretical guide for the engineers in the design of such reactors.     

Adaptive control of bifurcation and chaos in a time-delayed system

In this paper, the stabilization of a continuous time-delayed system is considered. To control the bifurcation and chaos in a time-delayed system, a parameter perturbation control and a hybrid control are proposed. Then, to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes, the adaptive control idea is introduced, i.e., the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws, respectively. The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem. The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods. They have the advantages of increased stability, adaptability to the changes of the system parameters, control cost saving, and simplicity. Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods. Besides, comparison of the two adaptive control methods are made in an experimental study.     

带有增益介质层的混合脊状等离子体波导的传输特性

在传统脊状等离子体波导的基础上设计了一种带有增益介质层的新型混合脊状等离子体波导,其结构中的介质层部分包含两个区域:前区为单一介质,后区的脊是由2种介质构成的双层脊区。采用二维时域有限差分方法分析了波导结构的传输特性,得到了TM模下的电场分布图,并对输出功率以及传输损耗与结构参数和介质折射率的变化规律进行了讨论。结果表明,在波导中引入的增益介质材料磷化铟后其损耗达到-6 dB/μm。此种波导结构对于光集成芯片的研究与制作具有重要意义。     

核爆发电问题中核燃料循环的中子学研究

研究核爆聚变电站中的一类中子学问题——如何利用核爆炸产生的大量中子生产核燃料.首先,根据核爆中子场的特点,确定可以利用的中子能量范围.用慢化理论对慢化材料的厚度进行估计,并用MCNP程序进行数值计算.研究如何利用中子反照效应减少造材料层的厚度,最后提出一个较合理的造材料技术路线.     

Removal of field-collected Microcystis aeruginosa in pilot-scale by a jet pump cavitation reactor

Hydrodynamic cavitation has been investigated extensively in the field of water treatment in the last decade and a well-designed hydrodynamic cavitation reactor is critical to the efficient removal of algal and large-scale application. In this paper, a jet pump cavitation reactor (JPCR) is developed for the removal of cyanobacteria Microcystis aeruginos in a pilot scale. The results demonstrate that the photosynthetic activity of M. aeruginosa is greatly inhibited immediately after treatment in the JPCR, and the growth is also hindered after 3 days culture. Moreover, a high cell disruptions of M. aeruginosa is detected after treated by JPCR. The release of chlorophyll-a indicates that the JPCR caused serious rupture to M. aeruginosa cells. The plausible cell disruption mechanisms are proposed in accordance with a fluorescence microscope and scanning electron microscope. Then, the optimization of cell disruption efficiency is also investigated for various operating conditions. The results showed that the algal cell disruption efficiency is improved at higher inlet pressure and the cavitation stage between the unstable limited operation cavitation stage and stable limited operation cavitation stage. The effect and optimization of JPCR on algal reduction are highlighted. The results of the study promote the application of hydrodynamic cavitation on algal removal and provide strong support for JPCR application in algal removal.     

Application of Euler Neural Networks with Soft Computing Paradigm to Solve Nonlinear Problems Arising in Heat Transfer

In this study, a novel application of neurocomputing technique is presented for solving nonlinear heat transfer and natural convection porous fin problems arising in almost all areas of engineering and technology, especially in mechanical engineering. The mathematical models of the problems are exploited by the intelligent strength of Euler polynomials based Euler neural networks (ENN’s), optimized with a generalized normal distribution optimization (GNDO) algorithm and Interior point algorithm (IPA). In this scheme, ENN’s based differential equation models are constructed in an unsupervised manner, in which the neurons are trained by GNDO as an effective global search technique and IPA, which enhances the local search convergence. Moreover, a temperature distribution of heat transfer and natural convection porous fin are investigated by using an ENN-GNDO-IPA algorithm under the influence of variations in specific heat, thermal conductivity, internal heat generation, and heat transfer rate, respectively. A large number of executions are performed on the proposed technique for different cases to determine the reliability and effectiveness through various performance indicators including Nash–Sutcliffe efficiency (NSE), error in Nash–Sutcliffe efficiency (ENSE), mean absolute error (MAE), and Thiel’s inequality coefficient (TIC). Extensive graphical and statistical analysis shows the dominance of the proposed algorithm with state-of-the-art algorithms and numerical solver RK-4.     

Multilevel Deep Feature Generation Framework for Automated Detection of Retinal Abnormalities Using OCT Images

Optical coherence tomography (OCT) images coupled with many learning techniques have been developed to diagnose retinal disorders. This work aims to develop a novel framework for extracting deep features from 18 pre-trained convolutional neural networks (CNN) and to attain high performance using OCT images. In this work, we have developed a new framework for automated detection of retinal disorders using transfer learning. This model consists of three phases: deep fused and multilevel feature extraction, using 18 pre-trained networks and tent maximal pooling, feature selection with ReliefF, and classification using the optimized classifier. The novelty of this proposed framework is the feature generation using widely used CNNs and to select the most suitable features for classification. The extracted features using our proposed intelligent feature extractor are fed to iterative ReliefF (IRF) to automatically select the best feature vector. The quadratic support vector machine (QSVM) is utilized as a classifier in this work. We have developed our model using two public OCT image datasets, and they are named database 1 (DB1) and database 2 (DB2). The proposed framework can attain 97.40% and 100% classification accuracies using the two OCT datasets, DB1 and DB2, respectively. These results illustrate the success of our model.     

A short walk through quantum optomechanics

This paper gives a brief review of the basic physics of quantum optomechanics and provides an overview of some of its recent developments and current areas of focus. It first outlines the basic theory of cavity optomechanical cooling and gives a brief status report of the experimental state‐of‐the‐art. It then turns to the deep quantum regime of operation of optomechanical oscillators and covers selected aspects of quantum state preparation, control and characterization, including mechanical squeezing and pulsed optomechanics. This is followed by a discussion of the “bottom‐up” approach that exploits ultracold atomic samples instead of nanoscale systems. It concludes with an outlook that concentrates largely on the functionalization of quantum optomechanical systems and their promise in metrology applications.