基于阿秒抖动光纤锁模激光器的时钟同步

光纤锁模激光器结构简单, 运转稳定, 且输出的超短脉冲序列具有极高的时钟稳定性, 在抽运探测、脉冲相干合成等要求高精度时钟同步的前沿领域有着广阔的应用前景. 本文通过激光器腔内的电光调制器进行反馈控制, 实现了两台光纤锁模激光器之间的紧密时钟信号同步; 并且通过平衡光学互相关方法, 对残余的时钟误差信号进行了测量, 分辨率达到了13 as. 通过优化激光器的腔内动力学过程及反馈环路的参数, 在[1 Hz, 10 MHz]的积分区间内得到了109 as的残余时钟误差, 对应单台激光器的平均时间抖动为77 as.     

超细Ni80Cr20合金丝冷拉拔烧头及穿模工艺

采用冷拉拔技术制备超细Ni80Cr20合金丝,探索了电化学法烧头和超景深显微镜辅助穿模方法,开展了直径25.60μm的超细丝拉拔至21.14μm的烧头和穿模工艺研究。实验结果表明:采用电解电压为5V,0.2mol/L的HCl溶液,烧头时间为1s,超景深显微镜200倍放大模式,成功拉制直径为21.14μm的微丝;电化学法可以精确控制烧头电压和时间,同时超景深显微镜可以放大金刚石模具孔径,解决了烧头时间控制不准确和人工穿模的难题,显著提高了穿模效率和成功率。     

混合微球谐振腔热非线性效应的增强方法（英文）

提出并实现了一种可增强微球谐振腔热非线性效应的方法。通过在微球谐振腔表面涂覆低折射率紫外胶形成并制备了混合谐振腔。通过分析混合谐振腔结构的热光系数,从理论和实验论证了混合谐振腔结构可获得更大的热非线性效应,同时验证了混合谐振腔的品质因素对热非线性的影响。应用此混合谐振腔结构于温度传感实验,结果表明通过增强方法制备的谐振腔其检测灵敏度提高了2.8倍。因此,此方法在传感应用、生物化学检测、通讯等领域也有广泛的应用前景。     

湍流模化的现状及发展趋势

本文讨论了湍流模化研究的发展现状,提出了今后湍流模式的可能改进途径。根据一组湍流封闭假定得到了各种2阶湍流模式,如Reynolds应力模式(RSM),代数应力模式(k-ε-A)及涡粘性模式(k-ε-E)。以自由剪切流、空腔流及通过偏心槽的流动为例作出了预报。虽然至今还不存在一个完备湍流模式,但2阶湍流模式已经具备了某些预报能力。湍流模化的不完备性可能要归咎于各向同性耗散和单湍流尺度等假定的不适当。利用多重湍流尺度概念,包括利用湍流涡的分维,可以改善湍流的预报。     

DIFFERENTIAL-ALGEBRAIC APPROACH TO COUPLED PROBLEMS OF DYNAMIC THERMOELASTICITY

An efficient numerical approach for the general thermomechanical problems was developed and it was tested for a two-dimensional thermoelasticity problem. The main idea of our numerical method is based on the reduction procedure of the original system of PDEs describing coupled thermomechanical behavior to a system of Differential Algebraic Equations (DAEs) where the stress-strain relationships are treated as algebraic equations. The resulting system of DAEs was then solved with a Backward Differentiation Formula (BDF) using a fully implicit algorithm. The described procedure was explained in detail, and its effectiveness was demonstrated on the solution of a transient uncoupled thermoelastic problem, for which an analytical solution is known, as well as on a fully coupled problem in the two-dimensional case.     

用代数应力模型模化型腔充填过程中的紊流流动

针对型腔充填过程中的紊流流动，用代数应力模型研究紊流流动现象．成功地将代数应力模型引入ＰＨＯＥＮＩＣＳ软件中，完成了恒温流体充填过程三维时均速度和自由表面的计算模拟．与实验结果相比说明，本文基于ＰＨＯＥＮＩＣＳ软件开发的充填模拟具备了对复杂型腔充填过程的数值计算．     

新型Poisson括号意义下的无穷维Lie代数

本文首先针对ＫｄＶ方程的Ｈａｍｉｌｔｏｎ形式，建立一种比较容易验证的新型Ｐｏｉｓｓｏｎ括号和无穷维Ｌｉｅ代数．其次，研究ＫｄＶ方程的Ｈａｍｉｌｔｏｎ形式的第一积分与新型Ｐｏｉｓｏｎ括号的关系，得到判定第一积分的充分必要条件．最后，构造ＫｄＶ方程的第一积分．     

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 阐述两种典型的计算机代数系统(CASes)------Matlab和Maple在基础 力学课程与有限元课程教学中的一些应用. CASes可以方便地将力学教学和有限元计算过程 中的模型建立、推理及其数值计算等进行演示和计算，为基础力学和有限元课程教学提供 了新的手段和途径.     

求解复杂湍流的非线性涡黏性系数模型和代数应力模型

非线性涡黏性系数模型和代数应力模型联系了线性涡黏性系数湍流模型和完整的微分 雷诺应力模型.随着它们受到日益关注,其形式也越来越多样化.本篇综述的目的是对这些模 型加以总结并比较它们之间的共同点及不同之处,指出它们与完整微分雷诺应力模型之间的 关系,以及相对于线性涡黏性系数模型而言它们在预报流场上所具有的优势.     

Application of scaled boundary finite element method in static and dynamic fracture problems

The scaled boundary finite element method (SBFEM) is a recently developed numerical method combining advantages of both finite element methods (FEM) and boundary element methods (BEM) and with its own special features as well. One of the most prominent advantages is its capability of calculating stress intensity factors (SIFs) directly from the stress solutions whose singularities at crack tips are analytically represented. This advantage is taken in this study to model static and dynamic fracture problems. For static problems, a remeshing algorithm as simple as used in the BEM is developed while retaining the generality and flexibility of the FEM. Fully-automatic modelling of the mixed-mode crack propagation is then realised by combining the remeshing algorithm with a propagation criterion. For dynamic fracture problems, a newly developed series-increasing solution to the SBFEM governing equations in the frequency domain is applied to calculate dynamic SIFs. Three plane problems are modelled. The numerical results show that the SBFEM can accurately predict static and dynamic SIFs, cracking paths and load-displacement curves, using only a fraction of degrees of freedom generally needed by the traditional finite element methods.The project supported by the National Natural Science Foundation of China (50579081) and the Australian Research Council (DP0452681)The English text was polished by Keren Wang.