耦合热弹性问题的分区变分原理及其广义变分原理

本文在文献[1]和[2]的基础上建立并论证了耦合热弹性问题的分区变分原理及其分区广义变分原理     

有限变形弹性动力学的非传统Gurtin型变分原理

根据古典阴阳互补和现代对偶互补的基本思想，通过作者早已提出的一条简单而统一的途径，系统地建立了有限变形弹性动力学的各类非传统Gurtin型变分原理，给出一个以卷积表示的重要关系式，可以认为，该式是有限变形动力学的广义虚功原理的表式。从该式出发，不仅能得到有限变形动力学的虚功原理，而且通过给出的一系列广义Legendre变换，还能系统地成对导出5类变量，3类变量，2类变量和1类变量非传统Gurtin型变分原理的互补泛函。通过这条途径还能清楚地阐明这些原理之间的内在联系。     

Lee极值原理与结构的大挠度塑性动力响应

本文介绍了利用Lee 极值原理确定结构的大挠度塑性动力响应的数值方法,给出了在均布冲击载荷作用下的理想刚塑性门形框架的大挠度进化模态解,指出如果模态形式取得合适,可使进化模态解接近于真实解.这样得到的门形框架的大挠度模态解与文献[8]中的实验结果和文献[9]中的大挠度完全解都符合得很好.     

微载荷含油轴承摩擦性能研究Ⅰ.摩擦试验机设计

研制了1种针对径向轴承的微载荷摩擦试验机,介绍了其工作原理及结构,即利用外加载荷抵消浮动测试架重量以施加微小载荷,并利用激光位置传感器(PSD传感器)实现无接触位移测量;同时测量了摩擦副的转动角度并计算出摩擦系数;采用摩擦转角测量法和外加力矩平衡摩擦法测量微载荷下的摩擦性能,以测量时间末端位置作为位置基准,通过极限偏载平衡进行载荷标定.结果表明:微载荷摩擦试验机可应用于径向轴承在微小载荷下的摩擦力测量;可以通过在较大范围内设置结构参数来研究径向轴承的摩擦特性;并可利用数据采集技术研究速度和载荷连续变化条件下的摩擦性能.     

THE FIRST ORDER APPROXIMATION OF NON-KIRCHHOFF-LOVE THEORYFOR ELASTIC CIRCULAR PLATE WITH FIXED BOUNDARY UNDERUNIFORM SURFACE LOADING (Ⅰ)

I.1ntroductionTheaxisymmetricproblemofthreedimensionalelasticcircularplatecanbetreatedasthreedimensionalaxisymmetricproblemofelasticity.Weconsideracircularplatewithauniformthicknessh,andsetupacircumferentialcoordinates(r,o)onitsmidd1esurfacewithabscissazp…     

一个厚薄板通用的三角形板弯元

本文提出了一个新的厚薄板通用的三角形板弯元,根据Hellinger-Reissner变分原理推导出来的新单元具有独立的转角、位移、剪应变和弯曲应变的插入函数,它没有其它混合元所存在的一些缺点。一些典型例子表明这个新单元具有很好的特性,刚度矩阵简单,计算精度高,收敛速度快以及厚薄板通用性强。     

Buoyancy-driven convection of water near its density maximum with time periodic partially active vertical walls

The effect of density inversion on transient natural convection heat transfer of cold water in a square cavity with partially active vertical walls is studied numerically. The governing equations are solved by control volume method with power law scheme. In the hot location the temperature is varied sinusoidally and in the cold location uniform temperature is maintained. Nine different positions of the active zones are considered. Results are discussed for various values of the amplitude, period and different Grashof numbers and presented graphically in the form of isotherms, streamlines, mid-height velocity profile and average Nusselt number. It is found that density inversion of water affects natural convection flow and heat transfer. Heat transfer rate is enhanced upto 80% when the heating location is in the middle of the hot wall.     

The Generalized Uncertainty Principle

The uncertainty principle lies at the heart of quantum physics, and is widely thought of as a fundamental limit of the measurement precision of incompatible observables. Here it is shown that the traditional uncertainty relation in fact belongs to the leading order approximation of a generalized uncertainty relation. That is, the leading order linear dependence of observables gives the Heisenberg type of uncertainty relations, while higher order nonlinear dependence may reveal more different and interesting correlation properties. Applications of the generalized uncertainty relation and the high order nonlinear dependence between observables in quantum information science are also discussed.     

Calibration Invariance of the MaxEnt Distribution in the Maximum Entropy Principle

The maximum entropy principle consists of two steps: The first step is to find the distribution which maximizes entropy under given constraints. The second step is to calculate the corresponding thermodynamic quantities. The second part is determined by Lagrange multipliers’ relation to the measurable physical quantities as temperature or Helmholtz free energy/free entropy. We show that for a given MaxEnt distribution, the whole class of entropies and constraints leads to the same distribution but generally different thermodynamics. Two simple classes of transformations that preserve the MaxEnt distributions are studied: The first case is a transform of the entropy to an arbitrary increasing function of that entropy. The second case is the transform of the energetic constraint to a combination of the normalization and energetic constraints. We derive group transformations of the Lagrange multipliers corresponding to these transformations and determine their connections to thermodynamic quantities. For each case, we provide a simple example of this transformation.     

Exact Recovery of Stochastic Block Model by Ising Model

In this paper, we study the phase transition property of an Ising model defined on a special random graph—the stochastic block model (SBM). Based on the Ising model, we propose a stochastic estimator to achieve the exact recovery for the SBM. The stochastic algorithm can be transformed into an optimization problem, which includes the special case of maximum likelihood and maximum modularity. Additionally, we give an unbiased convergent estimator for the model parameters of the SBM, which can be computed in constant time. Finally, we use metropolis sampling to realize the stochastic estimator and verify the phase transition phenomenon thfough experiments.