final_robotSearch-1.0_2learn-it

下面我们将给出一些基于Galerkin有限元法的微型泵模拟结果，模拟过程在商业软件COMSOL Multiphysics 3.2中实现。数值求解采用压力修正算法——SIMPLE，它首先假设一个压力场，然后通过求解不可压缩流动的Navier-Stokes方程得到速度场。这些速度不需要满足Possion型连续方程，所以对压力场的修正也带来速度场的修正，最终满足质量守恒。求解速度场的同时计算电势场方程。这会得到Lorentz力，然后将其反馈回N-S方程并作为体积力处理。连续耦合Lorentz力和速度场直到Newton迭代收敛。 (Below we will give some micro-pump simulation results based on the Galerkin finite element method, the simulation process in the commercial software COMSOL Multiphysics 3.2. The numerical solution of pressure correction algorithm- the SIMPLE, it begins by assuming a pressure field, and then by solving the incompressible Navier-Stokes equations, the velocity field. These velocities do not need to satisfy the continuity equation of Possion type pressure field correction to bring the amendment of the velocity field, and ultimately to meet the conservation of mass. Solving the velocity field at the same time to calculate the potential field equations. This will be the Lorentz force, and then fed back to the NS equations and processing as a volume force. Continuous coupling of the Lorentz force and the velocity field until the Newton iteration convergence.)

说明：  基于欧拉距离的KNN分类器，可自行调节map和预测点的位置。运行时首先显示分布散点图，之后输出预测值(Here is a KNN classifier based on Euler distance with self-adjusting map and prediction point positions. The distribution scatter will plot displayed map at first, then show the predicted value.)

QR分解法是目前求一般矩阵全部特征值的最有效并广泛应用的方法，一般矩阵先经过正交相似变化成为Hessenberg矩阵，然后再应用QR方法求特征值和特征向量。它是将矩阵分解成一个正规正交矩阵Q与上三角形矩阵R，所以称为QR分解法,(QR decomposition )

分享一个外国人编写的FDTD程序,可以用来计算微带线和微带贴片天线,程序中采用的是均匀网格划分,但也可以在容易地在它基础上改写成非均匀网格.其边界条件与Sheen的程序不同,这里采用二阶技术.(Prepared to share a foreigner FDTD procedures, can be used to calculate the microstrip lines and microstrip patch antenna, the procedure used is uniform mesh, but can also easily rewrite it into the basis of non-uniform grid. its boundary conditions with different processes and Sheen, where second-order technology.)

ABAQUS中用户材料子程序UMAT的开发主要解决两方面的问题：本构模型的建立和积分算法的选择。 本文主要研究非线性材料的UMAT实现方法，并重点研究其迭代算法部分，目前，用户材料子程序UMAT的迭代算法主要是常刚度法，常刚度法的优点在于算法原理较简单，程序编写较方便，缺点是当遇到复杂非线性材料时，其迭代次数较多，收敛速度也较慢，在这个情况下，本文采取的是一种迭代次数较少且收敛速度较快的切线刚度法，具体就是采用FORTRAN语言编制了基于Von-Mises模型的接口程序,并采用切线刚度算法，通过与ABAQUS自带本构关系计算的结果相比较，验证其正确性。(This paper studies the user subroutine UMAT of ABAQUS development methods, the use of FORTRAN language isotropic hardening material model of the interface program, studied the effects of such material is extremely elastic-plastic constitutive relation method. This article UMAT tightly around the secondary development of technology, the first principle of its interface detail, and then for the theory of nonlinear finite element incremental stiffness of the regular tangent stiffness method and the theory of algorithms to do an in-depth analysis of deduced a regular tangent stiffness and rigidity of the law of the specific expression of algorithm theory, and then the preparation of the two algorithms, respectively, of the UMAT program, and finally the establishment of a specific model checking, bringing with ABAQUS elasto-plastic constitutive relation of the calculated results compared to verify the correctness of the two.)

abaqus fortran 纤维拉伸 子程序(abaqus fortran fiber stress subumat)

说明：  有两个ARMA过程，其中信号1是宽带信号，信号2是窄带信号，分别用AR谱估计算法、ARMA谱估计算法和周期图法估计其功率谱。(There are two ARMA processes, in which signal 1 is a wideband signal and signal 2 is a narrowband signal. The power spectrum is estimated by AR spectrum estimation algorithm, ARMA spectrum estimation algorithm and periodogram method respectively.)

分数阶滑模工具箱，可用于解决阶次比较低的时候(fractional order sliding mode )

假设有一个能装入总体积为T的背包和n件体积分别为w1 , w2 , … , wn 的物品，能否从n件物品中挑选若干件恰好装满背包，即使w1 +w2 + … + wn=T，要求找出所有满足上述条件的解。例如：当T=10，各件物品的体积{1，8，4，3，5，2}时，可找到下列4组解：（1，4，3，2），（1，4，5），（8，2），（3，5，2）。 [需求分析](Suppose there are a load of the backpack of the total volume of T and n volumes were w1, w2, ... wn items, whether selected from n items a number of exactly filled backpack, even if w1+w2+ ...+ wn = T, find out the solution of all the above conditions are met. For example: when T = 10, the volume of items {1,8,4,3,5,2}, can be found in the following four solutions: (1,4,3,2), (1,4,5 ), (8,2), (3,5,2). [Needs Analysis])

Orthogonal Polynomials Approximation 数值分析，计算正交基多项式的系数 (Given a function f and a set of m >0 distinct points . You are supposed to write a function to approximate f by an orthogonal polynomial using the exact function values at the given m points with a weight assigned to each point . The total error must be no larger than a given tolerance. Format of function int OPA( double (*f)(double t), int m, double x[], double w[], double c[], double*eps ) where the function pointer double (*f)(double t) defines the function f int m is the number of points double x[] contains points double w[] contains the values of a weight function at the given points x[] double c[] contains the coefficients of the approximation polynomial double*eps is passed into the function as the tolerance for the error, and is supposed to be returned as the value of error. The function OPA is supposed to return the degree of the approximation polynomial. Note: a constant Max_n is defined so that if the total error is still not small enough when n = Ma)