A note on a generalized network flow model for manufacturing process

Manufacturing network flow （MNF） is a generalized network model that overcomes the limitation of an ordinary network flow in modeling more complicated manufacturing scenarios, in particular the synthesis of different materials into one product and/or the distilling of one type of material into many different products. Though a network simplex method for solving a simplified version of MNF has been outlined in the literature, more research work is still needed to give a complete answer whether some classical duality and optimality results of the classical network flow problem can be extended in MNF. In this paper, we propose an algorithmic method for obtaining an initial basic feasible solution to start the existing network simplex algorithm, and present a network-based approach to checking the dual feasibility conditions. These results are an extension of those of the ordinary network flow problem.     

A TRUST REGION METHOD FOR SOLVING DISTRIBUTED PARAMETER IDENTIFICATION PROBLEMS

This paper is concerned with the ill-posed problems of identifying a parameter in an elliptic equation which appears in many applications in science and industry. Its solution is obtained by applying trust region method to a nonlinear least squares error problem.Trust region method has long been a popular method for well-posed problems. This paper indicates that it is also suitable for ill-posed problems, Numerical experiment is given to compare the trust region method with the Tikhonov regularization method. It seems that the trust region method is more promising.     

A Prediction Model for Skin Wound Suture Forces With Uncertain Material Parameters北大核心CSCD

To evaluate the forces required for the suture of skin wounds quickly and effectively, the nonlinear finite element method was used to calculate the suture forces for skin wounds with different sizes and material parameters. With the calculated results as samples, the prediction model for skin wound suture forces was constructed by means of the EBF neural network model. Given the uncertain skin material parameters influencing the reliability of numerical results, the Monte-Carlo method was used to analyze the uncertainty propagation of skin material parameters. Finally, the prediction analysis and measuring experiment of wound suture forces were carried out with pig skin specimens to verify the reliability of the method. The results showed that, the suture force increases first and then decreases according to the suture point sequence, and the peak force occurs before the center of the wound. For a 40 mm×10 mm wound, the peak suture force is about 1.7 N, and that for a 40 mm×14 mm wound is about 2.5 N. Influenced by the uncertainty of material parameters, the prediction results of suture forces fluctuate by as much as ±0.6 N. The proposed theoretical prediction model provides an effective solution to the problem of parameter uncertainty propagation for biological soft tissue materials such as skins, and makes an important mechanical reference for robotic surgical suture. © 2023 Editorial Office of Applied Mathematics and Mechanics. All rights reserved.     

Branching structure of uniform recursive trees

The branching structure of uniform recursive trees is investigated in this paper. Using the method of sums for a sequence of independent random variables, the distribution law of ηn, the number of branches of the uniform recursive tree of size n are given first. It is shown that the strong law of large numbers, the central limit theorem and the law of iterated logarithm for ηn follow easily from this method. Next it is shown that ηn and ξn, the depth of vertex n, have the same distribution, and the distribution law of ζn,m, the number of branches of size m, is also given, whose asymptotic distribution is the Poisson distribution with parameter λ= 1/m. In addition, the joint distribution and the asymptotic joint distribution of the numbers of various branches are given. Finally, it is proved that the size of the biggest branch tends to infinity almost sure as n→∞.     

Restarted FOM Augmented with Ritz Vectors for Shifted Linear Systems

The restarted FOM method presented by Simoncini[7]according to the natural collinearity of all residuals is an efficient method for solving shifted systems,which generates the same Krylov subspace when the shifts are handled simultaneously.However,restarting slows down the convergence.We present a practical method for solving the shifted systems by adding some Ritz vectors into the Krylov subspace to form an augmented Krylov subspace. Numerical experiments illustrate that the augmented FOM approach(restarted version)can converge more quickly than the restarted FOM method.     

A VARIATIONAL EXPECTATION-MAXIMIZATION METHOD FOR THE INVERSE BLACK BODY RADIATION PROBLEM

The inverse black body radiation problem, which is to reconstruct the area temperature distribution from the measurement of power spectrum distribution, is a well-known ill-posed problem. In this paper, a variational expectation-maximization （EM） method is developed and its convergence is studied. Numerical experiments demonstrate that the variational EM method is more efficient and accurate than the traditional methods, including the Tikhonov regularization method, the Landweber method and the conjugate gradient method.     

0,1 distribution in the highest level sequences of primitive sequences over Z_(2~e)

In this paper, we discuss the 0,1 distribution in the highest level sequence αe-1 of primitive sequence over Z2e generated by a primitive polynomial of degree n. First we get an estimate of the 0,1 distribution by using the estimates of exponential sums over Galois rings, which is tight for e relatively small to n. We also get an estimate which is suitable for e relatively large to n. Combining the two bounds, we obtain an estimate depending only on n, which shows that the larger n is, the closer to 1/2 the proportion of 1 will be.     

Optimal Delaunay Triangulations

The Delaunay triangulation, in both classic and more generalized sense, is studied in this paper for minimizing the linear interpolation error (measure in L^P-norm) for a given function. The classic Delaunay triangulation can then be characterized as an optimal triangulation that minimizes the interpolation error for the isotropic function ‖x‖^2 among all the triangulations with a given set of vertices. For a more general function, a functiondependent Delaunay triangulation is then defined to be an optimal triangulation that minimizes the interpolation error for this function and its construction can be obtained by a simple lifting and projection procedure. The optimal Delaunay triangulation is the one that minimizes the interpolation error among all triangulations with the same number of vertices, i.e. the distribution of vertices are optimized in order to minimize the interpolation error. Such a function-depend entoptimal Delaunay triangulation is proved to exist for any given convex continuous function.On an optimal Delaunay triangulation associated with f, it is proved that △↓f at the interior vertices can be exactly recovered by the function values on its neighboring vertices.Since the optimal Delaunay triangulation is difficult to obtain in practice, the concept of nearly optimal triangulation is introduced and two sufficient conditions are presented for a triangulation to be nearly optimal.     

Symplectic RK Methods and Symplectic PRK Methods with Real Eigenvalues

Properties of symplectic Runge-Kutta (RK) methods and symplectic partitioned Runge-Kutta (PRK) methods with real eigenvalues are discussed in this paper. It is shown that an s stage such method can‘t reach order more than s 1. Particularly, we prove that no symplectic RK method with real eigenvalues exists in stage s of order s 1 when s is even. But an example constructed by using the W-transformation shows that PRK method of this type does not necessarily meet this order barrier. Another useful way other than W-transformation to construct symplectic PRK method with real eigenvalues is then presented. Finally, a class of efficient symplectic methods is recommended.     

ON THE ACCURACY OF THE LEAST SQUARES AND THE TOTAL LEAST SQUARES METHODS

Consider solving an overdetermined system of linear algebraic equations by both the least squares method (LS) and the total least squares method (TLS). Extensive published computational evidence shows that when the original system is consistent. one often obtains more accurate solutions by using the TLS method rather than the LS method. These numerical observations contrast with existing analytic perturbation theories for the LS and TLS methods which show that the upper bounds for the LS solution are always smaller than the corresponding upper bounds for the TLS solutions. In this paper we derive a new upper bound for the TLS solution and indicate when the TLS method can be more accurate than the LS method.Many applied problems in signal processing lead to overdetermined systems of linear equations where the matrix and right hand side are determined by the experimental observations (usually in the form of a lime series). It often happens that as the number of columns of the matrix becomes larger, the ra     

Analysis of nanoindentation experiments by means of atomic force microscopy

Nanoindentation is quite a common method for local material characterization. Values for hardness and Young's modulus can be determined directly from the recorded data. Essential for the correct determination of the material parameters is the precise measurement of the actual indentation depth of the indenter. The indenter measures the current depth by means of a Wheatstone bridge which correlates the indentation depth to a change in voltage. A possible tool for the verification of the recorded indentation depths is Atomic Force Microscopy (AFM). AFM is able to scan an area of indents for almost any surface. The deflection of the tip is measured by a laser spot reflected from the surface of the cantilever. The difference in height between the surface and the indent can directly be read off from the plotted image. However, using an AFM only allows us to measure the depth of the permanent indentation depth after unloading the indenter. Nevertheless, correlation between the remaining indentation depths measured by the explained methods allows for a first assessment of the correctness of the online recorded depth-data by the nanoindenter. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

分析土壤半无限域的一种有限层方法(Ⅰ)——一般理论

本文研究了一种用于横观各向同性体动力学的有限层法.将土壤介质半无限域视为一个横观各向同性半空间体,介质的材料函数沿深度变化,将介质沿深度方向分成若干层,在每一层内材料函数用一个指数函数来模拟.这样,使求解问题的方程得到简化,利用Fourier变换我们得到了各层处“节点”力与位移的关系.这种有限层法实际上是一种半解析法.具有一般半解析法所具备的数据前后处理量少及计算量小等优点.本文所研究的这种有限层法为分析土壤与结构相互作用问题提供了一条新途径.     

Homogenization of heat diffusion in a cracked medium

We develop in this Note a homogenization method to tackle the problem of a diffusion process through a cracked medium. We assume that the cracks are orthogonal to the surface of the material, where an incoming heat flux is applied. The cracks are supposed to be of depth 1, of small width, and periodically arranged. We show that the cracked surface of the domain induces a volume source term in the homogenized equation.     

Modeling of the material removal and heat affected zone formation in CFRP short pulsed laser processing

Short pulsed laser milling is a novel method to process the carbon fiber reinforced plastics (CFRP) which has bad machinability. This paper presents a numerical model studying the material removal mechanism of CFRP laser milling. It is confirmed by both the experiment and the simulation that laser ablation and mechanical erosion caused by the polymer pyrolysis are all involved in the material removal. Because the heating and cooling rate in short pulsed laser milling is high, ablation of two adjacent laser pulses almost has little influence on each other. By conducting the parametric analysis, it was found that the spacing distance under which the matrix between two adjacent laser pulses was completely degraded should be adopted to utilize the mechanical erosion effectively. Laser milling experiments of CFRP laminates were performed using a nanosecond pulsed laser system. The established model could predict the average ablation depth per scanning pass at an optimal spacing distance.     

专才还是通才?组织成员知识基础对创新绩效的影响

基于多主体仿真方法,构建了成员知识基础对创新绩效影响的动态仿真模型,分析了成员知识深度、知识宽度和知识交叠度对创新绩效的内在作用机理,解答了组织应该选择什么样的人、以及不同的人如何影响组织创新这两个重要问题。研究结果表明,知识宽度对创新绩效有积极效应,而知识深度的效应依赖于知识宽度与知识交叠度的交互影响。其中,知识宽度较低时,知识深度存在消极影响。知识宽度较高时,知识深度对创新绩效存在倒U型影响。知识宽度中等时,成员所拥有的优势知识是否重复至关重要。当优势知识均匀分布时,知识深度呈现积极效应;当优势知识高度重复时,不同领域的知识难以被融会贯通,知识深度的积极效应转变成消极效应。总体来说,兼具知识宽度和知识深度的T型人才最有利于提高创新绩效。此外,在专业型人才队伍中适当引入通用型人才,能够在多数情况下保证组织的最优表现。     

Scattering of an incident acoustic wave by an infinite elastic cylinder in a shallow sea

The scattering of sound waves by an isotropic elastic circular cylinder of infinite extent in a water of finite depth is investigated taking into account the shear waves that can exist in addition to compressional waves in scatterers of solid material. The axis of the cylinder is parallel to the water level. The reflected and transmitted energies are plotted for the various values of the radius of the cylinder, and the farfield scattered pressure is obtained for various depth and presented in a graphical form. Copyright © 2008 John Wiley & Sons, Ltd.     

Numerical simulation of powder mixed electric discharge machining (PMEDM) using finite element method

In the present paper, an axisymmetric two-dimensional model for powder mixed electric discharge machining (PMEDM) has been developed using the finite element method (FEM). The model utilizes the several important aspects such as temperature-sensitive material properties, shape and size of heat source (Gaussian heat distribution), percentage distribution of heat among tool, workpiece and dielectric fluid, pulse on/off time, material ejection efficiency and phase change (enthalpy) etc. to predict the thermal behaviour and material removal mechanism in PMEDM process. The developed model first calculates the temperature distribution in the workpiece material using ANSYS (version 5.4) software and then material removal rate (MRR) is estimated from the temperature profiles. The effect of various process parameters on temperature distributions along the radius and depth of the workpiece has been reported. Finally, the model has been validated by comparing the theoretical MRR with the experimental one obtained from a newly designed experimental setup developed in the laboratory.     

Scalar Conservation Laws with Nonconstant Coefficients with Application to Particle Size Segregation in Granular Flow

Granular materials will segregate by particle size when subjected to shear, as occurs, for example, in avalanches. The evolution of a bidisperse mixture of particles can be modeled by a nonlinear first order partial differential equation, provided the shear (or velocity) is a known function of position. While avalanche-driven shear is approximately uniform in depth, boundary-driven shear typically creates a shear band with a nonlinear velocity profile. In this paper, we measure a velocity profile from experimental data and solve initial value problems that mimic the segregation observed in the experiment, thereby verifying the value of the continuum model. To simplify the analysis, we consider only one-dimensional configurations, in which a layer of small particles is placed above a layer of large particles within an annular shear cell and is sheared for arbitrarily long times. We fit the measured velocity profile to both an exponential function of depth and a piecewise linear function which separates the shear band from the rest of the material. Each solution of the initial value problem is nonstandard, involving curved characteristics in the exponential case, and a material interface with a jump in characteristic speed in the piecewise linear case.     

Clustering Categorical Data via Ensembling Dissimilarity Matrices

We present a technique for clustering categorical data by generating many dissimilarity matrices and combining them. We begin by demonstrating our technique on low-dimensional categorical data and comparing it to several other techniques that have been proposed. We show through simulations and examples that our method is both more accurate and more stable. Then we give conditions under which our method should yield good results in general. Our method extends to high-dimensional categorical data of equal lengths by ensembling over many choices of explanatory variables. In this context, we compare our method with two other methods. Finally, we extend our method to high-dimensional categorical data vectors of unequal length by using alignment techniques to equalize the lengths. We give an example to show that our method continues to provide useful results, in particular, providing a comparison with phylogenetic trees. Supplementary material for this article is available online.