Constraint Force Analysis of Metamorphic Joints Based on the Augmented Assur Groups

In order to obtain a simple way for the force analysis of metamorphic mechanisms, the systematic method to unify the force analysis approach of metamorphic mechanisms as that of conventional planar mechanisms is proposed. A force analysis method of metamorphic mechanisms is developed by transforming the augmented Assur groups into Assur groups, so that the force analysis problem of metamorphic mechanisms is converted into the force analysis problems of conventional planar mechanisms. The constraint force change rules and values of metamorphic joints are obtained by the proposed method, and the constraint force analysis equations of revolute metamorphic joints in augmented Assur group RRRR and prismatic metamorphic joints in augmented Assur group RRPR are deduced. The constraint force analysis is illustrated by the constrained spring force design of paper folding metamorphic mechanism, and its metamorphic working process is controlled by the spring force and geometric constraints of metamorphic joints. The results of spring force show that developped design method and approach are feasible and practical. By transforming augmented Assur groups into Assur groups, a new method for the constraint force analysis of metamorphic joints is proposed firstly to provide the basis for dynamic analysis of metamorphic mechanism.

Modified Augmented Lagrange Multiplier Methods for Large-Scale Chemical Process Optimization

Chemical process optimization can be described as large-scale nonlinear constrained minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale nonlinear constrained minimization are studied in this paper. The Lagrange function contains the penalty terms on equality and inequality constraints and the methods can be applied to solve a series of bound constrained sub-problems instead of a series of unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical experiments are made for a variety of problems, from small to very large-scale, which show the stability and effectiveness of the methods in large-scale problems.

Accelerated Matrix Recovery via Random Projection Based on Inexact Augmented Lagrange Multiplier Method

In this paper, a unified matrix recovery model was proposed for diverse corrupted matrices. Resulting from the separable structure of the proposed model, the convex optimization problem can be solved efficiently by adopting an inexact augmented Lagrange multiplier (IALM) method. Additionally, a random projection accelerated technique (IALM+RP) was adopted to improve the success rate. From the preliminary numerical comparisons, it was indicated that for the standard robust principal component analysis (PCA) problem, IALM+RP was at least two to six times faster than IALM with an insignificant reduction in accuracy; and for the outlier pursuit (OP) problem, IALM+RP was at least 6.9 times faster, even up to 8.3 times faster when the size of matrix was 2 000×2 000.

CONTACT MODEL BASED ON AUGMENTED LAGRANGE METHOD AND ITS ENGINEERING APPLICATION

A kind of improved contact frictional model on basis of traditional Coulomb Friction model is adopted. Corresponding contact element is also given. The contact algorithm on basis of augmented Lagrange method is introduced and successfully applied to complex contact friction problem. Test example and actual engineering case all show that the algorithm of the model is efficient and computation results agree well with general rules.

The Rate of Convergence of Augmented Lagrangian Method for Minimax Optimization Problems with Equality Constraints

The augmented Lagrangian function and the corresponding augmented Lagrangian method are constructed for solving a class of minimax optimization problems with equality constraints.We prove that,under the linear independence constraint qualification and the second-order sufficiency optimality condition for the lower level problem and the second-order sufficiency optimality condition for the minimax problem,for a given multiplier vectorμ,the rate of convergence of the augmented Lagrangian method is linear with respect to||μu-μ^(*)||and the ratio constant is proportional to 1/c when the ratio|μ-μ^(*)||/c is small enough,where c is the penalty parameter that exceeds a threshold c_(*)>O andμ^(*)is the multiplier corresponding to a local minimizer.Moreover,we prove that the sequence of multiplier vectors generated by the augmented Lagrangian method has at least Q-linear convergence if the sequence of penalty parameters(ck)is bounded and the convergence rate is superlinear if(ck)is increasing to infinity.Finally,we use a direct way to establish the rate of convergence of the augmented Lagrangian method for the minimax problem with a quadratic objective function and linear equality constraints.

An Augmented Lagrangian based Semismooth Newton Method for a Class of Bilinear Programming Problems

This paper proposes a semismooth Newton method for a class of bilinear programming problems(BLPs)based on the augmented Lagrangian,in which the BLPs are reformulated as a system of nonlinear equations with original variables and Lagrange multipliers.Without strict complementarity,the convergence of the method is studied by means of theories of semismooth analysis under the linear independence constraint qualification and strong second order sufficient condition.At last,numerical results are reported to show the performance of the proposed method.

Modified iterative method for augmented system

The successive overrelaxation-like （SOR-like） method with the real param- eters ω is considered for solving the augmented system. The new method is called the modified SOR-like （MSOR-like） method. The functional equation between the parameters and the eigenvalues of the iteration matrix of the MSOR-like method is given. Therefore, the necessary and sufficient condition for the convergence of the MSOR-like method is derived. The optimal iteration parameter ω of the MSOR-like method is derived. Finally, the proof of theorem and numerical computation based on a particular linear system are given, which clearly show that the MSOR-like method outperforms the SOR-like （Li, C. J., Li, B. J., and Evans, D. J. Optimum accelerated parameter for the GSOR method. Neural, Parallel ＆ Scientific Computations, 7（4）, 453-462 （1999）） and the modified sym- metric SOR-like （MSSOR-like） methods （Wu, S. L., Huang, T. Z., and Zhao, X. L. A modified SSOR iterative method for augmented systems. Journal of Computational and Applied Mathematics, 228（4）, 424-433 （2009））.

Reduced projection augmented Lagrange bi-conjugate gradient method for contact and impact problems

Based on the numerical governing formulation and non-linear complementary conditions of contact and impact problems, a reduced projection augmented Lagrange bi- conjugate gradient method is proposed for contact and impact problems by translating non-linear complementary conditions into equivalent formulation of non-linear program- ming. For contact-impact problems, a larger time-step can be adopted arriving at numer- ical convergence compared with penalty method. By establishment of the impact-contact formulations which are equivalent with original non-linear complementary conditions, a reduced projection augmented Lagrange bi-conjugate gradient method is deduced to im- prove precision and efficiency of numerical solutions. A numerical example shows that the algorithm we suggested is valid and exact.

An Augmented IB Method&Analysis for Elliptic BVP on Irregular Domains

The immersed boundary method is well-known,popular,and has had vast areas of applications due to its simplicity and robustness even though it is only first order accurate near the interface.In this paper,an immersed boundary-augmented method has been developed for linear elliptic boundary value problems on arbitrary domains(exterior or interior)with a Dirichlet boundary condition.The new method inherits the simplicity,robustness,and first order convergence of the IB method but also provides asymptotic first order convergence of partial derivatives.Numerical examples are provided to confirm the analysis.

Augmented Lagrangian Methods for Numerical Solutions to Higher Order Differential Equations

A large number of problems in engineering can be formulated as the optimization of certain functionals. In this paper, we present an algorithm that uses the augmented Lagrangian methods for finding numerical solutions to engineering problems. These engineering problems are described by differential equations with boundary values and are formulated as optimization of some functionals. The algorithm achieves its simplicity and versatility by choosing linear equality relations recursively for the augmented Lagrangian associated with an optimization problem. We demonstrate the formulation of an optimization functional for a 4th order nonlinear differential equation with boundary values. We also derive the associated augmented Lagrangian for this 4th order differential equation. Numerical test results are included that match up with well-established experimental outcomes. These numerical results indicate that the new algorithm is fully capable of producing accurate and stable solutions to differential equations.

An optimization method for passive muzzle arc control devices in augmented railguns

In this paper,a passive muzzle arc control device(PMACD)of the augmented railguns is studied.By discussing its performance at different numbers of extra rails,a parameter optimization model is proposed.Through the calculation model,it is found that the PMACD works well in the simple railgun,which refers to the gun that there is only one pair of rails in the inner bore.The PMACD may decrease the simple railgun’s armature peak current and muzzle arc,but affect its muzzle velocity not much.However,in the augmented railguns it has different characteristics.If the parameters of the PMACD are not selected suitable.It may increase the armature peak current and muzzle arc,but greatly decrease the velocity.The reason for this problem is that the extra rails generate a strong magnetic field in front of the armature,which induces a large current to change the armature current.It is also found that when the resistance and inductance parameters of the PMACD satisfy with the optimization formula,the PMACD can also play a good role in arc suppression in the augmented railguns.Experiments of an augmented railgun with a stainless steel PMACD are carried out to verify this optimization method.Results show that the muzzle arc is obviously controlled.This work may provide a reference for the design of the muzzle arc control device.

An Optimization Model for the Strip-packing Problem and Its Augmented Lagrangian Method

This paper formulates a two-dimensional strip packing problem as a non- linear programming （NLP） problem and establishes the first-order optimality conditions for the NLP problem. A numerical algorithm for solving this NLP problem is given to find exact solutions to strip-packing problems involving up to 10 items. Approximate solutions can be found for big-sized problems by decomposing the set of items into small-sized blocks of which each block adopts the proposed numerical algorithm. Numerical results show that the approximate solutions to big-sized problems obtained by this method are superior to those by NFDH, FFDH and BFDH approaches.

A New Algorithm for Reducing Dimensionality of L1-CSVM Use Augmented Lagrange Method

Principal component analysis and generalized low rank approximation of matrices are two different dimensionality reduction methods. Two different dimensionality reduction algorithms are applied to the L1-CSVM model based on augmented Lagrange method to explore the variation of running time and accuracy of the model in dimensionality reduction space. The results show that the improved algorithm can greatly reduce the running time and improve the accuracy of the algorithm.

Augmented Lagrange方法在钢丝绳捻制成形摩擦接触数值模拟中的应用

钢丝绳中金属线间接触摩擦会影响捻制成形加工应力和结构强度。在经典的Coulom摩擦理论的基础上,本文采用AugmentedLagrange方法计算钢丝绳捻制过程中的法向接触力和摩擦接触力,并应用radial return径向回映法修正摩擦接触力试算值。以钢丝绳一次捻制成形过程为例,分析并讨论了摩擦系数和自扭转系数对接触应力和加工应力应变的影响,为钢丝绳成形工艺和结构强度的合理设计提供依据。

Partition method for impact dynamics of flexible multibody systems based on contact constraint

The impact dynamics of a flexible multibody system is investigated. By using a partition method, the system is divided into two parts, the local impact region and the region away from the impact. The two parts are connected by specific boundary conditions, and the system after partition is equivalent to the original system. According to the rigid-flexible coupling dynamic theory of multibody system, system＇s rigid-flexible coupling dynamic equations without impact are derived. A local impulse method for establishing the initial impact conditions is proposed. It satisfies the compatibility con- ditions for contact constraints and the actual physical situation of the impact process of flexible bodies. Based on the contact constraint method, system＇s impact dynamic equa- tions are derived in a differential-algebraic form. The contact/separation criterion and the algorithm are given. An impact dynamic simulation is given. The results show that system＇s dynamic behaviors including the energy, the deformations, the displacements, and the impact force during the impact process change dramatically. The impact makes great effects on the global dynamics of the system during and after impact.

Precipitation Retrieval from Himawari-8 Satellite Infrared Data Based on Dictionary Learning Method and Regular Term Constraint

In this paper,the application of an algorithm for precipitation retrieval based on Himawari-8 (H8) satellite infrared data is studied.Based on GPM precipitation data and H8 Infrared spectrum channel brightness temperature data,corresponding "precipitation field dictionary" and "channel brightness temperature dictionary" are formed.The retrieval of precipitation field based on brightness temperature data is studied through the classification rule of k-nearest neighbor domain (KNN) and regularization constraint.Firstly,the corresponding "dictionary" is constructed according to the training sample database of the matched GPM precipitation data and H8 brightness temperature data.Secondly,according to the fact that precipitation characteristics in small organizations in different storm environments are often repeated,KNN is used to identify the spectral brightness temperature signal of "precipitation" and "non-precipitation" based on "the dictionary".Finally,the precipitation field retrieval is carried out in the precipitation signal "subspace" based on the regular term constraint method.In the process of retrieval,the contribution rate of brightness temperature retrieval of different channels was determined by Bayesian model averaging (BMA) model.The preliminary experimental results based on the "quantitative" evaluation indexes show that the precipitation of H8 retrieval has a good correlation with the GPM truth value,with a small error and similar structure.

On the symplectic superposition method for free vibration of rectangular thin plates with mixed boundary constraints on an edge

A novel symplectic superposition method has been proposed and developed for plate and shell problems in recent years.The method has yielded many new analytic solutions due to its rigorousness.In this study,the first endeavor is made to further developed the symplectic superposition method for the free vibration of rectangular thin plates with mixed boundary constraints on an edge.The Hamiltonian system-based governing equation is first introduced such that the mathematical techniques in the symplectic space are applied.The solution procedure incorporates separation of variables,symplectic eigen solution and superposition.The analytic solution of an original problem is finally obtained by a set of equations via the equivalence to the superposition of some elaborated subproblems.The natural frequency and mode shape results for representative plates with both clamped and simply supported boundary constraints imposed on the same edge are reported for benchmark use.The present method can be extended to more challenging problems that cannot be solved by conventional analytic methods.

Fail-Safe Topology Optimization of Continuum Structures with Multiple Constraints Based on ICM Method

Traditional topology optimization methods may lead to a great reduction in the redundancy of the optimized structure due to unexpected material removal at the critical components.The local failure in critical components can instantly cause the overall failure in the structure.More and more scholars have taken the fail-safe design into consideration when conducting topology optimization.A lot of good designs have been obtained in their research,though limited regarding minimizing structural compliance(maximizing stiffness)with given amount of material.In terms of practical engineering applications considering fail-safe design,it is more meaningful to seek for the lightweight structure with enough stiffness to resist various component failures and/or to meet multiple design requirements,than the stiffest structure only.Thus,this paper presents a fail-safe topology optimization model for minimizing structural weight with respect to stress and displacement constraints.The optimization problem is solved by utilizing the independent continuous mapping(ICM)method combined with the dual sequence quadratic programming(DSQP)algorithm.Special treatments are applied to the constraints,including converting local stress constraints into a global structural strain energy constraint and expressing the displacement constraint explicitly with approximations.All of the constraints are nondimensionalized to avoid numerical instability caused by great differences in constraint magnitudes.The optimized results exhibit more complex topological configurations and higher redundancy to resist local failures than the traditional optimization designs.This paper also shows how to find the worst failure region,which can be a good reference for designers in engineering.

MULTILEVEL AUGMENTATION METHODS FOR SOLVING OPERATOR EQUATIONS

We introduce multilevel augmentation methods for solving operator equations based on direct sum decompositions of the range space of the operator and the solution space of the operator equation and a matrix splitting scheme. We establish a general setting for the analysis of these methods, showing that the methods yield approximate solutions of the same convergence order as the best approximation from the subspace. These augmentation methods allow us to develop fast, accurate and stable nonconventional numerical algorithms for solving operator equations. In particular, for second kind equations, special splitting techniques are proposed to develop such algorithms. These algorithms are then applied to solve the linear systems resulting from matrix compression schemes using wavelet-like functions for solving Fredholm integral equations of the second kind. For this special case, a complete analysis for computational complexity and convergence order is presented. Numerical examples are included to demonstrate the efficiency and accuracy of the methods. In these examples we use the proposed augmentation method to solve large scale linear systems resulting from the recently developed wavelet Galerkin methods and fast collocation methods applied to integral equations of the secondkind. Our numerical results confirm that this augmentation method is particularly efficient for solving large scale linear systems induced from wavelet compression schemes.

A LEVEL SET METHOD FOR STRUCTURAL TOPOLOGY OPTIMIZATION WITH MULTI-CONSTRAINTS AND MULTI-MATERIALS

Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in this paper.The method implicitly describes structural material in- terfaces by the vector level set and achieves the optimal shape and topology through the continuous evolution of the material interfaces in the structure.In order to increase computational efficiency for a fast convergence,an appropriate nonlinear speed mapping is established in the tangential space of the active constraints.Meanwhile,in order to overcome the numerical instability of general topology opti- mization problems,the regularization with the mean curvature flow is utilized to maintain the interface smoothness during the optimization process.The numerical examples demonstrate that the approach possesses a good flexibility in handling topological changes and gives an interface representation in a high fidelity,compared with other methods based on explicit boundary variations in the literature.