A new boundary-type scheme for sensitivity analysis using Trefftz formulation

This paper presents a new boundary-type scheme for a sensitivity analysis of the two-dimensional potential problem by using the Trefftz formulation.

Since the Trefftz method is the boundary-type solution procedure, input data generation is easier than the domain-type solution procedure. Moreover, the physical quantities are expressed by the regular equations, their sensitivities, which is derived from the direct differentiation of the original quantaties, are also regular. Therefore, they can be calculated more easily than the ordinary boundary element method using the singular boundary integral equation. The present schemes are applied to simple numerical examples in order to confirm the validity of the present formulation.     

Optimization with Variable Sets of Constraints and an Application to Truss Design

We discuss the minimization of a continuous function on a subset of Rⁿ subject to a finite set of continuous constraints. At each point, a given set-valued map determines the subset of constraints considered at this point. Such problems arise e.g. in the design of engineering structures.After a brief discussion on the existence of solutions, the numerical treatment of the problem is considered. It is briefly motivated why standard approaches generally fail. A method is proposed approximating the original problem by a standard one depending on a parameter. It is proved that by choosing this parameter large enough, each solution to the approximating problem is a solution to the original one. In many applications, an upper bound for this parameter can be computed, thus yielding the equivalence of the original problem to a standard optimization problem.The proposed method is applied to the problem of optimally designing a loaded truss subject to local buckling conditions. To our knowledge this problem has not been solved before. A numerical example of reasonable size shows the proposed methodology to work well.     

Theoretical and numerical analysis for the quasi-continuum approximation of a material particle model

In many applications materials are modeled by a large number of particles (or atoms) where any one of particles interacts with all others. Near or nearest neighbor interaction is expected to be a good simplification of the full interaction in the engineering community. In this paper we shall analyze the approximate error between the solution of the simplified problem and that of the full-interaction problem so as to answer the question mathematically for a one-dimensional model. A few numerical methods have been designed in the engineering literature for the simplified model. Recently much attention has been paid to a finite-element-like quasicontinuum (QC) method which utilizes a mixed atomistic/continuum approximation model. No numerical analysis has been done yet. In the paper we shall estimate the error of the QC method for this one-dimensional model. Possible ill-posedness of the method and its modification are discussed as well.

     

A feasible descent SQP algorithm for general constrained optimization without strict complementarity

In this paper, a class of optimization problems with equality and inequality constraints is discussed. Firstly, the original problem is transformed to an associated simpler problem with only inequality constraints and a parameter. The later problem is shown to be equivalent to the original problem if the parameter is large enough (but finite), then a feasible descent SQP algorithm for the simplified problem is presented. At each iteration of the proposed algorithm, a master direction is obtained by solving a quadratic program (which always has a feasible solution). With two corrections on the master direction by two simple explicit formulas, the algorithm generates a feasible descent direction for the simplified problem and a height-order correction direction which can avoid the Maratos effect without the strict complementarity, then performs a curve search to obtain the next iteration point. Thanks to the new height-order correction technique, under mild conditions without the strict complementarity, the globally and superlinearly convergent properties are obtained. Finally, an efficient implementation of the numerical experiments is reported.     

An Algorithm to Optimize the Layout of Boxes in Pallets

The problem of Optimum Pallet Layout at Rowntree Mackintosh Ltd is discussed. Production constraints reduce this three-dimensional box packing problem into the two-dimensional problem of packing large numbers of identical rectangles orthogonally into fixed-size containing rectangles. The exact solution procedure was found to require prohibitive amounts of computer time. A non-exact procedure is therefore described, its validity demonstrated, and the results obtained exhibited graphically in the form of a Pallet Layout Chart. This work has been implemented at Rowntree Mackintosh Ltd where improved pallet layouts and better design of new box shapes have resulted in cash savings.     

An approximate analytical solution for the stresses and strains in heterogeneous cubic materials

Continuous Fourier transforms (CFT) are used to derive analytical expressions for the stress and strain fields, respectively, in heterogeneous bodies consisting of cubic materials which additionally may be addressed to a uniform eigenstrain. The so‐called “equivalent inclusion method” (Mura 1987) builds the starting point of this analytical method. It allows to map the original problem onto an auxiliary problem, where as a simplification a homogeneous body is considered. Problems of this kind are effectively solved by means of the CFT. The application of this transformation results into an integral equation (IEQ) for the strains. For (cubic) anisotropic materials this equation can be further simplified by means of approximation techniques which have been demonstrated in [2,3]. For a particular geometry of the inhomogeneity it is illustrated how to derive a closed‐form solution of this approximated IEQ. This solution is compared with numerical results for different combinations of the matrix and the inhomogeneities.     

Multiobjective transportation problem with interval cost,source and destination parameters

In this paper, we focus on the solution procedure of the multiobjective transportation problem (MOTP) where the cost coefficients of the objective functions, and the source and destination parameters have been expressed as interval values by the decision maker. This problem has been transformed into a classical MOTP where to minimize the interval objective function, the order relations that represent the decision maker's preference between interval profits have been defined by the right limit, left limit, centre, and half-width of an interval. The constraints with interval source and destination parameters have been converted into deterministic ones. Finally, the equivalent transformed problem has been solved by fuzzy programming technique. Numerical examples have been provided to illustrate the solution procedure for three possible cases of the original problem.     

A novel recurrent nonlinear neural network for solving quadratic programming problems

This paper presents a new neural network for solving quadratic programming problems. The new model has a simple form, furthermore it has a good convergence rate with a less number calculation operation than the old models. It converges very fast to exact solution of the dual problem and by substituting in a formulation, the optimal solution of the original problem is obtained. Neural network model with one of numerical method is solved. Finally, simple numerical examples are provided for more illustration.     

Non-isothermal,compressible gas flow for the simulation of an enhanced gas recovery application

In this work, we present a framework for numerical modeling of CO₂ injection into porous media for enhanced gas recovery (EGR) from depleted reservoirs. Physically, we have to deal with non-isothermal, compressible gas flows resulting in a system of coupled non-linear PDEs. We describe the mathematical framework for the underlying balance equations as well as the equations of state for mixing gases. We use an object-oriented finite element method implemented in C++. The numerical model has been tested against an analytical solution for a simplified problem and then applied to CO₂ injection into a real reservoir. Numerical modeling allows to investigate physical phenomena and to predict reservoir pressures as well as temperatures depending on injection scenarios and is therefore a useful tool for applied numerical analysis.     

Numerical verification of delta shock waves for pressureless gas dynamics

The subject of this paper is theoretical analysis and numerical verification of delta shock wave existence for pressureless gas dynamic system. The existence of overcompressive delta shock wave solution in the framework of Colombeau generalized functions is proved. This result is verified numerically by specially designed procedure that is based on wave propagation method implemented in CLAWPACK. The method is coupled with dynamic refinement mesh. We also consider a strictly hyperbolic system obtained from the original one by perturbation and change of variables. The same numerical procedure is applied to the perturbed problem. The obtained numerical results in both cases confirm theoretical expectations.     

An efficient sensitivity computation strategy for the evolutionary structural optimization (ESO) of continuum structures subjected to self-weight loads

This work presents a modified version of the evolutionary structural optimization procedure for topology optimization of continuum structures subjected to self-weight forces. Here we present an extension of this procedure to deal with maximum stiffness topology optimization of structures when different combinations of body forces and fixed loads are applied. Body forces depend on the density distribution over the design domain. Therefore, the value and direction of the loading are coupled to the shape of the structure and they change as the material layout of the structure is modified in the course of the optimization process. It will be shown that the traditional calculation of the sensitivity number used in the ESO procedure does not lead to the optimum solution. Therefore, it is necessary to correct the computation of the element sensitivity numbers in order to achieve the optimum design. This paper proposes an original correction factor to compute the sensitivities and enhance the convergence of the algorithm. The procedure has been implemented into a general optimization software and tested in several numerical applications and benchmark examples to illustrate and validate the approach, and satisfactorily applied to the solution of 2D, 3D and shell structures, considering self-weight load conditions. Solutions obtained with this method compare favourably with the results derived using the SIMP interpolation scheme.     

A dynamic programming based heuristic for the assembly line balancing problem

The simple assembly line balancing problem is the simplification of a real problem associated to the assignment of the elementary tasks required for assembly of a product in an assembly line. This problem has been extensively studied in the literature for more than half a century. The present work proposes a new procedure to solve the problem we call Bounded Dynamic Programming. This use of the term Bounded is associated not only with the use of bounds to reduce the state space but also to the reduction of such space based on heuristics. This procedure is capable of obtaining an optimal solution rate of 267 out of 269 instances, which have been used in previous works, thus obtaining the best-known performance for the problem. These results are an improvement from any previous procedure found in the literature even when using smaller computing times.     

Discharge of gas into vacuum with temperature at the boundary subject to exponential law

A two-dimensional self-similar problem of discharge of a heat conducting gas Into vacuum is analyzed. The temperature at the boundary of gas and vacuum is assumed to change as an exponential function of time. The coefficient of thermal conductivity depends exponentially on temperature and density. The initial gas density is assumed to be finite and constant. With definite values of exponents this problem is self-similar i.e. the system of partial differential equations can be reduced to the solution of a system of ordinary equations.

The self-modeling properties of solutions of this kind of problems has been noted earlier in [1 and 2]. The problem analyzed here is a particular case of the problem of piston motion considered in [3]. In this problem, however, there appears at the boundary of gas and vacuum a new singular point which does not occur in the piston problem.

A numerical solution of the boundary value problem defined by a system of ordinary equations is made difficult by the presence in the latter of singular points, and of discontinuities in the sought solution. These difficulties have been overcome by a qualitative analysis of the behavior of integral curves, and by the selection of a suitable method of numerical integration.

It is shown in this work that, depending on the initial parameters of the problem, there may exist two kinds of solutions. This had been noted earlier in [1, 3 and 4]. Examples of these are presented here. The degeneration of the solution into a trivial one, when the thermal conductivity coefficient is either invariant of density, or increases with increasing density, is pointed out.     

An approximate solution of the MHD Falkner–Skan flow by Hermite functions pseudospectral method

Based on a new approximation method, namely pseudospectral method, a solution for the three order nonlinear ordinary differential laminar boundary layer Falkner–Skan equation has been obtained on the semi-infinite domain. The proposed approach is equipped by the orthogonal Hermite functions that have perfect properties to achieve this goal. This method solves the problem on the semi-infinite domain without truncating it to a finite domain and transforming domain of the problem to a finite domain. In addition, this method reduces solution of the problem to solution of a system of algebraic equations. We also present the comparison of this work with numerical results and show that the present method is applicable.     

A nonlinearity lagging for the solution of nonlinear steady state reaction diffusion problems

This paper concerns with the analysis of the iterative procedure for the solution of a nonlinear reaction diffusion equation at the steady state in a two dimensional bounded domain supplemented by suitable boundary conditions. This procedure, called Lagged Diffusivity Functional Iteration (LDFI)-procedure, computes the solution by “lagging” the diffusion term. A model problem is considered and a finite difference discretization for that model problem is described. Furthermore, properties of the finite difference operator are proved. Then, sufficient conditions for the convergence of the LDFI-procedure are given. At each stage of the LDFI-procedure a weakly nonlinear algebraic system has to be solved and the simplified Newton–Arithmetic Mean (Newton–AM) method is used. This method is particularly well suited for implementation on parallel computers. Numerical studies show the efficiency, for different test functions, of the LDFI-procedure combined with the simplified Newton–AM method. Better results are obtained when in the reaction diffusion equation also a convection term is present.     

Two-stage fuzzy production planning expected value model and its approximation method

This work develops a novel two-stage fuzzy optimization method for solving the multi-product multi-period (MPMP) production planning problem, in which the market demands and some of the inventory costs are assumed to be uncertainty and characterized by fuzzy variables with known possibility distributions. Some basic properties about the MPMP production planning problem are discussed. Since the fuzzy market demands and inventory costs usually have infinite supports, the proposed two-stage fuzzy MPMP production planning problem is an infinite-dimensional optimization problem that cannot be solved directly by conventional numerical solution methods. To overcome this difficulty, this paper adopts an approximation method (AM) to turn the original two-stage fuzzy MPMP production planning problem into a finite-dimensional optimization problem. The convergence about the AM is discussed to ensure the solution quality. After that, we design a heuristic algorithm, which combines the AM and simulated annealing (SA) algorithm, to solve the proposed two-stage fuzzy MPMP production planning problem. Finally, one real case study about a furniture manufacturing company is presented to illustrate the effectiveness and feasibility of the proposed modeling idea and designed algorithm.     

Iterative solution of matrix games using grid variational inequalities

A new approach to the approximate solution of matrix games is proposed. It is based on the reduction of the original problem to a variational inequality of a special form. In particular, this makes it possible to design preconditioned iterative methods, which proved to be effective as a tool for the numerical solution of large and ill-conditioned systems of linear algebraic equations.     

How to solve a design centering problem

This work considers the problem of design centering. Geometrically, this can be thought of as inscribing one shape in another. Theoretical approaches and reformulations from the literature are reviewed; many of these are inspired by the literature on generalized semi-infinite programming, a generalization of design centering. However, the motivation for this work relates more to engineering applications of robust design. Consequently, the focus is on specific forms of design spaces (inscribed shapes) and the case when the constraints of the problem may be implicitly defined, such as by the solution of a system of differential equations. This causes issues for many existing approaches, and so this work proposes two restriction-based approaches for solving robust design problems that are applicable to engineering problems. Another feasible-point method from the literature is investigated as well. The details of the numerical implementations of all these methods are discussed. The discussion of these implementations in the particular setting of robust design in engineering problems is new.     

Numerical Homotopies to Compute Generic Points on Positive Dimensional Algebraic Sets

Many applications modeled by polynomial systems have positive dimensional solution components (e.g., the path synthesis problems for four-bar mechanisms) that are challenging to compute numerically by homotopy continuation methods. A procedure of A. Sommese and C. Wampler consists in slicing the components with linear subspaces in general position to obtain generic points of the components as the isolated solutions of an auxiliary system. Since this requires the solution of a number of larger overdetermined systems, the procedure is computationally expensive and also wasteful because many solution paths diverge. In this article an embedding of the original polynomial system is presented, which leads to a sequence of homotopies, with solution paths leading to generic points of all components as the isolated solutions of an auxiliary system. The new procedure significantly reduces the number of paths to solutions that need to be followed. This approach has been implemented and applied to various polynomial systems, such as the cyclic n-roots problem.     

Artificial damping in multigrid methods

When the solution and problem coefficients are highly oscillatory, the computed solution may not show characteristics of the original physical problem unless the numerical mesh is sufficiently fine. In the case, the coarse grid problem of a multigrid (MG) algorithm must be still huge and poorly-conditioned, and therefore, it is hard to solve by either a direct method or an iterative scheme. This article suggests a MG algorithm for such problems in which the coarse grid problem is slightly modified by an artificial damping (compressibility) term. It has been numerically observed that the artificial damping, even if slight, makes the coarse grid problem much easier to solve, without deteriorating the overall convergence rate of the MG method. For most problems, 2–6 times speed up have been observed.