First‐Order system least squares for generalized‐Newtonian coupled Stokes‐Darcy flow

The coupled problem for a generalized Newtonian Stokes flow in one domain and a generalized Newtonian Darcy flow in a porous medium is studied in this work. Both flows are treated as a first‐order system in a stress‐velocity formulation for the Stokes problem and a volumetric flux‐hydraulic potential formulation for the Darcy problem. The coupling along an interface is done using the well‐known Beavers–Joseph–Saffman interface condition. A least squares finite element method is used for the numerical approximation of the solution. It is shown that under some assumptions on the viscosity the error is bounded from above and below by the least squares functional. An adaptive refinement strategy is examined in several numerical examples where boundary singularities are present. Due to the nonlinearity of the problem a Gauss–Newton method is used to iteratively solve the problem. It is shown that the linear variational problems arising in the Gauss–Newton method are well posed. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 1150–1173, 2015     

Indirect boundary integral formulation for the solution of shear‐thinning flow inside single rotor mixers

An efficient indirect boundary integral formulation for the evaluation of inelastic non‐Newtonian shear‐thinning flows at low Reynolds number is presented in this article. The formulation is based on the solution of a homogeneous Stokes flow field and the use of a particular solution for the nonlinear non‐Newtonian terms that yields the complete solution to the problem. Matrix multiplications are reduced in comparison to other means of handling nonlinear terms in boundary integral formulations such as the dual reciprocity method. The iterative solution of the nonlinear system of equations has been performed with a modified Newton‐Raphson method obtaining accurate results for values of the power law index as low as 0.4 without domain partitioning. Geometries such as Couette flow and a typical industrial polymer mixer have been analyzed with the proposed method obtaining good results with a reduction in computational cost compared with other equivalent formulations. © 2010 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 27:1610–1627, 2011     

A mixed finite element method for a quasi‐Newtonian fluid flow

We propose a mixed formulation for quasi‐Newtonian fluid flow obeying the power law where the stress tensor is introduced as a new variable. Based on such a formulation, a mixed finite element is constructed and analyzed. This finite element method possesses local (i.e., at element level) conservation properties (conservation of the momentum and the mass) as in the finite volume methods. We give existence and uniqueness results for the continuous problem and its approximation and we prove error bounds. © 2004 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2004.     

Dual‐primal mixed finite elements for elliptic problems

In this article, a novel dual‐primal mixed formulation for second‐order elliptic problems is proposed and analyzed. The Poisson model problem is considered for simplicity. The method is a Petrov—Galerkin mixed formulation, which arises from the one‐element formulation of the problem and uses trial functions less regular than the test functions. Thus, the trial functions need not be continuous while the test functions must satisfy some regularity constraint. Existence and uniqueness of the solution are proved by using the abstract theory of Nicolaides for generalized saddle‐point problems. The Helmholtz Decomposition Principle is used to prove the inf‐sup conditions in both the continuous and the discrete cases. We propose a family of finite elements valid for any order, which employs piecewise polynomials and Raviart—Thomas elements. We show how the method, with this particular choice of the approximation spaces, is linked to the superposition principle, which holds for linear problems and to the standard primal and dual formulations, addressing how this can be employed for the solution of the final linear system. © 2001 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 17: 137–151, 2001     

Unique solvability for the density‐dependent non‐Newtonian compressible fluids with vacuum

The paper is devoted to the existence and uniqueness of local solutions for the density‐dependent non‐Newtonian compressible fluids with vacuum in one‐dimensional bounded intervals. The important points in this paper are that the initial density may vanish in an open subset and the viscosity coefficient is nonlinearly dependent of density and shear rate.     

Mayer and optimal stopping stochastic control problems with discontinuous cost

We study two classes of stochastic control problems with semicontinuous cost: the Mayer problem and optimal stopping for controlled diffusions. The value functions are introduced via linear optimization problems on appropriate sets of probability measures. These sets of constraints are described deterministically with respect to the coefficient functions. Both the lower and upper semicontinuous cases are considered. The value function is shown to be a generalized viscosity solution of the associated HJB system, respectively, of some variational inequality. Dual formulations are given, as well as the relations between the primal and dual value functions. Under classical convexity assumptions, we prove the equivalence between the linearized Mayer problem and the standard weak control formulation. Counter-examples are given for the general framework.     

Numerical simulation of non-Newtonian blood flow in bypass models

The article presents the numerical investigation of non–Newtonian effects of steady blood flow in complete idealized 3–D bypass models, whose native artery is either coronary or femoral with average physiological parameters. Considering the blood to be a generalized Newtonian fluid, the shear–dependent viscosity is described by two well–known macroscopic non–Newtonian models (the Carreau–Yasuda model and the modified Cross model). The results were obtained by own developed computational software based on the pseudo–compressibility approach and on the cell–centred finite volume method defined on unstructured hexahedral grids. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Using Duality Theory for Identification of Primal Efficient Points and for Sensitivity Analysis in Multiple Objective Linear Programming

The dual of the multiple objective linear programming problem is defined as a multiparametric LP problem for the right-hand sides. The resulting dual variables are multidimensional and are related to the indifference regions in the primal problem. The formulation of the dual is shown to be preferable to the vector minimization formulation in terms of (a) identifying primal efficient points and indifference regions, and (b) sensitivity analysis.     

A Class of Subdifferential Inclusions for Elastic Unilateral Contact Problems

We consider a class of stationary subdifferential inclusions in a reflexive Banach space. We reformulate the problem in terms of a variational inequality with multivalued term and prove an existence result using the Kakutani-Fan-Glicksberg fixed point theorem. This approach allows to consider, in a natural way, a dual variational formulation of the problem. Next, we study the link between the primal and dual formulations and provide an equivalence result. Then, we consider a new mathematical model which describes the contact of an elastic body with a foundation. We apply the abstract formalism to derive the primal and the dual variational formulations of the problem, in terms of displacement and stress, respectively. Finally, we present existence and equivalence results in the study of this contact model.     

On the computational utility of posynomial geometric programming solution methods

Ten codes or code variants were used to solve the five equivalent posynomial GP problem formulations. Four of these codes were general NLP codes; six were specialized GP codes. A total of forty-two test problems was solved with up to twenty randomly generated starting points per problem. The convex primal formulation is shown to be intrinsically easiest to solve. The general purpose GRG code called OPT appears to be the most efficient code for GP problem solution. The reputed superiority of the specialized GP codes GGP and GPKTC appears to be largely due to the fact that these codes solve the convex primal formulation. The dual approaches are only likely to be competitive for small degree of difficulty, tightly constrained problems.     

Johri's general dual,the Lagrangian dual,and the surrogate dual

Duality formulations can be derived from a nonlinear primal optimization problem in several ways. One abstract theoretical concept presented by Johri is the framework of general dual problems. They provide the tightest of specific bounds on the primal optimum generated by dual subproblems which relax the primal problem with respect to the objective function or to the feasible set or even to both. The well-known Lagrangian dual and surrogate dual are shown to be special cases. Dominating functions and including sets which are the two relaxation devices of Johri's general dual turn out to be the most general formulations of augmented Lagrangian functions and augmented surrogate regions.     

Numerical Solution of Newtonian and Non-Newtonian Flows in Bypass

This paper deals with a numerical solution of laminar incompressible steady flows of Newtonian and non–Newtonian fluids through bypass of a restricted vessel. Blood flow is considered to be Newtonian in the case of vessels of large diameters as aorta. On the other hand, with decreasing diameter of a vessel the non–Newtonian behavior of blood can play a significant role. One could describe these problems using Navier–Stokes equations and continuity equation as a model. In the case of Newtonian fluids one considers constant viscosity compared to non–Newtonian fluids where viscosity varies and can depend on the tensor of deformation. In order to find numerical solution, the system of equations is completed using an artificial compressibility method. The space derivatives are discretised using a cell centered finite volume method and arising system of ordinary differential equations is solved using an explicit multistage Runge–Kutta method with given steady boundary conditions. The steady solution is achieved for time t→∞ and steady boundary conditions. The results can be used in the field of cardiovascular research. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Local strong solutions to a compressible non‐Newtonian fluid with density‐dependent viscosity

We consider the initial boundary problem for a compressible non‐Newtonian fluid with density‐dependent viscosity. The local existence of strong solution is established that is based on some compatibility condition. Moreover, it is also proved that the solutions are to blow up, and the maximum norm of velocity gradients controls the possible break down of the strong solutions. Copyright © 2016 John Wiley & Sons, Ltd.     

The multipliers‐free domain decomposition methods

This article concludes the development and summarizes a new approach to dual‐primal domain decomposition methods (DDM), generally referred to as “the multipliers‐free dual‐primal method.” Contrary to standard approaches, these new dual‐primal methods are formulated without recourse to Lagrange‐multipliers. In this manner, simple and unified matrix‐expressions, which include the most important dual‐primal methods that exist at present are obtained, which can be effectively applied to floating subdomains, as well. The derivation of such general matrix‐formulas is independent of the partial differential equations that originate them and of the number of dimensions of the problem. This yields robust and easy‐to‐construct computer codes. In particular, 2D codes can be easily transformed into 3D codes. The systematic use of the average and jump matrices, which are introduced in this approach as generalizations of the “average” and “jump” of a function, can be effectively applied not only at internal‐boundary‐nodes but also at edges and corners. Their use yields significant advantages because of their superior algebraic and computational properties. Furthermore, it is shown that some well‐known difficulties that occur when primal nodes are introduced are efficiently handled by the multipliers‐free dual‐primal method. The concept of the Steklov–Poincaré operator for matrices is revised by our theory and a new version of it, which has clear advantages over standard definitions, is given. Extensive numerical experiments that confirm the efficiency of the multipliers‐free dual‐primal methods are also reported here. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2010     

有界整规划中的渐近强非线性对偶

本文提出了一种整数规划中的指数一对数对偶.证明了此指数-对数对偶方法具有的渐近强对偶性质,并提出了不需要进行对偶搜索来解原整数规划问题的方法.特别地,当选取合适的参数和对偶变量时,原整数规划问题的解可以通过解一个非线性松弛问题来得到.对具有整系数目标函数及约束函数的多项式整规划问题,给出了参数及对偶变量的取法.     

Truss topology optimization including unilateral contact

This work extends the ground structure approach of truss topology optimization to include unilateral contact conditions. The traditional design objective of finding the stiffest truss among those of equal volume is combined with a second objective of achieving a uniform contact force distribution. Design variables are the volume of bars and the gaps between potential contact nodes and rigid obstacles. The problem can be viewed as that of finding a saddle point of the equilibrium potential energy function (a convex problem) or as that of minimizing the external work among all trusses that exhibit a uniform contact force distribution (a nonconvex problem). These two formulations are related, although not completely equivalent: they give the same design, but concerning the associated displacement states, the solutions of the first formulation are included among those of the second but the opposite does not necessarily hold.In the classical noncontact single-load case problem, it is known that an optimal truss can be found by solving a linear programming (LP) limit design problem, where compatibility conditions are not taken into account. This result is extended to include unilateral contact and the second objective of obtaining a uniform contact force distribution. The LP formulation is our vehicle for proving existence of an optimal design: by standard LP theory, we need only to show primal and dual feasibility; the primal one is obvious, and the dual one is shown by the Farkas lemma to be equivalent to a condition on the direction of the external load. This method of proof extends results in the classical noncontact case to structures that have a singular stiffness matrix for all designs, including a case with no prescribed nodal displacements.Numerical solutions are also obtained by using the LP formulation. It is applied to two bridge-type structures, and trusses that are optimal in the above sense are obtained.This work was supported by The Center for Industrial Information Technology (CENIIT) and the Swedish Research Council for Engineering Sciences (TFR).     

Nonanticipative duality,relaxations, and formulations for chance-constrained stochastic programs

We propose two new Lagrangian dual problems for chance-constrained stochastic programs based on relaxing nonanticipativity constraints. We compare the strength of the proposed dual bounds and demonstrate that they are superior to the bound obtained from the continuous relaxation of a standard mixed-integer programming (MIP) formulation. For a given dual solution, the associated Lagrangian relaxation bounds can be calculated by solving a set of single scenario subproblems and then solving a single knapsack problem. We also derive two new primal MIP formulations and demonstrate that for chance-constrained linear programs, the continuous relaxations of these formulations yield bounds equal to the proposed dual bounds. We propose a new heuristic method and two new exact algorithms based on these duals and formulations. The first exact algorithm applies to chance-constrained binary programs, and uses either of the proposed dual bounds in concert with cuts that eliminate solutions found by the subproblems. The second exact method is a branch-and-cut algorithm for solving either of the primal formulations. Our computational results indicate that the proposed dual bounds and heuristic solutions can be obtained efficiently, and the gaps between the best dual bounds and the heuristic solutions are small.     

A primal‐dual method for the Meyer model of cartoon and texture decomposition

In this paper, we study the original Meyer model of cartoon and texture decomposition in image processing. The model, which is a minimization problem, contains an l₁‐based TV‐norm and an l_∞‐based G‐norm. The main idea of this paper is to use the dual formulation to represent both TV‐norm and G‐norm. The resulting minimization problem of the Meyer model can be given as a minimax problem. A first‐order primal‐dual algorithm can be developed to compute the saddle point of the minimax problem. The convergence of the proposed algorithm is theoretically shown. Numerical results are presented to show that the original Meyer model can decompose better cartoon and texture components than the other testing methods.     

An upwinding cell‐centered method with piecewise constant velocity over covolumes

We analyze as a covolume method an upwinding cell‐centered method derived from a mixed formulation of the convection–diffusion equation. The covolume method uses primal and dual partitions of the problem domain to assign degrees of freedom and is a natural generalization of the well known MAC (Marker and Cell) method. The concentration is cell‐centered (piecewise constant with respect to the primal partition), and the velocity is covolume‐ or co‐cell centered (piecewise constant with respect to the dual partition). Convergence results are demonstrated in the L² norm. © 1999 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 15: 49–62, 1999     

Linearization Techniques for Controlled Piecewise Deterministic Markov Processes; Application to Zubov’s Method

We aim at characterizing domains of attraction for controlled piecewise deterministic processes using an occupational measure formulation and Zubov??s approach. Firstly, we provide linear programming (primal and dual) formulations of discounted, infinite horizon control problems for PDMPs. These formulations involve an infinite-dimensional set of probability measures and are obtained using viscosity solutions theory. Secondly, these tools allow to construct stabilizing measures and to avoid the assumption of stability under concatenation for controls. The domain of controllability is then characterized as some level set of a convenient solution of the associated Hamilton-Jacobi integral-differential equation. The theoretical results are applied to PDMPs associated to stochastic gene networks. Explicit computations are given for Cook??s model for gene expression.