Topology optimization of channel flow problems

This paper describes a topology design method for simple two-dimensional flow problems. We consider steady, incompressible laminar viscous flows at low-to-moderate Reynolds numbers. This makes the flow problem nonlinear and hence a nontrivial extension of the work of Borrvall and Petersson (2003).Further, the inclusion of inertia effects significantly alters the physics, enabling solutions of new classes of optimization problems, such as velocity-driven switches, that are not addressed by the earlier method. Specifically, we determine optimal layouts of channel flows that extremize a cost function which measures either some local aspect of the velocity field or a global quantity, such as the rate of energy dissipation. We use the finite element method to model the flow, and we solve the optimization problem with a gradient-based math-programming algorithm that is driven by analytical sensitivities. Our target application is optimal layout design of channels in fluid network systems. Using concepts borrowed from topology optimization of compliant mechanisms in solid mechanics, we introduce a method for the synthesis of fluidic components, such as switches, diodes, etc.     

Topology optimization in crashworthiness design

Topology optimization has developed rapidly, primarily with application on linear elastic structures subjected to static loadcases. In its basic form, an approximated optimization problem is formulated using analytical or semi-analytical methods to perform the sensitivity analysis. When an explicit finite element method is used to solve contact–impact problems, the sensitivities cannot easily be found. Hence, the engineer is forced to use numerical derivatives or other approaches. Since each finite element simulation of an impact problem may take days of computing time, the sensitivity-based methods are not a useful approach. Therefore, two alternative formulations for topology optimization are investigated in this work. The fundamental approach is to remove elements or, alternatively, change the element thicknesses based on the internal energy density distribution in the model. There is no automatic shift between the two methods within the existing algorithm. Within this formulation, it is possible to treat nonlinear effects, e.g., contact–impact and plasticity. Since no sensitivities are used, the updated design might be a step in the wrong direction for some finite elements. The load paths within the model will change if elements are removed or the element thicknesses are altered. Therefore, care should be taken with this procedure so that small steps are used, i.e., the change of the model should not be too large between two successive iterations and, therefore, the design parameters should not be altered too much. It is shown in this paper that the proposed method for topology optimization of a nonlinear problem gives similar result as a standard topology optimization procedures for the linear elastic case. Furthermore, the proposed procedures allow for topology optimization of nonlinear problems. The major restriction of the method is that responses in the optimization formulation must be coupled to the thickness updating procedure, e.g., constraint on a nodal displacement, acceleration level that is allowed.     

Topology optimization of heat conduction problems using the finite volume method

This note addresses the use of the finite volume method (FVM) for topology optimization of a heat conduction problem. Issues pertaining to the proper choice of cost functions, sensitivity analysis, and example test problems are used to illustrate the effect of applying the FVM as an analysis tool for design optimization. This involves an application of the FVM to problems with nonhomogeneous material distributions, and the arithmetic and harmonic averages have here been used to provide a unique value for the conductivity at element boundaries. It is observed that when using the harmonic average, checkerboards do not form during the topology optimization process. Preliminary results of the work reported here were presented at the WCSMO 6 in Rio de Janeiro 2005, see Gersborg-Hansen et al. (2005b).     

Adhesive surface design using topology optimization

Tailoring adhesive properties between surfaces is of great importance for micro-scale systems, ranging from managing stiction in MEMS devices to designing wall-scaling gecko-like robots. A methodology is introduced for designing adhesive interfaces between structures using topology optimization. Structures subjected to external loads that lead to delamination are studied for situations where displacements and deformations are small. Only the effects of adhesive forces acting normal to the surfaces are considered. An interface finite element is presented that couples a penalty contact formulation and a Lennard–Jones model of van der Waals adhesive forces. Two- and three dimensional design optimization problems are presented in which adhesive force distributions are designed such that load-displacement curves of delaminating structures match target responses. The design variables describe the adhesive energy per area of the interface between the surfaces, as well as the geometry of the delaminating structure. A built-in length scale in the formulation of the adhesion forces eliminates the need for filtering to achieve comparable optimal adhesive designs over a range of mesh densities. The resulting design problem is solved by gradient based optimization algorithms evaluating the design sensitivities by the adjoint method. Results show that the delamination response can be effectively manipulated by the method presented. Varying simultaneously both adhesive and geometric parameters yields a wider range of reachable target load-displacement curves than in the case varying adhesive energy alone.     

求解可满足性问题的信息传播算法研究综述

信息传播算法来自统计物理,被广泛应用于人工智能各个领域,特别是求解组合优化问题时,具有良好的有效性。通过对信息传播算法的相关文献进行分析,综述了信息传播算法以及其相关应用的发展史,根据信息传播算法的发展,介绍了求解可满足性问题的信息传播算法相关概念,主要涉及到警示传播算法、置信传播算法和调查传播算法,描述了三种算法发展中出现的收敛性、有效性研究,分别综述了各个算法在相关领域的应用情况,并总结了信息传播算法的研究路径和应用方向。     

Topology optimization of large scale stokes flow problems

This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1,125,000 elements in 2D and 128,000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs.     

Globally optimal benchmark solutions to some small-scale discretized continuum topology optimization problems

In this note, globally optimal solutions to three sets of small-scale discretized continuum topology optimization problems are presented. All the problems were discretized by the use of nine-node isoparametric finite elements. The idea is that these solutions can be used as benchmark problems when testing new algorithms for finding pure 0–1 solutions to topology optimization problems defined on discretized ground structures.     

High-order FEM domain decomposition models for high-frequency wave propagation in heterogeneous media

Large scale scientific computing models, requiring iterative algebraic solvers, are needed to simulate high-frequency wave propagation because large degrees of freedom are needed to avoid the Helmholtz computer model pollution effects. In this work, we investigate the use of multiple additive Schwarz type domain decomposition (DD) approximations to efficiently simulate two- and three-dimensional high-frequency wave propagation with high-order FEM. We compare our DD based results with those obtained using a standard geometric multigrid approach for up to 1,000 and $300$ wavelength models in two- and three-dimensions, respectively.     

Shape design optimization of stationary fluid-structure interaction problems with large displacements and turbulence

This paper presents general and efficient methods for analysis and gradient based shape optimization of systems characterized as strongly coupled stationary fluid-structure interaction (FSI) problems. The incompressible fluid flow can be laminar or turbulent and is described using the Reynolds-averaged Navier-Stokes equations (RANS) together with the algebraic Baldwin–Lomax turbulence model. The structure may exhibit large displacements due to the interaction with the fluid domain, resulting in geometrically nonlinear structural behaviour and nonlinear interface coupling conditions. The problem is discretized using Galerkin and Streamline-Upwind/Petrov–Galerkin finite element methods, and the resulting nonlinear equations are solved using Newtons method. Due to the large displacements of the structure, an efficient update algorithm for the fluid mesh must be applied, leading to the use of an approximate Jacobian matrix in the solution routine. Expressions for Design Sensitivity Analysis (DSA) are derived using the direct differentiation approach, and the use of an inexact Jacobian matrix in the analysis leads to an iterative but very efficient scheme for DSA. The potential of gradient based shape optimization of fluid flow and FSI problems is illustrated by several examples.     

Topology optimization of 2D continua for minimum compliance using parallel computing

Topology optimization is often used in the conceptual design stage as a preprocessing tool to obtain overall material distribution in the solution domain. The resulting topology is then used as an initial guess for shape optimization. It is always desirable to use fine computational grids to obtain high-resolution layouts that minimize the need for shape optimization and postprocessing (Bendsoe and Sigmund, Topology optimization theory, methods and applications. Springer, Berlin Heidelberg New York 2003), but this approach results in high computation cost and is prohibitive for large structures. In the present work, parallel computing in combination with domain decomposition is proposed to reduce the computation time of such problems. The power law approach is used as the material distribution method, and an optimality criteria-based optimizer is used for locating the optimum solution [Sigmund (2001)21:120–127; Rozvany and Olhoff, Topology optimization of structures and composites continua. Kluwer, Norwell 2000]. The equilibrium equations are solved using a preconditioned conjugate gradient algorithm. These calculations have been done using a master–slave programming paradigm on a coarse-grain, multiple instruction multiple data, shared-memory architecture. In this study, by avoiding the assembly of the global stiffness matrix, the memory requirement and computation time has been reduced. The results of the current study show that the parallel computing technique is a valuable tool for solving computationally intensive topology optimization problems.     

求解约束优化问题改进的水波优化算法

为提高约束优化模型的求解精度,提出一种改进的水波优化算法。设计主-从异构种群,结合ε约束处理技术使主群实现探索可行解,从群利用可行解搜寻全局最优解。为加快收敛速度和增强信息交互,主群中个体可以依概率进行个体间学习,设计水波波长函数,使其随着水波的适应度值和违反约束度及时调整。为避免早期收敛,从群采用自适应学习策略以平衡群体的探索和利用。设计随迭代次数变化的放松约束度,提高算法收敛精度。对比实验结果表明,该算法可以获得高质量的可行解。     

On the validity of using small positive lower bounds on design variables in discrete topology optimization

It is proved that an optimal {ε, 1} ⁿ solution to a “ε-perturbed” discrete minimum weight problem with constraints on compliance, von Mises stresses and strain energy densities, is optimal, after rounding to {0, 1} ⁿ , to the corresponding “unperturbed” discrete problem, provided that the constraints in the perturbed problem are carefully defined and ε > 0 is sufficiently small.     

Topology optimization of head suspension assemblies using modal participation factor for mode tracking

A method of mode tracking based on modal participation factor (MPF) is developed and integrated into topology optimization of head suspension assemblies (HSAs). This method is devised to track the lowest torsional and the lowest sway frequencies, which are maximized as design goals for suspension assembly. Topology optimization based on this method is successfully used to find optimum designs for maximum torsional frequency, maximum sway frequency, or maximum both goals. The resulting topology images are then interpreted and reduced into physical form with three thickness levels among which reduced thickness helps improve the lowest torsional frequency.     

An improved vector particle swarm optimization for constrained optimization problems

Increasing attention is being paid to solve constrained optimization problems (COP) frequently encountered in real-world applications. In this paper, an improved vector particle swarm optimization (IVPSO) algorithm is proposed to solve COPs. The constraint-handling technique is based on the simple constraint-preserving method. Velocity and position of each particle, as well as the corresponding changes, are all expressed as vectors in order to present the optimization procedure in a more intuitively comprehensible manner. The NVPSO algorithm [30], which uses one-dimensional search approaches to find a new feasible position on the flying trajectory of the particle when it escapes from the feasible region, has been proposed to solve COP. Experimental results showed that searching only on the flying trajectory for a feasible position influenced the diversity of the swarm and thus reduced the global search capability of the NVPSO algorithm. In order to avoid neglecting any worthy position in the feasible region and improve the optimization efficiency, a multi-dimensional search algorithm is proposed to search within a local region for a new feasible position. The local region is composed of all dimensions of the escaped particle’s parent and the current positions. Obviously, the flying trajectory of the particle is also included in this local region. The new position is not only present in the feasible region but also has a better fitness value in this local region. The performance of IVPSO is tested on 13 well-known benchmark functions. Experimental results prove that the proposed IVPSO algorithm is simple, competitive and stable.     

Topology optimization for minimum compliance under multiple loads based on continuous distribution of members

A method to minimize the compliance of structures subject to multiple load cases is presented. Firstly, the material distribution in design domain is optimized to form a truss-like continuum. The anisotropic composite is employed as the material model to simulate the constitutive relation of the truss-like continuum. The member densities and orientations at the nodes are taken as design variables. The member densities and orientations at any point in an element vary continuously. Then, parts of members, which are formed according to the member distribution field, are chosen to form the nearly optimum discrete structure. Lastly, the positions of the nodes and the cross-sectional areas of the members are optimized. In the above process, numerical instabilities such as checkerboard and mesh dependencies disappear without any additional technique. The sensitivities of the compliance are derived. Examples are presented to demonstrate the capability of the proposed method.     

A wave propagation approach for reduced dynamic modeling of distillation columns: Optimization and control

Reduced models enable real-time optimization of large-scale processes. We propose a reduced model of distillation columns based on multicomponent nonlinear wave propagation (Kienle 2000). We use a nonlinear wave equation in dynamic mass and energy balances. We thus combine the ideas of compartment modeling and wave propagation. In contrast to existing reduced column models based on nonlinear wave propagation, our model deploys a hydraulic correlation. This enables the column holdup to change as load varies. The model parameters can be estimated solely based on steady-state data. The new transient wave propagation model can be used as a controller model for flexible process operation including load changes. To demonstrate this, we implement full-order and reduced dynamic models of an air separation process and multi-component distillation column in Modelica. We use the open-source framework DyOS for the dynamic optimizations and an Extended Kalman Filter for state estimation. We apply the reduced model in-silico in open-loop forward simulations as well as in several open- and closed-loop optimization and control case studies, and analyze the resulting computational speed-up compared to using full-order stage-by-stage column models. The first case study deals with tracking control of a single air separation distillation column, whereas the second one addresses economic model predictive control of an entire air separation process. The reduced model is able to adequately capture the transient column behavior. Compared to the full-order model, the reduced model achieves highly accurate profiles for the manipulated variables, while the optimizations with the reduced model are significantly faster, achieving more than 95% CPU time reduction in the closed-loop simulation and more than 96% in the open-loop optimizations. This enables the real-time capability of the reduced model in process optimization and control.     

A method for non-differentiable optimization problems

We introduce a new method for solving a class of non-smooth unconstrained optimization problems. The method constructs a sequence<texlscub>x _k </texlscub>in ? ⁿ , and at the kth iteration, a search direction h _k is considered, where h _k is a solution to a variational inequality problem. A convergence theorem for our algorithm model and its discrete version can be easily proved. Furthermore, preliminary computational results show that the new method performs quite well and can compete with other methods.     

Structure testing of wave propagation models used in identification of viscoelastic materials

In this paper, matrix perturbation theory is applied to test the structure of wave propagation models used to identify the complex modulus of a viscoelastic material. The analysis is based on a data matrix, containing the measured data from a number of independent experiments. The key observation is that if the structure of the model is correct then the unperturbed (noise-free) matrix is rank deficient of a known order. This means that the noise corrupted matrix will have a known number of singular values that diverge from zero only due to the measurement noise. A test quantity based on the distribution of these perturbed singular values is used, assuming that the signal-to-noise ratio is large and that measurement noise is white and Gaussian distributed. If the magnitudes of the smallest singular values are too large to be explained by the measurement noise only, the model is rejected. Data from two different types of experimental setups is explored; longitudinal wave propagation in a slender bar and the non-equilibrium SHPB procedure. It is shown that the model can be accepted in the first case, but should be rejected in the second.     

Design of phononic materials/structures for surface wave devices using topology optimization

We develop a topology optimization approach to design two- and three-dimensional phononic (elastic) materials, focusing primarily on surface wave filters and waveguides. These utilize propagation modes that transmit elastic waves where the energy is contained near a free surface of a material. The design of surface wave devices is particularly attractive given recent advances in nano- and micromanufacturing processes, such as thin-film deposition, etching, and lithography, which make it possible to precisely place thin film materials on a substrate with submicron feature resolution. We apply our topology optimization approach to a series of three problems where the layout of two materials (silicon and aluminum) is sought to achieve a prescribed objective: (1) a grating to filter bulk waves of a prescribed frequency in two and three dimensions, (2) a surface wave device that uses a patterned thin film to filter waves of a single or range of frequencies, and (3) a fully three-dimensional structure to guide a wave generated by a harmonic input on a free surface to a specified output port on the surface. From the first to the third example, the resulting topologies increase in sophistication. The results demonstrate the power and promise of our computational framework to design sophisticated surface wave devices.