A web-based topology optimization program

The paper presents a web-based interface for a topology optimization program. The program is accessible over the World Wide Web at the address http://www.topopt.dtu.dk. The paper discusses implementation issues and educational aspects as well as statistics and experience with the program. Received September 29, 2000     

Evolutionary truss topology optimization using a graph-based parameterization concept

A novel parameterization concept for the optimization of truss structures by means of evolutionary algorithms is presented. The main idea is to represent truss structures as mathematical graphs and directly apply genetic operators, i.e., mutation and crossover, on them. For this purpose, new genetic graph operators are introduced, which are combined with graph algorithms, e.g., Cuthill–McKee reordering, to raise their efficiency. This parameterization concept allows for the concurrent optimization of topology, geometry, and sizing of the truss structures. Furthermore, it is absolutely independent from any kind of ground structure normally reducing the number of possible topologies and sometimes preventing innovative design solutions. A further advantage of this parameterization concept compared to traditional encoding of evolutionary algorithms is the possibility of handling individuals of variable size. Finally, the effectiveness of the concept is demonstrated by examining three numerical examples.     

A new approach for the solution of singular optima in truss topology optimization with stress and local buckling constraints

The present paper investigates problems of truss topology optimization under local buckling constraints. A new approach for the solution of singular problems caused by stress and local buckling constraints is proposed. At first, a second order smooth-extended technique is used to make the disjoint feasible domains connect, then the so-called ε-relaxed method is applied to eliminate the singular optima from problem formulation. By means of this approach, the singular optimum of the original problem caused by stress and local buckling constraints can be searched approximately by employing the algorithms developed for sizing optimization problems with high accuracy. Therefore, the numerical problem resulting from stress and local buckling constraints can be solved in an elegant way. The applications of the proposed approach and its effectiveness are illustrated with several numerical examples. Received May 2, 2000     

An alternative interpolation scheme for minimum compliance topology optimization

We consider the discretized zero-one continuum topology optimization problem of finding the optimal distribution of two linearly elastic materials such that compliance is minimized. The geometric complexity of the design is limited using a constraint on the perimeter of the design. A common approach to solve these problems is to relax the zero-one constraints and model the material properties by a power law which gives noninteger solutions very little stiffness in comparison to the amount of material used. We propose a material interpolation model based on a certain rational function, parameterized by a positive scalar q such that the compliance is a convex function when q is zero and a concave function for a finite and a priori known value on q. This increases the probability to obtain a zero-one solution of the relaxed problem. Received July 20, 2000     

Discrete sizing/layout/topology optimization of truss structures with an advanced Jaya algorithm

Discrete optimization of truss structures is a hard computing problem with many local minima. Metaheuristic algorithms are naturally suited for discrete optimization problems as they do not require gradient information. A recently developed method called Jaya algorithm (JA) has proven itself very efficient in continuous engineering problems. Remarkably, JA has a very simple formulation and does not utilize algorithm-specific parameters. This study presents a novel JA formulation for discrete optimization of truss structures under stress and displacement constraints. The new algorithm, denoted as discrete advanced JA (DAJA), implements efficient search mechanisms for generating new trial designs including discrete sizing, layout and topology optimization variables. Besides the JA’s basic concept of moving towards the best design of the population and moving away from the worst design, DAJA tries to form a set of descent directions in the neighborhood of each candidate designs thus generating high quality trial designs that are very likely to improve current population. Results collected in seven benchmark problems clearly demonstrate the superiority of DAJA over other state-of-the-art metaheuristic algorithms and multi-stage continuous–discrete optimization formulations.     

Optimal truss design including plastic collapse constraints

A new algorithm is presented for size optimization of truss structures with any kind of smooth objectives and constraints, together with constraints on the collapse loading obtained by limit analysis, for several loading conditions. The main difficulty of this problem is the fact that the collapse loading is a nonsmooth function of the design variables. In this paper we avoid nonsmooth optimization techniques based on the fact that limit analysis constraints are linear by parts. Our approach is based on a feasible directions interior point algorithm for nonlinear constrained optimization. Three illustrative examples are discussed. The numerical results show that the calculation effort when limit analysis constraints are included is only slightly increased with respect to classic constraints.     

Growth method for size,topology, and geometry optimization of truss structures

The problem of optimally designing the topology of plane trusses has, in most cases, been dealt with as a size problem in which members are eliminated when their size tends to zero. This article presents a novel growth method for the optimal design in a sequential manner of size, geometry, and topology of plane trusses without the need of a ground structure. The method has been applied to single load case problems with stress and size constraints. It works sequentially by adding new joints and members optimally, requiring five basic steps: (1) domain specification, (2) topology and size optimization, (3) geometry optimization, (4) optimality verification, and (5) topology growth. To demonstrate the proposed growth method, three examples were carried out: Michell cantilever, Messerschmidt–Bölkow–Blohm beam, and Michell cantilever with fixed circular boundary. The results obtained with the proposed growth method agree perfectly with the analytical solutions. A Windows XP program, which demonstrates the method, can be downloaded from http://www.upct.es/~deyc/software/tto/.     

Metamorphic development: a new topology optimization method for continuum structures

An effective optimization procedure for finding structural shapes and topologies that minimize structural compliance and weight subject to stress and deflection constraints is presented. This new approach, called “Metamorphic Development” (MD), can allow a structure to grow and degenerate towards an optimum topological layout. In this method, the optimization can start from the simplest possible geometry (layout) or any degree of development of the structure rather than from a complex ground mesh. The structure is then developed metamorphically using rectangular and triangular elements that can be of any specified sizes. Examples demonstrate the potential of the MD optimization procedure to generate innovative solutions to structural design problems. Results are given and the growth and degeneration histories during optimization are illustrated. Received August 20, 1999     

Optimum design of truss topology under buckling constraints

The present paper studies the optimum design of truss topology under buckling constraints based on a new formulation of the problem. Through the incorporation of a global system stability constraint into the problem formulation, isolated compressive bars are eliminated from the final optimal topology. Furthermore, by including overlapping bars in the initial ground structure, the difficulty caused by hinge cancellation as pointed out by Rozvany (1996) can be overcome. Also, the importance of inclusion of compatibility conditions in the problem formulation is demonstrated. Finally, several numerical examples are presented for demonstration of the effectiveness of the proposed approach.     

A 99 line topology optimization code written in Matlab

The paper presents a compact Matlab implementation of a topology optimization code for compliance minimization of statically loaded structures. The total number of Matlab input lines is 99 including optimizer and Finite Element subroutine. The 99 lines are divided into 36 lines for the main program, 12 lines for the Optimality Criteria based optimizer, 16 lines for a mesh-independency filter and 35 lines for the finite element code. In fact, excluding comment lines and lines associated with output and finite element analysis, it is shown that only 49 Matlab input lines are required for solving a well-posed topology optimization problem. By adding three additional lines, the program can solve problems with multiple load cases. The code is intended for educational purposes. The complete Matlab code is given in the Appendix and can be down-loaded from the web-site http://www.topopt.dtu.dk. Received October 22, 1999     

空间桁架结构优化设计

为获得空间桁架结构的合理构型,以某空间设备支撑结构为例,分析结构材料在设计空间的分布形式和桁架结构的传力路径。在已知载荷约束和设计空间大小的条件下,基于连续体拓扑优化方法,以静态多工况刚度和动态固有频率为多目标函数进行优化分析。依据设计要求确定计算模型的结点数和结点位置,获得满足要求的空间桁架结构并进行优化设计。优化结果比原模型质量减少36.7%,一阶模态提高3.6%。     

Constrained adaptive topology optimization for vibrating shell structures

This paper describes an algorithm for structural topology optimization entitled Constrained Adaptive Topology Optimization or CATO which is applied here to produce the optimum design of shell structures under free vibration conditions. The algorithm, based on an artificial material model and an updating scheme, combines ideas from the more mathematically rigorous homogenization (h) methods and the more intuitive evolutionary (e) methods. Thus, CATO can be seen as a hybrid h/e method. The optimization problem is defined as maximizing or minimizing a chosen frequency with a constraint on the structural volume/mass by redistributing the material through the structure. The efficiency of the proposed algorithm is illustrated through several numerical examples. Received February 17, 2000     

A hierarchical neighbourhood search method for topology optimization

This paper presents a hierarchical neighbourhood search method for solving topology optimization problems defined on discretized linearly elastic continuum structures. The design of the structure is represented by binary design variables indicating material or void in the various finite elements.Two different designs are called neighbours if they differ in only one single element, in which one of them has material while the other has void. The proposed neighbourhood search method repeatedly jumps to the best neighbour of the current design until a local optimum has been found, where no further improvement can be made. The engine of the method is an efficient exploitation of the fact that if only one element is changed (from material to void or from void to material) then the new global stiffness matrix is just a low-rank modification of the old one. To further speed up the process, the method is implemented in a hierarchical way. Starting from a coarse finite element mesh, the neighbourhood search is repeatedly applied on finer and finer meshes.Numerical results are presented for minimum-weight problems with constraints on respectively compliance, strain energy densities in all non-void elements, and von Mises stresses in all non-void elements.     

A unified aggregation and relaxation approach for stress-constrained topology optimization

In this paper, we propose a unified aggregation and relaxation approach for topology optimization with stress constraints. Following this approach, we first reformulate the original optimization problem with a design-dependent set of constraints into an equivalent optimization problem with a fixed design-independent set of constraints. The next step is to perform constraint aggregation over the reformulated local constraints using a lower bound aggregation function. We demonstrate that this approach concurrently aggregates the constraints and relaxes the feasible domain, thereby making singular optima accessible. The main advantage is that no separate constraint relaxation techniques are necessary, which reduces the parameter dependence of the problem. Furthermore, there is a clear relationship between the original feasible domain and the perturbed feasible domain via this aggregation parameter.     

Reliability-based topology optimization

The objective of this work is to integrate reliability analysis into topology optimization problems. The new model, in which we introduce reliability constraints into a deterministic topology optimization formulation, is called Reliability-Based Topology Optimization (RBTO). Several applications show the importance of this integration. The application of the RBTO model gives a different topology relative to deterministic topology optimization. We also find that the RBTO model yields structures that are more reliable than those produced by deterministic topology optimization (for the same weight).     

A dual mesh method with adaptivity for stress-constrained topology optimization

Structural and Multidisciplinary Optimization - This paper is concerned with the topological optimization of elastic structures, with the goal of minimizing the compliance and/or mass of the...