• Journal of Korean Association for Spatial Structures
• /
• v.10 no.4
• /
• pp.59-66
• /
• 2010

This study presents the topology optimization technique by density method to determine the initial shape of space truss structures. Most initial shape design is performed by designer's previous experiences and trial and error method instead of the application of reasonable optimization method. Thus, the reasonable and economical optimization methods are needed to be introduced for the initial shape design. Therefore, we set design domain for cantilever space truss structure as an example model. And topology optimization is used to obtain optimum layout for them, and then size optimization method is used to find the optimum member size. Therefore, the reasonable initial optimal shapes of spatial truss structures can be obtained through the topology and size optimization using density method.

• Steel and Composite Structures
• /
• v.16 no.6
• /
• pp.681-701
• /
• 2014

The main aim of this study is to propose an efficient meta-heuristic algorithm for topology optimization of geometrically nonlinear single layer domes by serially integration of computational advantages of firefly algorithm (FA) and particle swarm optimization (PSO). During the optimization process, the optimum number of rings, the optimum height of crown and tubular section of the member groups are determined considering geometric nonlinear behaviour of the domes. In the proposed algorithm, termed as FA-PSO, in the first stage an optimization process is accomplished using FA to explore the design space then, in the second stage, a local search is performed using PSO around the best solution found by FA. The optimum designs obtained by the proposed algorithm are compared with those reported in the literature and it is demonstrated that the FA-PSO converges to better solutions spending less computational cost emphasizing on the efficiency of the proposed algorithm.

• Architectural research
• /
• v.11 no.1
• /
• pp.15-23
• /
• 2009

An application of the constrained adaptive topology optimization (CATO) algorithm is described for three-dimensional topology optimization of engineering structures. The enhanced assumed strain lower order solid finite element (FE) is used to evaluate the values of objective and constraint functions required in optimization process. The strain energy (SE) terms such as elastic and modal SEs are employed as the objective function to be minimized and the initial volume of structures is introduced as the constraint function. The SIMP model is adopted to facilitate the material redistribution and also to produce clearer and more distinct structural topologies. The linearly weighted objective function is introduced to consider both static and dynamic characteristics of structures. Several numerical tests are tackled and it is used to investigate the performance of the proposed three-dimensional topology optimization process. From numerical results, it is found to be that the CATO algorithm is easy to implement and extremely applicable to produce the reasonable optimum topologies for three dimensional optimization problems.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.33 no.8
• /
• pp.786-792
• /
• 2009

Topology optimization is to find the optimal material distribution of the specified design domain minimizing the objective function while satisfying the design constraints. Since the genetic algorithm (GA) has its advantage of locating global optimum with high probability, it has been applied to the topology optimization. To guarantee the structural connectivity, the concept of compliance pattern is proposed and to improve the convergence rate, small number of population size and variable probability in genetic operators are incorporated into GA. The rank sum weight method is applied to formulate the fitness function consisting of compliance, volume, connectivity and checkerboard pattern. To substantiate the proposed method design examples in the previous works are compared with respect to the number of function evaluation and objective function value. The comparative study shows that the compliance pattern based GA results in the reduction of computational cost to obtain the reasonable structural topology.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.603-608
• /
• 2008

It is well known that the topology optimization for plastic problem is not easy since the iterative analyses to evaluate the objective and cost function with respect to the design variation are very time-consuming. The finite element limit analysis is an efficient tool which is possible to predict collapse modes and sequential collapse loads of a structure considering not only large deformation but also plastic material behavior with moderate computing cost. In this paper, the optimum topology of a structure considering large and plastic deformation is obtained using the finite element limit analysis. To verify the constructed optimization code, topology optimizations of some typical problems are performed and the optimal topologies by elastic design and plastic design are compared.

• Wind and Structures
• /
• v.18 no.1
• /
• pp.21-35
• /
• 2014

The latest developments in topology optimization are integrated with Computational Fluid Dynamics (CFD) for the conceptual design of building structures. The wind load on a building is simulated using CFD, and the structural response of the building is obtained from finite element analysis under the wind load obtained. Multiple wind directions are simulated within a single fluid domain by simply expanding the simulation domain. The bi-directional evolutionary structural optimization (BESO) algorithm with a scheme of material interpolation is extended for an automatic building topology optimization considering multiple wind loading cases. The proposed approach is demonstrated by a series of examples of optimum topology design of perimeter bracing systems of high-rise building structures.

• Advances in Computational Design
• /
• v.1 no.1
• /
• pp.1-25
• /
• 2016

Domes are architectural and elegant structures which cover a vast area with no interrupting columns in the middle, and with suitable shapes can be also economical. Domes are built in a wide variety of forms and specialized terms are available to describe them. According to their form, domes are given special names such as network, lamella, Schwedler, ribbed, and geodesic domes. In this paper, an optimum topology design algorithm is performed using the enhanced colliding bodies optimization (ECBO) method. The network, lamella, ribbed and Schwedler domes are studied to determine the optimum number of rings, the optimum height of crown and tubular sections of these domes. The minimum volume of each dome is taken as the objective function. A simple procedure is defined to determine the dome structures configurations. This procedure includes calculating the joint coordinates and element constructions. The design constraints are implemented according to the provision of LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Constitution). The wind loading act on domes according to ASCE 7-05 (American Society of Civil Engineers). This paper will explore the efficiency of various type of domes and compare them at the first stage to investigate the performance of these domes under different kind of loading. At the second stage the wind load on optimum design of domes are investigated for Schwedler dome. Optimization process is performed via ECBO algorithm to demonstrate the effectiveness and robustness of the ECBO in creating optimal design for domes.

• Journal of Korean Association for Spatial Structures
• /
• v.7 no.5
• /
• pp.67-74
• /
• 2007

The unsymmetrically layered artificial material model is consistently introduced to find the optimum topologies of the plate structures. Reissner-Mindlin (RM) plate theory is adopted to formulate the present 9-node plate element considering the first-order shear deformation of the plates. In the topology optimization process, the strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. In addition, the resizing algorithm based on the optimality criteria is used to update the hole size introduced in the proposed artificial material model. Several numerical examples are rallied out to investigate the performance of the proposed technique. From numerical results, the proposed topology optimization techniques are found to be very effective to produce the optimum topology of plate structures. In particular, the proposed unsymmetric stiffening layer model make it possible to produce more realistic stiffener design of the plate structures.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.4
• /
• pp.766-776
• /
• 2001

In the constructing of the multi layer neural network, the network topology is often chosen arbitrarily for different applications, and the optimum topology of the network is determined by the long processing of the trial and error. In this paper, we propose the automatic topology construction using the fuzzy rule that optimizes the neurons of hidden layer, and prune the weights connecting the hidden layer and the output layer during the training process. The simulation of pattern recognition, and the experiment of the mapping of the inverted pendulum showed the effectiveness of the proposed method.

• Journal of Korean Association for Spatial Structures
• /
• v.21 no.2
• /
• pp.89-97
• /
• 2021

This paper describes an adaptive hybrid evolutionary firefly algorithm for a topology optimization of truss structures. The truss topology optimization problems begins with a ground structure which is composed of all possible nodes and members. The optimization process aims to find the optimum layout of the truss members. The hybrid metaheuristics are then used to minimize the objective functions subjected to static or dynamic constraints. Several numerical examples are examined for the validity of the present method. The performance results are compared with those of other metaheuristic algorithms.