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Showing 5 results for Space Structures

A. Kaveh, M. Farahani, N. Shojaei,
Volume 10, Issue 4 (12-2012)
Abstract

Barrel vaults are attractive space structures that cover large area without intermediate supports. In this paper, the charged

search system (CSS) optimization algorithm is employed for optimal design of barrel vaults. This method utilizes the governing

laws of Coulomb and Gauss from electrostatics and the Newtonian law of mechanics. The results demonstrate the efficiency of

the discrete CSS algorithm compared to other meta-heuristic algorithms.


A. Kaveh, S. Beheshti,
Volume 11, Issue 2 (6-2013)
Abstract

For the analysis of structures, the first step consists of configuration processing followed by data generation. This step is the most time consuming part of the analysis for large-scale structures. In this paper new graph products called triangular and circular graph products are developed for the formation of the space structures. The graph products are extensively used in graph theory and combinatorial optimization, however, the triangular and circular products defined in this paper are more suitable for the formation of practical space structural models which can not be generated easily by the previous products. The new products are employed for the configuration processing of space structures that are of triangular or a combination of triangular and rectangular shapes, and also in circular shapes as domes and some other space structural models. Cut out products are other new types of graph products which are defined to eliminate all of the connected elements to the considered node to configure the model or grid with some vacant panels inside of the model. The application of the presented graph products can be extended to the formation of finite element models.
R. Kamyab Moghadas, E. Salajegheh,
Volume 11, Issue 2 (6-2013)
Abstract

The present paper focuses on size optimization of scallop domes subjected to static loading. As this type of space structures includes a large number of the structural elements, optimum design of such structures results in efficient structural configurations. In this paper, an efficient optimization algorithm is proposed by hybridizing particle swarm optimization (PSO) algorithm and cellular automata (CA) computational strategy, denoted as enhanced particle swarm optimization (EPSO) algorithm. In the EPSO, the particles are distributed on a small dimensioned grid and the artificial evolution is evolved by a new velocity updating equation. In the new equation, the difference between the design variable vector of each site and an average vector of its neighboring sites is added to the basic velocity updating equation. This new term decreases the probability of premature convergence and therefore increases the chance of finding the global optimum or near global optima. The optimization task is achieved by taking into account linear and nonlinear responses of the structure. In the optimization process considering nonlinear behaviour, the geometrical and material nonlinearity effects are included. The numerical results demonstrate that the optimization process considering nonlinear behaviour results in more efficient structures compared with the optimization process considering linear behaviour. .
A. Kaveh, A. Nasrolahi,
Volume 12, Issue 1 (3-2014)
Abstract

In this paper, a new enhanced version of the Particle Swarm Optimization (PSO) is presented. An important modification is made by adding probabilistic functions into PSO, and it is named Probabilistic Particle Swarm Optimization (PPSO). Since the variation of the velocity of particles in PSO constitutes its search engine, it should provide two phases of optimization process which are: exploration and exploitation. However, this aim is unachievable due to the lack of balanced particles’ velocity formula in the PSO. The main feature presented in the study is the introduction of a probabilistic scheme for updating the velocity of each particle. The Probabilistic Particle Swarm Optimization (PPSO) formulation thus developed allows us to find the best sequence of the exploration and exploitation phases entailed by the optimization search process. The validity of the present approach is demonstrated by solving three classical sizing optimization problems of spatial truss structures.
Mohammadreza Sheidaii, Mehdi Babaei,
Volume 15, Issue 2 (3-2017)
Abstract

Engineering design usually requires considering multiple variances in a design and integrating them appropriately in order to achieve the most desirable alternative. This consideration takes particular importance in the constructional projects of civil engineering. However, frequently, the structural designer’s considerations in civil engineering teams contrast the stylish and creative novelties of architectures. Then, we should take up new methodologies to yield appropriate alternatives which meet artistic aspects of design and simultaneously satisfy the structural designer’s demands. Consequently, the process of design should incorporate the multi-fold aspects of engineer’s requirements and their personal preference. So, in this study, we preset a systematic approach, so-called desirability based design, to perform a directed multi-objective optimal design considering various aspects of a design, based on soft-computing methods. Fuzzy logic integrated with genetic algorithm is employed to build a decision-making fuzzy system based on expert knowledge. It will be employed to conduct the designing process. Illustrative examples show practicality and efficiency of the presented methodology in structural design of several space structures.



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