space trusses
123264300
Design of Space Trusses Using Ant Colony Optimization
A design procedure utilizing an ant colony optimization (ACO) technique is developed for discrete optimization of space trusses. The objective function considered is the total weight (or cost) of the structure subjected to material and performance constraints in the form of stress and deflection limits. The design of space trusses using discrete variables is transformed into a modified traveling salesman problem (TSP) where the network of the TSP reflects the structural topology and the length of the TSP tour is the weight of the structure. The resulting truss, mapped into a TSP, is minimized using an ACO algorithm. The ACO design procedure uses discrete design variables, an open format for prescribing constraints, a penalty function to enforce design constraints, and allows for multiple loading cases. A comparison is presented between the ACO truss design procedure and designs developed using a genetic algorithm and classical continuous optimization methods.
Charles V Camp Barron J Bichon
110359873
DESIGN OF SPACE TRUSSES USING BIG BANG BIG CRUNCH OPTIMIZATION
A procedure for designing low weight space trusses based on the innovative Big Bang Big Crunch (BB BC) optimization method is developed for both discrete and continuous variable optimization. BB BC optimization is a population based heuristic search consisting of two parts: The Big Bang where candidate solutions are randomly distributed over the search space; and a Big Crunch where a contraction operation estimates a weighted average or center of mass for the population. Each sequential Big Bang is then randomly distributed about the center of mass. The objective of the optimization is to minimize the total weight (or cost) of the structure subjected to material and performance constraints in the form of stress and deflection limits. Designs are evaluated for fitness based on their penalized structural weight, which represents the actual truss weight and the degree to which the design constraints are violated. BB BC optimization has several advantages over other evolutionary methods: Most significantly, a.
Charles V Camp
121977698
Design of space trusses using modified teaching learning based optimization
Abstract A modified teaching learning based optimization (TLBO) algorithm is applied to fixed geometry space trusses with discrete and continuous design variables. Designs generated by the modified TLBO algorithm are compared with other popular evolutionary optimization methods. In all cases, the objective function is the total weight of the structure subjected to strength and displacement limitations. Designs are evaluated for fitness based on their penalized structural weight, which represents the actual truss weight and the degree to which the design constraints are violated. TLBO is conceptually modeled on the two types of pedagogy within a classroom: class level learning from a teacher and individual learning between students. TLBO uses a relatively simple algorithm with no intrinsic parameters controlling its performance and can easily handle a mixture of both continuous and discrete design variables. Without introducing any additional algorithmic parameters, the modified TLBO algorithm uses a fitness based weighted mean in the teaching phase and a refined student updating process. The computational performance of TLBO designs for several benchmark space truss structures is presented and compared with classical and evolutionary optimization methods. Optimization results indicate that the modified TLBO algorithm can generate improved designs when compared to other population based techniques and in some cases improve the overall computational efficiency.
Charles V Camp Mohammad Farshchin
123490668
Size optimization of space trusses using Big Bang Big Crunch algorithm
A Hybrid Big Bang Big Crunch (HBB BC) optimization algorithm is employed for optimal design of truss structures. HBB BC is compared to Big Bang Big Crunch (BB BC) method and other optimization methods including Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization and Harmony Search. Numerical results demonstrate the efficiency and robustness of the HBB BC method compared to other heuristic algorithms.
Ali Kaveh Siamak Talatahari
53347572
Effective properties of the octet truss lattice material
The effective mechanical properties of the octet truss lattice structured material have been investigated both experimentally and theoretically. Analytical and FE calculations of the elastic properties and plastic yielding collapse surfaces are reported. The intervention of elastic buckling of the struts is also analysed in an approximate manner. Good agreement is found between the predictions of the strength and experimental observations from tests on the octet truss material made from a casting aluminium alloy. Moreover, the strength and stiffness of the octet truss material are stretching dominated and compare favourably with the corresponding properties of metallic foams. Thus, the octet truss lattice material can be considered as a promising alternative to metallic foams in lightweight structures.
V Deshpande Norman A Fleck M F Ashby
10736651
Linear elastic trusses leading to continua with exotic mechanical interactions
We study the statics of some trusses, i.e. networks of nodes linked by linear springs. The trusses are designed in such a way that a few number of floppy modes are present and remain when considering the homogenized limit of the truss. We then obtain linear elastic materials with exotic mechanical interactions which cannot be described in the classical framework of Cauchy stress theory. For aim of simplicity, the structures described here are two dimensional. The extension to the 3D case does not present any difficulty.
Pierre Seppecher Jean Jacques Alibert Francesco Dell Isola
123100571
Multiobjective optimization of trusses using genetic algorithms
Abstract In this paper we propose the use of the genetic algorithm (GA) as a tool to solve multiobjective optimization problems in structures. Using the concept of min max optimum, a new GA based multiobjective optimization technique is proposed and two truss design problems are solved using it. The results produced by this new approach are compared to those produced by other mathematical programming techniques and GA based approaches, proving that this technique generates better trade offs and that the genetic algorithm can be used as a reliable numerical optimization tool.
Carlos A Coello Coello Alan D Christiansen
630742
Design of truss structures for minimum weight using genetic algorithms
Optimization of truss structures for finding optimal cross sectional size, topology, and configuration of 2 D and 3 D trusses to achieve minimum weight is carried out using real coded genetic algorithms (GAs) All the above three optimization techniques have been made possible by using a novel representation scheme. Although the proposed GA uses a fixed length vector of design variables representing member areas and change in nodal coordinates, a simple member exclusion principle is introduced to obtain differing topologies. Moreover, practical considerations, such as inclusion of important nodes in the optimized structure is taken care of by using a concept of basic and non basic nodes. Stress, deflection, and kinematic stability considerations are also handled using constraints. In a number of 2 D and 3 D trusses, the proposed technique finds intuitively optimal or near optimal trusses, which are also found to have smaller weight than those that are reported in the literature.
Kalyanmoy Deb Surendra Gulati
10951265
Artificial Bee Colony algorithm for optimization of truss structures
The main goal of the structural optimization is to minimize the weight of structures while satisfying all design requirements imposed by design codes. In this paper, the Artificial Bee Colony algorithm with an adaptive penalty function approach (ABC AP) is proposed to minimize the weight of truss structures. The ABC algorithm is swarm intelligence based optimization technique inspired by the intelligent foraging behavior of honeybees. Five truss examples with fixed geometry and up to 200 elements were studied to verify that the ABC algorithm is an effective optimization algorithm in the creation of an optimal design for truss structures. The results of the ABC AP compared with results of other optimization algorithms from the literature show that this algorithm is a powerful search and optimization technique for structural design.
Appl. Soft Comput.
Mustafa Sonmez
108436824
Truss Structure Integrity Identification Using PZT Sensor Actuator
This paper presents a frequency domain impedance signature based technique for health monitoring of an assembled truss structure. Unlike conventional modal analysis approaches, the technique uses piezoceramic (PZT) elements as integrated sensor actuators for acquisition of signature pattern of the truss. The concept of the localization of sensing/actuation area for damage detection of an assembled structure is presented for the first time. Through a PZT patch bonded to a truss node and the measurement of its electric admittance, which is coupled with the mechanical impedance of the truss, the signature pattern of a truss is monitored. The admittance of a truss in question is compared with that of the original healthy truss. Statistic algorithm is then applied to extract a damage index of the truss based on the signature pattern difference. Experimental proof that over a selected band, the detection range of a bonded PZT sensor on a truss is highly constrained to its immediate neighborhood is presented. This characteristic allows accurate determination of the damage location in a complex real world structure with a minimum mathematical modeling and numerical computation.
Fanping P Sun Zaffir Chaudhry Chen Liang Craig A Rogers