Optimal design of nonlinear large-scale suspendome using cascade optimization

2017 ◽  
Vol 33 (1) ◽  
pp. 3-18 ◽  
Author(s):  
Ali Kaveh ◽  
Masoud Rezaei ◽  
MR Shiravand

Large-scale suspendomes are elegant architectural structures which cover a vast area with no interrupting columns in the middle. These domes have attractive shapes which are also economical. Domes are built in a wide variety of forms. In this article, an algorithm is developed for optimum design of domes considering the topology, geometry, and size of member section using the cascade-enhanced colliding bodies optimization method. In large-scale space steel structures, a large number of design variables are involved. The idea of cascade optimization allows a single optimization problem to be tackled in a number of successive autonomous optimization stages. The variables are the optimum height of crown and tubular sections of these domes, the initial strain, the length of the struts, and the cross-sectional areas of the cables in the tensegrity system of domes. The number of joints in each ring and the number of rings are considered for topology optimization of ribbed and Schwedler domes. Weight of the dome is taken as the objective function for minimization. A simple procedure is defined to determine the configuration of the domes. The design constraints are considered according to the provisions of Load and Resistance Factor Design–American Institute of Steel Constitution. In order to investigate the efficiency of the presented method, a large-scale suspendome with more than 2266 members is investigated. Numerical results show that the utilized method is an efficient tool for optimal design of large-scale domes. Additionally, in this article, a topology and geometry optimization for two common ribbed and Schwedler domes are performed to find their optimum graphs considering various spans.

1991 ◽  
Vol 113 (4) ◽  
pp. 294-299 ◽  
Author(s):  
C. H. Tseng ◽  
K. Y. Kao ◽  
J. C. Yang

In this paper, an optimal design concept has been utilized to find the best designs for a complex and large-scale ocean thermal energy conversion (OTEC) plant. The OTEC power plant under this study is divided into three major subsystems consisting of power subsystem, seawater pipe subsystem, and containment subsystem. The design optimization model for the entire OTEC plant is integrated from these subsystems under the considerations of their own various design criteria and constraints. The mathematical formulations of this optimization model for the entire OTEC plant are described. The design variables, objective function, and constraints for a pilot plant under the constraints of the feasible technologies at this stage in Taiwan have been carefully examined and selected. The numerical optimization method called Sequential Quadratic Programming (SQP) is selected to obtain the optimum results. The main purpose of this paper is to demonstrate the design procedure with the optimization techniques for engineering and economics in the OTEC plant so that anyone else can build upon their models according to their needs.


Author(s):  
Lifang Zeng ◽  
Dingyi Pan ◽  
Shangjun Ye ◽  
Xueming Shao

A fast multiobjective optimization method for S-duct scoop inlets considering both inflow and outflow is developed and validated. To reduce computation consumption of optimization, a simplified efficient model is proposed, in which only inflow region is simulated. Inlet pressure boundary condition of the efficient model is specified by solving an integral model with both inflow and outflow. An automated optimization system integrating the computational fluid dynamics analysis, nonuniform rational B-spline geometric representation technique, and nondominated sorting genetic algorithm II is developed to minimize the total pressure loss and distortion at the exit of diffuser. Flow field is numerically simulated by solving the Reynolds-averaged Navier–Stokes equation coupled with k–ω shear stress transport turbulence model, and results are validated to agree well with previous experiment. S-duct centreline shape and cross-sectional area distribution are parameterized as the design variables. By analyzing the results of a suggested optimal inlet chosen from the obtained Pareto front, total pressure recovery has increased from 97% to 97.4%, and total pressure distortion DC60 has decreased by 0.0477 (21.7% of the origin) at designed Mach number 0.7. The simplified efficient model has been validated to be reliable, and by which the time cost for the optimization project has been reduced by 70%.


2018 ◽  
Vol 33 (3-4) ◽  
pp. 115-123
Author(s):  
Ali Kaveh ◽  
Majid Ilchi Ghazaan ◽  
Soroush Mahjoubi

Barrel vaults are effective semi-cylindrical forms of roof systems that are widespread for multipurpose facilities including warehouse, rail station, pools, sports center, airplane hungers, and community centers because of providing long-span and economical roof with significant amount of space underneath. In the present study, size optimization of double-layer barrel vaults with different configurations is studied. Four recently developed algorithms consisting of the CBO, ECBO, VPS, and MDVC-UVPS are employed and their performances are compared. The structures are subjected to stress, stability, and displacement limitations according to the provisions of AISC-ASD. The design variables are the cross-sectional areas of the bar elements which are selected from steel pipe sections. The numerical results indicate that the MDVC-UVPS outperforms the other algorithms in finding optimal design in all examples.


2019 ◽  
Vol 9 (20) ◽  
pp. 4267
Author(s):  
Chien Yang Huang ◽  
Tai Yan Kam

A new and effective elastic constants identification technique is presented to extract the elastic constants of a composite laminate subjected to uniaxial tensile testing. The proposed technique consists of a new multi-level optimization method that can solve different types of minimization problems, including the extraction of material constants of composite laminates from given strains. In the identification process, the optimization problem is solved by using a stochastic multi-start dynamic search minimization algorithm at the first level in order to obtain the statistics of the quasi-optimal design variables for a set of randomly generated starting points. The statistics of the quasi-optimal elastic constants obtained at this level are used to determine the reduced feasible region in order to formulate the second-level optimization problem. The second-level optimization problem is then solved using the particle swarm algorithm in order to obtain the statistics of the new quasi-optimal elastic constants. The iteration process between the first and second levels of optimization continues until the standard deviations of the quasi-optimal design variables at any level of optimization are less than the prescribed values. The proposed multi-level optimization method, as well as several existing global optimization algorithms, is used to solve a number of well-known mathematical minimization problems to verify the accuracy of the method. For the adopted numerical examples, it has been shown that the proposed method is more efficient and effective than the adopted global minimization algorithms to produce the exact solutions. The proposed method is then applied to identify four elastic constants of a [0°/±45°]s composite laminate using three strains in 0°, 45°, and 90° directions, respectively, of the composite laminate subjected to uniaxial testing. For comparison purposes, several existing global minimization techniques are also used to solve the elastic constants identification problem. Again, it has been shown that the proposed method is capable of producing more accurate results than the adopted available methods. Finally, experimental data are used to demonstrate the applications of the proposed method.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniele Peri

PurposeA recursive scheme for the ALIENOR method is proposed as a remedy for the difficulties induced by the method. A progressive focusing on the most promising region, in combination with a variation of the density of the alpha-dense curve, is proposed.Design/methodology/approachALIENOR method is aimed at reducing the space dimensions of an optimization problem by spanning it by using a single alpha-dense curve: the curvilinear abscissa along the curve becomes the only design parameter for any design space. As a counterpart, the transformation of the objective function in the projected space is much more difficult to tackle.FindingsA fine tuning of the procedure has been performed in order to identity the correct balance between the different elements of the procedure. The proposed approach has been tested by using a set of algebraic functions with up to 1,024 design variables, demonstrating the ability of the method in solving large scale optimization problem. Also an industrial application is presented.Originality/valueIn the knowledge of the author there is not a similar paper in the current literature.


2019 ◽  
Vol 16 (08) ◽  
pp. 1841004 ◽  
Author(s):  
Thang Le-Duc ◽  
Quoc-Hung Nguyen

In this work, a new approach for aerodynamic optimization of horizontal axis wind turbine (HAWT) airfoil is presented. This technique combines commercial computational fluid dynamics (CFD) codes with differential evolution (DE), a reliable gradient-free global optimization method. During the optimization process, commercial CFD codes are used to evaluate aerodynamic characteristics of HAWT airfoil and an improved DE algorithm is utilized to find the optimal airfoil design. The objective of this research is to maximize the aerodynamic coefficients of HAWT airfoil at the design angle of attack (AOA) with specific ambient environment. The airfoil shape is modeled by control points which their coordinates are design variables. The reliability of CFD codes is validated by comparing the analytical results of a typical HAWT airfoil with its experimental data. Finally, the optimal design of wind turbine airfoil is evaluated about aerodynamic performance in comparison with existing airfoils and some discussions are performed.


2011 ◽  
Vol 50-51 ◽  
pp. 135-139
Author(s):  
Tie Yi Zhong ◽  
Chao Yi Xia ◽  
Feng Li Yang

Based on optimization theories, considering soil-structure interaction and running safety, the optimal design model of the seismic isolation system with lead-rubber bearings (LRB) for a simply supported railway beam bridge is established by using the first order optimization method in ANSYS, which the parameters of the isolation bearing are taken as design variables and the maximum moments at the bottom of bridge piers are taken as objective functions. The optimal calculations are carried out under the excitation of three practical earthquake waves respectively. The research results show that the ratio of the stiffness after yielding to the stiffness before yielding has important effect on the structural seismic responses. Through the optimal analysis of isolated bridge system, the optimal design parameters of isolation bearing can be determined properly, and the seismic forces can be reduced maximally as meeting with the limits of relative displacement between pier top and beam, which provides efficient paths and beneficial references for dynamic optimization design of seismic isolated bridges.


Buildings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 49
Author(s):  
Gebrail Bekdaş ◽  
Melda Yucel ◽  
Sinan Melih Nigdeli

Truss structures are one of the major civil engineering members studied in the optimization research area. In this area, various optimization applications such as topology, size, cost, weight, material usage, etc., can be conducted for different truss structure types. In this scope with the present study, various optimization processes were carried out concerning two different large-scale space trusses to minimize the structural weight. According to this state, three structural models provided via two different truss structures, including 25 bar and 72 bar truss models, were handled for evaluation of six different metaheuristics together with the modification of Lèvy flight for three of the algorithms using swarm intelligence by considering both constant and variable populations, and different ranges for iterations, too. Additionally, the effects of the Lèvy flight function and whether it is successful or not in terms of the target of optimization were also investigated by comparing with some documented studies. In this regard, some statistical calculations were also realized to evaluate the optimization method performance and detection of optimum values for any data stably and successfully. According to the results, the Jaya algorithm can handle the optimization process successfully, including the case, without grouping truss members. The positive effect of Lèvy flight on swarm-based algorithms can be seen especially for the gray wolf algorithm.


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