Size and Shape Optimization of Truss Structures with Natural Frequency Constraints Using Modified Simulated Annealing Algorithm

Millan-Paramo, Carlos; Filho, João Elias Abdalla

doi:10.1007/s13369-019-04138-5

Cited by 18 publications

(6 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Silva et al 28 used the sequential linear programming algorithm to optimize the finite element model of partially interacting steel-concrete composite beams. Millan-Paramo and Abdalla Filho 29 proposed a new improved simulated annealing algorithm for truss structure shape optimization and verified that this method is more reliable, stable, and effective than other heuristic optimization methods. Solarte-Pardo et al 30 combined genetic algorithm and artificial neural network to develop a cutting edge selection and cutting parameter optimization system.…”

Section: Introductionmentioning

confidence: 91%

Optimization design of curved outrigger structure based on buckling analysis and multi-island genetic algorithm

et al. 2021

View full text Add to dashboard Cite

In the present work, the working state of the crane leg is analyzed and discussed, and its structure is optimized. SolidWorks software is used for modeling; ANSYS software is used for finite element analysis. First of all, the constrained finite element method (CFEM) is used to analyze the linear eigenvalue buckling and geometric nonlinear buckling of outriggers with different cross-section shapes. Prove that the curved leg has certain advantages in buckling. At the same time, analyzing the leg along a different path of buckling condition and stress changes provide the basis for the design of the subsequent reinforcement. After selecting the best cross-section shape of the outrigger, the agent-based multi-island genetic algorithm is used to optimize the structural parameters of the outrigger under the transverse stiffened plate reinforced structure and the longitudinally stiffened plate reinforced structure respectively. It is proved that the outrigger with the transverse stiffened plate has a significant effect in improving the bearing capacity and in the lightweight of the structure. Finally, the gap between the movable leg and the fixed leg was changed, the stress of different gaps was analyzed by using the finite element method, and the appropriate gap value was selected according to the high-order fitting curve.

show abstract

Section: Introductionmentioning

confidence: 91%

Optimization design of curved outrigger structure based on buckling analysis and multi-island genetic algorithm

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Millan-Paramo and Abdalla Filho [32,33] Modified simulated annealing algorithm (MSAA) and improved modified simulated annealing algorithm (IMSAA) Kaveh and Mahjoubi [34] Hypotrochoid spiral optimization algorithm (HSPO)…”

Section: Author Metaheuristicmentioning

confidence: 99%

Truss Optimization with Natural Frequency Constraints Using Modified Social Engineering Optimizer

Millan-Paramo¹,

Millán-Romero²,

Wilches³

2020

International Journal of Engineering Research and Technology

View full text Add to dashboard Cite

“…Truss structures are one of the most important structures in civil engineering and have been widely used in different applications such as bridges, transmission towers, outriggers, roofs, etc. Over the decades, designing truss structures to satisfy both safety and economic requirements has received much attention and several studies have addressed this issue [1][2][3][4][5][6][7][8][9][10]. These studies have imposed limitations on nodal displacements and axial stress of the members as a safety criterion as well as limitation on truss weight as an economic criterion.…”

Section: Introductionmentioning

confidence: 99%

Reliability-based multi-objective optimal design of spatial trusses using NSGA-II

Semiromi

Keyhani

2022

NMCE

View full text Add to dashboard Cite

This paper addresses a reliability-based multi-objective design method for spatial truss structures. The uncertainties of the applied load and the resistance of the truss members have been taken into account by generating a set of 50 random numbers. The failure probability of each truss member has been evaluated and consequently, the failure probability of the entire truss system has been calculated considering a series system. A multi-objective optimization problem has been defined with objective functions of truss weight and failure probability of the entire truss structure. The cross-sectional area of the truss members has been considered as the design variable. Also ,The limitations of nodal displacements and allowable stress of the members have been defined as constraints. A 25-bar benchmark spatial truss has been considered as the case study structure and has been optimally designed using the non-dominated sorting genetic algorithm II (NSGA-II). The results show thr effectiveness and simplicity of the proposed method which can provide a wide range of optimal solutions through Pareto fronts. These optimal solutions can provide both safety and reliability for the truss structure. Also, the results indicate that the failure probability of the truss structure reduces by increasing the uncertainty level of load and resistance. D

show abstract

Size and Shape Optimization of Truss Structures with Natural Frequency Constraints Using Modified Simulated Annealing Algorithm

Cited by 18 publications

References 32 publications

Optimization design of curved outrigger structure based on buckling analysis and multi-island genetic algorithm

Optimization design of curved outrigger structure based on buckling analysis and multi-island genetic algorithm

Truss Optimization with Natural Frequency Constraints Using Modified Social Engineering Optimizer

Reliability-based multi-objective optimal design of spatial trusses using NSGA-II

Contact Info

Product

Resources

About