Optimization of steel web core sandwich panel with genetic algorithm

2022 ◽  
Vol 253 ◽  
pp. 113805
Author(s):  
Pier Giovanni Benzo ◽  
João M. Pereira ◽  
José Sena-Cruz
Keyword(s):  
Genetic Algorithm ◽  
Sandwich Panel

Genetic Optimization for the Design of a Machine Tool Slide Table for Reduced Energy Consumption

2021 ◽  
Vol 143 (10) ◽  
Author(s):  
Matthew J. Triebe ◽  
Fu Zhao ◽  
John W. Sutherland
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Energy Consumption ◽  
Machine Tool ◽  
Machine Tools ◽  
Sandwich Panel ◽  
Sustainable Manufacturing ◽  
Element Model ◽  
Genetic Optimization ◽  
Use Phase

Abstract Reducing the energy consumption of machine tools is important from a sustainable manufacturing perspective. Much of a machine tool’s environmental impact comes from the energy it consumes during its use phase. To move elements of a machine tool requires energy, and if the mass of those elements can be reduced, then the required energy would be reduced. Therefore, this paper proposes a genetic algorithm to design lightweight machine tools to reduce their energy consumption. This is specifically applied to optimize the structure of a machine tool slide table, which moves throughout the use of the machine tool, with the goal of reducing its mass without sacrificing its stiffness. The table is envisioned as a sandwich panel, and the proposed genetic algorithm optimizes the core of the sandwich structure while considering both mass and stiffness. A finite element model is used to assess the strength of the proposed designs. Finite element results indicate that the strength of the lightweight tables is comparable with a traditional table design.

Optimization of Dimensions of a Sandwich Structure Using Genetic Algorithm (GA)

2008 ◽  
Vol 47-50 ◽  
pp. 371-374 ◽  
Author(s):  
Mohammad Reza Khoshravan ◽  
M. Hosseinzadeh
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Execution Time ◽  
Sandwich Structure ◽  
Sandwich Panel ◽  
Multilayer Composite ◽  
The Core ◽  
Optimum Height

Optimum height of the core and thickness of the composite faces of a sandwich panel under a defined loading have been computed in order to obtain the lowest weight of structure and its highest stiffness. Either by choosing adequate lay up sequence of multilayer composite faces, desired properties of the composite faces was chosen. The Genetic Algorithm (GA) based on statistics was used and to obtain the best methods of G.A., sensitivity analysis was carried out. In result, the influence of sensitivity analysis was found useful because it leaded to a better convergence of problem and decreased the execution time of the problem.

scholarly journals Multi-Criteria Optimization of Energy-Efficient Cementitious Sandwich Panels Building Systems Using Genetic Algorithm

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 6001
Author(s):  
Ehsan Mirnateghi ◽  
Ayman S. Mosallam
Keyword(s):  
Genetic Algorithm ◽  
Optimum Design ◽  
Energy Efficient ◽  
Sandwich Panel ◽  
Sandwich Panels ◽  
Optimization Techniques ◽  
Pareto Optimal ◽  
Cementitious Composite ◽  
Composite Sandwich Panels ◽  
Composite Sandwich

This paper presents results of a study that focuses on developing a genetic algorithm (GA) for multi-criteria optimization of orthotropic, energy-efficient cementitious composite sandwich panels (CSP). The current design concept of all commercially produced CSP systems is based on the assumption that such panels are treated as doubly reinforced sections without the consideration of the three-dimensional truss contribution of the orthotropic panel system. This leads to uneconomical design and underestimating both the strength and stiffness of such system. In this study, two of the most common types of commercially produced sandwich were evaluated both numerically and experimentally and results were used as basis for developing a genetic algorithm optimization process using numerical modeling simulations. In order to develop a sandwich panel with high structural performance, design optimization techniques are needed to achieve higher composite action, while maintaining the favorable features of such panels such as lightweight and high thermal insulation. The study involves both linear and nonlinear finite element analyses and parametric optimization. The verification and calibration of the numerical models is based on full-scale experimental results that were performed on two types of commercially produced sandwich panels under different loading scenarios. The genetic algorithm technique is used for optimization to identify an optimum design of the cementitious composite sandwich panels. The GA technique combines Darwin’s principle of survival of fittest and a structured information exchange using randomized crossover operators to evolve an optimum design for the cementitious sandwich panel. Parameters evaluated in the study include: (i) shear connectors’ geometry, its volume fraction and distribution; (ii) exterior cementitious face sheets thickness and (iii) size and geometry steel wires reinforcements. The proposed optimization method succeeded in reducing cost of materials of CSP by about 48% using genetic algorithm methodology. In addition, an optimized design for CSP is proposed that resulted in increasing the panel’s thermal resistance by 40% as compared to existing panels, while meeting ACI Code structural design criteria. Pareto-optimal front and Pareto-optimal solutions have been identified. Correlation between the design variables is also verified and design recommendation are proposed.

Optimization of composite sandwich panel against impact using genetic algorithm

2010 ◽  
Vol 37 (6) ◽  
pp. 599-604 ◽  
Author(s):  
Mehdi Kalantari ◽  
Mohammad Rahim Nami ◽  
Mohammad Hasan Kadivar
Keyword(s):  
Genetic Algorithm ◽  
Sandwich Panel ◽  
Composite Sandwich

Optimal Design of an Asymmetrical Sandwich Panel for Acoustical and Mechanical Properties

2012 ◽  
Author(s):  
Pierre Leite ◽  
Marc Thomas ◽  
Frank Simon ◽  
Yves Bréchet
Keyword(s):  
Mechanical Properties ◽  
Genetic Algorithm ◽  
Optimal Design ◽  
Sandwich Panel ◽  
Transmission Loss ◽  
Minimum Weight ◽  
Bending Test ◽  
Multi Objective ◽  
Minimal Weight ◽  
The Mean

The aim of the present study is to develop specific tools to design optimal panels for multi-objective applications. The objectives considered are stiffness, strength and acoustic insulation at minimum weight. A genetic algorithm is used to design optimal sandwich structures with a good balance of mechanical and acoustical properties. The bending stiffness and mechanical strength of the panel are calculated using beam theory. This analysis is focused on a 3-point bending test, giving the stiffness as the ratio between the concentrated force and the deflection at the center of the sandwich panel. The strength is calculated as the critical force at the onset of plastic deformation. A vibro-acoustical model based on Lagrange’s equations is used to give access to the sound transmission loss of the sandwich panel with anisotropic elastic layers. The main interest is on the mean transmission loss for a diffused incident acoustic field over the frequency range 500–10000Hz. First of all, the optimal design for mechanical properties is assessed at a minimal weight. Quite expectedly, the best solutions are composite-skin with high specific stiffness and soft cores with high shear modulus for a minimum weight. The geometry depends on the required stiffness and strength. The design/properties relationship is discussed by monitoring the evolution of both the material properties and the geometry of the panel. Similarly, a parametric study is performed for acoustical design at minimal weight. In order to maximize the mean transmission loss, it is preferable to lower the critical frequency for which acoustic radiating is maximal. Then, the best solutions for the panel are those who maximize the square root of the density over Young’s modulus. The trade-off between mass and loss transmission is then explored. A comparison between all these solutions provides significant differences in the design with respect to the objectives. In the next step, a multi-objective genetic algorithm is used to find an optimized panel with a good compromise between acoustical and mechanical properties. The optimization is considered with several approaches depending on whether the mass is regarded as the cost function or as a constraint. This study thus provides a preview of the capabilities of multi-objective optimization in design of sandwich panel.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
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