A comparison of simulated annealing schedules for constructal design of complex cavities intruded into conductive walls with internal heat generation

Gonzales, Gill Velleda; Estrada, Emanuel; Emmendorfer, Leonardo Ramos; Isoldi, Liércio André; Xie, Gongnan; Rocha, Luíz Alberto Oliveira; Santos, Elizaldo Domingues dos

doi:10.1016/j.energy.2015.09.058

Cited by 28 publications

(20 citation statements)

References 19 publications

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“…For all simulations, the volume of resin injected up For complete optimization, Steps 6b to 9b, illustrated in Figure 2, are executed. It should be emphasized that heuristic-based optimization methods, e.g., genetic algorithm and simulated annealing, have also been associated with constructal design [48]. These kinds of tools are more used in software packages such as FLUENT [41] and Magma 5 [49].…”

Section: Numerical Modeling and Code Validationmentioning

confidence: 99%

Numerical Analysis of the Influence of Empty Channels Design on Performance of Resin Flow in a Porous Plate

et al. 2020

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This numerical study aims to investigate the influence of I and T-shaped empty channels’ geometry on the filling time of resin in a rectangular porous enclosed mold, mimicking the main operating principle of a liquid resin infusion (LRI) process. Geometrical optimization was conducted with the constructal design (CD) and exhaustive search (ES) methods. The problem was subjected to two constraints (areas of porous mold and empty channels). In addition, the I and T-shaped channels were subjected to one and three degrees of freedom (DOF), respectively. Conservation equations of mass and momentum for modeling of resin/air mixture flow were numerically solved with the finite volume method (FVM). Interaction between the phases was considered with the volume of fluid method (VOF), and the effect of porous medium resistance in the resin flow was calculated with Darcy’s law. For the studied conditions, the best T-shaped configuration resulted in a filling time nearly three times lower than that for optimal I-shaped geometry, showing that the complexity of the channels benefited the performance. Moreover, the best T-shaped configurations were achieved for long single and bifurcated branches, except for configurations with skinny channels, which saw the generation of permanent voids.

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Section: Numerical Modeling and Code Validationmentioning

confidence: 99%

Numerical Analysis of the Influence of Empty Channels Design on Performance of Resin Flow in a Porous Plate

et al. 2020

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“…(4) Perform within-subsystem migration. [27] adopted the concept of Boltzmann's probability distribution. This means that if a system maintains its thermal equilibrium at temperature , the probability distribution of its energy can be calculated by the following [27]:…”

Section: Bbo/complex and Simulated Annealingmentioning

confidence: 99%

“…Save the vectors of all the populations (before migration) in matrix mm 1 with size 1 * 2 and their cost functions vector vv1 Save the vectors of all the populations (after migration) in matrix mm 2 with size 1 * 2 and their cost functions in vector vv2 Randomly select indices from ( ) and select immigrating islands based immigration rates. (25) if pbi ( new | , * ) ⩽ pbi ( | , * ) (26) save the best islands new for emigrating(27) else(28) Save the vectors of all the populations (before mutation) in matrix mm 3 with size 3 * 4 and their cost functions in vector vv 3…”

mentioning

confidence: 99%

An Improved Hybrid Algorithm Based on Biogeography/Complex and Metropolis for Many‐Objective Optimization

Wang

et al. 2017

Mathematical Problems in Engineering

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It is extremely important to maintain balance between convergence and diversity for many-objective evolutionary algorithms. Usually, original BBO algorithm can guarantee convergence to the optimal solution given enough generations, and the Biogeography/Complex (BBO/Complex) algorithm uses within-subsystem migration and cross-subsystem migration to preserve the convergence and diversity of the population. However, as the number of objectives increases, the performance of the algorithm decreases significantly. In this paper, a novel method to solve the many-objective optimization is called Hmp/BBO (Hybrid Metropolis Biogeography/Complex Based Optimization). The new decomposition method is adopted and the PBI function is put in place to improve the performance of the solution. On the within-subsystem migration the inferior migrated islands will not be chosen unless they pass the Metropolis criterion. With this restriction, a uniform distribution Pareto set can be obtained. In addition, through the above-mentioned method, algorithm running time is kept effectively. Experimental results on benchmark functions demonstrate the superiority of the proposed algorithm in comparison with five state-of-the-art designs in terms of both solutions to convergence and diversity.

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“…The SA algorithm is constructed based on the statistical mechanics, which was demonstrated by Metropolis et al in 1953[25] through the concept of Boltzmann's probability distribution. It means if a system is maintained in a thermal equilibrium at temperature T, then the probability distribution p of its energy E can be achieved by [26]:…”

Section: Simulated Annealing Algorithmmentioning

confidence: 99%

Hybrid Biogeography/Complex-based Optimization

Wang¹,

Yang²

2016

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation

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The optimization of complex systems is a very difficult problem in modern engineering technology. It is with multi-subsystems, multi-objectives and multi-constraints. In this paper, a novel solution to the complex systems optimization called HBBO/Complex. HBBO/Complex adapted from biogeography-based optimization (BBO) and combined the simulated annealing (SA). The inferior migrated islands will not be selected unless they pass the Metropolis criterion of SA. This method can prevent the local optimal solution. Compared with typical existing many-objective optimization algorithms, HBBO/complex has better convergence characteristics. The results confirm the HBBO/complex provides the best performance in the benchmark problems.

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A comparison of simulated annealing schedules for constructal design of complex cavities intruded into conductive walls with internal heat generation

Cited by 28 publications

References 19 publications

Numerical Analysis of the Influence of Empty Channels Design on Performance of Resin Flow in a Porous Plate

Numerical Analysis of the Influence of Empty Channels Design on Performance of Resin Flow in a Porous Plate

An Improved Hybrid Algorithm Based on Biogeography/Complex and Metropolis for Many‐Objective Optimization

Hybrid Biogeography/Complex-based Optimization

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