Investigation on the Association of Differential Evolution and Constructal Design for Geometric Optimization of Double Y-Shaped Cooling Cavities Inserted into Walls with Heat Generation

Author:

Gonzales Gill Velleda12ORCID,Biserni Cesare3ORCID,da Silva Diaz Estrada Emanuel1ORCID,Platt Gustavo Mendes4ORCID,Isoldi Liércio André1ORCID,Rocha Luiz Alberto Oliveira1,da Silva Neto Antônio José5,dos Santos Elizaldo Domingues1ORCID

Affiliation:

1. Graduate Program in Computational Modeling, Federal University of Rio Grande, Rio Grande 96201-900, RS, Brazil

2. Sul-Rio-Grandense Federal Institute, Pelotas Campus, Pelotas 96015-360, RS, Brazil

3. Department of Industrial Engineering (DIN), Alma Mater Studiorum-University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy

4. School of Chemistry and Food, Federal University of Rio Grande, Santo Antônio da Patrulha 95500-000, RS, Brazil

5. Polytechnic Institute, State University of Rio de Janeiro, Nova Friburgo 28625-570, RJ, Brazil

Abstract

In the constructal design method, the comprehension of the effect of design on the system performance is crucial to understanding the contributions of the degrees of freedom or constraints in the system evolution in direction of optimal configurations. However, problems with many degrees of freedom are prohibitive of optimization with exhaustive search, requiring meta-heuristic strategies. Therefore, the investigation of the optimization algorithms is essential. This work investigates the canonical differential evolution algorithm associated with the constructal design for the geometric optimization of an isothermal double Y-shaped cooling cavity inserted into a wall with internal heat generation. The effect of four degrees of freedom over the thermal performance of the system is investigated using sixteen different combinations of differential evolution algorithms: four variations of mutation parameter, two values of amplification factor (F) and two values of crossover rate (CR). The non-parametric statistical methods of Kruskal–Wallis and Dunn test were used to identify the parameters that improve the meta-heuristic efficiency. Results indicated that the proposed methodology selected the proper combination of DE algorithm parameters (CR, F, and mutation) that led to the best effect of degrees of freedom over the thermal performance in all optimization levels investigated.

Funder

Brazilian Coordination for the Improvement of Higher Education Personnel

Brazilian National Council for Scientific and Technological Development

FAPERGS—Fundação de Apoio à Pesquisa do Estado do Rio Grande do Sul

FAPERJ—Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro

Italian Ministry for Education, University and Research

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference30 articles.

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2. Bejan, A. (2020). Freedom and Evolution: Hierarchy in Nature, Society and Science, Springer International Publishing.

3. Bejan, A. (2000). Shape and Structure, from Engineering to Nature, Cambridge University Press.

4. Rincón-Mejía, E., and de las Heras, A. (2017). Sustainable Energy Technologies, CRC Press.

5. Rocha, L.A.O., Lorente, S., and Bejan, A. (2017). Handbook of Thermal Science and Engineering, Springer International Publishing. [1st ed.].

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