Single and multi-objective optimization of nanofluid flow in flat tube to enhance heat transfer using antlion optimizer algorithms

This optimization problem focuses to determine the five independent design variables to find out the optimal values of heat transfer coefficient ( H ∼ ) and pressure drop ( Δ P ) parameters. It consists of two conflicting optimization problem as discrete objective functions: first to maximize heat t...

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Bibliographic Details
Published in:International journal of system assurance engineering and management Vol. 12; no. 6; pp. 1026 - 1035
Main Authors: Dinkar, Shail Kumar, Deep, Kusum
Format: Journal Article
Language:English
Published: New Delhi Springer India 01.12.2021
Springer Nature B.V
Subjects:
Algorithms
Aluminum oxide
Computational fluid dynamics
Design modifications
Design optimization
Engineering
Engineering Economics
Fluid flow
Heat transfer
Heat transfer coefficients
Independent variables
Logistics
Marketing
Multiple objective analysis
Nanofluids
Optimization
Organization
Original Article
Pareto optimization
Pressure drop
Quality Control
Reliability
Response surface methodology
Safety and Risk
Temperature
Pressure drop value
Antlion optimizer
Heat transfer coefficient
Nanofluid
Optimization
ISSN:0975-6809, 0976-4348
Online Access:Get full text
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Summary:This optimization problem focuses to determine the five independent design variables to find out the optimal values of heat transfer coefficient ( H ∼ ) and pressure drop ( Δ P ) parameters. It consists of two conflicting optimization problem as discrete objective functions: first to maximize heat transfer coefficient and second to minimize pressure drop value. In this work, the problem is optimized using two approaches: First, single objective approach for both the objective functions separately to determine the optimal values of design variables using classical ALO and its modified variants. Secondly, multi-objective approach in which both the objective functions are optimized simultaneously to determine objective function values of heat transfer coefficient and pressure drop while optimizing design variables. This purpose is achieved using two different methods of multi-objective optimization: (i) Using weighted sum approach of multi-objective optimization using classical ALO and its proposed variants (ii) Pareto based multi-objective optimization using multi-objective antlion optimizer. The model used in this work is developed using Al 2 O 3 -water nanofluid using horizontal flat tube with the help of computational fluid dynamics and response surface methodology (RSM). The obtained results show superiority of ALO and its modified variants approach and also compared with RSM.
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ISSN:0975-6809
0976-4348
DOI:10.1007/s13198-021-01091-1