Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm
R. Venkata Rao,Vivek Patel +1 more
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TLDR
In this paper, a modified version of the TLBO algorithm is introduced and applied for the multi-objective optimization of heat exchangers, where the objective function is to maximize the heat exchanger effectiveness and minimize the total cost of the exchanger.About:
This article is published in Applied Mathematical Modelling.The article was published on 2013-02-01 and is currently open access. It has received 305 citations till now. The article focuses on the topics: Plate fin heat exchanger & Shell and tube heat exchanger.read more
Citations
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Heat exchangers for cooling supercritical carbon dioxide and heat transfer enhancement: a review and assessment
Wenguang Li,Zhibin Yu +1 more
TL;DR: In this paper, a critical review of heat exchangers for cooled supercritical carbon dioxide (SCO2) flows, within which CO2 is close to its critical point and thus is likely to experience heat transfer deterioration or enhancement due to the dramatical change of thermo-physical properties.
Journal ArticleDOI
Multi‐Objective Optimization of a Cross‐Flow Plate Heat Exchanger Using Entropy Generation Minimization
TL;DR: In this article, a multi-objective optimization of a cross-flow plate fin heat exchanger (PFHE) by means of an entropy generation minimization technique is described.
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Prediction of berm geometry using a set of laboratory tests combined with teaching–learning-based optimization and artificial bee colony algorithms
TL;DR: In this paper, a wave flume with regular waves, considering different values for the wave height (H0), wave period (T), bed slope (m), and mean sediment diameter (d50), was used to determine the geometric parameters of the resulting berms.
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Exergoeconomic optimization of a shell-and-tube heat exchanger
TL;DR: In this paper, the authors presented an economic optimization of a STHX with two commonly adopted (i.e., Kern and Bell-Delaware) and one rarely explored (e.g., Wills-Johnston) methods.
Journal ArticleDOI
Hierarchical multi-swarm cooperative teaching–learning-based optimization for global optimization
TL;DR: In this paper, a two-level hierarchical multi-swarm cooperative TLBO variant called HMCTLBO is presented to solve global optimization problems, where all learners are randomly divided into several sub-swarms with equal amounts of learners at the bottom level of the hierarchy.
References
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Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems
TL;DR: The effectiveness of the TLBO method is compared with the other population-based optimization algorithms based on the best solution, average solution, convergence rate and computational effort and results show that TLBO is more effective and efficient than the other optimization methods.
Journal ArticleDOI
Compact heat exchangers
TL;DR: The third edition of the second edition as discussed by the authors was published in 1964 and contains basic test data for eleven new surface configurations, including some of the very compact ceramic matrices, in both the English and the Systeme International (SI) system of units.
Journal ArticleDOI
Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems
TL;DR: An efficient optimization method called 'Teaching-Learning-Based Optimization (TLBO)' is proposed in this paper for large scale non-linear optimization problems for finding the global solutions.
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An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems
R. Rao,Vivek Patel +1 more
TL;DR: Elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated and the effects of common controlling parameters such as the population size and the number of generations on the results are investigated.
Journal ArticleDOI
Heat exchanger design based on economic optimisation
TL;DR: In this paper, a procedure for optimal design of shell and tube heat exchangers is proposed, which utilizes a genetic algorithm to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping.
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