A simultaneous approach for the synthesis of multiperiod heat exchanger network using particle swarm optimization

Silva, Gercio P.; Miranda, Camila de Brito; Carvalho, Esdras P.; Ravagnani, Mauro A.S.S.

doi:10.1002/cjce.23065

Cited by 5 publications

(2 citation statements)

References 32 publications

(71 reference statements)

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“…In addition, some novel optimization algorithms were also applied in heat exchanger configuration optimization, including Particle Swarm Optimization (PSO), [13][14][15] biogeography based optimization algorithm, 16 teaching-learning-based optimization algorithm, 17 genetic simulated annealing algorithm, 18 differential evolution algorithm, 19 Jaya algorithm, 20,21 Artificial immune system 22 and so on. A three fluid heat exchanger was researched by Mohapatra et al 23 and the configuration parameters including curvature ratio, non-dimensional coil pitch, and coil side Reynolds number were optimized by Taguchi method to strengthen heat transfer and weaken flow resistance.…”

Section: Introductionmentioning

confidence: 99%

Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

Guo

Yang³

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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A performance calculation method based on heat transfer unit (HTU) simulation is proposed to calculate heat transfer capacity and air-side pressure drop of Annular radiator (AR), which can avoid the problem of a huge amount of grids, and at the same time, ensure the calculation accuracy. Calculation results are compared with experimental data, and the average errors of heat transfer capacity and air-side pressure drop are 11.5%, and 5.9%, respectively, which effectively validates the effectiveness and the reliability of this method. Besides, based on HTU simulation knowledge database, a configuration optimization method of AR using Non-dominated Sorted Genetic Algorithm-II (NSGA-II) is introduced. Number of fins in circumferential direction, number of fins in axial direction, and fin height are chosen as design parameters, and two conflicting optimization objectives include heat transfer capacity maximization and air-side pressure drop minimization. Three optimal structures of AR are obtained, and the optimal results indicate that the heat transfer capacity of the optimal configurations increases by 34.31% on average compared with the original one, while the air-side pressure drop decreases by 24.00% on average, which indicates that this method is feasible and valid and can provide significant guidance for structural design of AR.

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Section: Introductionmentioning

confidence: 99%

Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

Guo

Yang³

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…17 Silva et al applied Particle Swarm Optimization, wherein all variables were optimized simultaneously. 18 Zheng et al proposed an approach for flexible HEN synthesis under severe operation uncertainty, represented by the probability bounds analysis theory and sampled with a double-loop sampling method. 19 Li et al presented a two-step approach for the synthesis of flexible HENs.…”

Section: Introductionmentioning

confidence: 99%

A Robust Decomposition Methodology for Synthesis of Flexible Processes with Many Uncertainty Parameters – Application to HEN Synthesis

Zirngast

Kravanja

Pintarič

2019

Chem.Biochem.Eng.Q.

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This contribution presents a new robust decomposition methodology for generating optimal flexible process flow sheets with a large number of uncertain parameters. During the initial steps, first-stage variables are determined by performing mixed-integer nonlinear programming (MINLP) synthesis of a flow sheet at the nominal conditions, and then by exposing the obtained flow sheet sequentially over a set of extreme MINLP scenarios of uncertain parameters. As a result, the sizes of the flow-sheet units gradually increase, and/or new units are added until the required feasibility is achieved. After testing the flexibility of the obtained design, a Monte Carlo stochastic optimization of the second-stage variables is performed using a sampling method in order to obtain an optimum value of the expected objective variable. The advantages of the proposed methodology are the independence of process model sizes from the number of uncertain parameters, the straightforward use of deterministic models for incorporating uncertainty, and relatively simple execution of MINLP synthesis of processes under uncertainty. Thus, it could be used for designing large processes with a large number of uncertain parameters. The methodology is illustrated by synthesis of a flexible Heat Exchanger Network.

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An innovative damping random walk algorithm with compulsive evolution for the synthesis of heat exchanger networks

Huang,

Liu,

Duan

et al. 2024

Applied Thermal Engineering

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A simultaneous approach for the synthesis of multiperiod heat exchanger network using particle swarm optimization

Cited by 5 publications

References 32 publications

Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

A Robust Decomposition Methodology for Synthesis of Flexible Processes with Many Uncertainty Parameters – Application to HEN Synthesis

An innovative damping random walk algorithm with compulsive evolution for the synthesis of heat exchanger networks

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