A trust region framework for heat exchanger network synthesis with detailed individual heat exchanger designs

Kazi, Saif R.; Short, Michael; Biegler, Lorenz T.

doi:10.1016/j.compchemeng.2021.107447

Cited by 9 publications

(7 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to that, stochastic algorithms, such as simulated annealing, 31 genetic algorithms, 32 and particle swarm optimization, 33 are frequently used to generate a good solution within affordable time for large‐scale strongly nonconvex MINLP problems. However, the stochastic algorithms lead to long computational times and no guarantee of optimality 34 . Another class of methods are to relax an MINLP problem as an NLP problem and add some special constraints to force the integrality of the relaxed integer variables gradually 35 .…”

Section: Introductionmentioning

confidence: 99%

“…For example, a trust region filter (TRF) method has been proposed 56 and refined 57 for optimization of chemical processes with high-fidelity models, and for heat exchanger network synthesis with detailed exchanger design. 34,55 However, the convergence of the algorithm may largely rely on the robust convergence and accurate derivative information of the simulation using the original model, which may be unavailable or unreliable in some cases. In addition, which parts of the high-fidelity model are substituted with what kinds of surrogate models might need expert knowledge to achieve good convergence and high efficiency.…”

mentioning

confidence: 99%

“…However, the stochastic algorithms lead to long computational times and no guarantee of optimality. 34 Another class of methods are to relax an MINLP problem as an NLP problem and add some special constraints to force the integrality of the relaxed integer variables gradually. 35 Such method has been applied to optimization of distillation columns 36 and synthesis of reaction-separation-recycle processes.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Homotopy continuation enhanced branch and bound algorithms for strongly nonconvex mixed‐integer nonlinear optimization

2022

AIChE Journal

View full text Add to dashboard Cite

Large‐scale strongly nonlinear and nonconvex mixed‐integer nonlinear programming (MINLP) models frequently appear in optimization‐based process synthesis, integration, intensification, and process control. However, they are usually difficult to solve by existing algorithms within acceptable time. In this study, we propose two robust homotopy continuation enhanced branch and bound (HCBB) algorithms (denoted as HCBB‐FP and HCBB‐RB) where the homotopy continuation method is employed to gradually approach the optimum of the NLP subproblem at a node from the solution at its parent node. A variable step length is adapted to effectively balance feasibility and computational efficiency. The computational results from solving four existing process synthesis problems demonstrate that the proposed HCBB algorithms can find the same optimal solution from different initial points, while the existing MINLP algorithms fail or find much worse solutions. In addition, HCBB‐RB is superior to HCBB‐FP due to much lower computational effort required for the same locally optimal solution.

show abstract

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Homotopy continuation enhanced branch and bound algorithms for strongly nonconvex mixed‐integer nonlinear optimization

2022

AIChE Journal

View full text Add to dashboard Cite

show abstract

“…16 Recently, heat exchanger models associated with numerical discretization procedures have also been used for the design optimization 17 and heat exchanger network synthesis. 18,19 The limitations exposed above of the closed-form analytical solutions hinder the utilization of design optimization tools for engineering practice. 20 Therefore, this paper discusses the optimization of heat exchangers based on models where the physical properties and the heat transfer coefficients vary along the heat transfer surface.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, several papers addressed the simulation of heat exchangers through discretization techniques or even computational fluid dynamics . Recently, heat exchanger models associated with numerical discretization procedures have also been used for the design optimization and heat exchanger network synthesis. , …”

Section: Introductionmentioning

confidence: 99%

Design Optimization of Double-Pipe Heat Exchangers Using a Discretized Model

Nahes

Bagajewicz

Costa

2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

The design optimization of heat exchangers is a topic extensively investigated in the literature. The majority of the papers that addressed this problem employed closed-form analytical solutions to describe the behavior of the equipment, such as the logarithmic mean temperature difference (LMTD) and effectiveness (ε-NTU) methods. These analytical solutions are based on the hypothesis of uniform values of the physical properties and heat transfer coefficients. This assumption may imply considerable errors in several situations. Aiming at eliminating these limitations, we present a novel integer linear model for the optimal design of hairpin double-pipe heat exchangers. Our novel method discretizes the temperature field inside the exchangers and, together with appropriate rigorous reformulations, renders a linear model. Numerical results illustrate the performance of the proposed approach, showing that the analytical solutions can significantly undersize or oversize the heat exchanger.

show abstract

Global optimization of the design of intensified shell and tube heat exchanger using tube inserts

Chang,

Shen

2023

Can J Chem Eng

View full text Add to dashboard Cite

This paper investigates global optimization of the detailed design of intensified shell and tube heat exchangers using two tube inserts: twisted tape and coiled wire. Three objectives, including heat exchanger area, total annualized cost, and environmental impact, are respectively minimized. All the design variables are considered as the ones that have discrete values based on their physical nature or manufacturing standards. We present, for the first time, a tailored global optimization approach for the design of intensified shell and tube heat exchanger: Set trimming procedure. We compare the computational performance of our set trimming procedure, exhaustive enumeration, and commercial solvers. The proposed three objectives have certain competitive relationships and multi‐objective optimization is performed to analyze the conflicts among them. Two literature examples are tested for illustration purposes. The solution results indicate that the intensified heat exchanger designed using tube inserts compares well to the regular heat exchanger using plain tube. Compared with commercial solvers, set trimming procedure runs fast and can converge to global optimum without initial value. The pareto‐optimal solutions of multi‐objective optimization provide holistic trade‐offs between different objectives, hence helping the process designer make proper decisions for the design of intensified shell and tube heat exchangers.

show abstract

A trust region framework for heat exchanger network synthesis with detailed individual heat exchanger designs

Cited by 9 publications

References 52 publications

Homotopy continuation enhanced branch and bound algorithms for strongly nonconvex mixed‐integer nonlinear optimization

Homotopy continuation enhanced branch and bound algorithms for strongly nonconvex mixed‐integer nonlinear optimization

Design Optimization of Double-Pipe Heat Exchangers Using a Discretized Model

Global optimization of the design of intensified shell and tube heat exchanger using tube inserts

Contact Info

Product

Resources

About