Adiabatic reactor network synthesis using coupled genetic algorithm with quasi linear programming method

Soltani, Hadi; Shafiei, Sirous

doi:10.1016/j.ces.2015.06.068

Cited by 18 publications

(9 citation statements)

References 49 publications

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“…The maximal entropy is achieved if all individuals are unique in the population. If the number of individuals per generation is 50, the maximal entropy of the system is log 2 (50) ≈ 5.64 (p i = 1/50, ∀i ∈ [1,50]).…”

Section: Selection and Replacement Methodsmentioning

confidence: 99%

“…The search of an optimal design for reaction-separation-recycle systems can be seen as global (process scale) intensification strategy based on flowsheet architecture improvement [2], and has been dealt in many papers [e.g. 30,48,49,50,23]. This makes reaction-separation-recycle systems a relevant example to validate the developed method and its implementation.…”

Section: Case Study With a Reaction-separation-recycle Systemmentioning

confidence: 99%

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Ab-initio process synthesis using evolutionary programming

Neveux

2018

Chemical Engineering Science

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Process synthesis methods enable the determination of unit operations and their interconnection into a process flowsheet, with associated design and operating parameters, and responding to given objectives. Modern methods are optimization-based, using for example Mixed Integer Non-Linear Programming (MINLP) formulation to optimize a process superstructure. Finding an adequate definition of the search space is a non-trivial problem in such approaches, especially when the number of possible combinations is high due to the process complexity, and is mostly driven by expertise (e.g. heuristics). Consequently, an inductive bias is intrinsically introduced due to restriction of a limited search space, such as the choice of a superstructure representing a limited set of process alternatives. In this work, an evolutionary method is proposed to generate several process architectures based on a set of available unit operations (and associated models) as elementary building blocks. The procedure is here called ab-initio process synthesis since it does not require any pre-defined process structure. The developed method relies on the use of an Evolutionary Programming (EP), mimicking natural evolution at species-level, for the automatic construction of a process by using mutation operators to choose, assemble and connect elementary building blocks (i.e. unit operations). A Non-Linear Programming (NLP) is used for process evaluation, by simultaneously solving balances and optimizing process degrees of freedom. The method is implemented in a newly developed tool called PSEvo (Process Synthesis by Evolution). An application to a typical reaction-separation problem is presented, using various problem definitions and evolution control parameters, which demonstrates the method capability to generate optimal processes. The possible uses and the challenges of ab-initio process synthesis are finally discussed.

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Section: Selection and Replacement Methodsmentioning

confidence: 99%

Section: Case Study With a Reaction-separation-recycle Systemmentioning

confidence: 99%

Ab-initio process synthesis using evolutionary programming

Neveux

2018

Chemical Engineering Science

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“…Furthermore, different feeding, recycling, and bypassing strategies were included in order to realize complex flow configurations. Further methods have been proposed, combining stochastic optimization and mathematical programming in order to solve the reactor network synthesis problem on the basis of general superstructures of CSTRs and PFRs. − However, in most of these methods, some sort of model simplification is established in order to reduce the computational effort such as the quasilinear programming method applied by Soltani and Shafiei . One major advantage of such superstructure optimization approaches is the fact that the number of considered reactors is variable and that a distinct objective function, other than the maximum product composition, can be implemented.…”

Section: Phenomena-based Process Synthesis Approachmentioning

confidence: 99%

“…Taking into account the structure of the introduced PS method, the implementation of a superstructure-based reactor network model presents a straightforward extension that is expected to work well with the memetic optimization approach, considering the positive results reported in the literature. − The novel RN-PBB is therefore based on a combination of the basic reactor concepts, CSTR, PFR, and DSR, whereas the latter are approximated by a series of CSTRs in accordance with the CSTR equivalence principle introduced by Feinberg and Ellison . As such, the novel RN-PBB extends the portfolio of (reactive) separation PBBs, introduced in the preceding work and summarized in the previous section.…”

Section: Phenomena-based Process Synthesis Approachmentioning

confidence: 99%

“…50−53 However, in most of these methods, some sort of model simplification is established in order to reduce the computational effort such as the quasilinear programming method applied by Soltani and Shafiei. 53 One major advantage of such superstructure optimization approaches is the fact that the number of considered reactors is variable and that a distinct objective function, other than the maximum product composition, can be implemented. Furthermore, nonisothermal reactor networks for complex reaction systems containing multiple consecutive and parallel reactions can be determined without specific modifications.…”

Section: Reactor Network Synthesismentioning

confidence: 99%

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Optimization-Based Approach to Process Synthesis for Process Intensification: Synthesis of Reaction-Separation Processes

Kuhlmann

Veith

Möller

et al. 2017

Ind. Eng. Chem. Res.

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Process synthesis and intensification are powerful tools for the development of cost-and energy-efficient chemical processes. However, even though their combination maximizes the potential for improvements, they are mostly applied separately. The current article presents the extension of a phenomena-based process synthesis method by an aditional building block for reactor network synthesis and reactive separations. The method facilitates the automatic generation of thermodynamically feasible phenomena-based flowsheet variants by means of superstructure optimization, which are subsequently translated into equipment-based flowsheets taking into account classical as well as intensified equipment. By composing a flowsheet from mass and energy transfer phenomena instead of predefined unit operations, counterintuitive solutions and significant improvements can be achieved. In the current contribution, the capabilities of the method are demonstrated using the transesterification of propylene carbonate with methanol as a case study. The resulting optimal flowsheet represents a combination of integrated and hybrid separation steps for overcoming the intrinsic limitations of this system. The obtained result presents significant cost saving potential compared to those flowsheet variants previously generated by an alternative process synthesis method.

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Integration of reactor network synthesis: A literature review and opportunities for future research

Zhou

Deng

Gao

et al. 2023

Asia-Pacific J Chem Eng

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The reactor network synthesis (RNS) is one of the subtopics of the chemical process synthesis, the purpose of which is to find an optimal reactor network for the specific objective function of the studied reaction system. This review discusses the principles, advantages, and disadvantages of various methods of RNS, together with the state of the research in each field. These methods could be divided into four categories: the process‐based approach (such as the attainable region, the targeting approach, and the method based on the elementary process functions), superstructure‐based approach, stochastic optimization, and parametric method. Finally, the paper discusses the existing problems of RNS in academic researches and practical applications, as well as its research directions in the future. This paper is helpful to the readers who have interests in the design and optimization of the reactor networks.

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Adiabatic reactor network synthesis using coupled genetic algorithm with quasi linear programming method

Cited by 18 publications

References 49 publications

Ab-initio process synthesis using evolutionary programming

Ab-initio process synthesis using evolutionary programming

Optimization-Based Approach to Process Synthesis for Process Intensification: Synthesis of Reaction-Separation Processes

Integration of reactor network synthesis: A literature review and opportunities for future research

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