Process Optimization by Nonlinear Programming

Bella, C. W. Di; Stevens, William F.

doi:10.1021/i260013a005

Cited by 28 publications

(10 citation statements)

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“…Despite this, it is remarkable that the target did a good job of predicting the objective function and the optimal structure. Example E. This example, the "plant problem", is a modified form of the Williams and Otto problem (as stated in Ray and Szekely (1973) and in Di Bella and Stevens (1965)).…”

Section: Cagk3mentioning

confidence: 99%

Developing targets for the performance index of a chemical reactor network: isothermal systems

Achenie¹,

Biegler²

1988

Ind. Eng. Chem. Res.

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Target-based synthesis is a systems approach to reactor synthesis; it maximizes the performance index of a chemical reactor network as measured by its objective function (such as yield or reactor volume). The approach converts the synthesis problem into an optimal control formulation in which the residence time density function and the micromixing function are the control variables. The optimal control problem is then solved by using a gradient-based algorithm that employs successive quadratic programing and adjoint variables. Examples are given to illustrate the approach taken.

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Section: Cagk3mentioning

confidence: 99%

Developing targets for the performance index of a chemical reactor network: isothermal systems

Achenie¹,

Biegler²

1988

Ind. Eng. Chem. Res.

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“…This engineering problem was first proposed in [56] and has been used by many researchers as a benchmark for constrained NLP studies [15,50] and recently in bi-objective economic optimization [9,30]. The case study [42] reproduces the characteristics of a typical chemical plant.…”

Section: Problem Formulationmentioning

confidence: 99%

Multi-Objective Genetic Algorithms for Chemical Engineering Applications

Hernandez-Rodriguez

Morales-Mendoza

Pibouleau

et al. 2014

Applications of Metaheuristics in Process Engineering

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“…x Because ofits general nature (many standard unit operations and a recycle stream) it was used frequently in the past for optimization and control studies, see Dibella and Stevens (1965), Adelman and Stevens (2972), Luus and Jaakola (1973), Davison and Chadha (1972), Jung et al (1971). The reactions…”

Section: Example 3: Distillation Columnmentioning

confidence: 99%

Studies in the synthesis of control structures for chemical processes: Part II: Structural aspects and the synthesis of alternative feasible control schemes

1980

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The classification of control objectives and external disturbances in a chemical plant determines the extent of the optimizing and regulatory control structures (see Part I). In this article we discuss the structural design of alternative regulatory control schemes to satisfy the posed objective. Within the framework of hierarchical control, criteria are developed for the further decomposition of the process subsystems, reducing the combinatorial problem while not eliminating feasible control structures. We use structural models to describe the interactions among the units of a plant and the physicochemical phenomena occurring in the various units. The relevance of controllability and observability in the synthesis of control structures is discussed, and modified versions are used to develop all the alternative feasible regulatory structures in an algorithmic fashion. Various examples illustrate the developed concepts and strategies, including the application of the overall synthesis method to an integrated chemical plant.

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Process Optimization by Nonlinear Programming

Cited by 28 publications

References 0 publications

Developing targets for the performance index of a chemical reactor network: isothermal systems

Developing targets for the performance index of a chemical reactor network: isothermal systems

Multi-Objective Genetic Algorithms for Chemical Engineering Applications

Studies in the synthesis of control structures for chemical processes: Part II: Structural aspects and the synthesis of alternative feasible control schemes

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