Multi-objective Optimization of a Batch Transesterification Reactor Considering Reactor and Methanol Separation Unit Together

De, Riju; Bhartiya, Sharad; Shastri, Yogendra

doi:10.1016/b978-0-444-63965-3.50369-x

Cited by 1 publication

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References 4 publications

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“…One of the most widely used MOO algorithms for the optimization of engineering problems is the non-dominated sorting hybrid algorithm [24]. In the last five years, there has been a significant usage of MOO in chemical engineering [25][26][27][28][29][30][31][32][33]. The advantage of MOO over SOO is that it allows for a multi-criteria analysis for choosing the best solution [26].…”

Section: Dynamic Process Intensification and Forced Periodic Operation Analysismentioning

confidence: 99%

Rapid Multi-Objective Optimization of Periodically Operated Processes Based on the Computer-Aided Nonlinear Frequency Response Method

et al. 2020

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The dynamic optimization of promising forced periodic processes has always been limited by time-consuming and expensive numerical calculations. The Nonlinear Frequency Response (NFR) method removes these limitations by providing excellent estimates of any process performance criteria of interest. Recently, the NFR method evolved to the computer-aided NFR method (cNFR) through a user-friendly software application for the automatic derivation of the functions necessary to estimate process improvement. By combining the cNFR method with standard multi-objective optimization (MOO) techniques, we developed a unique cNFR–MOO methodology for the optimization of periodic operations in the frequency domain. Since the objective functions are defined with entirely algebraic expressions, the dynamic optimization of forced periodic operations is extraordinarily fast. All optimization parameters, i.e., the steady-state point and the forcing parameters (frequency, amplitudes, and phase difference), are determined rapidly in one step. This gives the ability to find an optimal periodic operation around a sub-optimal steady-state point. The cNFR–MOO methodology was applied to two examples and is shown as an efficient and powerful tool for finding the best forced periodic operation. In both examples, the cNFR–MOO methodology gave conditions that could greatly enhance a process that is normally operated in a steady state.

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Section: Dynamic Process Intensification and Forced Periodic Operation Analysismentioning

confidence: 99%

Rapid Multi-Objective Optimization of Periodically Operated Processes Based on the Computer-Aided Nonlinear Frequency Response Method

et al. 2020

View full text Add to dashboard Cite

show abstract

Multi-objective Optimization of a Batch Transesterification Reactor Considering Reactor and Methanol Separation Unit Together

Cited by 1 publication

References 4 publications

Rapid Multi-Objective Optimization of Periodically Operated Processes Based on the Computer-Aided Nonlinear Frequency Response Method

Rapid Multi-Objective Optimization of Periodically Operated Processes Based on the Computer-Aided Nonlinear Frequency Response Method

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