Numerical Simulation and Optimal Control of Air Separation Plants

The Floating Spiral pipeline installation method consists basically in winding the pipeline into a huge floating spiral, and towing this assembly to the installation site, where the spiral is then unwound and lowered to the seabed. In this method the pipeline is fabricated onshore, as the spiral is created, under well controlled conditions and relatively relaxed time constraints. Therefore the welds can be better inspected, which allows for optimal control of quality in pipeline manufacturing. The first stage of the installation process by this method consists in setting the pipeline afloat and winding it elastically to form a large flat spiral. This stage is studied in a companion paper [1], to be also presented at IPC2008. The second stage consists in towing the floating spiral pipeline employing standard tugboats before laying it at the installation site. The objective of this work is, therefore, to present results of parametric studies for a large length pipeline at this second stage of the Floating Spiral method. The focus now is in the pipeline behavior under wave environmental conditions during transportation. Several numerical simulations are performed and the results are discussed and compared.

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Analysis of Atangana–Baleanu fractional-order SEAIR epidemic model with optimal control

Advances in Difference Equations ◽

10.1186/s13662-021-03334-8 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Chernet Tuge Deressa ◽

Gemechis File Duressa

Keyword(s):

Numerical Simulation ◽

Optimal Control ◽

Fractional Order ◽

Control Strategy ◽

Epidemic Model ◽

Numerical Scheme ◽

Order Derivative ◽

Control Analysis ◽

Fractional Order Derivative ◽

Fractional Orders

AbstractWe consider a SEAIR epidemic model with Atangana–Baleanu fractional-order derivative. We approximate the solution of the model using the numerical scheme developed by Toufic and Atangana. The numerical simulation corresponding to several fractional orders shows that, as the fractional order reduces from 1, the spread of the endemic grows slower. Optimal control analysis and simulation show that the control strategy designed is operative in reducing the number of cases in different compartments. Moreover, simulating the optimal profile revealed that reducing the fractional-order from 1 leads to the need for quick starting of the application of the designed control strategy at the maximum possible level and maintaining it for the majority of the period of the pandemic.

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An efficient and rigorous thermodynamic library and optimal-control of a cryogenic air separation unit

Computer Aided Chemical Engineering - 27th European Symposium on Computer Aided Process Engineering ◽

10.1016/b978-0-444-63965-3.50259-2 ◽

2017 ◽

pp. 1543-1548

Author(s):

Jozsef Gaspar ◽

Tobias K.S. Ritschel ◽

John Bagterp Jørgensen

Keyword(s):

Optimal Control ◽

Air Separation ◽

Separation Unit ◽

Air Separation Unit

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Towards Nonlinear Model-Based Predictive Optimal Control of Large-Scale Process Models with Application to Air Separation Plants

Online Optimization of Large Scale Systems ◽

10.1007/978-3-662-04331-8_21 ◽

2001 ◽

pp. 385-410 ◽

Cited By ~ 1

Author(s):

Thomas Kronseder ◽

Oskar von Stryk ◽

Roland Bulirsch ◽

Andreas Kröner

Keyword(s):

Optimal Control ◽

Nonlinear Model ◽

Large Scale ◽

Air Separation ◽

Process Models ◽

Model Based

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Dynamic model for population distribution and optimum immigration and job creation policies

Canadian Studies in Population ◽

10.25336/p63k62 ◽

2004 ◽

Vol 31 (2) ◽

pp. 261

Author(s):

N. U. Ahmed ◽

Yongjuan He

Keyword(s):

Numerical Simulation ◽

Optimal Control ◽

Control Theory ◽

Dynamic Model ◽

Optimal Control Theory ◽

Close Agreement ◽

Population Distribution ◽

Job Creation ◽

Population Level ◽

Decision Control

In this paper we demonstrate that by use of modern Systems and Optimal Control theory, it is possible to formulate optimum immigration and job creation strategies while maintaining population level close to certain pre-specified targets. With this objective in mind, we consider a simplified dynamic model based on a previous model developed in (Ahmed and Rahim, 2001:325-358) to describe the population distribution in Canada. Numerical results demonstrate that the model population is in close agreement with the actual population. This model was then used to formulate a control problem with immigration and job creation rates being the decision (control) variables. Using optimal control theory, optimum immigration and job creation policies were determined. Results are illustrated by numerical simulation and they are found to be very encouraging.

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