Optimisation-based simulation of a pressure swing adsorption process
| Autor: | Daniel Tondeur, Mohamed Abderrazak Latifi, D. Salhi |
|---|---|
| Přispěvatelé: | Laboratoire des Sciences du Génie Chimique (LSGC), Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Réactions et Génie des Procédés (LRGP), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2008 |
| Předmět: |
Mathematical optimization
State variable General Chemical Engineering PSA process · Cyclic steady-state · Simulation · Optimisation Finite difference Process (computing) 02 engineering and technology Surfaces and Interfaces General Chemistry simulation 021001 nanoscience & nanotechnology Nonlinear programming Pressure swing adsorption [CHIM.GENI]Chemical Sciences/Chemical engineering Adsorption Decision variables 020401 chemical engineering Pressure-Swing-Adsorption [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering 0204 chemical engineering 0210 nano-technology optimization Mathematics Sequential quadratic programming |
| Zdroj: | Adsorption-Journal of the International Adsorption Society Adsorption-Journal of the International Adsorption Society, Springer Verlag, 2008, 14, pp.567-573 Adsorption-Journal of the International Adsorption Society, Springer Verlag, 2008, 14 (4-5), pp.567-573. ⟨10.1007/s10450-008-9130-0⟩ |
| ISSN: | 1572-8757 0929-5607 |
| Popis: | Presented at Fundamentals of Adsorption FOA9, Giardini Naxos, Sicily, May 2007 From the issue entitled "Special Issue: Fundamentals of Adsorption 9, Part IV, Guest Editor: Marco Mazzotti; International audience; In this paper, an optimisation-based approach is developed for the determination of the cyclic steady-sate (CSS) of a pressure swing adsorption process (PSA). It consists in treating the simulation problem as a single dynamic optimisation problem where the performance index is the CSS condition, the decision variables are the state variables at the start of the cycle and the constraints are given by the process model equations with associated initial conditions. The resulting optimisation problem is solved using a gradient-based non linear programming (NLP)method, e.g. SQP method, where the gradients are computed bymeans of four different methods : finite differences, numerical and analytical sensitivities and adjoint system methods. |
| Databáze: | OpenAIRE |
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