Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10495/16117
Título : Towards a framework for the development of control-oriented multiscale models of dynamical systems: semibatch emulsion polymerization case study
Autor : Urrea Quintero, Jorge Humberto
metadata.dc.contributor.advisor: Ochoa, Silvia
Hernandez, Hugo
metadata.dc.subject.*: Emulsion polymerization
Finite element method
Multiscale modeling
Polymers
Polímero
Laboratory equipment
Material de laboratorio
Chemical kinetics
Cinética química
Algebra
Álgebra
Statistics
Estadística
Equations
Ecuación
Industrial management
Gestión industrial
Ecuación fokker-planck
Fokker-planck equation
Control-oriented models
Controllability verification
Kinetic Monte Carlo
Reduce-order model
http://id.loc.gov/authorities/subjects/sh85042949
http://id.loc.gov/authorities/subjects/sh85048349
http://id.loc.gov/authorities/subjects/sh2010012486
http://vocabularies.unesco.org/thesaurus/concept5035
http://vocabularies.unesco.org/thesaurus/concept10109
http://vocabularies.unesco.org/thesaurus/concept4997
http://vocabularies.unesco.org/thesaurus/concept2018
http://vocabularies.unesco.org/thesaurus/concept119
http://vocabularies.unesco.org/thesaurus/concept8945
http://vocabularies.unesco.org/thesaurus/concept3402
Fecha de publicación : 2020
Resumen : ABSTRACT: This work develops a framework for the construction of a control-oriented model from a multiscale perspective, using a semibatch emulsion polymerization process as a case study. First, a so-called full multiscale model (considering the macro-, meso-, and micro-scopic scales) was developed which is composed of a set of Partial/Ordinary Differential Equations and a kinetic Monte Carlo simulation (PDE/ODE - kMC). Then, to obtain a reduced-order representation of the multiscale model, Variance Algebra concepts are used as a tool for representing, at the mesoscopic scale, a disperse-phase system from which only statistical information is available. After that, a dataset considering several process operational conditions is built to capture the main dynamics at the microscopic scale. This dataset is used to derive a closed-form model of the microscopic state variables by adopting a statistical modeling approach. The final obtained control-oriented model is composed of a set of ODEs comprising the macroscopic and the mesoscopic scales that can be solved by using standard ODEs integration schemes, whereas the microscopic scale variables are conveniently defined as some of the system outputs, represented by a set of algebraic equations. In order to consistently solve the full multiscale model, a numerical scheme based on the Finite Element Method is developed capturing the nonlinear evolution of the Particle Size Distribution (PSD). The validity of the obtained reduced-order model is verified through several simulations with respect to the system inputs. Finally, the multiscale control-oriented representation is employed to perform a batch output-controllability analysis based on a set-theoretic approach. The proposed framework might be adopted as a tool for the derivation of dynamical multiscale models keeping a good balance between their tractability and predictive capability, which can constitute an advantage when implementing real-time optimization and process control.
Aparece en las colecciones: Doctorados de la Facultad de Ingeniería

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