Control and optimization of multiscale process systems
TL;DR: An overview of recently developed methods for control and optimization of complex process systems described by multiscale models using examples of thin film growth processes to motivate the development of these methods and illustrate their application.
About: This article is published in Computers & Chemical Engineering.The article was published on 2006-09-12. It has received 102 citations till now. The article focuses on the topics: Context (language use).
Citations
More filters
TL;DR: In this article, a kinetic Monte Carlo (kMC) simulation is used to model the crystal nucleation, growth, and dissolution through a fines trap in a continuous crystallization process.
86 citations
Cites methods from "Control and optimization of multisc..."
...In the present work, the kMC methodology is further developed to model a continuous protein crystallization process, and implemented in the way described in Christofides et al. (2008) using the rate equations on the crystal surface reaction initially developed by Durbin and Feher (1991)....
[...]
TL;DR: This work details the construction and evaluation of a low computational cost hybrid multiscale thin film deposition model that couples artificial neural networks (ANNs) with a mechanistic (first-principles) multiscales model.
73 citations
TL;DR: This work explores a systematic framework to analyze model parameter uncertainty for robust control and optimization of multiscale models and proposes a PSE-based method for uncertainty analysis, which is more computationally efficient in comparison to the traditional Monte Carlo approach.
65 citations
TL;DR: In this article, the modeling and control of a batch crystallization process used to produce tetragonal hen egg white lysozyme crystals are studied, and the MPC method is shown to successfully regulate both the crystal size and shape distributions to different setpoint values.
Abstract: In this work, the modeling and control of a batch crystallization process used to produce tetragonal hen egg white lysozyme crystals are studied. Two processes are considered, crystal nucleation and growth. Crystal nucleation rates are obtained from previous experiments. The growth of each crystal progresses via kinetic Monte Carlo simulations comprising of adsorption, desorption, and migration on the (110) and (101) faces. The expressions of the rate equations are similar to Durbin and Feher. To control the nucleation and growth of the protein crystals and produce a crystal population with desired shape and size, a model predictive control (MPC) strategy is implemented. Specifically, the steady-state growth rates for the (110) and (101) faces are computed and their ratio is expressed in terms of the temperature and protein concentration via a nonlinear algebraic equation. The MPC method is shown to successfully regulate both the crystal size and shape distributions to different set-point values. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2317–2327, 2013
64 citations
TL;DR: In this paper, a multiscale modeling and operation framework for plasma-enhanced chemical vapor deposition (PECVD) of thin film silicon solar cells with uniform thickness and film surface microstructure that optimizes light trapping is proposed.
61 citations
Cites methods from "Control and optimization of multisc..."
...The governing equations have been developed at length for CVD-type applications (e.g., (Vlachos, 1997; Lam and Vlachos, 2001; Christofides and Armaou, 2006)); however, here we apply the formulation by Armaou and Christofides (1999) as radial dependence of species concentration is desired....
[...]
..., (Vlachos, 1997; Lam and Vlachos, 2001; Christofides and Armaou, 2006)); however, here we apply the formulation by Armaou and Christofides (1999) as radial dependence of species concentration is desired....
[...]
References
More filters
01 Jan 1950
TL;DR: A First Course in Probability (8th ed.) by S. Ross is a lively text that covers the basic ideas of probability theory including those needed in statistics.
Abstract: Office hours: MWF, immediately after class or early afternoon (time TBA). We will cover the mathematical foundations of probability theory. The basic terminology and concepts of probability theory include: random experiments, sample or outcome spaces (discrete and continuous case), events and their algebra, probability measures, conditional probability A First Course in Probability (8th ed.) by S. Ross. This is a lively text that covers the basic ideas of probability theory including those needed in statistics. Theoretical concepts are introduced via interesting concrete examples. In 394 I will begin my lectures with the basics of probability theory in Chapter 2. However, your first assignment is to review Chapter 1, which treats elementary counting methods. They are used in applications in Chapter 2. I expect to cover Chapters 2-5 plus portions of 6 and 7. You are encouraged to read ahead. In lectures I will not be able to cover every topic and example in Ross, and conversely, I may cover some topics/examples in lectures that are not treated in Ross. You will be responsible for all material in my lectures, assigned reading, and homework, including supplementary handouts if any.
10,221 citations
TL;DR: In this paper, an exact method is presented for numerically calculating, within the framework of the stochastic formulation of chemical kinetics, the time evolution of any spatially homogeneous mixture of molecular species which interreact through a specified set of coupled chemical reaction channels.
5,875 citations
TL;DR: In this paper, it was shown that the chemical master equation is exact for any gas-phase chemical system that is kept well stirred and thermally equilibrated, and that the exactness of the master equation has no rigorous microphysical basis, and hence no a priori claim to validity.
Abstract: It is widely believed that the chemical master equation has no rigorous microphysical basis, and hence no a priori claim to validity. This view is challenged here through arguments purporting to show that the chemical master equation is exact for any gas-phase chemical system that is kept well stirred and thermally equilibrated.
1,123 citations
TL;DR: In this paper, a simple model is given which describes the process by which a particle settles and comes to rest on the existing surface of the packing and from this a set of Langevin equations for the Fourier modes of the surface are derived.
Abstract: The problem of the surface fluctuations in a settled granular material is posed. A simple model is given which describes the process by which a particle settles and comes to rest on the existing surface of the packing and from this a set of Langevin equations for the Fourier modes of the surface are derived. These equations imply that the Fourier amplitudes behave like the velocities of a set of independent Brownian particles. We show that this results in logarithmically divergent surface fluctuations if the flux of particles onto the surface is random, the divergence being removed by a more accurate description of the settling material, for example by having the granules fall through a sieve.
1,068 citations