Documents disponibles écrits par cet auteur

Semianalytical bubble - flow models for the development of a novel bubble - column simulator / Waldo Coetzee in Industrial & engineering chemistry research, Vol. 51 N° 21 (Mai 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 21 (Mai 2012) . - pp. 7398-7409 Titre : Semianalytical bubble - flow models for the development of a novel bubble - column simulator Type de document : texte imprimé Auteurs : Waldo Coetzee, Auteur ; Roelof L. J. Coetzer, Auteur ; Randhir Rawatlal, Auteur Année de publication : 2012 Article en page(s) : pp. 7398-7409 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Bubble  column  Modeling  Bubble  flow Résumé : The simulation of bubble columns is a computationally expensive task because of the complexity of the hydrodynamics. A novel bubble-column simulation approach attempts to increase the computational efficiency by accounting for the flow regions around individual bubbles with an algebraic flow model. To improve the accuracy and reduce the number of parameters of the flow model, the linear combination of the creeping and potential flow analytical solutions is considered as a first approximation, which is found to accurately model large portions of the flow field within the considered operating range (Rc ≤ 270). The residual consists of significant nonlinear features, e.g., bubble wake, for which two statistically based strategies, i.e., Design and Analysis of Computer Experiments (DACE) and regression with empirical models, are evaluated. Both resulted in good fits, with the DACE strategy making fewer assumptions about the data, however, requiring more parameters. The combination of analytical and empirical models is therefore recommended for use as an accurate algebraic approximation of the flow field. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25948480 [article] Semianalytical bubble - flow models for the development of a novel bubble - column simulator [texte imprimé] / Waldo Coetzee, Auteur ; Roelof L. J. Coetzer, Auteur ; Randhir Rawatlal, Auteur . - 2012 . - pp. 7398-7409. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 21 (Mai 2012) . - pp. 7398-7409 Mots-clés : Bubble  column  Modeling  Bubble  flow Résumé : The simulation of bubble columns is a computationally expensive task because of the complexity of the hydrodynamics. A novel bubble-column simulation approach attempts to increase the computational efficiency by accounting for the flow regions around individual bubbles with an algebraic flow model. To improve the accuracy and reduce the number of parameters of the flow model, the linear combination of the creeping and potential flow analytical solutions is considered as a first approximation, which is found to accurately model large portions of the flow field within the considered operating range (Rc ≤ 270). The residual consists of significant nonlinear features, e.g., bubble wake, for which two statistically based strategies, i.e., Design and Analysis of Computer Experiments (DACE) and regression with empirical models, are evaluated. Both resulted in good fits, with the DACE strategy making fewer assumptions about the data, however, requiring more parameters. The combination of analytical and empirical models is therefore recommended for use as an accurate algebraic approximation of the flow field. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=25948480

A statistical approach to microkinetic analysis / Pieter van Helden in Industrial & engineering chemistry research, Vol. 51 N° 19 (Mai 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 19 (Mai 2012) . - pp. 6631–6640 Titre : A statistical approach to microkinetic analysis Type de document : texte imprimé Auteurs : Pieter van Helden, Auteur ; Jan-Albert van den Berg, Auteur ; Roelof L. J. Coetzer, Auteur Année de publication : 2012 Article en page(s) : pp. 6631–6640 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Microkinetic  Analysis Résumé : An in-depth understanding of fundamental heterogeneous catalysis can be obtained by the use of Microkinetic Analysis of the elementary reaction steps. Unfortunately, for complex reaction networks, the sheer number of parameters present in such models can make the interpretation and deeper understanding of such microkinetic models very difficult. In this work, a Microkinetic Analysis Methodology, which incorporates statistical methods, is demonstrated, with application to a typical set of fundamental catalytic reactions. A uniform statistical experimental design is implemented, varying a selection of parameters within the microkinetic model. The responses of the simulated model are fitted to construct approximation models. We illustrate the extension of some known methods in order to successfully implement the proposed methodology, such as Kriging approximation models applied to additive log-ratio transformations of the surface coverage compositions, as well as a multivariate scaled EIGF criterion to iteratively improve the global model fit. We demonstrate that the methodology yields statistical approximation models that are capable of yielding accurate predictions of the complete parameter space. The proposed methodology can be applied to any number of microkinetic model parameters of interest. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2013086 [article] A statistical approach to microkinetic analysis [texte imprimé] / Pieter van Helden, Auteur ; Jan-Albert van den Berg, Auteur ; Roelof L. J. Coetzer, Auteur . - 2012 . - pp. 6631–6640. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 19 (Mai 2012) . - pp. 6631–6640 Mots-clés : Microkinetic  Analysis Résumé : An in-depth understanding of fundamental heterogeneous catalysis can be obtained by the use of Microkinetic Analysis of the elementary reaction steps. Unfortunately, for complex reaction networks, the sheer number of parameters present in such models can make the interpretation and deeper understanding of such microkinetic models very difficult. In this work, a Microkinetic Analysis Methodology, which incorporates statistical methods, is demonstrated, with application to a typical set of fundamental catalytic reactions. A uniform statistical experimental design is implemented, varying a selection of parameters within the microkinetic model. The responses of the simulated model are fitted to construct approximation models. We illustrate the extension of some known methods in order to successfully implement the proposed methodology, such as Kriging approximation models applied to additive log-ratio transformations of the surface coverage compositions, as well as a multivariate scaled EIGF criterion to iteratively improve the global model fit. We demonstrate that the methodology yields statistical approximation models that are capable of yielding accurate predictions of the complete parameter space. The proposed methodology can be applied to any number of microkinetic model parameters of interest. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2013086

Statistical robustness study for kinetic models / Roelof L. J. Coetzer in Industrial & engineering chemistry research, Vol. 49 N° 6 (Mars 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 6 (Mars 2010) . - pp. 2932–2942 Titre : Statistical robustness study for kinetic models Type de document : texte imprimé Auteurs : Roelof L. J. Coetzer, Auteur ; J. Pirow Engelbrecht, Auteur ; Christo Crause, Auteur Année de publication : 2010 Article en page(s) : pp. 2932–2942 Note générale : Industrial Chemistry Langues : Anglais (eng) Mots-clés : Robustness--Statistica--Kinetic--Models Résumé : Kinetic models are nonlinear systems that depict the dependence between process variables and components or products where the process variables are usually assumed to be fixed. This is under the assumption that the process variables that govern the outputs are fully controllable. However, process variables are not always fully controllable and are more often hard-to-control during normal operation on a full-scale chemical production plant. This Article outlines the methodology of statistical robustness studies for kinetic models. Such an application is apparently new in engineering design and analysis. We illustrate the use of computer experiments and evaluate different response models and designs for determining optimum conditions, which are robust against the variability in the hard-to-control variables. The methodology is demonstrated with two examples, the main one being the ethoxylation of ethylene glycol in an inter cooled pipe reactor. The practical value of statistical robustness studies is that it quantifies the convoluted effect of model uncertainty and model input deviation. Note de contenu : Bibiogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900924g [article] Statistical robustness study for kinetic models [texte imprimé] / Roelof L. J. Coetzer, Auteur ; J. Pirow Engelbrecht, Auteur ; Christo Crause, Auteur . - 2010 . - pp. 2932–2942. Industrial Chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 6 (Mars 2010) . - pp. 2932–2942 Mots-clés : Robustness--Statistica--Kinetic--Models Résumé : Kinetic models are nonlinear systems that depict the dependence between process variables and components or products where the process variables are usually assumed to be fixed. This is under the assumption that the process variables that govern the outputs are fully controllable. However, process variables are not always fully controllable and are more often hard-to-control during normal operation on a full-scale chemical production plant. This Article outlines the methodology of statistical robustness studies for kinetic models. Such an application is apparently new in engineering design and analysis. We illustrate the use of computer experiments and evaluate different response models and designs for determining optimum conditions, which are robust against the variability in the hard-to-control variables. The methodology is demonstrated with two examples, the main one being the ethoxylation of ethylene glycol in an inter cooled pipe reactor. The practical value of statistical robustness studies is that it quantifies the convoluted effect of model uncertainty and model input deviation. Note de contenu : Bibiogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie900924g