Les Inscriptions à la Bibliothèque sont ouvertes en
ligne via le site: https://biblio.enp.edu.dz
Les Réinscriptions se font à :
• La Bibliothèque Annexe pour les étudiants en
2ème Année CPST
• La Bibliothèque Centrale pour les étudiants en Spécialités
A partir de cette page vous pouvez :
Retourner au premier écran avec les recherches... |
Détail de l'auteur
Auteur Mariano D. Cristaldi
Documents disponibles écrits par cet auteur
Affiner la rechercheDesign of dynamic experiments in modeling for optimization of batch processes / Ernesto C. Martinez in Industrial & engineering chemistry research, Vol. 48 N° 7 (Avril 2009)
[article]
in Industrial & engineering chemistry research > Vol. 48 N° 7 (Avril 2009) . - pp. 3453–3465
Titre : Design of dynamic experiments in modeling for optimization of batch processes Type de document : texte imprimé Auteurs : Ernesto C. Martinez, Auteur ; Mariano D. Cristaldi, Auteur ; Ricardo J. Grau, Auteur Année de publication : 2009 Article en page(s) : pp. 3453–3465 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Designing dynamic experiments Hamilton−Jacobi−Bellman optimality equation Model-based policy iteration algorithm Résumé : Finding optimal operating conditions fast with a scarce budget of experimental runs is a key problem to speeding up the development of innovative products and processes. Modeling for optimization is proposed as a systematic approach to bias data gathering for iterative policy improvement through experimental design using first-principles models. Designing dynamic experiments that are optimally informative in order to reduce the uncertainty about the optimal operating conditions is addressed by integrating policy iteration based on the Hamilton−Jacobi−Bellman optimality equation with global sensitivity analysis. A conceptual framework for run-to-run convergence of a model-based policy iteration algorithm is proposed. Results obtained in the fed-batch fermentation of penicillin G are presented. The well-known Bajpai and Reuss bioreactor model validated with industrial data is used to increase on a run-to-run basis the amount of penicillin obtained by input policy optimization and selective (re)estimation of relevant model parameters. A remarkable improvement in productivity can be gain using a simple policy structure after only two modeling runs despite initial modeling uncertainty. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8000953 [article] Design of dynamic experiments in modeling for optimization of batch processes [texte imprimé] / Ernesto C. Martinez, Auteur ; Mariano D. Cristaldi, Auteur ; Ricardo J. Grau, Auteur . - 2009 . - pp. 3453–3465.
Chemical engineering
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 48 N° 7 (Avril 2009) . - pp. 3453–3465
Mots-clés : Designing dynamic experiments Hamilton−Jacobi−Bellman optimality equation Model-based policy iteration algorithm Résumé : Finding optimal operating conditions fast with a scarce budget of experimental runs is a key problem to speeding up the development of innovative products and processes. Modeling for optimization is proposed as a systematic approach to bias data gathering for iterative policy improvement through experimental design using first-principles models. Designing dynamic experiments that are optimally informative in order to reduce the uncertainty about the optimal operating conditions is addressed by integrating policy iteration based on the Hamilton−Jacobi−Bellman optimality equation with global sensitivity analysis. A conceptual framework for run-to-run convergence of a model-based policy iteration algorithm is proposed. Results obtained in the fed-batch fermentation of penicillin G are presented. The well-known Bajpai and Reuss bioreactor model validated with industrial data is used to increase on a run-to-run basis the amount of penicillin obtained by input policy optimization and selective (re)estimation of relevant model parameters. A remarkable improvement in productivity can be gain using a simple policy structure after only two modeling runs despite initial modeling uncertainty. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie8000953 Finding the simplest mechanistic kinetic model describing the homogeneous catalytic hydrogenation of avermectin to ivermectin / Mariano D. Cristaldi in Industrial & engineering chemistry research, Vol. 50 N° 8 (Avril 2011)
[article]
in Industrial & engineering chemistry research > Vol. 50 N° 8 (Avril 2011) . - pp. 4252–4263
Titre : Finding the simplest mechanistic kinetic model describing the homogeneous catalytic hydrogenation of avermectin to ivermectin Type de document : texte imprimé Auteurs : Mariano D. Cristaldi, Auteur ; Maria I. Cabrera, Auteur ; Ernesto C. Martinez, Auteur Année de publication : 2011 Article en page(s) : pp. 4252–4263 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Kinetic Catalytic hydrogenation Résumé : Six mechanistic kinetic models of increasing complexity are analyzed to describe the RhCl(Ph3P)3 catalyzed hydrogenation process to produce ivermectin from avermectins B1a and B1b. Global sensitivity analysis (GSA) usefulness for selecting the simplest and the most suitable model is shown. First-order and total effect sensitivity indices for model parameters computed from GSA have been used for establishing those elementary reaction steps which were the most important in an extensive reaction framework. The prediction capability of the chosen model is corroborated by comparing its predictions with experimental data from both a lab-scale reactor and an industrial-scale reactor operating under isothermal and nonisothermal conditions, respectively. The best model is simple to use while resulting in a significant computational effort saving because there is no need to perform iterative algorithms for solving model equations. Another interesting feature is that ODEs for such a model have an analytical solution for isothermal hydrogenation processes. These features make modeling more amenable for cost-effective simulation and to include the selected model into computational frameworks for design of the hydrogenation process and control systems of the most usual catalytic method for producing ivermectin. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101289h [article] Finding the simplest mechanistic kinetic model describing the homogeneous catalytic hydrogenation of avermectin to ivermectin [texte imprimé] / Mariano D. Cristaldi, Auteur ; Maria I. Cabrera, Auteur ; Ernesto C. Martinez, Auteur . - 2011 . - pp. 4252–4263.
Chimie industrielle
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 50 N° 8 (Avril 2011) . - pp. 4252–4263
Mots-clés : Kinetic Catalytic hydrogenation Résumé : Six mechanistic kinetic models of increasing complexity are analyzed to describe the RhCl(Ph3P)3 catalyzed hydrogenation process to produce ivermectin from avermectins B1a and B1b. Global sensitivity analysis (GSA) usefulness for selecting the simplest and the most suitable model is shown. First-order and total effect sensitivity indices for model parameters computed from GSA have been used for establishing those elementary reaction steps which were the most important in an extensive reaction framework. The prediction capability of the chosen model is corroborated by comparing its predictions with experimental data from both a lab-scale reactor and an industrial-scale reactor operating under isothermal and nonisothermal conditions, respectively. The best model is simple to use while resulting in a significant computational effort saving because there is no need to perform iterative algorithms for solving model equations. Another interesting feature is that ODEs for such a model have an analytical solution for isothermal hydrogenation processes. These features make modeling more amenable for cost-effective simulation and to include the selected model into computational frameworks for design of the hydrogenation process and control systems of the most usual catalytic method for producing ivermectin. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101289h