The Experts below are selected from a list of 288 Experts worldwide ranked by ideXlab platform
Michele Ciofalo - One of the best experts on this subject based on the ideXlab platform.
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influence of drag and turbulence modelling on cfd predictions of solid liquid suspensions in stirred vessels
Chemical Engineering Research & Design, 2014Co-Authors: Alessandro Tamburini, Andrea Cipollina, G Micale, A Brucato, Michele CiofaloAbstract:Abstract Suspensions of solid particles into liquids within industrial stirred tanks are frequently carried out at an impeller speed lower than the minimum required for complete suspension conditions. This choice allows power savings which usually overcome the drawback of a smaller particle-liquid interfacial area. Despite this attractive economical perspective, only limited attention has been paid so far to the modelling of the partial suspension regime. In the present work two different baffled tanks stirred by Rushton turbines were simulated by employing the Eulerian-Eulerian Multi Fluid Model (MFM) along with either the Sliding Grid Algorithm (transient simulations) or the Multiple Reference Frame technique (steady state simulations). In particular, a comparison of alternative modelling approaches for inter-phase drag force and turbulence closure is presented. The results are evaluated against a number of experimental data concerning sediment features (amount and shape) and local axial profiles of solids concentration, with emphasis on the partial suspension regime. Results show that some of the approaches commonly adopted to account for dense particle effects or turbulent fluctuations of the volumetric fractions may actually lead to substantial discrepancies from the experimental data. Conversely simpler models which do not include such additional effects give the best overall predictions in the whole range of partial to complete suspension conditions.
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CFD SIMULATIONS OF DENSE SOLID-LIQUID SUSPENSIONS IN BAFFLED STIRRED TANKS: PREDICTION OF THE MINIMUM IMPELLER SPEED FOR COMPLETE SUSPENSION
Chemical Engineering Journal, 2012Co-Authors: Alessandro Tamburini, Andrea Cipollina, Giorgio Micale, Alberto Brucato, Michele CiofaloAbstract:In the literature on mechanically agitated solid–liquid systems, several methods are described to estimate the minimum impeller speed Njs at which all particles are suspended, but few studies have been devoted so far to their critical comparative assessment [67]. In the present paper, several alternative Njs prediction methods are applied to CFD results obtained for selected test cases covering a broad range of suspension conditions and impeller speeds. Results are compared with one another and with classic empirical correlations [88]. The aim of the work is to assess the adequacy of different methods for predicting Njs and, more generally, to contribute to a viable CFD-based strategy for the design of solid–liquid mixing equipment. To this purpose, transient RANS simulations using the sliding Grid Algorithm were carried out. An Unsuspended Solids Criterion (USC) was introduced to judge whether the solids contained in a generic control volume should be regarded as suspended or unsuspended. Based on this criterion, the concept of impeller speed for sufficient suspension, Nss, was proposed. The results suggest that it may be convenient to base the design of solid–liquid contactors on the sufficient suspension speed Nss rather than on the traditional Njs concept.
Alessandro Tamburini - One of the best experts on this subject based on the ideXlab platform.
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influence of drag and turbulence modelling on cfd predictions of solid liquid suspensions in stirred vessels
Chemical Engineering Research & Design, 2014Co-Authors: Alessandro Tamburini, Andrea Cipollina, G Micale, A Brucato, Michele CiofaloAbstract:Abstract Suspensions of solid particles into liquids within industrial stirred tanks are frequently carried out at an impeller speed lower than the minimum required for complete suspension conditions. This choice allows power savings which usually overcome the drawback of a smaller particle-liquid interfacial area. Despite this attractive economical perspective, only limited attention has been paid so far to the modelling of the partial suspension regime. In the present work two different baffled tanks stirred by Rushton turbines were simulated by employing the Eulerian-Eulerian Multi Fluid Model (MFM) along with either the Sliding Grid Algorithm (transient simulations) or the Multiple Reference Frame technique (steady state simulations). In particular, a comparison of alternative modelling approaches for inter-phase drag force and turbulence closure is presented. The results are evaluated against a number of experimental data concerning sediment features (amount and shape) and local axial profiles of solids concentration, with emphasis on the partial suspension regime. Results show that some of the approaches commonly adopted to account for dense particle effects or turbulent fluctuations of the volumetric fractions may actually lead to substantial discrepancies from the experimental data. Conversely simpler models which do not include such additional effects give the best overall predictions in the whole range of partial to complete suspension conditions.
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CFD SIMULATIONS OF DENSE SOLID-LIQUID SUSPENSIONS IN BAFFLED STIRRED TANKS: PREDICTION OF THE MINIMUM IMPELLER SPEED FOR COMPLETE SUSPENSION
Chemical Engineering Journal, 2012Co-Authors: Alessandro Tamburini, Andrea Cipollina, Giorgio Micale, Alberto Brucato, Michele CiofaloAbstract:In the literature on mechanically agitated solid–liquid systems, several methods are described to estimate the minimum impeller speed Njs at which all particles are suspended, but few studies have been devoted so far to their critical comparative assessment [67]. In the present paper, several alternative Njs prediction methods are applied to CFD results obtained for selected test cases covering a broad range of suspension conditions and impeller speeds. Results are compared with one another and with classic empirical correlations [88]. The aim of the work is to assess the adequacy of different methods for predicting Njs and, more generally, to contribute to a viable CFD-based strategy for the design of solid–liquid mixing equipment. To this purpose, transient RANS simulations using the sliding Grid Algorithm were carried out. An Unsuspended Solids Criterion (USC) was introduced to judge whether the solids contained in a generic control volume should be regarded as suspended or unsuspended. Based on this criterion, the concept of impeller speed for sufficient suspension, Nss, was proposed. The results suggest that it may be convenient to base the design of solid–liquid contactors on the sufficient suspension speed Nss rather than on the traditional Njs concept.
Chiehjen Wang - One of the best experts on this subject based on the ideXlab platform.
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a ga based feature selection and parameters optimizationfor support vector machines
Expert Systems With Applications, 2006Co-Authors: Chenglung Huang, Chiehjen WangAbstract:Support Vector Machines, one of the new techniques for pattern classification, have been widely used in many application areas. The kernel parameters setting for SVM in a training process impacts on the classification accuracy. Feature selection is another factor that impacts classification accuracy. The objective of this research is to simultaneously optimize the parameters and feature subset without degrading the SVM classification accuracy. We present a genetic Algorithm approach for feature selection and parameters optimization to solve this kind of problem. We tried several real-world datasets using the proposed GA-based approach and the Grid Algorithm, a traditional method of performing parameters searching. Compared with the Grid Algorithm, our proposed GA-based approach significantly improves the classification accuracy and has fewer input features for support vector machines. q 2005 Elsevier Ltd. All rights reserved.
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a ga based feature selection and parameters optimizationfor support vector machines
Expert Systems With Applications, 2006Co-Authors: Chenglung Huang, Chiehjen WangAbstract:Support Vector Machines, one of the new techniques for pattern classification, have been widely used in many application areas. The kernel parameters setting for SVM in a training process impacts on the classification accuracy. Feature selection is another factor that impacts classification accuracy. The objective of this research is to simultaneously optimize the parameters and feature subset without degrading the SVM classification accuracy. We present a genetic Algorithm approach for feature selection and parameters optimization to solve this kind of problem. We tried several real-world datasets using the proposed GA-based approach and the Grid Algorithm, a traditional method of performing parameters searching. Compared with the Grid Algorithm, our proposed GA-based approach significantly improves the classification accuracy and has fewer input features for support vector machines. q 2005 Elsevier Ltd. All rights reserved.
Andrea Cipollina - One of the best experts on this subject based on the ideXlab platform.
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influence of drag and turbulence modelling on cfd predictions of solid liquid suspensions in stirred vessels
Chemical Engineering Research & Design, 2014Co-Authors: Alessandro Tamburini, Andrea Cipollina, G Micale, A Brucato, Michele CiofaloAbstract:Abstract Suspensions of solid particles into liquids within industrial stirred tanks are frequently carried out at an impeller speed lower than the minimum required for complete suspension conditions. This choice allows power savings which usually overcome the drawback of a smaller particle-liquid interfacial area. Despite this attractive economical perspective, only limited attention has been paid so far to the modelling of the partial suspension regime. In the present work two different baffled tanks stirred by Rushton turbines were simulated by employing the Eulerian-Eulerian Multi Fluid Model (MFM) along with either the Sliding Grid Algorithm (transient simulations) or the Multiple Reference Frame technique (steady state simulations). In particular, a comparison of alternative modelling approaches for inter-phase drag force and turbulence closure is presented. The results are evaluated against a number of experimental data concerning sediment features (amount and shape) and local axial profiles of solids concentration, with emphasis on the partial suspension regime. Results show that some of the approaches commonly adopted to account for dense particle effects or turbulent fluctuations of the volumetric fractions may actually lead to substantial discrepancies from the experimental data. Conversely simpler models which do not include such additional effects give the best overall predictions in the whole range of partial to complete suspension conditions.
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CFD SIMULATIONS OF DENSE SOLID-LIQUID SUSPENSIONS IN BAFFLED STIRRED TANKS: PREDICTION OF THE MINIMUM IMPELLER SPEED FOR COMPLETE SUSPENSION
Chemical Engineering Journal, 2012Co-Authors: Alessandro Tamburini, Andrea Cipollina, Giorgio Micale, Alberto Brucato, Michele CiofaloAbstract:In the literature on mechanically agitated solid–liquid systems, several methods are described to estimate the minimum impeller speed Njs at which all particles are suspended, but few studies have been devoted so far to their critical comparative assessment [67]. In the present paper, several alternative Njs prediction methods are applied to CFD results obtained for selected test cases covering a broad range of suspension conditions and impeller speeds. Results are compared with one another and with classic empirical correlations [88]. The aim of the work is to assess the adequacy of different methods for predicting Njs and, more generally, to contribute to a viable CFD-based strategy for the design of solid–liquid mixing equipment. To this purpose, transient RANS simulations using the sliding Grid Algorithm were carried out. An Unsuspended Solids Criterion (USC) was introduced to judge whether the solids contained in a generic control volume should be regarded as suspended or unsuspended. Based on this criterion, the concept of impeller speed for sufficient suspension, Nss, was proposed. The results suggest that it may be convenient to base the design of solid–liquid contactors on the sufficient suspension speed Nss rather than on the traditional Njs concept.
Chenglung Huang - One of the best experts on this subject based on the ideXlab platform.
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a ga based feature selection and parameters optimizationfor support vector machines
Expert Systems With Applications, 2006Co-Authors: Chenglung Huang, Chiehjen WangAbstract:Support Vector Machines, one of the new techniques for pattern classification, have been widely used in many application areas. The kernel parameters setting for SVM in a training process impacts on the classification accuracy. Feature selection is another factor that impacts classification accuracy. The objective of this research is to simultaneously optimize the parameters and feature subset without degrading the SVM classification accuracy. We present a genetic Algorithm approach for feature selection and parameters optimization to solve this kind of problem. We tried several real-world datasets using the proposed GA-based approach and the Grid Algorithm, a traditional method of performing parameters searching. Compared with the Grid Algorithm, our proposed GA-based approach significantly improves the classification accuracy and has fewer input features for support vector machines. q 2005 Elsevier Ltd. All rights reserved.
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a ga based feature selection and parameters optimizationfor support vector machines
Expert Systems With Applications, 2006Co-Authors: Chenglung Huang, Chiehjen WangAbstract:Support Vector Machines, one of the new techniques for pattern classification, have been widely used in many application areas. The kernel parameters setting for SVM in a training process impacts on the classification accuracy. Feature selection is another factor that impacts classification accuracy. The objective of this research is to simultaneously optimize the parameters and feature subset without degrading the SVM classification accuracy. We present a genetic Algorithm approach for feature selection and parameters optimization to solve this kind of problem. We tried several real-world datasets using the proposed GA-based approach and the Grid Algorithm, a traditional method of performing parameters searching. Compared with the Grid Algorithm, our proposed GA-based approach significantly improves the classification accuracy and has fewer input features for support vector machines. q 2005 Elsevier Ltd. All rights reserved.
