Titre : | Dimensional analysis of food processes | Type de document : | texte imprimé | Auteurs : | Guillaume Delaplace ; Karine Loubière ; Fabrice Ducept ; Romain Jeantet | Editeur : | London : ISTE Press Ltd | Année de publication : | 2015 | Autre Editeur : | Oxford : Elsevier | Collection : | Modeling and Control of Food Processes Set | Importance : | 1 vol. (XVIII-337 p.) | Présentation : | ill., couv. ill. en coul. | Format : | 24 cm | ISBN/ISSN/EAN : | 978-1-78548-040-9 | Note générale : | Bibliogr. p.329-333. Index. Annexes | Langues : | Anglais (eng) | Catégories : | Liste Plan de classement 16.12 (GENIE DES PROCEDES) [Classement Massy] Thésaurus Agro-alimentaire GENIE DES PROCEDES ; MODELISATION ; ANALYSE MULTIDIMENSIONNELLE ; GENIE ALIMENTAIRE
| Résumé : | This book is dedicated to the modeling of food processing using dimensional analysis. Dimensional analysis has evolved very little since it was founded and first applied to chemical engineering. Most semi-empirical correlations between dimensionless numbers do not include the spatio-temporal variations of the physical properties of products during the transformation process.
In order to bring dimensional analysis up to modern use standards, the authors provide a review of the theoretical framework which allows the principles of similarity theory to be respected in the case of processes using a material with constant or variable physical properties in the course of the transformation.
Rules to rigorously construct a semi-empirical correlation between dimensionless numbers are discussed to promote and develop chemical engineering practice. This book offers reliable, robust and relevant tools to better model transformations of matter and the interactions between product and processes using a synthetic and physical view of phenomena as well as for the dimensioning, diagnosis and control of product transformation processes, reverse engineering and scale changing. | Type de document : | Livre | Table des matières : | CHAPTER 1. OBJECTIVES AND VALUE OF DIMENSIONAL ANALYSIS
1.1. Grouping dimensional variables in the form of a set of dimensionless numbers with a precise physical sense
1.2. Constructing generic models which can be used on other scales
1.3. Reduce the number of experiments by providing a synthetic and physical view of the phenomena
1.4. A tool for carrying out processes and assisting a reverse engineering approach
CHAPTER 2. DIMENSIONAL ANALYSIS: PRINCIPLES AND METHODOLOGY
2.1. Terminology and theoretical elements
2.1.1. Physical quantities and measures. Dimensions and unit systems
2.1.2. The principle of homogeneity
2.1.3. Fundamental rules for constructing the set (or space) of dimensionless numbers associated with a physical phenomenon
2.2. From internal measures to the form of a process relationship
2.2.1. Choosing a set of internal measures suitable for the experimental program used
2.2.2. What form of mathematical relationship should be chosen to correlate the dimensionless numbers?
2.3. Configuration and operating point of a system
2.3.1. Definition of the configuration of the system and its links with internal measures
2.3.2. Graphic representation of the operating points of a system
2.3.3. Conclusion
2.4. Guided example 1: power consumption
for a Newtonian fluid in a mechanically stirred tank
2.4.1. List of relevant independent physical quantities
2.4.2. Determining the dimensions of the physical quantities
2.4.3. Application of the Vaschy–Buckingham theorem and the construction of dimensionless numbers
2.4.4. Rearrangements of dimensionless numbers
2.4.5. From internal measures to the establishment of the process relationship
2.4.6. Comments
2.4.7. Conclusion
CHAPTER 3. PRACTICAL TOOLS FOR UNDERTAKING THE DIMENSIONAL ANALYSIS PROCESS
3.1. Establishment of the list of relevant physical quantities which influence the target variable
3.1.1. Approach to adopt in order to facilitate the establishment of the list of relevant physical quantities
3.1.2. Consequences of omitting physical quantities
3.1.3. Consequences of introducing a superfluous physical quantity
3.1.4. Conclusion
3.2. Choosing the base
3.3. Some techniques for reducing the set of dimensionless numbers (configuration of the system)
3.3.1. Introduction of an intermediate variable
3.3.2. Increase in the number of fundamental dimensions
CHAPTER 4. DIMENSIONAL ANALYSIS OF PROCESSES INFLUENCED BY THE VARIABILITY OF PHYSICAL PROPERTIES
4.1. Introduction
4.1.1. Objective
4.1.2. Approach
4.2. Influence of the material function on the process relationship and material similarity
4.2.1. Definitions and notations
4.2.2. Illustrating the influence of the variability of a physical property on the target internal measure
4.2.3. A necessary condition for the application of a process relationship to different materials: material similarity
4.3. Dimensionless material functions: standard non-dimensionalization method and invariance properties
4.3.1. Influence of the reference abscissa and the non-dimensionalization method on the form of the dimensionless material function
4.3.2. Non-dimensionalization method and theory of similarity
4.3.3. Standard non-dimensionalization method
4.3.4. Standard material functions with specific properties: reference-invariant standard material functions
4.4. How to construct the π – space in the case of a process involving a material with a variable physical property
4.4.1. Determining the dimensionless numbers and/or physical quantities to add to the initial relevance list
4.4.2. Examples
4.4.3. Relevant choice of the reference abscissa
4.5. Guided example 2
4.5.1. Pseudoplastic fluid
4.5.2. Bingham fluid
CHAPTER 5. DIMENSIONAL ANALYSIS: A TOOL FOR ADDRESSING PROCESS SCALE-UP ISSUES
5.1. Conditions to satisfy to ensure complete similarity between the two scales: conservation of the operating point
5.1.1. Configuration of the system and operating points
5.1.2. Rules of similarity
5.2. Guided example 3: cooking a chicken
5.2.1. Establishing the configuration of the system
5.2.2. Analysis of the configuration of the system and similarity relationship
5.3. Guided example 4: power of a vertical impeller on an industrial scale
5.3.1. Establishing the configuration of the system
5.3.2. Analysis of the configuration of the system and similarity relationships
5.3.3. Contribution of the process relationship to the scale change
5.4. Guided example 5: emulsification process in an agitation tank
5.4.1. Determining the configuration of the system
5.4.2. Analysis of the configuration of the system and similarity relationships
5.4.3. Contribution of the process relationship in the scale change
5.5. Specific case of a scale change in a process involving a material with a variable physical property (guided example 6)
5.5.1. Preamble
5.5.2. Guided example 6: scaling of a scraped surface heat exchanger
CHAPTER 6. CASE STUDIES
6.1. Rehydration time for milk powder in a stirred tank
6.1.1. Target variable and relevance list of independent physical quantities
6.1.2. Establishing dimensionless numbers
6.1.3. From the configuration of the system to the establishment of the process relationship
6.2. Continuous foaming by whipping
6.2.1. Target variable and list of relevant independent physical quantities
6.2.2. Establishing dimensionless numbers
6.2.3. From the configuration of the system to establishing a process relationship
6.3. Fouling of a plate heat exchanger by a milk protein solution
6.3.1. Target variables and list of relevant independent physical quantities
6.3.2. Establishing dimensionless numbers
6.3.3. From configurational analysis to the process relationship
6.4. Dry mixing of powders: mixing time and power consumption
6.4.1. List of relevant physical quantities
6.4.2. Establishing dimensionless numbers
6.4.3. From the configuration of the system to establishing the process relationship: the advantage of introducing an intermediate variable
6.4.4. Analysis of the process relationship obtained
6.5. Gas–liquid mass transfer in a mechanically stirred tank containing shear-thinning fluids
6.5.1. Case study with Newtonian fluids: target variable, list of relevant independent physical quantities and the configuration of the system
6.5.2. Extension to shear-thinning fluids
6.5.3. From the configuration of the system to establishing the process relationship
6.5.4. Conclusion
6.6. Ohmic heating
6.6.1. Description of the problem
6.6.2. Target variable and relevance list of independent physical quantities
6.6.3. Establishing dimensionless numbers and the configuration of the system
6.6.4. Analytical expression of the process relationship
6.6.5. Validation of the process relationship
6.6.6. Conclusion
CONCLUSIONS
APPENDICES
APPENDIX 1: SHIFT RELATIONSHIPS BETWEEN SPACES OF DIMENSIONLESS NUMBERS
APPENDIX 2: PHYSICAL MEANING OF DIMENSIONLESS NUMBERS COMMONLY USED IN PROCESS ENGINEERING
APPENDIX 3: THE TRANSITIVITY PROPERTY OF THE STANDARD NON-DIMENSIONALIZATION METHOD AND ITS CONSEQUENCES ON THE MATHEMATICAL EXPRESSION OF REFERENCE-INVARIANT STANDARD DIMENSIONLESS MATERIAL FUNCTIONS (RSDMFS)
APPENDIX 4: CASES WHERE THE ANALYTICAL EXPRESSION OF THE MATERIAL FUNCTION IS KNOWN
APPENDIX 5: CASES WHERE THERE IS NO KNOWN ANALYTICAL EXPRESSION OF THE MATERIAL FUNCTION
APPENDIX 6: RELEVANT CHOICE OF THE REFERENCE ABSCISSA FOR NON-NEWTONIAN FLUIDS
BIBLIOGRAPHY
INDEX | Permalien de la notice : | https://infodoc.agroparistech.fr/index.php?lvl=notice_display&id=182724 |
Dimensional analysis of food processes [texte imprimé] / Guillaume Delaplace ; Karine Loubière ; Fabrice Ducept ; Romain Jeantet . - London : ISTE Press Ltd : Oxford : Elsevier, 2015 . - 1 vol. (XVIII-337 p.) : ill., couv. ill. en coul. ; 24 cm. - ( Modeling and Control of Food Processes Set) . ISBN : 978-1-78548-040-9 Bibliogr. p.329-333. Index. Annexes Langues : Anglais ( eng) Catégories : | Liste Plan de classement 16.12 (GENIE DES PROCEDES) [Classement Massy] Thésaurus Agro-alimentaire GENIE DES PROCEDES ; MODELISATION ; ANALYSE MULTIDIMENSIONNELLE ; GENIE ALIMENTAIRE
| Résumé : | This book is dedicated to the modeling of food processing using dimensional analysis. Dimensional analysis has evolved very little since it was founded and first applied to chemical engineering. Most semi-empirical correlations between dimensionless numbers do not include the spatio-temporal variations of the physical properties of products during the transformation process.
In order to bring dimensional analysis up to modern use standards, the authors provide a review of the theoretical framework which allows the principles of similarity theory to be respected in the case of processes using a material with constant or variable physical properties in the course of the transformation.
Rules to rigorously construct a semi-empirical correlation between dimensionless numbers are discussed to promote and develop chemical engineering practice. This book offers reliable, robust and relevant tools to better model transformations of matter and the interactions between product and processes using a synthetic and physical view of phenomena as well as for the dimensioning, diagnosis and control of product transformation processes, reverse engineering and scale changing. | Type de document : | Livre | Table des matières : | CHAPTER 1. OBJECTIVES AND VALUE OF DIMENSIONAL ANALYSIS
1.1. Grouping dimensional variables in the form of a set of dimensionless numbers with a precise physical sense
1.2. Constructing generic models which can be used on other scales
1.3. Reduce the number of experiments by providing a synthetic and physical view of the phenomena
1.4. A tool for carrying out processes and assisting a reverse engineering approach
CHAPTER 2. DIMENSIONAL ANALYSIS: PRINCIPLES AND METHODOLOGY
2.1. Terminology and theoretical elements
2.1.1. Physical quantities and measures. Dimensions and unit systems
2.1.2. The principle of homogeneity
2.1.3. Fundamental rules for constructing the set (or space) of dimensionless numbers associated with a physical phenomenon
2.2. From internal measures to the form of a process relationship
2.2.1. Choosing a set of internal measures suitable for the experimental program used
2.2.2. What form of mathematical relationship should be chosen to correlate the dimensionless numbers?
2.3. Configuration and operating point of a system
2.3.1. Definition of the configuration of the system and its links with internal measures
2.3.2. Graphic representation of the operating points of a system
2.3.3. Conclusion
2.4. Guided example 1: power consumption
for a Newtonian fluid in a mechanically stirred tank
2.4.1. List of relevant independent physical quantities
2.4.2. Determining the dimensions of the physical quantities
2.4.3. Application of the Vaschy–Buckingham theorem and the construction of dimensionless numbers
2.4.4. Rearrangements of dimensionless numbers
2.4.5. From internal measures to the establishment of the process relationship
2.4.6. Comments
2.4.7. Conclusion
CHAPTER 3. PRACTICAL TOOLS FOR UNDERTAKING THE DIMENSIONAL ANALYSIS PROCESS
3.1. Establishment of the list of relevant physical quantities which influence the target variable
3.1.1. Approach to adopt in order to facilitate the establishment of the list of relevant physical quantities
3.1.2. Consequences of omitting physical quantities
3.1.3. Consequences of introducing a superfluous physical quantity
3.1.4. Conclusion
3.2. Choosing the base
3.3. Some techniques for reducing the set of dimensionless numbers (configuration of the system)
3.3.1. Introduction of an intermediate variable
3.3.2. Increase in the number of fundamental dimensions
CHAPTER 4. DIMENSIONAL ANALYSIS OF PROCESSES INFLUENCED BY THE VARIABILITY OF PHYSICAL PROPERTIES
4.1. Introduction
4.1.1. Objective
4.1.2. Approach
4.2. Influence of the material function on the process relationship and material similarity
4.2.1. Definitions and notations
4.2.2. Illustrating the influence of the variability of a physical property on the target internal measure
4.2.3. A necessary condition for the application of a process relationship to different materials: material similarity
4.3. Dimensionless material functions: standard non-dimensionalization method and invariance properties
4.3.1. Influence of the reference abscissa and the non-dimensionalization method on the form of the dimensionless material function
4.3.2. Non-dimensionalization method and theory of similarity
4.3.3. Standard non-dimensionalization method
4.3.4. Standard material functions with specific properties: reference-invariant standard material functions
4.4. How to construct the π – space in the case of a process involving a material with a variable physical property
4.4.1. Determining the dimensionless numbers and/or physical quantities to add to the initial relevance list
4.4.2. Examples
4.4.3. Relevant choice of the reference abscissa
4.5. Guided example 2
4.5.1. Pseudoplastic fluid
4.5.2. Bingham fluid
CHAPTER 5. DIMENSIONAL ANALYSIS: A TOOL FOR ADDRESSING PROCESS SCALE-UP ISSUES
5.1. Conditions to satisfy to ensure complete similarity between the two scales: conservation of the operating point
5.1.1. Configuration of the system and operating points
5.1.2. Rules of similarity
5.2. Guided example 3: cooking a chicken
5.2.1. Establishing the configuration of the system
5.2.2. Analysis of the configuration of the system and similarity relationship
5.3. Guided example 4: power of a vertical impeller on an industrial scale
5.3.1. Establishing the configuration of the system
5.3.2. Analysis of the configuration of the system and similarity relationships
5.3.3. Contribution of the process relationship to the scale change
5.4. Guided example 5: emulsification process in an agitation tank
5.4.1. Determining the configuration of the system
5.4.2. Analysis of the configuration of the system and similarity relationships
5.4.3. Contribution of the process relationship in the scale change
5.5. Specific case of a scale change in a process involving a material with a variable physical property (guided example 6)
5.5.1. Preamble
5.5.2. Guided example 6: scaling of a scraped surface heat exchanger
CHAPTER 6. CASE STUDIES
6.1. Rehydration time for milk powder in a stirred tank
6.1.1. Target variable and relevance list of independent physical quantities
6.1.2. Establishing dimensionless numbers
6.1.3. From the configuration of the system to the establishment of the process relationship
6.2. Continuous foaming by whipping
6.2.1. Target variable and list of relevant independent physical quantities
6.2.2. Establishing dimensionless numbers
6.2.3. From the configuration of the system to establishing a process relationship
6.3. Fouling of a plate heat exchanger by a milk protein solution
6.3.1. Target variables and list of relevant independent physical quantities
6.3.2. Establishing dimensionless numbers
6.3.3. From configurational analysis to the process relationship
6.4. Dry mixing of powders: mixing time and power consumption
6.4.1. List of relevant physical quantities
6.4.2. Establishing dimensionless numbers
6.4.3. From the configuration of the system to establishing the process relationship: the advantage of introducing an intermediate variable
6.4.4. Analysis of the process relationship obtained
6.5. Gas–liquid mass transfer in a mechanically stirred tank containing shear-thinning fluids
6.5.1. Case study with Newtonian fluids: target variable, list of relevant independent physical quantities and the configuration of the system
6.5.2. Extension to shear-thinning fluids
6.5.3. From the configuration of the system to establishing the process relationship
6.5.4. Conclusion
6.6. Ohmic heating
6.6.1. Description of the problem
6.6.2. Target variable and relevance list of independent physical quantities
6.6.3. Establishing dimensionless numbers and the configuration of the system
6.6.4. Analytical expression of the process relationship
6.6.5. Validation of the process relationship
6.6.6. Conclusion
CONCLUSIONS
APPENDICES
APPENDIX 1: SHIFT RELATIONSHIPS BETWEEN SPACES OF DIMENSIONLESS NUMBERS
APPENDIX 2: PHYSICAL MEANING OF DIMENSIONLESS NUMBERS COMMONLY USED IN PROCESS ENGINEERING
APPENDIX 3: THE TRANSITIVITY PROPERTY OF THE STANDARD NON-DIMENSIONALIZATION METHOD AND ITS CONSEQUENCES ON THE MATHEMATICAL EXPRESSION OF REFERENCE-INVARIANT STANDARD DIMENSIONLESS MATERIAL FUNCTIONS (RSDMFS)
APPENDIX 4: CASES WHERE THE ANALYTICAL EXPRESSION OF THE MATERIAL FUNCTION IS KNOWN
APPENDIX 5: CASES WHERE THERE IS NO KNOWN ANALYTICAL EXPRESSION OF THE MATERIAL FUNCTION
APPENDIX 6: RELEVANT CHOICE OF THE REFERENCE ABSCISSA FOR NON-NEWTONIAN FLUIDS
BIBLIOGRAPHY
INDEX | Permalien de la notice : | https://infodoc.agroparistech.fr/index.php?lvl=notice_display&id=182724 |
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