Author: Geoffrey Hewitt
Publisher: Elsevier
ISBN: 1483285235
Category : Technology & Engineering
Languages : en
Pages : 327
Book Description
Annular Two-Phase Flow presents the wide range of industrial applications of annular two-phase flow regimes. This book discusses the fluid dynamics and heat transfer aspects of the flow pattern. Organized into 12 chapters, this book begins with an overview of the classification of the various types of interface distribution observed in practice. This text then examines the various regimes of two-phase flow with emphasis on the regions of occurrence of the annular flow regime. Other chapters consider the single momentum and energy balances, which illustrate the differences and analogies between single- and two-phase flows. This book discusses as well the simple modes for annular flow with consideration to the calculation of the profile of shear stress in the liquid film. The final chapter deals with the techniques that are developed for the measurement of flow pattern, entrainment, and film thickness. This book is a valuable resource for chemical engineers.
Annular Two-Phase Flow
Author: Geoffrey Hewitt
Publisher: Elsevier
ISBN: 1483285235
Category : Technology & Engineering
Languages : en
Pages : 327
Book Description
Annular Two-Phase Flow presents the wide range of industrial applications of annular two-phase flow regimes. This book discusses the fluid dynamics and heat transfer aspects of the flow pattern. Organized into 12 chapters, this book begins with an overview of the classification of the various types of interface distribution observed in practice. This text then examines the various regimes of two-phase flow with emphasis on the regions of occurrence of the annular flow regime. Other chapters consider the single momentum and energy balances, which illustrate the differences and analogies between single- and two-phase flows. This book discusses as well the simple modes for annular flow with consideration to the calculation of the profile of shear stress in the liquid film. The final chapter deals with the techniques that are developed for the measurement of flow pattern, entrainment, and film thickness. This book is a valuable resource for chemical engineers.
Publisher: Elsevier
ISBN: 1483285235
Category : Technology & Engineering
Languages : en
Pages : 327
Book Description
Annular Two-Phase Flow presents the wide range of industrial applications of annular two-phase flow regimes. This book discusses the fluid dynamics and heat transfer aspects of the flow pattern. Organized into 12 chapters, this book begins with an overview of the classification of the various types of interface distribution observed in practice. This text then examines the various regimes of two-phase flow with emphasis on the regions of occurrence of the annular flow regime. Other chapters consider the single momentum and energy balances, which illustrate the differences and analogies between single- and two-phase flows. This book discusses as well the simple modes for annular flow with consideration to the calculation of the profile of shear stress in the liquid film. The final chapter deals with the techniques that are developed for the measurement of flow pattern, entrainment, and film thickness. This book is a valuable resource for chemical engineers.
Two-phase (gas-liquid) System: Heat Transfer and Hydraulics
Author: Robert R. Kepple
Publisher:
ISBN:
Category : Gas
Languages : en
Pages : 440
Book Description
A systematic search for the references appearing in this bibliography was made in the following for the period 1950 to 1962: Nuclear Science Abstracts; Chemical Abstracts; Science Abstracts, Section A; Engineering Index; Applied Mechanics Review. In addition, Chemical and Engineering Progress and Dissertation abstracts were consulted for theses, and the references in many bibliographies already prepared on this subject were checked. Many references appearing prior to this period have been included because of their importance to the subject.
Publisher:
ISBN:
Category : Gas
Languages : en
Pages : 440
Book Description
A systematic search for the references appearing in this bibliography was made in the following for the period 1950 to 1962: Nuclear Science Abstracts; Chemical Abstracts; Science Abstracts, Section A; Engineering Index; Applied Mechanics Review. In addition, Chemical and Engineering Progress and Dissertation abstracts were consulted for theses, and the references in many bibliographies already prepared on this subject were checked. Many references appearing prior to this period have been included because of their importance to the subject.
Heat Transfer & Fluid Flow Digest
Reactor Technology
Nuclear Science Abstracts
Scientific and Technical Aerospace Reports
Applied Mechanics Reviews
Energy Research Abstracts
Machine Learning and Flow Assurance in Oil and Gas Production
Author: Bhajan Lal
Publisher: Springer Nature
ISBN: 3031242319
Category : Technology & Engineering
Languages : en
Pages : 179
Book Description
This book is useful to flow assurance engineers, students, and industries who wish to be flow assurance authorities in the twenty-first-century oil and gas industry. The use of digital or artificial intelligence methods in flow assurance has increased recently to achieve fast results without any thorough training effectively. Generally, flow assurance covers all risks associated with maintaining the flow of oil and gas during any stage in the petroleum industry. Flow assurance in the oil and gas industry covers the anticipation, limitation, and/or prevention of hydrates, wax, asphaltenes, scale, and corrosion during operation. Flow assurance challenges mostly lead to stoppage of production or plugs, damage to pipelines or production facilities, economic losses, and in severe cases blowouts and loss of human lives. A combination of several chemical and non-chemical techniques is mostly used to prevent flow assurance issues in the industry. However, the use of models to anticipate, limit, and/or prevent flow assurance problems is recommended as the best and most suitable practice. The existing proposed flow assurance models on hydrates, wax, asphaltenes, scale, and corrosion management are challenged with accuracy and precision. They are not also limited by several parametric assumptions. Recently, machine learning methods have gained much attention as best practices for predicting flow assurance issues. Examples of these machine learning models include conventional approaches such as artificial neural network, support vector machine (SVM), least square support vector machine (LSSVM), random forest (RF), and hybrid models. The use of machine learning in flow assurance is growing, and thus, relevant knowledge and guidelines on their application methods and effectiveness are needed for academic, industrial, and research purposes. In this book, the authors focus on the use and abilities of various machine learning methods in flow assurance. Initially, basic definitions and use of machine learning in flow assurance are discussed in a broader scope within the oil and gas industry. The rest of the chapters discuss the use of machine learning in various flow assurance areas such as hydrates, wax, asphaltenes, scale, and corrosion. Also, the use of machine learning in practical field applications is discussed to understand the practical use of machine learning in flow assurance.
Publisher: Springer Nature
ISBN: 3031242319
Category : Technology & Engineering
Languages : en
Pages : 179
Book Description
This book is useful to flow assurance engineers, students, and industries who wish to be flow assurance authorities in the twenty-first-century oil and gas industry. The use of digital or artificial intelligence methods in flow assurance has increased recently to achieve fast results without any thorough training effectively. Generally, flow assurance covers all risks associated with maintaining the flow of oil and gas during any stage in the petroleum industry. Flow assurance in the oil and gas industry covers the anticipation, limitation, and/or prevention of hydrates, wax, asphaltenes, scale, and corrosion during operation. Flow assurance challenges mostly lead to stoppage of production or plugs, damage to pipelines or production facilities, economic losses, and in severe cases blowouts and loss of human lives. A combination of several chemical and non-chemical techniques is mostly used to prevent flow assurance issues in the industry. However, the use of models to anticipate, limit, and/or prevent flow assurance problems is recommended as the best and most suitable practice. The existing proposed flow assurance models on hydrates, wax, asphaltenes, scale, and corrosion management are challenged with accuracy and precision. They are not also limited by several parametric assumptions. Recently, machine learning methods have gained much attention as best practices for predicting flow assurance issues. Examples of these machine learning models include conventional approaches such as artificial neural network, support vector machine (SVM), least square support vector machine (LSSVM), random forest (RF), and hybrid models. The use of machine learning in flow assurance is growing, and thus, relevant knowledge and guidelines on their application methods and effectiveness are needed for academic, industrial, and research purposes. In this book, the authors focus on the use and abilities of various machine learning methods in flow assurance. Initially, basic definitions and use of machine learning in flow assurance are discussed in a broader scope within the oil and gas industry. The rest of the chapters discuss the use of machine learning in various flow assurance areas such as hydrates, wax, asphaltenes, scale, and corrosion. Also, the use of machine learning in practical field applications is discussed to understand the practical use of machine learning in flow assurance.