Описание: This book provides a complete guide on tools and techniques for modeling of supercritical and subcritical fluid extraction (SSFE) processes and phenomena. It provides details for SSFE from managing the experiments to modeling and optimization. It includes the fundamentals of SSFE as well as the necessary experimental techniques to validate the models. The optimization section includes the use of process simulators, conventional optimization techniques and state-of-the-art genetic algorithm methods. Numerous practical examples and case studies on the application of the modeling and optimization techniques on the SSFE processes are also provided. Detailed thermodynamic modeling with and without co-solvent and non equilibrium system modeling is another feature of the book.
The book consists of seven chapters. Chapter 1 presents an overview of the field of supercritical and subcritical fluid extraction (SSFE) and their importance to food, cosmetic and pharmaceutical industries. Chapter 2 describes the concepts and methodologies for modeling, simulation as well as optimization. It presents conservation laws related to SFE traditional first principle modeling and optimization techniques, statistical modeling as well as advanced artificial intelligence (AI) techniques like genetic algorithm, fuzzy logic and artificial neural network (ANN). The characteristics and physical properties of palm oil as the most referred solute in the book, and descriptions of some existing palm oil industrial processes are presented in Chapter 3. In Chapter 4, the first principle methodology is applied for modeling of properties of palm oil components, mixtures and for the supercritical fluid extraction of palm oil components. Modeling applications involving advanced techniques such as AI, ANN and fuzzy logics and ANFIS are discussed in Chapter 5. Next, Chapter 6 describes experimental design concepts and procedures as well as statistical optimization techniques involving SSFE processes. Finally, optimisation of SSFE using first principle modeling and other advanced techniques are presented in Chapter 7.
Название: Modeling of Steelmaking Processes ISBN: 1420062433 ISBN-13(EAN): 9781420062434 Издательство: Taylor&Francis Рейтинг: Цена: 28327.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addresses fundamental principles of physical and mathematical modeling in steelmaking processes. This book presents an overview of steelmaking, the relevance of modeling and measurements, the evolution of steelmaking, and modern technology. It discusses issues such as environmental emissions, recycling, and product development and quality.
Автор: Yakimov Название: Thermal Protection Modeling of Hypersonic Flying Apparatus ISBN: 3319782169 ISBN-13(EAN): 9783319782164 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is devoted to studies of unsteady heat and mass exchange processes taking into account thermochemical destruction of thermal protective materials, research of transpiration cooling systems, thermal protection of composite materials exposed to low-energy disturbances, as well as the numerical solution of heat and mass transfer of the exchange. It proposes several mathematical models of passive and active thermal protection systems with regard to factors such as surface ablation, surface roughness, phase transition of a liquid in porous materials, rotation of the body around its longitudinal axis, and exposure to low-energy disturbances. The author studies the possibilities to control thermochemical destruction and heat mass exchange processes in transpiration cooling systems exposed to low-energy disturbances. The numerical analysis of the heat and mass exchange process in carbon plastics under repeated impulse action is also presented. The numerical solutions of problems are compared with the known experimental data. The book is intended for specialists in the field of thermal protection and heat mass exchange, as well as graduate and undergraduates in physics and mathematics.
Автор: Shouting Gao; Xiaofan Li Название: Cloud-Resolving Modeling of Convective Processes ISBN: 9048178290 ISBN-13(EAN): 9789048178292 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Clouds and cloud systems and their interactions with larger scales of motion, radiation, and the Earth's surface are extremely important parts of weather and climate systems. Their treatment in weather forecast and climate models is a significant source of errors and uncertainty. As computer power increases, it is beginning to be possible to explicitly resolve cloud and precipitation processes in these models, presenting opportunities for improving precipitation forecasts and larger-scale phenomena such as tropical cyclones which depend critically on cloud and precipitation physics.
This book by Professor Shouting Gao of the Institute of Atmospheric Physics in Beijing and Xiaofan Li of NOAA's National Environmental Satellite Data and Information Services (NESDIS) presents an update and review of results of high-resolution, mostly two-dimensional models of clouds and precipitation and their interactions with larger scales of motion and the Earth's surface. It provides a thorough description of cloud and precipitation physics, including basic governing equations and related physics, such as phase changes of water, radiation and mixing. Model results are compared with observations from the 1992-93 Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment (TOGA COARE) experiment. The importance of the ocean to tropical convective systems is clearly shown here in the numerical results of simulations with their air-sea coupled modeling system. While the focus is on tropical convection, the methodology and applicability can be extended to cloud and precipitation processes elsewhere.
The results described in this well-written book form a solid foundation for future high-resolution model weather forecasts and climate simulations that resolve clouds explicitly in three dimensions--a future that has great promise for the understanding and prediction of weather and climate for the great benefit of society.
Автор: Manabu Iguchi; Olusegun J. Ilegbusi Название: Modeling Multiphase Materials Processes ISBN: 1489981845 ISBN-13(EAN): 9781489981844 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes the methodology and application of physical and mathematical modeling to multi-phase flow phenomena in materials processing. The focus is on systems involving gas-liquid interaction, the most prevalent in current metallurgical processes.
Автор: Stefan Hiermaier Название: Predictive Modeling of Dynamic Processes ISBN: 1489979263 ISBN-13(EAN): 9781489979261 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This work provides an overview of hydrocode technology, applicable to a variety of industries and areas of engineering design. It successfully blends crash simulations with hydrocode technology, and offers an explanation of the fundamental code components.
Автор: Stefan Hiermaier Название: Predictive Modeling of Dynamic Processes ISBN: 1441907262 ISBN-13(EAN): 9781441907264 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides an overview of hydrocode technology, applicable to a variety of industries and areas of engineering design. This book covers automotive crash, blast impact, and hypervelocity impact phenomena, and offers an explanation of the fundamental code components. It explains the specific requirements pertaining to each predictive hydrocode.
Автор: Gunnar Stiesch Название: Modeling Engine Spray and Combustion Processes ISBN: 3642056296 ISBN-13(EAN): 9783642056291 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The utilization of mathematical models to numerically describe the performance of internal combustion engines is of great significance in the development of new and improved engines.
Описание: This book treats modeling and simulation in a simple way, that builds on the existing knowledge and intuition of students. They will learn how to build a model and solve it using Excel.Most chemical engineering students feel a shiver down the spine when they see a set of complex mathematical equations generated from the modeling of a chemical engineering system. This is because they usually do not understand how to achieve this mathematical model, or they do not know how to solve the equations system without spending a lot of time and effort.Trying to understand how to generate a set of mathematical equations to represent a physical system (to model) and solve these equations (to simulate) is not a simple task. A model, most of the time, takes into account all phenomena studied during a Chemical Engineering course. In the same way, there is a multitude of numerical methods that can be used to solve the same set of equations generated from the modeling, and many different computational languages can be adopted to implement the numerical methods. As a consequence of this comprehensiveness and combinatorial explosion of possibilities, most books that deal with this subject are very extensive and embracing, making need for a lot of time and effort to go through this subject. It is expected that with this book the chemical engineering student and the future chemical engineer feel motivated to solve different practical problems involving chemical processes, knowing they can do that in an easy and fast way, with no need of expensive software.
Автор: Francisco Chinesta; El?as Cueto Название: PGD-Based Modeling of Materials, Structures and Processes ISBN: 3319348361 ISBN-13(EAN): 9783319348360 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
1 Introduction.- 1.1 Recurrent issues in numerical simulation.- 1.2 Model reduction: information versus relevant information.- 1.3 PGD at a glance.- 1.4 Revisiting the simulation challenges.- 1.5 A brief state of the art on PGD-based model order reduction.- 2 Multiscale modelling.- 2.1 From quantum mechanics to kinetic theory.- 2.2 Advanced solvers for multi-dimensional models.- 2.3 Numerical examples.- 2.4 Conclusions.- 3 Homogenization.- 3.1 Homogenization of linear heterogenous models.- 3.2 Non-concurrent nonlinear homogenization.- 3.3 Numerical examples.- 3.4 Conclusions.- 4 Coupled models.- 4.1 Efficient coupling of global and local models.- 4.2 Fully globalized local models.- 4.3 Heterogeneous time integration.- 4.4 Numerical example.- 4.5 Discussion.- 5 Parametric models in evolving domains.- 5.1 Evolving domains issues.- 5.2 PGD in evolving domains.- 5.3 Separated representation constructor.- 5.4 Numerical test.- 5.5 Towards parametric modeling in evolving domains.- 5.6 Numerical test involving parametric modeling.- 5.7 Conclusions.- 6 Space separation.- 6.1 In-plane/out-of-plane separated representation.- 6.2 Laminates.- 6.3 Conclusions.- 7 Process optimization.- 7.1 Parametric boundary conditions.- 7.2 Parametric modeling of pultrusion.- 7.3 Optimization strategy.- 7.4 Conclusion 8 Shape optimization.- 8.1 Introduction.- 8.2 Geometrical parameters as extra-coordinates.- 8.3 Numerical results.- 8.4 Conclusions.- 9 DDDAS.- 9.1 Introduction to DDDAS.- 9.2 PGD solution of a flowing process.- 9.3 Simulating a breakdown scenario.- 9.4 Post-processing in a smartphone.- 9.5 Conclusions.- 10 Inverse analysis.- 10.1 PGD based parameter identification.- 10.2 PGD based Cauchy's problem.- 10.3 Parameter identification examples.- 10.4 Cauchy's problem example.- 10.5 Conclusions.- 11 Tape placement.- 11.1 Parametric modeling.- 11.2 ATP thermal model.- 11.3 ATP mechanical modeling.- 11.4 Numerical results.- 11.5 Conclusions.- 12 Augmented learning.- 12.1 Towards augmented learning.- 12.2 Examples of augmented learning.- 12.3 Conclusions.- References.- Index.
Автор: Francisco Chinesta; El?as Cueto Название: PGD-Based Modeling of Materials, Structures and Processes ISBN: 331906181X ISBN-13(EAN): 9783319061818 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
1 Introduction.- 1.1 Recurrent issues in numerical simulation.- 1.2 Model reduction: information versus relevant information.- 1.3 PGD at a glance.- 1.4 Revisiting the simulation challenges.- 1.5 A brief state of the art on PGD-based model order reduction.- 2 Multiscale modelling.- 2.1 From quantum mechanics to kinetic theory.- 2.2 Advanced solvers for multi-dimensional models.- 2.3 Numerical examples.- 2.4 Conclusions.- 3 Homogenization.- 3.1 Homogenization of linear heterogenous models.- 3.2 Non-concurrent nonlinear homogenization.- 3.3 Numerical examples.- 3.4 Conclusions.- 4 Coupled models.- 4.1 Efficient coupling of global and local models.- 4.2 Fully globalized local models.- 4.3 Heterogeneous time integration.- 4.4 Numerical example.- 4.5 Discussion.- 5 Parametric models in evolving domains.- 5.1 Evolving domains issues.- 5.2 PGD in evolving domains.- 5.3 Separated representation constructor.- 5.4 Numerical test.- 5.5 Towards parametric modeling in evolving domains.- 5.6 Numerical test involving parametric modeling.- 5.7 Conclusions.- 6 Space separation.- 6.1 In-plane/out-of-plane separated representation.- 6.2 Laminates.- 6.3 Conclusions.- 7 Process optimization.- 7.1 Parametric boundary conditions.- 7.2 Parametric modeling of pultrusion.- 7.3 Optimization strategy.- 7.4 Conclusion 8 Shape optimization.- 8.1 Introduction.- 8.2 Geometrical parameters as extra-coordinates.- 8.3 Numerical results.- 8.4 Conclusions.- 9 DDDAS.- 9.1 Introduction to DDDAS.- 9.2 PGD solution of a flowing process.- 9.3 Simulating a breakdown scenario.- 9.4 Post-processing in a smartphone.- 9.5 Conclusions.- 10 Inverse analysis.- 10.1 PGD based parameter identification.- 10.2 PGD based Cauchy's problem.- 10.3 Parameter identification examples.- 10.4 Cauchy's problem example.- 10.5 Conclusions.- 11 Tape placement.- 11.1 Parametric modeling.- 11.2 ATP thermal model.- 11.3 ATP mechanical modeling.- 11.4 Numerical results.- 11.5 Conclusions.- 12 Augmented learning.- 12.1 Towards augmented learning.- 12.2 Examples of augmented learning.- 12.3 Conclusions.- References.- Index.
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