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This book illustrates the computational framework based on knowledge of flow and mass transfer together with optimization techniques to solve problems relevant to micromixing technology. The authors provide a detailed analysis of the different numerical techniques applied to the design of micromixers. Flow and mixing analysis is based on both the Eulerian and Lagrangian approaches; relative advantages and disadvantages of the two methods and suitability to different types of mixing problems are analysed. The book also discusses the various facets of numerical schemes subjected to discretization errors and computational grid requirements. Since a large number of studies are based on commercial computational fluid dynamics (CFD) packages, relevant details of these packages to the mixing problem using them are presented. Numerical optimization techniques coupled with CFD analysis of flow and mixing have proved to be an important tool for micromixers design, and therefore, are an important part of the book. These techniques are presented briefly, and focus is on surrogate modeling and optimization applied to design of micromixers.
Fluid mechanics --- Matter physics --- Chemistry of complexes --- complexen (chemie) --- materialen (technologie) --- ingenieurswetenschappen --- mechanica --- vloeistoffen
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This book illustrates the computational framework based on knowledge of flow and mass transfer together with optimization techniques to solve problems relevant to micromixing technology. The authors provide a detailed analysis of the different numerical techniques applied to the design of micromixers. Flow and mixing analysis is based on both the Eulerian and Lagrangian approaches; relative advantages and disadvantages of the two methods and suitability to different types of mixing problems are analysed. The book also discusses the various facets of numerical schemes subjected to discretization errors and computational grid requirements. Since a large number of studies are based on commercial computational fluid dynamics (CFD) packages, relevant details of these packages to the mixing problem using them are presented. Numerical optimization techniques coupled with CFD analysis of flow and mixing have proved to be an important tool for micromixers design, and therefore, are an important part of the book. These techniques are presented briefly, and focus is on surrogate modeling and optimization applied to design of micromixers.
Amorphous substances. --- Complex fluids. --- Fluid mechanics. --- Fluids. --- Soft and Granular Matter, Complex Fluids and Microfluidics. --- Engineering Fluid Dynamics. --- Fluid- and Aerodynamics. --- Hydraulics --- Mechanics --- Physics --- Hydrostatics --- Permeability --- Hydromechanics --- Continuum mechanics --- Complex liquids --- Fluids, Complex --- Amorphous substances --- Liquids --- Soft condensed matter --- Mixing. --- Flow chemistry. --- Mass transfer. --- Mass transport (Physics) --- Thermodynamics --- Transport theory --- Chemical processes --- Fluid dynamics --- Blending --- Chemical engineering --- Hydrodynamics
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Fluid mechanics --- Matter physics --- Chemistry of complexes --- complexen (chemie) --- materialen (technologie) --- ingenieurswetenschappen --- mechanica --- vloeistoffen
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Micro-total analysis systems and lab-on-a-chip platforms are widely used for sample preparation and analysis, drug delivery, and biological and chemical syntheses. A micromixer is an important component in these applications. Rapid and efficient mixing is a challenging task in the design and development of micromixers. The flow in micromixers is laminar, and, thus, the mixing is primarily dominated by diffusion. Recently, diverse techniques have been developed to promote mixing by enlarging the interfacial area between the fluids or by increasing the residential time of fluids in the micromixer. Based on their mixing mechanism, micromixers are classified into two types: active and passive. Passive micromixers are easy to fabricate and generally use geometry modification to cause chaotic advection or lamination to promote the mixing of the fluid samples, unlike active micromixers, which use moving parts or some external agitation/energy for the mixing. Many researchers have studied various geometries to design efficient passive micromixers. Recently, numerical optimization techniques based on computational fluid dynamic analysis have been proven to be efficient tools in the design of micromixers. The current Special Issue covers new mechanisms, design, numerical and/or experimental mixing analysis, and design optimization of various passive micromixers.
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Micro-total analysis systems and lab-on-a-chip platforms are widely used for sample preparation and analysis, drug delivery, and biological and chemical syntheses. A micromixer is an important component in these applications. Rapid and efficient mixing is a challenging task in the design and development of micromixers. The flow in micromixers is laminar, and, thus, the mixing is primarily dominated by diffusion. Recently, diverse techniques have been developed to promote mixing by enlarging the interfacial area between the fluids or by increasing the residential time of fluids in the micromixer. Based on their mixing mechanism, micromixers are classified into two types: active and passive. Passive micromixers are easy to fabricate and generally use geometry modification to cause chaotic advection or lamination to promote the mixing of the fluid samples, unlike active micromixers, which use moving parts or some external agitation/energy for the mixing. Many researchers have studied various geometries to design efficient passive micromixers. Recently, numerical optimization techniques based on computational fluid dynamic analysis have been proven to be efficient tools in the design of micromixers. The current Special Issue covers new mechanisms, design, numerical and/or experimental mixing analysis, and design optimization of various passive micromixers.
Choose an application
Micro-total analysis systems and lab-on-a-chip platforms are widely used for sample preparation and analysis, drug delivery, and biological and chemical syntheses. A micromixer is an important component in these applications. Rapid and efficient mixing is a challenging task in the design and development of micromixers. The flow in micromixers is laminar, and, thus, the mixing is primarily dominated by diffusion. Recently, diverse techniques have been developed to promote mixing by enlarging the interfacial area between the fluids or by increasing the residential time of fluids in the micromixer. Based on their mixing mechanism, micromixers are classified into two types: active and passive. Passive micromixers are easy to fabricate and generally use geometry modification to cause chaotic advection or lamination to promote the mixing of the fluid samples, unlike active micromixers, which use moving parts or some external agitation/energy for the mixing. Many researchers have studied various geometries to design efficient passive micromixers. Recently, numerical optimization techniques based on computational fluid dynamic analysis have been proven to be efficient tools in the design of micromixers. The current Special Issue covers new mechanisms, design, numerical and/or experimental mixing analysis, and design optimization of various passive micromixers.
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