Mohamed F. El-Amin – författare
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6 produkter
6 produkter
Häftad, Engelska, 2023
1 938 kr
Skickas inom 10-15 vardagar
Numerical Modeling of Nanoparticle Transport in Porous Media: MATLAB/PYTHON Approach focuses on modeling and numerical aspects of nanoparticle transport within single- and two-phase flow in porous media. The book discusses modeling development, dimensional analysis, numerical solutions and convergence analysis. Actual types of porous media have been considered, including heterogeneous, fractured, and anisotropic. Moreover, different interactions with nanoparticles are studied, such as magnetic nanoparticles, ferrofluids and polymers. Finally, several machine learning techniques are implemented to predict nanoparticle transport in porous media. This book provides a complete full reference in mathematical modeling and numerical aspects of nanoparticle transport in porous media.
It is an important reference source for engineers, mathematicians, and materials scientists who are looking to increase their understanding of modeling, simulation, and analysis at the nanoscale.
Explains the major simulation models and numerical techniques used for predicting nanoscale transport phenomena Provides MATLAB codes for most of the numerical simulation and Python codes for machine learning calculations Uses examples and results to illustrate each model type to the reader Assesses major application areas for each model type
E-bok
Engelska, 20232 662 kr
Läs direkt efter köp
Numerical Modeling of Nanoparticle Transport in Porous Media: MATLAB/PYTHON Approach focuses on modeling and numerical aspects of nanoparticle transport within single- and two-phase flow in porous media. The book discusses modeling development, dimensional analysis, numerical solutions and convergence analysis. Actual types of porous media have been considered, including heterogeneous, fractured, and anisotropic. Moreover, different interactions with nanoparticles are studied, such as magnetic nanoparticles, ferrofluids and polymers. Finally, several machine learning techniques are implemented to predict nanoparticle transport in porous media. This book provides a complete full reference in mathematical modeling and numerical aspects of nanoparticle transport in porous media.It is an important reference source for engineers, mathematicians, and materials scientists who are looking to increase their understanding of modeling, simulation, and analysis at the nanoscale.- Explains the major simulation models and numerical techniques used for predicting nanoscale transport phenomena- Provides MATLAB codes for most of the numerical simulation and Python codes for machine learning calculations- Uses examples and results to illustrate each model type to the reader- Assesses major application areas for each model type
Häftad, Engelska, 2025
2 063 kr
Skickas inom 10-15 vardagar
Fractional Modeling of Fluid Flow and Transport Phenomena focuses on mathematical and numerical aspects of fractional-order modeling in fluid flow and transport phenomena. The book covers fundamental concepts, advancements, and practical applications, including modeling developments, numerical solutions, and convergence analysis for both time and space fractional order models. Various types of flows are explored, such as single- and multi-phase flows in porous media, involving different fluid types like Newtonian, non-Newtonian, nanofluids, and ferrofluids. This book serves as a comprehensive reference on fractional-order modeling of fluid flow and transport phenomena, offering a single resource that is currently unavailable.Fractional-order modeling has gained traction in engineering and science, particularly in fluid dynamics and transport phenomena. However, its mathematical and numerical advancements have progressed relatively slowly compared to other aspects. Therefore, this book emphasizes the fractional-order modeling of fluid flow and transport phenomena to bridge this gap. Each chapter in the book delves into a specific topic closely related to the others, ensuring a cohesive and self-contained structure.Covers advancements in fractional-order fluid flow problemsServes as a comprehensive reference on fractional-order modeling of fluid flow and transport phenomenaDemonstrates the topic with different aspects, including modeling, mathematical, computational, and physical commentary
E-bok
Engelska, 20252 611 kr
Läs direkt efter köp
Fractional Modeling of Fluid Flow and Transport Phenomena focuses on mathematical and numerical aspects of fractional-order modeling in fluid flow and transport phenomena. The book covers fundamental concepts, advancements, and practical applications, including modeling developments, numerical solutions, and convergence analysis for both time and space fractional order models. Various types of flows are explored, such as single- and multi-phase flows in porous media, involving different fluid types like Newtonian, non-Newtonian, nanofluids, and ferrofluids. This book serves as a comprehensive reference on fractional-order modeling of fluid flow and transport phenomena, offering a single resource that is currently unavailable.Fractional-order modeling has gained traction in engineering and science, particularly in fluid dynamics and transport phenomena. However, its mathematical and numerical advancements have progressed relatively slowly compared to other aspects. Therefore, this book emphasizes the fractional-order modeling of fluid flow and transport phenomena to bridge this gap. Each chapter in the book delves into a specific topic closely related to the others, ensuring a cohesive and self-contained structure.- Covers advancements in fractional-order fluid flow problems- Serves as a comprehensive reference on fractional-order modeling of fluid flow and transport phenomena- Demonstrates the topic with different aspects, including modeling, mathematical, computational, and physical commentary
Häftad, Engelska, 2025
1 826 kr
Skickas inom 10-15 vardagar
Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques.This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.Provides comprehensive coverage of mathematical and statistical techniques for big data analyticsGives readers practical guidance on how to approach and solve complex data analysis problems using mathematical modeling techniques, with an emphasis on effective communication and presentation of resultsIncludes leading-edge information on current trends and emerging technologies and tools in the field of big data analytics, with discussions on ethical considerations and data privacy
E-bok
Engelska, 20252 379 kr
Läs direkt efter köp
Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques.This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource. - Provides comprehensive coverage of mathematical and statistical techniques for big data analytics- Gives readers practical guidance on how to approach and solve complex data analysis problems using mathematical modeling techniques, with an emphasis on effective communication and presentation of results- Includes leading-edge information on current trends and emerging technologies and tools in the field of big data analytics, with discussions on ethical considerations and data privacy