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Medicine > Diagnosis
Advanced Methods and Mathematical Modeling of Biofilms: Applications in health care, medicine, food, aquaculture, environment, and industry
Delavar, Mojtaba Aghajani
ISBN 13: 
9780323856904
ISBN 10: 
032385690X
Category: 
Diagnosis
Edition: 
1
Publisher: 
Elsevier
Format: 
Paperback
Status: 
Print on Demand
Imprint: 
Academic Press
Audience: 
Professional and scholarly
Pages: 
264
Weight: 
0.99
Retail Price: 
150.00
Quantity On Hand: 
0
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Synopsis:

Advanced Mathematical Modelling of Biofilms and its Applications covers the concepts and fundamentals of biofilms, including sections on numerical discrete and numerical continuum models and different biofilms methods, e.g., the lattice Boltzmann method (LBM) and cellular automata (CA) and integrated LBM and individual-based model (iBM). Other sections focus on design, problem-solving and state-of-the-art modelling methods. Addressing the needs to upgrade and update information and knowledge for students, researchers and engineers on biofilms in health care, medicine, food, aquaculture and industry, this book also covers areas of uncertainty and future needs for advancing the use of biofilm models.

Over the past 25-30 years, there have been rapid advances in various areas of computer technologies, applications and methods (e.g. complex programming and algorithms, lattice Boltzmann method, high resolution visualization and high-performance computation). These new and emerging technologies are providing unprecedented opportunities to develop modeling frameworks of biofilms and their applications.



  • Introduces state-of-the-art methods of biofilm modeling, such as integrated lattice Boltzmann method (LBM) and cellular automata (CA) and integrated LBM and individual-based model (iBM)
  • Provides recent progress in more powerful tools for a deeper understanding of biofilm complexity by implementing state-of-the art biofilm modeling programs
  • Compares advantages and disadvantages of different biofilm models and analyzes some specific problems for model selection
  • Evaluates novel process designs without the cost, time and risk of building a physical prototype of the process to identify the most promising designs for experimental testing

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