Delavar / Wang Advanced Methods and Mathematical Modeling of Biofilms

Applications in Health Care, Medicine, Food, Aquaculture, Environment, and Industry
1. Auflage 2022
ISBN: 978-0-323-90374-5
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 264 Seiten

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

Dr. Mojtaba Aghajani Delavar is a postdoctoral fellow at Athabasca University. He received his B.Sc. in mechanical engineering from Amirkabir University of Technology in 2001, M.Sc. and Ph.D. in mechanical Engineering from Mazandaran University in 2003 and 2010, respectively. He worked at Babol Noshirvani University of Technology in Iran as assistant and associate professor from 2010 until 2019. Then he joined professor Wang's research group at Athabasca university. Dr. Delavar has about 20 year's experience in modelling of various industrial and biological systems using different modelling schemes including mathematical and numerical analysis and simulation. He has authored/co-authored over 80 papers including more than 45 peer reviewed journal papers.

Autoren/Hrsg.

Delavar, Mojtaba Aghajani

Wang, Junye