Organized around problem solving, this book gently introduces the reader to computational simulation of biomedical transport processes, bridging fundamental theory with real-world applications. Using this book the reader will gain a complete foundation to the subject, starting with problem simplification, implementing it in software, through to interpreting the results, validation, and optimization. Ten case studies, focusing on emerging areas such as thermal therapy and drug delivery, with easy to follow step-by-step instructions, provide ready-to-use templates for further applications. Solution process using the commonly used tool COMSOL Multiphysics is described in detail; useful biomedical property data and correlations are included; and background theory information is given at the end of the book for easy reference. A mixture of short and extended exercises make this book a complete course package for undergraduate and beginning graduate students in biomedical and biochemical engineering curricula, as well as a self-study guide.
Ashim Datta is a Professor in the Department of Biological and Environmental Engineering at Cornell University, where he has developed and taught modeling of biomedical processes as a course since 1996. He is recipient of the Michael Tien '72 Excellence in Teaching Award from the College of Engineering, and he has authored and co-authored over 85 technical papers and book chapters, authored a textbook and also co-edited three books on biological heat and mass transfer.
Vineet Rakesh is a Research Scientist in the Computational Medicine and Biology Division of a biomedical research company.He received his Ph.D. in Biological Engineering from Cornell University.He has also worked as a teaching assistant for the biomedical process modeling course at Cornell for three years and has been presented with the Outstanding Teaching Assistant award. His research has included modeling of airflow in the upper airway and drug transport in cancer therapy.
Part I. Essential Steps: 1. Problem formulation; 2. Software implementation: what to solve; 3. Software implementation: how to solve (preprocessing); 4. Software implementation: visualizing and manipulating solution (postprocessing); 5. Validation, sensitivity analysis, optimization and debugging; Part II. Case Studies: 6. Case studies; Part III. Background Material; 7. Governing equations and boundary conditions; 8. Source terms; 9. Material properties and other input parameters; 10. Solving the equations: numerical methods.