Multidisciplinary Mathematical Modelling: Applications of Mathematics to the Real World (SEMA SIMAI Springer Series, 11)

✍ Scribed by Francesc Font (editor), Tim G. Myers (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 97
• Category: Library

✦ Synopsis

This book presents a selection of the talks resulting from research carried out by different groups at the Centre de Recerca Matemàtica and presented at the International Congress on Industrial and Applied Mathematics, held in Valencia in 2019. The various chapters describe a wide variety of topics: cancer modelling, carbon capture by adsorption, nanoscale diffusion and complex systems to predict earthquakes. These mathematical studies were specifically aided via collaborations with biomedical engineers, physicists and chemists. The book is addressed to researchers in all of these areas as well as in general mathematical modelling.

✦ Table of Contents

Preface
Contents
Editors and Contributors
About the Editors
Contributors
Spatiotemporal Dynamics of Cancer Phenotypic Quasispecies Under Targeted Therapy
1 Introduction
2 Mathematical and Computational Models of Cancer Phenotypic Quasispecies
2.1 Differential Equations Model
2.2 Stochastic Bit-Strings Model
2.3 The Impact of Targeted Therapy
3 Conclusions
References
Guyer–Krumhansl Heat Conduction in ThermoreflectanceExperiments
1 Introduction
2 Mathematical Model
3 Connections to Linear Viscoelasticity
4 Time-Harmonic Heating
5 Arbitrary Heating Functions
6 Conclusions
References
A Mathematical Model of Carbon Capture by Adsorption
1 Introduction
2 Mathematical Model
2.1 Nondimensional Model
3 Travelling Wave Solution
4 Asymptotic Solution for Small Times
5 Numerical Solution
6 Results and Discussion
7 Conclusions
References
Diffusion Processes at Nanoscale
1 Why Nanoscale Is so Interesting?
2 Nanoparticles Growth
2.1 Model for a Single Particle
2.2 Ostwald Ripening
2.3 N Particles System
3 Drug Delivery
3.1 Non-Newtonian Fluids
3.2 Advection–Diffusion Equation
3.3 Preliminary Results
4 Conclusions
References
Maximum Likelihood Estimation of Power-Law Exponents for Testing Universality in Complex Systems
1 Introduction
2 Merging Datasets
3 Performance Over Synthetic Datasets
4 Earthquake and Charcoal Labquake Catalogs
4.1 Effect of the Magnitude Resolution in Earthquake Catalogs
5 Merging Earthquake Catalogs
6 Merging Earthquake and Labquake Catalogs: Universality
7 Conclusions
References