Mathematical Modelling for Engineering and Physical Applications

This edited volume from mathematical modelling experts employs a structured approach to showcase the latest research and provide a comprehensive guide to the principles, techniques and practical applications of mathematical modelling in the fields of engineering and the physical sciences. Readers will gain an insight into the fundamentals of mathematical modelling, its application in engineering and the physical sciences, recent advances in the field, real-world case studies and challenges and future directions in the field. The book first introduces readers to the fundamentals of mathematical modelling, including the definition, scope and steps involved in the modelling process. Mathematical tools and techniques relevant to modelling are explained. The book then addresses the application of mathematical modelling in engineering and the physical sciences. It covers various domains, such as mechanical, biomedical, chemical, computer and environmental engineering, as well as green energy, physics and other physical science applications. Furthermore, the book explores the integration of data-driven approaches, leveraging the power of big data and analytics to enhance modelling capabilities. Through real-life case studies, readers gain practical insights into how mathematical modelling is applied in various industries and scientific disciplines. These case studies analyse the modelling process, challenges faced and outcomes achieved. Readers will gain a solid foundation to develop effective mathematical models and apply them to solve complex engineering and physical problems. This foundation will also enable them to tackle problems and make informed decisions in their own projects. Finally, readers will be able to anticipate and adapt to evolving technologies and stay ahead in their respective fields. This book is a valuable resource primarily for undergraduate and graduate students seeking a comprehensive guide to this important discipline. Researchers, engineers and scientists will also benefit from the discussions within. Overall, the book empowers readers with the knowledge, skills and practical insights to effectively apply mathematical modelling in engineering and the physical sciences.

Mohd Hafiz Mohd earned a BSc (Hons) in mathematics at the Imperial College London, an MSc in mathematics at the Universiti Sains Malaysia and a PhD in computational and applied mathematics at the University of Canterbury, New Zealand. He is an Associate Professor at Universiti Sains Malaysia, researching mathematical modelling in biology, engineering and distinct complex systems. Noor Atinah Ahmad earned a BSc (Hons) in mathematics at the University of Bristol, UK, and a PhD in mathematics at the University of Southampton, UK. She is an Associate Professor at the Universiti Sains Malaysia, and her research interests include data-driven modelling of dynamical systems. Syakila Ahmad is a Senior Lecturer at the School of Mathematical Sciences, Universiti Sains Malaysia. She earned a PhD in fluid dynamics at the Universiti Putra Malaysia. Her research interests include fluid dynamics, convective heat and mass transfer and mathematical modelling. Md Yushalify Misro earned a BSc (Hons) and an MSc (Hons) in mathematics and a PhD in computer-aided graphic design at the Universiti Sains Malaysia. He joined the faculty of the Universiti Sains Malaysia in 2018 and has since researched various areas, including trigonometric and fractional Bézier curves and surfaces, developable surfaces, numerical splines and träc simulation. Mohamad Hekarl Uzir earned a BEng (Hons) in chemical engineering at the University of Leeds, an MSc in advanced chemical engineering at the University of London and a PhD in biochemical engineering at the University College London. He is an Associate Professor at the Universiti Sains Malaysia, specialising in biocatalysis, biotransformation and modelling of biocatalytic and bioprocess systems.

1. Introduction to Mathematical Modelling for Engineering and Physical Applications. 2. Forecasting Stock Price Fluctuation Using Geometric Brownian Motion Modelling. 3. Collective Dynamics in a Random Network of Pulse-Coupled Oscillators with Heterogeneous Intrinsic Frequencies. 4. Dynamical Analysis of a Reaction-Diffusion System for Biocatalytic Exothermic Reactions. 5. Stability Analysis of Magnetohydrodynamic Flow and Heat Transfer over an Exponentially Permeable Stretching/Shrinking Sheet in Ferrofluids with the Influence of Heat Generation. 6. Computational Fluid Dynamics Modelling on the Flow Behavior of a High-Speed Train under Crosswinds. 7. Numerical Solution of Linear Simultaneous Equations Based on Particle Swarm Optimisation of Multi-Agent System. 8. Tracking Abrupt Changes in Physical and Engineering Systems Using Recursive System Identification. 9. A Comparative Analysis of Random Forest and ARIMA-GARCH Models: A Case Study in Forecasting Particulate Matter Concentration in Penang, Malaysia. 10. Applications of --Curves to Robot Trajectory Generation. 11. Solving the Global Path Planning of an Unmanned Ground Vehicle Using a Clustered Travelling Salesman Path Problem Approach. 12. Energy and Exergy Analyses of Hybrid Solar Drier for Seaweed Drying.