Mathematical Modelling for Engineering and Physical Applications: Practical Examples and Case Studies

· · · ·
· CRC Press
Ebook
252
Pages
Eligible
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About this ebook

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.

About the author

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 traffic 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.

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