Foundations of Mathematical Modeling and Analysis in Engineering
Published on 8. December 2025
400 pages
978-0-443-29593-5 (ISBN)
Description
Foundations of Mathematical Modeling and Analysis in Engineering offers a comprehensivepresentation of the mathematical principles underpinning modern engineering and the quantitative sciences, and develops mathematical modeling as a foundational intellectual discipline. Designed for graduate and advanced undergraduate students, and accessible to seasoned professionals, it provides the means to develop and employ mathematical representations of physical processes and systems.
- A comprehensive toolbox for graduate engineering students, covering foundational and advanced mathematical concepts and methods
- Emphasizes real-world applications of mathematical models, bolstering problem-solving skills through worked examples and end-of-chapter exercises
- Aids the transition from undergraduate to graduate studies, ensuring comprehensive understanding and application of the mathematical concepts for advanced engineering courses and research
- Offers teaching support, including an image bank, and full Solutions Manual, for qualified instructors, available for request at educate.elsevier.com/9780443295928
More details
Other editions
Additional editions
Book
approx. 12/2025
Butterworth-Heinemann
€101.50
Not yet published
Person
Professor Emeritus A. Ted Watson holds a BS from University of Texas at Austin and a PhD from California Institute of Technology, both in chemical engineering. He attained the position of Professor at Texas A&M University (TAMU) before joining Colorado State University (CSU) as the founding department head of chemical & biological engineering. He has advanced mathematical modeling and system and parameter identification while working within a variety of fields. He established the Engineering Imaging Laboratory at TAMU and Rocky Mountain Magnetic Resonance at CSU and was elected Fellow of the American Institute of Chemical Engineers (AIChE).
Content
1. Introduction2. Mathematical representations of physical phenomena3. Solving linear algebraic equations4. Vector spaces and their representations5. Linear transformations and representations6. Inner product spaces7. Operators and matrix representations8. Ordinary differential equations9. Function representation and transforms10. Partial differential equations11. System and parameter identification
