Foundations of Mathematical Modeling and Analysis in Engineering
- 1st Edition - January 13, 2026
- Latest edition
- Author: A. Ted Watson
- Language: English
Foundations of Mathematical Modeling and Analysis in Engineering offers a comprehensivepresentation of the mathematical principles underpinning modern engineering and the quantita… Read more
Foundations of Mathematical Modeling and Analysis in Engineering offers a comprehensive
presentation 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 https://educate.elsevier.com/9780443295928
This book was designed to provide the essential mathematical foundations for first-year graduate students within all engineering disciplines. It is accessible to all upper-division undergraduate and graduate students within engineering and the quantitative sciences, as well as associated practitioners within those fields.
1. Introduction
2. Mathematical representations of physical phenomena
3. Solving linear algebraic equations
4. Vector spaces and their representations
5. Linear transformations and representations
6. Inner product spaces
7. Operators and matrix representations
8. Ordinary differential equations
9. Function representation and transforms
10. Partial differential equations
11. System and parameter identification
Appendices
A. A Word on Proofs
B. Vector calculus and operations
C. Simulate measurement errors
D. Additional operations with square matrices
E. Addendum to Chapter 7
F. Higher-Order Linear ODEs
G. QR Factorization
H. Sequences and Convergence
I. Eulers Equidimensional Equation
J. Sturm-Liouville Equations
K. Bessel’s equation
L. Best linear unbiased predictions and estimates
2. Mathematical representations of physical phenomena
3. Solving linear algebraic equations
4. Vector spaces and their representations
5. Linear transformations and representations
6. Inner product spaces
7. Operators and matrix representations
8. Ordinary differential equations
9. Function representation and transforms
10. Partial differential equations
11. System and parameter identification
Appendices
A. A Word on Proofs
B. Vector calculus and operations
C. Simulate measurement errors
D. Additional operations with square matrices
E. Addendum to Chapter 7
F. Higher-Order Linear ODEs
G. QR Factorization
H. Sequences and Convergence
I. Eulers Equidimensional Equation
J. Sturm-Liouville Equations
K. Bessel’s equation
L. Best linear unbiased predictions and estimates
- Edition: 1
- Latest edition
- Published: January 13, 2026
- Language: English
AW
A. Ted Watson
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).
Affiliations and expertise
School of Biomedical & Chemical Engineering, Colorado State University, Fort Collins, CO, USARead Foundations of Mathematical Modeling and Analysis in Engineering on ScienceDirect