Based on course notes from over twenty years of teaching engineering and physical sciences at Michigan Technological University, Tomas Co's engineering mathematics textbook is rich with examples, applications and exercises. Professor Co uses analytical approaches to solve smaller problems to provide mathematical insight and understanding, and numerical methods for large and complex problems. The book emphasises applying matrices with strong attention to matrix structure and computational issues such as sparsity and efficiency. Chapters on vector calculus and integral theorems are used to build coordinate-free physical models with special emphasis on orthogonal co-ordinates. Chapters on ODEs and PDEs cover both analytical and numerical approaches. Topics on analytical solutions include similarity transform methods, direct formulas for series solutions, bifurcation analysis, Lagrange-Charpit formulas, shocks/rarefaction and others. Topics on numerical methods include stability analysis, DAEs, high-order finite-difference formulas, Delaunay meshes, and others. MATLAB (R) implementations of the methods and concepts are fully integrated.
Tomas Co is a professor of chemical engineering at Michigan Technological University. After completing his PhD in chemical engineering at the University of Massachusetts, Amherst he was a postdoctoral researcher at Lehigh University, a visiting researcher at Honeywell Corp., and a visiting professor at Korea University. He has been teaching applied mathematics to graduate and advanced undergraduate students at Michigan Tech for more than twenty years. His research areas include advanced process control including plant-wide control, nonlinear control and fuzzy logic. His journal publications span broad areas in such journals as IEEE Transactions in Automatic Control, Automatica, the AIChE Journal, Computers in Chemical Engineering, and Chemical Engineering Progress. He is a regular nominee for the Distinguished Teaching Awards at Michigan Tech and is a member of the Michigan Technological University Academy of Teaching Excellence.
1. Matrix algebra; 2. Solution of multiple equations; 3. Matrix analysis; 4. Vectors and tensors; 5. Integral theorems; 6. Ordinary differential equations: analytical solutions; 7. Numerical solution of initial and boundary value problems; 8. Qualitative analysis of ordinary differential equations; 9. Series solutions of linear ordinary differential equations; 10. First order partial differential equations and the method of characteristics; 11. Linear partial differential equations; 12. Integral transform methods; 13. Finite difference methods; 14. Method of finite elements.