Engineering Mathematics
Welcome
Chemical engineering occupies a unique position at the interface between molecular sciences and engineering. Intimately linked with the fundamental subjects of chemistry, biology, mathematics, and physics — and in close collaboration with fellow engineering disciplines like materials science, computer science, and mechanical, electrical, and civil engineering — chemical engineering offers unparalleled opportunities to do great things
Contents
Part I
- Introduction to Differential Equations
- First-Order Differential Equations
- Higher-Order Differential Equations
- The Laplace Transform
- Series Solutions of Linear Differential Equations
- Matrices
- Systems of Linear Differential Equations
- Systems of Nonlinear Differential Equations
Part II
- Vectors
- Vector Calculus
- Orthogonal Functions and Fourier Series
- Parabolic Partial Differential Equations
- Hyperbolic Partial Differential Equations
- Elliptic Partial Differential Equations
Scientific Computing in Python
- Numpy: Vectors, Matrices, and Multidimensional Arrays
- Sympy: Symbolic Computing
- Sympy: Laplace Transform
- Equation Solving
- Optimization
- Interpolation
- Integration
- Ordinary Differential Equations
- Double Pendulum
- Partial Differential Equations
Ploting and Data Analysis in Python
References
- D.G. Zill and W.S. Wright, Advanced Engineering Mathematics, 7th ed., Jones and Bartlett, 2022.
- E.A. Coddington, An Introduction to Ordinary Differential Equations, Prentice-Hall, 1961. (Dover Publications Inc., 1989 - Unabridged, corrected republication)
- G.E. Shilov, Linear Algebra, Prentice-Hall, 1971. (Dover Publications Inc., 1977 - Unabridged republication)
- S.J. Farlow, Partial Differential Equations for Scientists and Engineers, John Wiely & Sons, 1982. (Dover Publications Inc., 1993 – Unabridged, corrected republication)
- H.F. Weinberger, A First Course in Partial Differential Equations with Complex Variables and Transform Methods, Blaisdell Publishing Company, 1965. (Dover Publications Inc., 1995 - New edition)
- R. Johansson, Numerical Python: Scientific Computing and Data Science Applications with Numpy, Scipy and Matplotlib, 2nd ed., Apress, 2018.