| Course Name | Computational Methods for Engineers |
| Course Code | 23AEE354 |
| Program | B. Tech. in Aerospace Engineering |
| Credits | 3 |
| Campus | Coimbatore |
Introduction to Numerical Techniques: Numerical Methods – Round off and truncation errors – Approximations – Order of Convergence – Numerical interpolation. Solution techniques of a linear system of equations: Gauss elimination – Gauss- Jordan method– LU Decomposition – Iterative methods for linear systems.
Taylor series expansion of multivariate functions, conditions for maxima, minima and saddle points, Concept of gradient and hessian matrices, Multivariate regression and regularized regression.
Theory of convex and non-convex optimization, Newton method for unconstrained optimization. Computational methods for ODEs: Newton-Raphson method, Eigen values – Single step methods – multi-step methods. Stability, consistency, accuracy and efficacy of these methods.
The objective of the course is to introduce students to the numerical techniques commonly used in solving engineering problems.
CO1: Given an engineering problem, understand the mathematical model required to describe the problem.
CO2: Comprehend the physics represented by the mathematical model to select an appropriate method/algorithm.
CO3: Apply the numerical solution method via a well-designed computer program.
CO4: Analyse the numerical solutions that were obtained in regard to their accuracy and suitability for applications.
| PO/PSO | PO1 | PO2 | PO3 | PO4 | PO5 | PO6 | PO7 | PO8 | PO9 | PO10 | PO11 | PO12 | PSO1 | PSO2 | PSO3 |
| CO | |||||||||||||||
| CO1 | 3 | 3 | 2 | – | – | – | – | – | – | – | – | – | 3 | 1 | – |
| CO2 | 3 | 2 | 3 | – | – | – | – | – | – | – | – | – | 3 | 1 | – |
| CO3 | 1 | 2 | 2 | 3 | 3 | – | – | – | – | – | – | 2 | 2 | – | |
| CO4 | 1 | 1 | 2 | 2 | 3 | 3 | – | – | – | – | – | 3 | 3 | 3 | 2 |
| Assessment | Internal | End Semester |
| Midterm Exam | 30 | |
| *Continuous Assessment (CA) | 30 | |
| End Semester | 40 |
*CA – Can be Quizzes, Assignment, Projects, and Reports
Text Book(s)
S.C. Chapra, and R. P. Canale. Numerical methods for engineers. Boston: McGraw-Hill Higher Education, 2010. Gilbert Strang, Linear Algebra and Learning from Data, Wellesley, Cambridge press, 2019.
William Flannery, “Mathematical Modeling and Computational Calculus”, Vol-1, Berkeley Science Books, 2013. Stephen Boyd and Lieven Vandenberghe, “Convex Optimization “, Cambridge University Press, 2018.
Reference(s)
S. P. Venkateshan, and P. Swaminathan. Computational methods in engineering. Elsevier, 2013.
R.H. Landau, M.J.Paez and C.C.Bordeianu, Computational Physics -Problem Solving with Computers, Wiley-VCH, 2001. Stephen Boyd and Lieven Vandenberghe, “Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares”, Cambridge University Press, 2018.
DISCLAIMER: The appearance of external links on this web site does not constitute endorsement by the School of Biotechnology/Amrita Vishwa Vidyapeetham or the information, products or services contained therein. For other than authorized activities, the Amrita Vishwa Vidyapeetham does not exercise any editorial control over the information you may find at these locations. These links are provided consistent with the stated purpose of this web site.
