Computational Courses for Aerospace & Mechanical Engineering
This course will provide students with an introduction to CFD and MATLAB. Topics covered throughout the course will include: errors, condition numbers and roots of equations; Navier-Stokes; direct and iterative methods for linear systems; finite differences for elliptic, parabolic and hyperbolic equations; Fourier decomposition, error analysis, and stability; high-order and compact finite-differences; finite volume methods; time marching methods; Navier-Stokes solvers; grid generation; finite volumes on complex geometries and panel methods; boundary layers. Subject includes a final year research project.
The specific objectives of the course are:
- To introduce and develop the main approaches and techniques that constitute the basis of numerical fluid mechanics for engineers and applied scientists.
- To familiarize students with the numerical implementation of these techniques and numerical schemes, so as to provide them with the means to write their own codes and software, and so acquire the knowledge necessary for the skillful utilization of CFD packages or other more complex software.
- To cover a range of modern approaches for numerical and computational fluid dynamics, without entering all these topics in detail, but aiming to provide students with a general knowledge and understanding of the subject, including recommendations for further studies.
This course continues to be a work in progress. New curricular materials are being developed for this course, and feedback from students is always welcome and appreciated during the term. For example, recitations and reviews on specific topics can be provided based on requests from students.
An understanding (in some cases review) of the mathematical ingredients on which numerical methods are based: calculus; linear algebra; and differential equations.
An understanding of the basic “canon” of numerical approaches and numerical methods relevant to MechE: To what problems does an approach or method apply? How does the method work? What are the limitations and pros/cons? What can go wrong? What are the sources of error and uncertainty?
An understanding of elementary programming concepts and of the basic MATLAB architecture/environment, data types, syntax, and mathematical/numerical routines.
The ability to formulate an engineering problem in a mathematical form appropriate for subsequent computational treatment and to choose an appropriate numerical approach.
The ability to select, test, and use (or reject) third-party numerical programs with confidence.
The ability to solve engineering problems by computational approaches through a combination of MATLAB scripts (typically rather short) and validated and informed calls to MATLAB or third-party numerical routines.
Attitudes and Professional Values
A commitment to always provide with any numerical prediction or recommendation some indication of error and uncertainty—and associated engineering implications—due to numerical treatment (and modeling error, however the latter is the emphasis of other MechE subjects).
The course delivery includes lectures, recitations, Programming assignments, problem sets and MATLAB exercises.
Lectures will comprise motivation/engineering demonstrations, blackboard review of key concepts, animations of numerical techniques, and examples of MATLAB implementations. The lectures will emphasize the math and numerics, but also the connection to MATLAB programming.
INR. 30000/- (One Time Payment) NOTE: Course fee includes CATIA, MATLAB & ANSYS-Fluent training.