1. Handbook
  2. Subjects
  3. Computational Fluid Dynamics

Computational Fluid Dynamics (ENGR90024)

Graduate courseworkPoints: 12.5On Campus (Parkville)

You’re viewing the 2019 Handbook:
Or view archived Handbooks

Overview

Year of offer2019
Subject levelGraduate coursework
Subject codeENGR90024
Campus
Parkville
Availability
Semester 1
FeesSubject EFTSL, Level, Discipline & Census Date

AIMS

This subject provides presents fundamental numerical techniques relevant to the simulation of fluid flow and heat/mass transfer. It will give students an understanding of common numerical methods operating “under the hood” in Computational Fluid Dynamics software, and will provide students with an introductory basis for writing computer code to implement such numerical procedures.

INDICATIVE CONTENT

Ordinary Differential Equations: explicit and implicit methods, stability, systems of ODEs, boundary value problems, MATLAB. Partial Differential Equations: overview, types of equations, boundary conditions, convection-diffusion equations, differencing schemes, finite volume method, stability - von Neumann analysis, error analysis - dispersion, diffusion errors, solving Laplace and Poisson equations, methods for solving Navier-Stokes equations. OpenFoam: fundamentals of OpenFoam - examples, solving simple 2D problems, Laplace and Poisson equations with OpenFoam, solving complex 2D fluid flow problems. C and C++ programming.

Intended learning outcomes

On completion of this subject the student is expected to:

  • Formulate strategies for the solution of engineering problems by applying the differential equations governing fluid flow, heat transfer and mass transport
  • Solve these equations numerically using a appropriate methods and a computer
  • Solve engineering problems using a computational fluid dynamics software package

Generic skills

  • In-depth technical competence in at least one engineering discipline
  • Ability to undertake problem identification, formulation, and solution
  • Ability to utilise a systems approach to complex problems and to design and operational performance
  • Capacity for lifelong learning and professional development.

Last updated: 8 June 2019