2024/25 Taught Postgraduate Module Catalogue

MECH5015M Computational Fluid Dynamics Analysis

15 creditsClass Size: 200

Module manager: Dr Masoud Jabbari
Email: M.Jabbari@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2024/25

Pre-requisite qualifications

UG fluid mechanics and thermodynamics concepts

This module is mutually exclusive with

MECH5770M

Computational Fluid Dynamics Analysis

This module is not approved as an Elective

Module summary

This module provides the theoretical and practical knowledge to allow a student to competently perform Computational Fluid Dynamics (CFD) analysis using commercial software packages used in industry. This is reinforced through a series of taught practical sessions which explore problem solving including fault diagnostics and critical analysis.

Objectives

On successful completion of the module students will;
• Understand the governing equations for fluid dynamics and appreciate the limitations of numerical methods/algorithms required for solving them;
• Appreciate the challenges and limitations of CFD application including the importance of verification and validation;
• Evaluate and select the most appropriate solution strategy for a particular application;
• Undertake the simulation and analysis of practical problems using a commercial CFD package and critically assess the output solution.

Learning outcomes
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:

On completion of this module, the student will be able to:

1. Understand the governing equations for fluid dynamics and appreciate the limitations of numerical methods/algorithms required for solving them;
2. Appreciate the challenges and limitations of CFD application including the importance of verification and validation;
3. Evaluate and select the most appropriate solution strategy for a particular application;
4. Undertake the simulation and analysis of practical problems using a commercial CFD package and critically assess the output solution.

Upon successful completion of this module the following Engineering Council Accreditation of Higher Education Programmes (AHEP) learning outcome descriptors (fourth edition) are satisfied:
5. Apply a comprehensive knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems. Much of the knowledge will be at the forefront of the particular subject of study and informed by a critical awareness of new developments and the wider context of engineering. (M1)
6. Formulate and analyse complex problems to reach substantiated conclusions. This will involve evaluating available data using first principles of mathematics, statistics, natural science and engineering principles, and using engineering judgment to work with information that may be uncertain or incomplete, discussing the limitations of the techniques employed. (M2)
7. Select and apply appropriate computational and analytical techniques to model complex problems, discussing the limitations of the techniques employed. (M3)

Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills:

a. Time management,
b. planning & organising,
c. Problem solving & analytical skills,
d. Critical thinking,
e. Digital proficiency and productivity,
f. Computational Mechanics

Syllabus

1. Introduction to Computational Fluid Dynamics
2. Fundamentals of numerical schemes: discretisation schemes, iterative methods and numerical diffusion
3. Mesh generation including best practice guidelines
4. Boundary conditions: types, uses and implementation
5. Numerics: pressure and density based solvers, grid staggering and the finite volume method, pressure-velocity coupling algorithms
6. Turbulence modelling: energy cascade, hierarchy of models (RANS, URANS, DES, LES, DNS), wall functions and best practice guidelines
7. Verification & Validation (V&V): dealing with sources of error and uncertainty during the application of CFD
8. Post-processing & data presentation: types of post-processing, drag extraction techniques and best practice guidelines
9. High Performance Computing (HPC) and simulation strategies: scalability, scripting, under relaxation, solver techniques
10. Multi-physics simulation: heat transfer, species transport, multiphase, fluid-structure interaction (FSI) and radiation modelling
11. Current capabilities and future trends

Methods of Assessment

We are currently refreshing our modules to make sure students have the best possible experience. Full assessment details for this module are not available before the start of the academic year, at which time details of the assessment(s) will be provided.

Assessment for this module will consist of;

2 x Report

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	11	1.00	11.00
Practical	9	1.00	9.00
Private study hours			130.00
Total Contact hours			20.00
Total hours (100hr per 10 credits)			150.00

Opportunities for Formative Feedback

Students are encouraged to complete a series of 10 tasks which are linked to the main learning resource, the Tutorial Handbook. It is expected that one task is completed per week. Following the completion of each task, students will have access to a short multiple-choice questionnaire (MCQ), which provides instant formative feedback. These MCQs allow students to check that they understand the concepts and that they are on track. Students also have the opportunity to ask questions in forums which are monitored by academic staff delivering the module.

Reading list

The reading list is available from the Library website

Last updated: 29/04/2024

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