MECH4620 Computational Fluid Dynamics - Lecture 1 Notes

Course Information

  • Course Code: MECH4620

  • Lecturers:

    • Prof Guan Heng Yeoh (J17, Room 401B, g.yeoh@unsw.edu.au)

    • A/Prof Victoria Timchenko (Teams v.timchenko@unsw.edu.au)

  • CFD Demonstrators:

    • Ivan (i.decachinhocordeiro@unsw.edu.au)

    • Rachel (jiayi.li2@unsw.edu.au)

    • Lingchen (lingcheng.kong@student.unsw.edu.au)

    • Jingang (jingang.li@student.unsw.edu.au)

    • Frank (ao.li@unsw.edu.au)

  • Course Details: Lectures and Labs are located in Moodle.

Weekly Schedule

  • Week 1 (GHY): Introduction to CFD and examples.

    • Lab: Backward facing step exercise, problem setup.

  • Week 2 (GHY): Introduction to ANSYS CFX and Fluent.

    • Lab: Creating geometry and meshing, defining a CFD problem, creating/importing geometry in Design Modeler.

    • Due: Release group allocation.

  • Week 3 (GHY): Mass and momentum conservation, Navier-Stokes equations.

    • Lab: Creating geometry and meshing, heat exchanger exercise (meshes), discussions of group project topics.

  • Week 4 (VT): Energy conservation and dynamic similarity.

    • Lab: T1 work, group project work.

    • Due: T1: Conservation Laws.

  • Week 5 (GHY): Turbulence: Basics and introduction.

    • Lab: Backward facing step exercise; Convergence and Discretisation, Turbulence Models, T2 work, group project work.

    • Feedback: T1: Conservation Laws.

  • Week 7 (GHY): Turbulence: applications of models.

    • Lab: T2 work, group project work.

    • Due: T2: Turbulence.

  • Week 8 (VT): Initial and boundary conditions: practical guidelines, post-processing (analysis, validation, and verification).

    • Lab: Characterization of boundary conditions, Heat exchanger exercise, group project work.

    • Feedback: T2: Turbulence.

  • Week 9 (VT): Computational methods – discretisation.

    • Lab: Computational method online tutorial, T3 work, group project work.

    • Due: Group project report.

  • Week 10 (VT): Solution Procedures.

    • Lab: Revision/consultation, consultation for exams.

    • Due: T3: Discretisation.

  • Study Week (GHY, VT): Exam revision.

    • Feedback: Group project report and T3 discretisation.

Main Texts

  • J. Tu, G.Yeoh, C. Liu "Computational Fluid dynamics: A Practical Approach”, Butterworth-Heinemann/Elsevier, 3rd Edition, 2018; 4rd Edition, 2023

  • H.K. Versteeg and W. Malalasekera, An introduction to Computational Fluid Dynamics. The Finite Volume Method, 2nd Edition

Additional Reading

  • J.D. Anderson, Computational Fluid Dynamics

  • P.J. Roache, Fundamentals of Computational Fluid Dynamics

  • P.J. Roache, Verification and Validation in Computational Science and Engineering

  • J.C. Tannehill, D.A. Anderson and R.H. Pletcher, Computational Fluid Mechanics and Heat Transfer

  • S.V. Patankar, Numerical Heat Transfer and Fluid Flow

  • D.C. Wilcox, Turbulence modelling for CFD

Assessment

  • Tutorial style problems:

    • Length: 2-3 pages

    • Weight: 15% (3 x 5% each)

    • Due: 4 pm Friday, Week 4, Week 7 and Week 10 via Moodle

    • Deadline absolute fail: Same as assignment deadline.

    • Marks returned: 1 week after due date.

  • Group Project:

    • Length: 15 pages

    • Weight: 35%

    • Due: 4 pm Friday, Week 9 via Moodle

    • Deadline absolute fail: 4 pm Monday, Week 10

    • Marks returned: 1 week after due date.

  • Final exam:

    • Length: 2 hours

    • Weight: 50%

    • Due: Exam period, date TBC

    • Deadline absolute fail: N/A

    • Marks returned: During exam period.

Group Project Details

  • Solve a problem using ANSYS, a commercial CFD code.

  • CFD analysis process: CAD, meshing, pre-processing, solving, and post-processing.

  • Groups announced in Week 2, project topics announced in Week 3.

  • Focus on analysis and report writing.

  • ANSYS help in tutorials, but self-learning is expected via tutorial problems and examples.

  • Set project problems will be offered.

  • Use the preliminary template to write your report.

Group Project Report Structure

  • Short literature review (~ ½ page):

    • Find 2-3 relevant papers with numerical work descriptions (mesh, turbulence model).

    • Synthesize info and comment on the difference of your approach.

  • Project Description (~1 page):

    • Describe original project proposal and how the final project differs.

    • Outline what you wanted to achieve and why.

  • Grid Description and Refinement (~2 pages):

    • Discuss features of the grids and design rationale, comparing solutions on two or three grid sizes.

    • Use <2 million cells.

    • Suggest whether you have reached grid convergence.

  • Numerical Model (~8 pages, total):

    • Discuss validation and verification, assumptions, and limitations.

    • Boundary Conditions: Examine the effect of changing the boundary conditions, both type and specification of values. Are your boundaries placed at the correct location?

    • Discretization Schemes: Obtain solutions using two different discretization schemes. Explain the scheme. Are the results as you expect? Which scheme do you recommend for this problem?

    • Convergence: What convergence level do you suggest for your problem? Why?

    • CFD Models (3 pages): Discuss extra models (turbulence, energy, multiphase). Which model do you recommend and why?

  • Results (~3 pages): Discuss major flow features, their significance, and justification.

  • The project is 35% of the total mark.

  • Thinking about the CFD problem early saves time in the long run.

What is CFD?

  • Fluid mechanics: study of fluids in motion (dynamic) or at rest (stationary).

  • CFD focuses on fluids in motion and how fluid flow influences processes like heat transfer and chemical reactions.

  • Physical characteristics of fluid motion are described by fundamental mathematical equations, usually partial differential equations (governing equations).

Art in Meshing

  • A good mesh minimizes errors.

  • The grid should be fine enough not to influence results.

  • Assess grid convergence via Validation and Verification lecture.

  • Use at least 2 meshes to compare (3 is better).

Meshing Types

  • Structured Meshing:

    • Better results for a given mesh density.

    • Lower residual errors and faster solver.

    • Can take a long time to create.

    • Sometimes not possible.

  • Unstructured Meshing:

    • Tetrahedral meshes combined with hexahedral meshes.

    • Polyhedral meshes becoming more popular.

    • Cut-cell meshing (ANSYS).

  • Flexibility of meshing:

    • Sweep meshing.

    • Automatic (Tetrahedral & Sweep).

    • Assembly.

    • CutCell.

  • Geometry containing small details:

    • Patch Conforming: All geometric detail is captured

    • Patch Independent: Can ignore and defeature geometry

Meshing Summary

  • Use structured mesh (inflation layer) where a boundary layer will form.

  • Put more mesh where flow gradients are strongest (use a coarse mesh to check).

  • Mesh should look “smooth” with no sudden changes in volume.

  • Different mesh types should blend nicely.

  • Check mesh for skew and negative volumes.

CFD Analysis Framework

  • Pre-processor:

    • Creation of geometry

    • Mesh generation

    • Material properties

    • Boundary conditions

  • Solver:

    • Governing equations solve on a mesh

      • Transport Equations

        • Mass

        • Momentum

        • Energy

        • Other transport variables

      • Equation of state

      • Supporting physical models

    • Physical Models

      • Turbulence

      • Combustion

      • Radiation

      • Other processes

    • Solver Settings

      • Initialization

      • Solution control

      • Monitoring solution

      • Convergence criteria

  • Post-processor:

    • X-Y graphs

    • Contour

    • Velocity vectors

    • Others

Importance of Governing Equations

  • Represent mathematical statements of conservation laws.

    • Conservation of Mass: Mass is conserved for the fluid.

    • Conservation of Momentum: Newton’s second law, the rate of change of momentum equals the sum of forces acting on the fluid.

    • Conservation of Energy: First law of thermodynamics, the rate of change of energy equals the sum of the rate of heat addition to and the rate of work done on the fluid.

Importance of Boundary Conditions

  • Physical aspects and mathematical statements of boundary conditions must be developed.

  • Numerical form depends on mathematical form of governing equations and numerical algorithm.

  • "Garbage In, Garbage Out" (GIGO) - Late Prof Eddie Leonardi (UNSW)

Importance of Turbulence

  • Many engineering flows are turbulent.

  • Turbulence effects must be captured in solving everyday problems.

  • Laminar flows are described by the governing equations.

  • More complex flows require numerical solutions with turbulence modeling.

What is Discretisation?

  • CFD is based on approximate forms of governing equations solved iteratively.

Overview of Solution Procedure

  1. Solution control

  2. Initialization

  3. Monitoring solution

  4. CFD calculation

  5. Check for convergence

    • If no, modify solution parameters or mesh and return to step 4.

    • If yes, stop.

Analysis of Results

  • Qualitative analysis: Visual representation of flow features.

  • Quantitative analysis: X-Y plots.

Verification and Validation

  • Verification: Assessing numerical simulation uncertainty and estimating error.

  • Validation: Assessing simulation model uncertainty using benchmark experimental data and estimating modeling error.

  • Is the solution correct? How correct do we need?

Application of CFD

  • Automotive engineering:

    • Shorten design cycles, optimize components for energy efficiency, improve in-car environment, and study external aerodynamics.

  • Biomedical science and engineering:

    • Particle formation/dispersion from nasal sprayers and particle transport/deposition in the nasal cavity

    • Bronchial tree geometry created from CT data for CFD simulation and CFD prediction of pressure coefficient (C_p) values for specific patient cases with and without asthma

    • Flow behavior in a carotid bifurcation of artery.

    • Nanoparticle flow in arteries and arterioles (swirling flow vs. viscosity-dominated Stokes flow).

  • Abrasive Jet:

    • Mesh of the computational domain is 75,817 polyhedral elements

    • Nozzle Diameter 0.36 mm

    • Inlet Pressure 0.43 MPa

  • Aggregation of nanoparticles:

    • Self-organization of nanoparticles (50 nm) in a dense suspension medium

  • Aggregation of microparticles:

    • Numerical simulation is performed by examining the aggregation behavior of micro aerosols advected in a circular pipe flow

  • Magnetic particles in a quiescent fluid:

    • Nanoparticles uniform particle diameter of 100 nm in a computational domain of 5 μm × 5 μm × 0.25 μm

  • Magnetic particles in a shear flow:

    • Nanoparticles of 100 nm with a shear velocity of 0.005 m/s with periodic boundaries, B = 1 Tesla

  • Bubble motion in a quiescent fluid:

    • Cases presented are 1mm, 2.5mm, 5mm and 10mm bubbles.

  • Fire engineering:

    • Buoyant fire: Temperature, Density, Air Entrainment, Convective Heat Transfer, Radiative Heat Transfer, Combustion, Soot Production & Oxidation

    • Compartment fire: Layout a full scale compartment fire

    • Swirling fire: Presentation of Magnitude and Temperature results

  • Power generation:

    • Optimize turbine blades for constant power under varying wind conditions.

    • Model wind farm resource distribution, even for complex terrain.

    • PV-integrated facade.

    • Turbulent structures enhance heat transfer and lower surface temperature at the heated wall.

Key Framework Reminder

  • Physical interpretation of computational results is critical.

  • Reiterate the CFD analysis framework (Pre-processor, Solver, Post-processor).

This information is found in the "Art in Meshing" section.