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Application of CFD modelling in Water Resources Engineering

Md Nazmul Azim Beg

Early Stage Researcher, Marie Curie Actions ITN (QUICS)

University of Coimbra, Portugal

Department of Water Recourses Engineering

Bangladesh University of Engineering and Technology, Dhaka

Date: 8 January, 2017

Partners and Acknowledgements

This project has received funding from the European Union’s Seventh FrameworkProgramme for research, technological development and demonstration under grantagreement no 607000.

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Content

•What is CFD?

•Basic equations

•Basic steps to prepare a CFD simulation

•Application areas•Turbulence modelling•Flow with a free surface

•Some CFD software

•Some examples / Case studies

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What is CFD?• Computational Fluid Dynamics (CFD) is the science of

predicting fluid flow related to:a) mass transferb) heat transferc) chemical reactions, and d) related phenomena

• The result of CFD analyses is relevant engineering data:• conceptual studies of new designs• detailed product development• troubleshooting• redesign

• CFD analysis complements testing and experimentation• Reduces the total effort required in the laboratory.

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Why CFD?

•Real world flows are too complex to be addressed solely by theory or experimentation

•The flow can beo Nonlinearo Complicated Geometryo Coupled (Heat & Mass Transfer, Chemical Reaction,

Fluid-Structure Interaction)o Turbulent

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Basic Equations

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A CFD solver solves mathematical equations that represent physical laws, using a numerical process.

• Conservation of mass, • Conservation of momentum, • Conservation of energy and species, ...

Claude-Louis Navier from France George Gabriel Stokes from England

Basically a CFD solver solves Navier-Stokes equation

These equations can be applied to both compressible and incompressible fluids

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Define your modeling goals.

Identify the domain

Design and create the grid.

Set up the numerical model

Compute and monitor the solution.

Pre-Processing

Examine the results

Consider revisions to the model

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CFD Analysis: Basic Steps

Solver Settings

Post-Processing

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• Meshing is the most important issue for a CFD model

• For simple geometries, quad/hex meshes can provide high-quality solutions

• For complex geometries, quad/hex meshes show no numerical advantage, meshing effort by using a tri/tet mesh.

• Both tetrahedral and hexahedral can also be used in one domain.

• Both efficiency and accuracy are enhanced relative to a hexahedral or tetrahedral mesh alone.

triangle quadrilateral

tetrahedronpyramid prism/wedge hexahedron

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CFD Analysis: Basic StepsMeshing

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CFD Analysis: Basic Steps

• Transport Equations• mass

•species mass fraction

•phasic volume fraction

• momentum

• energy

• Equation of State

• Supporting Physical Models

Physical Models

Turbulence

Combustion

Radiation

Multiphase

Phase Change

Moving Zones

Moving Mesh

Material Properties

Boundary Conditions

Initial Conditions

Equations solved on mesh

Solver

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For a given problem, one needs to:• Define proper material properties.

• Fluid : (Density, temperature, pressure, viscosity, compressibility, …)

• Solid : (Thermal conductivity, Elasticity, density, …..)

• Mixture : (liquid + gas, liquid + solid, …)

• Prescribe operating conditions (temperature, pressure …)

• Prescribe boundary conditions at all boundary zones

• Provide an initial solution.

• Set up solver controls.

• Set up convergence monitors. Solving initially in 2D will provide valuable experience with the models and solver settings for your problem in a short amount of time.

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CFD Analysis: Basic StepsSolver

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• Examine the results to review solution and extract useful data.• Visualization Tools can be used to answer such questions as:

• What is the overall flow pattern?• Is there separation?• Where do shocks, shear layers, etc. form?• Are key flow features being resolved?

• Numerical Reporting Tools can be used to calculate quantitative results:• Forces and Moments• Average heat transfer coefficients• Surface and Volume integrated quantities• Flux Balances

• Are physical models appropriate?• Is flow turbulent?• Is flow unsteady?• Are there compressibility effects?• Are there 3D effects?

• Are boundary conditions correct?• Is the computational domain large enough?• Are boundary conditions appropriate?• Are boundary values reasonable?

• Is grid adequate?• Can grid be adapted to improve results?• Does solution change significantly with adaption, or is the solution grid independent?• Does boundary resolution need to be improved?

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CFD Analysis: Basic StepsPost Processing

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Turbulence modelling

• DNS resolves all the spatial and temporal scales of turbulence structure

• DNS solution is highly accurate

• Very highly computationally expensive as most real world flows are turbulent

• Transference of energy from the largest scales (productive scales) to the smallest (viscous or dissipative scales) can be described through turbulence spectrum of energy (Kolmogorov, 1941)

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• Turbulence is a chaotic change of pressure and velocity• Turbulent flows fluctuate on a broad range of time and length

scales• Therefore it can be very hard to correctly simulate these types

of flows

Numerical modelling + Navier-Stokes equation =Direct Numerical Solution (DNS)

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Turbulence modelling

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• The Kolmogorov scales are given for:

η =ν3

ε

1 4

; ε =U3

L

η is the smallest length of turbulence scales, U is the mean velocity and L is the characteristic length or the domain length

To capture the smallest turbulence phenomena, the cell size of a model has to be η. Thus, the number of cells (N) within a certain characteristic length (L) direction becomes:

N =L

η

Combining the three equations: N=Re3/4; Re = Reynolds Number

For a 3D model: N3D= (Re3/4)3=Re9/4

For Re = 100000, N= 1.8x1011

This means, for DNS, in a characteristic length, the model should have at least 1.8x1011 Computational cellsAssumptions are made to reduce computational expenses

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Turbulence modellingClassical models, based on Reynols Average Navier Stokes (RANS) (time averaged)

1. zero-equation model (Mixing-length),

2. one-equation model Spalart–Allmaras (S–A)

3. two-equations model (k-ε, k-ω, SST k-ω) and

4. seven-equations (RSM - Reynolds Stress Model

Another option: Large Eddy Simulation (LES)• Turbulence effects on the mean flow and the large eddies

are completely resolved• small eddies are included on the solutions by means of a

sub-grid scale model

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Free surface modelling

• Fluid flow problems often involve free surfaces in complex geometry

• In many cases are they are highly transient

• Examples:• flows over spillways,

• in rivers,

• around bridge pilings,

• flood overflows,

• flows in sluices, locks, and a

• host of other structures.

• Two different techniques are commonly followed• Rigid lid approximation and

• Volume of Fluid (VOF) method

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Free surface modelling• Rigid lid approximation

• The free surface is assumed as a frictionless lid

• It is located at a fixed position

• Example work: Lau et al. (2007), Stovin et al. (2013)

• Requires prior knowledge of the exact location of free surface

• Volume of Fluid (VOF) method• The free surface position is not approximated but modelled

• Introduces the concept of volume fraction in each cell

• Is good for dam break type problem where free surface position unknown

• Requires too much computational effort

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Popular CFD Software

Name Site Type Discretization method

ANSYS CFX http://www.ansys.com commercial Finite Volume

FLUENT http://www.fluent.com commercial Finite Volume

STAR-CD http://www.cd-adapco.com commercial Finite Volume

COMSOL Multiphysics http://www.comsol.com commercial Finite Elements

FLOW-3D https://www.flow3d.com/ commercial Finite Difference

FEATFLOW http://www.featflow.de open-source Finite Element

OpenFOAM http://www.openfoam.com open-source Finite Volume

As of now, CFD software is not yet at the level where it can be blindly used by designers or analysts without a basic knowledge of the underlying numeric.

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Experiments vs. Simulations

Experiments Simulations

Quantitative description of flow phenomena using measurements• for one quantity at a time• at a limited number of points and time

instants• for a laboratory-scale model• for a limited range of problems and

operating conditionsError sources: measurement errors, flow disturbances by the probes

Quantitative prediction of flow phenomena using CFD software• for all desired quantities• with high resolution in space and time

• for the actual flow domain• for virtually any problem and realistic

operating conditionsError sources: modeling, discretization, iteration, implementation

CFD gives an insight into flow patterns that are difficult, expensive or impossible to study using traditional (experimental) techniques

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CFD Applications

Fluid flows encountered in everyday life include • meteorological phenomena (rain, wind, hurricanes, floods, fires)

• environmental hazards (air pollution, transport of contaminants through air or water)

• heating, ventilation and air conditioning of buildings, cars etc.

• combustion in automobile engines and other propulsion systems

• interaction of various objects with the surrounding air/water

• complex flows in furnaces, heat exchangers, chemical reactors etc.

• processes in human body (blood flow, breathing, drinking . . . )

• and many more

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CFD Applications

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Rising of an air bubble

Drop impacting a water pool

Source: www.youtube.com/watch?v=4hSJ7_5PDL4

Source: www.youtube.com/watch?v=uVFrCNNQU1I

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CFD Applications

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CFD simulation of a mulita flap wave energy converter CFD Flexible Cylinder_ wave generation in FSI+Free-Surface flow

Scouring in a river due to a rectangular pier Wave breaking on a light house

Source: www.youtube.com/watch?v=9NzewSmADuk www.youtube.com/watch?v=1sMxI80Xveg

Source: www.youtube.com/watch?v=yM394whLGbYSource: www.youtube.com/watch?v=zyJudx28UK4

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Institut für Numerische Simulation University of Bonnwww.quics.eu

CFD Applications

Flow through a weir

Source: www.youtube.com/watch?v=P0Pb_sXQUsY

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CFD Applications

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Flood in a valley

Source: www.youtube.com/watch?v=3q8EY4zBf3w08/01/2017 24

• CFD modelling can be applied to

simulation of smoke emission from

a power plant

• Simulation done by Ansys CFX

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Source: https://www.youtube.com/watch?v=kAkRZtyI72g

Smoke flow from a Nuclear Chimney

CFD Applications

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Application of CFD

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Source: https://www.youtube.com/watch?v=kAkRZtyI72g

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Source: www.youtube.com/watch?v=e9oEv_Tw7ow

CFD Applications

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One should know about the software package• Different software package comes in different forms• One should know the pro’s con’s of Software packages s/he usingMeshing and Geometry• In CFD solution method and results is largely dependent on the mesh• It is expected to check mesh independency for the solutionMomentum Equation vs. Approximate Flow Models• An accurate treatment of fluid momentum is important, as

• it is the only way to predict how fluid will flow through complicated geometry• the dynamic forces (i.e., pressures) exerted by the fluid can only be computed from

momentum considerations• to compute the convective transport of thermal energy, it is necessary to have an

accurate picture of how individual fluid particles move in relation to other fluid particles and confining boundaries

Liquid-Solid Heat Transfer Area• In case of metal to liquid heat transfer between a liquid and a solid (e.g., metal-to-mold),

it requires an accurate estimate of the interfacial areaControl Volume Effects on Heat Transfer• The size of control volumes can influence the rate and amount of heat exchanged

Important things to notice in CFD

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Implicitness and Accuracy• Implicit methods for nonlinear and coupled equations require iterative solution

methods that have the character of an under-relaxation in each iteration. This behavior can cause significant errors (or very slow convergence)

Implicit Numerical Methods For Convective Transport• Implicit numerical techniques that allow large time-step sizes, which is popular

to use in calculations to reduce CPU time requirements• Unfortunately, these methods are not accurate for convective processes• Implicit methods gain their time-step independence by introducing diffusive

effects into the approximating equations (numerical diffusion)• The addition of numerical diffusion to physical diffusion, e.g., to heat

conduction, may not cause a serious problem as it only modifies the diffusion rate.

• However, adding numerical diffusion to convective processes completely changes the character of the physical phenomena being modeled

Important things to notice in CFD

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Know your Math!!!

Important things to notice in CFD

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Oh really!

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Case Study

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Effect of surcharge on gully-manhole flow , Beg et al. (2016); under review

Physical model setup08/01/2017 31

Numerical Model set up

X= 0m

Y= 0m

Y= 0.4m

Y= 0.1m

Y= 1.5m

X= 4.5m

P23

Inlet flow

meterOutlet

Valve

Inflow

Manhole 1Manhole 2

X= 14m

P11

X= 15mX= 6m

P22

X= 12.5m

P12

X= 9.25m

P18

Numerical

Model

Domain

2

2

1

1

3

Inlet

Outlet

Atmosphere

3

• SnappyHexMesh• Mesh size 2.5cm at manhole and 2.5-10cm at the pipe

• 1.75 cm at the walls• 210,000 computational meshes

Case Study

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Case Study

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Beg et al. (2016)

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Case Study

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Beg et al. (2016); under review

0.64m surcharge 1.22m surcharge 2.15m surcharge

Q= 7.44 l/s Q= 5.52 l/s Q= 6.44 l/s

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Case Study

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Beg et al. (2016); under review

Cd Remarks

Zone 1 0.677 Free outfall to the atmosphere, like a plunging jet to the manhole

Zone 2 0.755 Submerged jet condition

Zone 3 0.820 Reverse flow from manhole to the gully

Discharge coefficient of the gully outlet for different surcharge conditions

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Case Study

Experimental Numérico (usando laminar)Numerical (using Smagorinsky LES)

Dimension: 60x30x30cm Q= 4 l/s

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Case Study: Flow around a circular pier

The flow structure around a pier is one extensively checked phenomena. Two cases are shown together: Baykal et. al. (2014)

Flow and scour around a vertical cylinder exposed to current • Three-dimensional numerical model based on incompressible Reynolds averaged Navier–

Stokes equations• The model incorporates

(i) k-ω turbulence closure for Baykal et. al. (2014) and LES for Ramos et al. (2016), (ii) vortex shedding processes, (iii) sediment transport (both bed and suspended load), as well as (iv) bed morphology

Findings:• Bed material is eroded and piled up along the edges of the scour hole downstream by

means of the small-scale counter-rotating streamwise• The slopes of the scour hole at both the upstream and downstream sides of the pile in

the simulations are found to be in agreement with observations(Baykal et. al. 2014, DOI: 10.1098/rsta.2014.0104)

(Ramos et al. 2016, DOI: 1015142/T3C014)www.quics.eu08/01/2017 37

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Case Study: Flow around a circular pier

(Ramos et al. 2016)08/01/2017 38

Case Study: Flow around a circular pier

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(Baykal et. al. 2014)

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Conclusion•CFD is a newer era of computational fluid dynamics

• It is based on Navier-Stokes equations

•The application can be from very small scale structures to very large scale structures

•The modeller needs to have good knowledge about the solver before starting a simulation

•There could be vast amount of information in a CFD simulation results. One needs to have a good idea what to acquire

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Thank youfor your attention

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Md Nazmul Azim BegEmail: mnabeg@uc.pt, nazmul.azim@gmail.com

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Special Thanks

I would like to thank to P. Lopes, University of Coimbra PT and P. Ramos, University of Ghent BE; for helping me with their CFD modelling examples to

show in this presentation

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References1. Baykal C, Sumer BM, Fuhrman DR, Jacobsen NG, Fredsøe J. 2015 Numerical investigation of flow and

scour around a vertical circular cylinder. Phil. Trans. R. Soc. A 373: 20140104. http://dx.doi.org/10.1098/rsta.2014.0104

2. CFD-Wiki http://www.cfd-online.com/Wiki/Main Page

3. Lau, S. D. (2007). “Scaling Dispersion Processes in Surcharged Manholes.” Department of Civil and Structural Engineering, University of Sheffield, University of Sheffield, SHeffield, UK.

4. Stovin, V. R., Bennett, P., and Guymer, I. (2013). “Absence of a Hydraulic Threshold in Small-Diameter Surcharged Manholes.” ASCE Journal of Hydraulic Engineering, 139(September), 984–994.

5. Beg, M. N. A., Carvalho, R., Lopes, P., Leandro, J., and Melo, N. (2016). “Numerical Investigation of the Flow Field inside a Manhole-Pipe Drainage System.” Hydraulic Structures and Water System Management. 6th IAHR International Symposium on Hydraulic Structures, B. Crookston and B. Tullis, eds., Portland, Oregon, USA, 1–11

6. Institute of Numerical Simulations, University of Bonn: https://www.ins.uni-bonn.de; https://www.youtube.com/channel/UCY51fXOLUUz2h_wRPgagR6g

7. Beg, Md Nazmul Azim, R. F. Carvalho, J. Leandro, P. Lopes, and L. Cartaxo. 2016. "Investigation of the Flow Field inside a Drainage System: Gully – Pipe – Manhole." Full Proceedings: IJREWHS 2016. Lubeck: International Association for Hydro-Environmental Engineering and Research. 12. doi:10.15142/T3859Z.

8. Ramos, P. X., R. Maia, L. Schindfessel, T. De Mulder, and J. P. Pêgo. 2016. "Large Eddy Simulation of the water flow around a cylindrical pier mounted in a flat and fixed bed." Full Proceedings: IJREWHS 2016. Lubeck: International Association for Hydro-Environmental Engineering and Research. 86-100. doi:10.15142/T3C014.

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