CFD : Modern Applications, Challenges and Future Trends

Computational Fluid Dynamics
Modern Applications, Challenges and Future
Trends

Arab Academy for Science, Technology and Maritime Transport, 28th March 2012

Dr. Khalid M. Saqr
B.Sc (Alex. Uni.), M.Eng (UTM), PhD (UTM)

© All copyrights belong to Dr. Khalid M. Saqr. All rights reserved.
28/03/2012

Outlines
I. CFD in a nutshell
• Tool or an engineering science?
• Frame of reference of CFD
II. Modern CFD codes
• Building blocks of modern codes
• Commercial vs. open source codes
III. Modern applications of CFD
• Industrial sector
• Medicine and biomechanics
• Homeland security
IV. CFD for combustion applications
• Modeling of turbulent vortex flames
V. Contemporary challenges
• Physical models
• Computational requirements
• Benchmarking and validation
VI. Future trends
• Mesh-free methods
• Low-cost HPC
• Runtime validation concept


I. CFD in a nutshell (definition)

?
CFD: An engineering tool…? Or an independent branch of engineering
science ?
Computational
homodynamic

Computational
Oceanography

2nd World War weaponry
1930s – 1940s 2000 – 2010s

I. CFD in a nutshell (definition)

Computer Science
Fluid Mechanics
&
Software Engineering
Heat Transfer

CFD
Electromagnetic field Processor development

Chemical reaction Parallel computing

Physical
& Life Sciences
Engineering science

Geophysics Vascular medicine

Oceanography
21st Century definition of CFD:
Solving the governing equations of fluid flow -by using computational methods-
under various physical conditions (e.g. heat transfer, radiation, electromagnetic
field, nuclear reaction…etc.) to study different phenomena encountered in the
numerous branches of physical science.


I. CFD in a nutshell (frame of reference)

Frame of reference of engineering CFD

Theories of Continuum Molecular / Quantum theory
matter: hypothesis Kinetic theory

Mechanics: Newtonian Relativistic

Chaos theory: Deterministic Random chaos
chaos

1. Matter (i.e. fluid) is assumed to be a continuum, and its properties
and characteristics can be described by field functions.
2. These field functions are functions in Euclidian space and time, and
their frame of reference is an inertial one.
3. The sensitive dependence on initial conditions described by the
governing partial differential equation does not involve any random
events


II. Modern CFD Codes (theoretical basis)

Formulation of field equations

Eulerian Lagrangian
Methods are not sufficiently
FVM FEM mature for engineering
applications.
Commercial codes: Commercial codes:
-Fluent -Lattice Boltzmann Method
-COMSOL
-CFX -DSMC
-CFD++ -ADINA
-FLACS -SPH
-FloTHERM
-COSMOS Open-Source:
-EFDLab
-Elmer No commercial codes.
-FlowVision
-PHOENIX Only “experimental”
-… many more ! Open-Source codes !
Open-Source:
-OpenFOAM
-Code_Saturne
-FDS
-OpenFVM


II. Modern CFD Codes (building blocks)

What to :
Building Blocks

Geometry &
Presume • Boundary / initial conditions
• Physical models

grid generation
and what to :
module • Physical phenomena (i.e. heat

Neglect transfer, chemical reaction…etc)
• Properties (i.e. compressibility, real
Problem settings gas…etc)

module
and what to :

Calculate
• Unknowns
• Relationships between field variables
Solution module

Visualization Solution methods and algorithms
module • Spatial / temporal descritization schemes
• Convergence criterion
• Interpolation methods
• …etc.


II. Modern CFD Codes (Open-source vs. commercial)

Feature Open-source Commercial
Customization of Excellent Good
physical models

Customization of Excellent Poor
numerical schemes

Authenticity of Excellent Good
physical models
User friendliness Poor Excellent

Free technical Poor Good
support
Paid technical Excellent Excellent
support
Academic use Excellent Poor ~ Good

Industrial use Poor Excellent


III. Modern Applications of CFD
• Industrial sector (examples)
– Electronics cooling

– Chemical engineering



Vascular homodynamic

Respiratory system
aerodynamics

Air-breathing disease
transmission

Velocity magnitude plotted on a midplane slice of the abdominal aorta for one representative
subject under resting (left) and simulated exercise (right) conditions.




Respiratory system
aerodynamics

Airborne transmission of
respiratory infectious diseases

Deposition enhancement factors (DEFs) for a steady state inhalation ﬂow rate of 30 L/min in a
cast-based model of the upper TB airways with particle sizes of (a) 40 nm and
(b) 4 μm. DEF values represent the ratio of locally deposited mass to total deposited mass in
the airway. Signiﬁcant enhancement in local deposition is observed for both nanometer
(factor of 25) and micrometer (factor of 110) aerosols.




Respiratory system
aerodynamics

Airborne transmission of
respiratory infectious diseases

Airflow streamlines of supplied and exhaled airflows in Scenario #1: (a) supplied airflow; (b)
exhaled airflow of P8; (c) exhaled airflow of P12; (d) exhaled airflow of P21; (e) exhaled
airflow of P27; (f) exhaled airflow of P30.


• Homeland security

– Simulation of
atmospheric dispersion
of a contaminant
released in downtown
Portland, Oregon. The
wind is from the west
and the contaminant is
released at the small
yellow “+.”

Annu. Rev. Fluid Mech.
2006. 38:87–110


1- Deflagration
Stationary Flames
Propagating flames 2- Detonation
Classification according Flames
to temporal development Propagating Flames
Stationary flames
1- Laminar Flames
2- Turbulent Flames

1- Laminar Flames
Premixed Flames 2- Turbulent Flames
3- Propagating Flames
Classification according 1- Laminar Flames
to pre-mixing between Flames Non-premixed (diffusion) Flames 2- Turbulent Flames

fuel and air 1- Laminar Flames
Partially-premixed Flames 2- Turbulent Flames

Bluff-body stabilization
Stable Flames
Aerodynamic stabilization
Classification according 1- Swirl stabilized flames
2- Vortex stabilized flames
to stability criterion Flames 3- Flow field stabilized flames

1- Thermal instability
2- Aerodynamic instability
Unstable Flames 3- Acoustic instability
4- Chemical instability
5- Electromagnetic instability


• It is a fact that most of engineering combustion systems involve turbulent
flames
• It is also a fact that any turbulent flow problem represent a challenge for CFD
!
• The bottleneck of CFD combustion solvers is the modeling of turbulence-
chemistry interaction

Chemical
Modeling kinetics
problems problems

Turbulence (?) Mixing Chemical reaction (?)

Time scale problem ?
Damköhler number

Density
Pressure
Heat
Thermal conductivity
Viscosity



Turbulence modeling approaches

Isotropic turbulence DNS Anisotropic turbulence

• Algebraic models • Reynolds stress models
• Eddy viscosity models (2 • Filtering approaches (LES,
equations, 4 equations) DES, VLES)
Coupling
Technique • PDF model
• EDM
• Flamelet model • Detailed chemical
• EDC kinetics
Eddy break-up theory Flamelet theory Detailed chemistry

Chemical Reaction modeling approaches


• Modeling of vortex flames

Vortex flame

Swirling flame
1. Enhanced flame stability Applications:
- Micro gas turbines
2. Shorter flame length
- Micro jet engines for miniaturized
UAVs
3. Added flame controllability



Problems that had to be Secondary
recirculation
solved: zones
1. Turbulence modeling of
the vortex flow field in
this complex geometry
2. Find suitable parameters
to study the aerodynamic
vortex field
stability mechanism of
the flame
3. Conduct a parametric
study to reveal the major
characteristics of the
flame


• Major contributions:
1. Formulation of the Rε/k-ε turbulence model
2. The new model variant has been coded into Fluent and
OpenFOAM, tested and validated for several cases of rotation
flows
3. Complete description of all main-flow phenomena in the
asymmetric vortex combustor
4. Identification of the aerodynamic stability mechanism of vortex
flames

Stoichiometric
Reaction Zones


V. Contemporary Challenges
• Physical models

Turbulence Multiphase flow Chemical reaction

- Highly strained - Interaction - Optimize between
flows between primary and physical assumptions
secondary phase and correct chemical
- Atmospheric flow
kinetics
modeling - Integration with
new turbulence - Efficient coupling
- Transitional flow
models with turbulence
regimes
models


• Computational requirements
– Faster processors and larger memories
– Smarter software algorithms
Computational requirements DNS

DES
LES

RANS

Turbulence models (example)


• Benchmarking and validation

Error sources in CFD

Physical models Numerical schemes

Encountered by Encountered by grid
benchmarking and independency studies
validation
Challenges:
1- Unavailability of sufficient experimental data
for some problems (i.e. biomechanics)
2- Generalization of the validation procedure


VI. Future trends in CFD research
• Mesh-free methods (late 1970s – today)
– Smoothed Particle Hydrodynamics (SPH)
– Diffuse Element Method (DEM)

• Hybrid Methods
– Particle in Cell (PIC)
– Lattice Boltzmann Method (LBM)
– Direct Simulation Monte Carlo (DSMC)


• Low-cost HPC Clustering concept
Old / Unused PCs

Linux OS

Network

Parallel CFD code
HPC


• Runtime validation concept (LES, DES)

Problem setup Problem setup Fine tuning

Solution Basic
Pre-solution Validation
Change
Results Model(s)
Solution

Validation invalid Results
valid
Final results
Final results


Thank you


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