Demonstrate the importance of CFD simulations applied to evaluate pressure
and velocity distributions in the engineering setting:
What is Computational Fluid Dynamics (CFD)?
-Historically Analytical Fluid Dynamics (AFD) and EFD (Experimental Fluid
Dynamics) was used. CFD has become feasible due to the advent of high
speed digital computers. Computer simulation for prediction of fluid-flow
phenomena.
What is the objective Computational Fluid Dynamics (CFD)
The objective of CFD is to model the continuous fluids with Partial Differential
Equations (PDEs) and discretize PDEs into an algebra problem (Taylor series),
solve it, validate it and achieve simulation based design.
Importance and usage of Computational Fluid Dynamics (CFD)
1-Analysis and Design
A- Simulation-based design instead of “build & test”
-More cost effectively and more rapidly than with experiments
-CFD solution provides high-fidelity database for interrogation of flow field
B- Simulation of physical fluid phenomena that is difficult to be measured by
experiments
- Scale simulations (full-scale ships, airplanes)
- Hazards (explosions, radiation, pollution)
-Physics (weather prediction, planetary boundary layer, and stellar evolution)
2- Knowledge and exploration of flow physic
Where is Computational Fluid Dynamics (CFD) used?
1- Aerospace
Computational fluid dynamics (CFD) is the numerical study of steady and unsteady fluid
motion. The aerodynamic performance of flight vehicles is of critical concern to airframe
manufacturers, just as is the propulsive performance of aircraft power plants, including
those that are propeller-, gas turbine-, rocket, and electric driven. CFD is used throughout
the design process, from conceptual-to-detailed, to inform initial concepts and refine
advanced concepts. CFD is also used to lessen the amount of physical testing that must
be done to validate a design and measure its performance. CFD is used to predict the
drag, lift, noise, structural and thermal loads, combustion., etc., performance in aircraft
systems and subsystems.
2-Automotive
The achievement of CFD in car simulation is based totally on providing enterprise needs in
place of choosing issues we may additionally simulate: discover an essential broken
manner and offer a solution Numerical simulation tools might be adopted best while they
healthy the product improvement technique: robust, accurate and established solver,
rapid turn-over Experimental and numerical work complement every other even if
sufficient accuracy for predictive simulations can’t be performed Validation of simulation
results information experimental set-up Parametric studies: speeding up experimental
turn-over True impact of simulation equipment is beyond the obvious uses: enterprise
will power the studies effort to answer its needs
3-Biomedical
In the biomedical field, CFD is still emerging. The main reason why CFD in the biomedical
field has lagged behind is the tremendous complexity of human body fluid behaviour.
Recently, CFD biomedical research is more accessible, because high performance
hardware and software are easily available with advances in computer science, Initial
accurate geometric modelling and boundary conditions are essential to achieve adequate
results. Medical imaging, such as ultrasound imaging, computed tomography, and
magnetic resonance imaging can be used for modelling, and Doppler ultrasound, pressure
wire, and non-invasive pressure measurements are used for flow velocity and pressure as
a boundary condition.
4-Chemical Processing
They are started early to make use of CFD as an important tool in chemical
engineering. Experimental CFD codes as well as various sub models to
commercial CFD solvers have been developed recently and have been
successfully applied in various projects such as ‘’ Computational fluid dynamics
(process engineering, energy technology), Flow measurement (unit
operations, multi-phase flow phenomena), Flow and system behaviour of high
temperature industrial processes, Chemical, biotechnological and
environmental applications of thermal separation processes (downstream
processing) and Thermal process engineering (membrane processes,
rectification, absorption)’’
5-HVAC&R
Using smart computer modelling software, CFD enables designers to realistically simulate
air flows within the project space in advance. As a result, we can accurately predict where
problems such as drafts, high sound levels, or poor ventilation may occur. This allows us
to optimise the HVAC system’s design and ensure comfort and effectiveness – before
actual installation work begins.
7-Hydraulics
Computational fluid dynamics (CFD), also known as three-dimensional (3D) hydraulic
modelling, is a practical way to predict and visualize how water flows in real-world
conditions – including in rivers, stormwater structures, and wastewater systems. CFD
solves fundamental flow equations that describe how physical laws govern fluid motion.
It also provides detail and insight that one-dimensional (1D) and two-dimensional (2D)
hydraulic models cannot deliver by resolving the flow in three directions. Simply put, CFD
delivers the practical benefits of physical modelling in a reasonable time and budget.
8-Marine
CFD methods are unexpectedly gaining popularity in the industry. Engineers who design
complicated marine structures including ships and oil structures, an increasing number of
rely on CFD to predict such things as ship drag and dynamic movement in waves, wave
loading on offshore structures and the behavior of water when tons of it gather on a
ship’s deck because of big, storm-pushed waves.
9-Oil & Gas
The CFD Analysis for a horizontal separator used for crude oil. Under normal operation the
separator splits the crude oil into its 3 phases (oil, water & gas) while maintaining a certain
level of water at the bottom. The water at the bottom of the vessel helps prevent gas from
leaving through the water and oil outlets. CFD Analysis can help determine what happens
when an upstream slug of gas hits the separator. Predictions can be made that help
determine the mixture interface levels and where the interfaces need to be located to
withstand given amounts of upstream gas slugging.
10-Power Generation
The power generation and combustion industries. The intention is to illustrate what may
be carried out and additionally to pick out trends and people areas where similarly
paintings is needed. Examples encompass coal-fired low-NOx burner design, furnace
optimizations, over-hearth air, and gasoline reborn, and laminar flames. It is argued that
the fashion is for CFD fashions to become more complete and accessible through being
coupled to other technique models and embedded in automated facts and method
control systems.
Importance of Computational Fluid Dynamic (CFD) simulations applied to
evaluate pressure and velocity distributions in the engineering setting
Experiments
Simulations
for a limited range of problems and
operating conditions
for virtually any problem and realistic
operating conditions
Error sources: measurement errors,
flow disturbances by the probes
Error sources: modelling, discretize ton, iteration, implementation
at a limited number of points and
time instants
with high resolution in space and
time
for a laboratory-scale model
with high resolution in space and
time
expensive
cheap
slow
fast
Quantitative description of flow
phenomena using measurements
Quantitative prediction of flow
phenomena using CFD software
for one quantity at a time
for all desired quantities
sequential
parallel
single-purpose
multiple-purpose
The results of a CFD simulation are never reaching 100% reliable
1-the mathematical model of the problem at hand may be inadequate
2-the input data may involve too much guessing or imprecision
3- The accuracy of the results is limited by the available computing power
Complete CFD simulation to evaluate pressure and velocity distributions
within an engineering setting:
-components of fluid mechanics
-Compressible and Incompressible flow
A fluid flow is said to be compressible when the pressure variation in the flow
field is large enough to cause substantial changes in the density of fluid.
Viscous and Inviscid Flow
In a viscous flow the fluid friction has significant effects on the solution where
the viscous forces are more significant than inertial forces
Evaluate the application and limitations of CFD in an engineering context
Applications (CFD):
1-Determining cause of performance issues
2-analysis and evaluation of user comfort by using a 2D or 3D flow simulation
3-Validating initial design performance
4-analyses of glass roofs on top of atriums and malls and the implementation
of smoke and heat exhaust ventilation systems
5-planning and optimization of procedural air streams
6-Optimizing design to improve performance
Advantages (CFD):
1-specific physical boundary conditions or effects can be considered in
isolation
2-simulations provide at any point (of the pattern) measured data,
experiments in contrast only a few selected points
3-many flow parameters are gathered, which are not accessible in
experiments
4-in the beginning of the planning process, a variety of prototypes are
simulated in order to quickly gather information for further planning
5-simulations are able to contribute to a greater understanding of the problem
than experiments
6-the costs are usually much lower compared to experiments
7-It makes it possible to evaluate geometric changes with much less time and
cost than would be involved in laboratory testing
8- It provides flexibility to change design parameters without changing actual
system changes thereby allowing engineers to try more alternative designs
which would be feasible
9- CFD results can provide the necessary confidence which other simulating
tools are unable to provide
10-CFD offers low cost than the physical testing methods which help in
understanding essential engineering data for design which can be expensive
11- It helps in modifying the design of various equipment’s like spray drier.
Here CFD is used to analyse the performance of industrial spray drier so as to
make necessary changes to drier when possible
12- It allows the analyst to examine large number of locations in particular
region of interest
Limitations (CFD):
1-errors may occur due to simple flow models or simplified boundary
conditions
2-possible uncertainties caused by too little computing values per cell and
hence therefore resulting interpolation errors
3-computation time may extend for large models
4-the costs may be much higher due to wrong consulting compared to
experiments
5- If you don’t have experimental setup, then CFD is the only choice
6- An option to validate experimental results
Simulations
1-for virtually any problem and realistic operating
conditions
2-Error sources: modelling, discretize -ton, iteration,
implementation
3-with high resolution in space and time
4-with high resolution in space and time
5-cheap
6-fast
7-Quantitative prediction of flow phenomena using
CFD software
8-for all desired quantities
9-parallel
10-multiple-purpose
Provide supported and appropriate recommendations for improving efficiency
and the generation of suitable mesh for CFD simulations:
Grid generation
Grids can either be structured (hexahedral) or unstructured (tetrahedral).
Depends upon type of discretization scheme and application
Scheme
1-Finite differences: structured
2-Finite volume or finite element: structured or unstructured
Application
1-Thin boundary layers best resolved with highly-stretched structured grids
2-Unstructured grids useful for complex geometries
3-Unstructured grids permit automatic adaptive refinement based on the
pressure gradient, or regions of interest (FLUENT)
Grid generation and transformation
1-Grids designed to resolve important flow features which are dependent
upon flow parameters
2-Commercial codes such as Gridgen, Gambit
3-For research code, grid generated by one of several methods (algebraic vs.
PDE based, conformal mapping)
4-For complex geometries, body-fitted coordinate system will have to be
applied (next slide). Grid transformation from the physical domain to the
computational domain will be necessary
Grid transformation
Transformation between physical (x,y,z) and computational domains,
important for body-fitted grids. The partial derivatives at these two domains
have the relationship (2D as an example)
Velocity Map
Determine the faults in the application of simulation techniques:
1-User faults
User errors result from incorrect use of CFD software and are usually a result
of insufficient expertise by the CFD user. Errors can be reduced or avoided by
additional training and experience in combination with high-quality project
management and by provision and use of Best Practice Guidelines and
associated checklists.
2-Modeling faults
Modelling errors result from the necessity to describe flow phenomena such
as turbulence, combustion, and multi-phase flows by empirical models. For
turbulent flows, the necessity for using empirical models derives from the
excessive computational effort to solve the exact equations with a Direct
Numerical Simulation (DNS) approach
3-Numerical faults
Numerical errors result from the differences between the exact equations and
the discretized equations solved by the CFD code. For consistent discretization
schemes, these errors can be reduced by an increased spatial grid density
and/or by smaller time steps
4-Software faults.
Software errors are the result of an inconsistency between the documented
equations and the actual implementation in the CFD software.
Discuss and evaluate the modelling method and data accuracy
1-Analog signal input.
An analog input converts a voltage level into a digital value that can be stored and
processed in a computer. The signals from sensors that measure surrounding natural
factors such as temperature, pressure, and flow rate are often analog signals, and most
control actuators move according to analog signals. On the other hand, only digital signals
can be handled by computers. For this reason, in order to input a signal from a sensor
using a computer, or to output a signal to an actuator, it's necessary to have a device that
can bridge the analog signal and the digital signal handled by the computer. That bridge is
called an analog I/O interface.
2-A/D converter.
In electronics, an analog-to-digital converter (ADC, A/D, or A-to-D) is a system that
converts an analog signal, such as a sound picked up by a microphone or light entering a
digital camera, into a digital signal. An ADC may also provide an isolated measurement
such as an electronic device that converts an input analog voltage or current to a digital
number representing the magnitude of the voltage or current. Typically the digital output
is a two's complement binary number that is proportional to the input, but there are
other possibilities. A digital-to-analog converter (DAC) performs the reverse function; it
converts a digital signal into an analog signal.
Applications
1-Music recording
2-Digital signal processing
3-Scientific instruments
4-Rotary encoder
3-Anti-alias filter
An anti-aliasing filter (AAF) is a filter used before a signal sampler to restrict
the bandwidth of a signal to approximately or completely satisfy the Nyquist–
Shannon sampling theorem over the band of interest. Since the theorem
states that unambiguous reconstruction of the signal from its samples is
possible when the power of frequencies above the Nyquist frequency is zero,
a real anti-aliasing filter trades off between bandwidth and aliasing. A
realizable anti-aliasing filter will typically either permit some aliasing to occur
or else attenuate some in-band frequencies close to the Nyquist limit. For this
reason, many practical systems sample higher than would be theoretically
required by a perfect AAF in order to ensure that all frequencies of interest
can be reconstructed, a practice called oversampling.
4-Overlap
Overlap technique, a very short spectral event (particularly one that does not even last as
long as one frame) can be seen (even if at reduced amplitude) in many sets of spectra
that are displayed adjacent to each other.
5- Windowing
Windowing system, a graphical user interface (GUI) which implements
windows as a primary metaphor
6-Averaging
A-Linear averaging
B-Peak hold
C-Exponential
D- Synchronous time averaging
7-FFT
Redundantly called “Time Synchronous averaging”, was discussed earlier as a
method of background noise reduction in spectra of complex signals. ...
Synchronous averaging is a fundamentally different process.
8-Display / storage.
Signal processing storage techniques are used to improve signal transmission fidelity,
storage efficiency, and subjective quality, and to emphasize or detect components of
interest in a measured signal.
7-Extract relevant information from simulation (Vibration monitoring, Acoustic emission,
Oil analysis, Particle analysis, Corrosion monitoring, Thermography, Performance
monitoring).
-What is predictive maintenance?
Predictive maintenance is a technique that uses condition-monitoring tools and
techniques to track the performance of equipment during normal operation to detect
possible defects and fix them before they result in failure. Ideally, predictive maintenance
allows the maintenance frequency to be as low as possible to prevent unplanned reactive
maintenance, without incurring costs associated with doing too much preventive
maintenance.
1- What is the Acoustic emission of predictive maintenance?
-MHC sensors are quite unlike conventional acoustic emission sensors used for condition
monitoring purposes. The key to their predictive maintenance success is the unique
crystal arrangement which enhances sensor-to-sensor reproducibility and forms the
foundation on which successful and rapid signal interpretation is based.
-The MHC sensor range extends from a simple transducer with integral preamplifier
design, all the way through to industry-leading intelligent microprocessor sensors.
2- Vibration monitoring for predictive maintenance
For example: - vibration sensor connect to a motor to detect vibration in a CNC mill. The
sensor is new, shiny, and sends notifications when vibration exceeds a set value. The
software accompanying the sensor also sends notifications about vibration history and
suggests when and what type of maintenance should be done on the motor based on
data.
3- Oil Analysis for predictive maintenance
Oil analysis is another powerful technology which has many applications across different
industries. An oil sample can be tested for viscosity, wear particles, the presence of
water, and more. In industrial facilities, oil analysis is commonly used to monitor critical
equipment such as compressors and gearboxes. In the transportation industry, tests on
diesel engines are common and vital. Diesel engines found in trains, buses, trucks, and
ships are often pushed to the limit in harsh operating conditions. Oil analysis provides an
opportunity to monitor the condition of these engines in a way that other predictive
technologies cannot.
4- Particle Analysis
Particle analysis is widely described as the process in which dry, free-flowing material is
analysed to determine the size and shape of the individual particles, Particle analysis is
conducted by companies that want to ensure that the product, whether it's something
they are producing or purchasing from another company to put into their products, meets
the standards needed to provide the consistency or quality they are looking for, In plastic
extrusion, for example, particle analysis is used to determine the batch size of the
material. When it comes time to melt the plastic for production, they use this batch size
to determine the temperature in which the plastic needs to be heated to for adequate
throughput, Failure to implement reliable particle analysis can lead to product recalls and
early product failure because the starting material was not the right size and could not
withstand production.
5-Predictive Maintenance Infrared (IR) Thermography
Technicians can use the thermal camera to check the temperature of critical equipment
which allow to track the operating condition over time and quickly identify readings for
future comparisons as well, Thus by monitoring the performance can schedule
maintenance only when it’s required which will result in unplanned downtime due to
equipment failure and can also contribute to extend the working life of machine assets.
6- Corrosion monitoring
The field of corrosion measurement, control, and prevention covers a very broad
spectrum of technical activities. Within the sphere of corrosion control and prevention,
there are technical options such as cathodic and anodic protection, materials selection,
chemical dosing and the application of internal and external coatings. Corrosion
measurement employs a variety of techniques to determine how corrosive the
environment is and at what rate metal loss is being experienced. Corrosion measurement
is the quantitative method by which the effectiveness of corrosion control and prevention
techniques can be evaluated and provides the feedback to enable corrosion control and
prevention methods to be optimized.
7- Performance monitoring
A system performance monitor primarily collects and reports key performance indicators
and metrics into the operational state of a system. Most operating systems have a native
SPM application/component that displays factual and graphical stats for system
performance. Some of the performance metrics/data collected by an SPM include the use
of the CPU, memory, hard disk and network. It also includes the ability to provide
suggestions and guidelines toward improving performance and tuning/optimizing the
system automatically. SPM is a key tool in any system administrator's job because it
provides system-wide insight and aids in decision-making.
8-
1- Belt drive problems
-Belt-drive problems, which include shaft misalignment, pulley misalignment, belt wear,
belt resonance, belts too tight, belts too loose, pulley eccentricity and bent shafts, can be
relatively straight forward to detect but can be far more difficult to specifically diagnose
and correct. That is mainly due to the wide variety of problems that can occur in the
installation and assembling of the belt drive, the difficulty of doing field testing on belts
and the possibility of other influences (i.e. the base) having some effect.
- The good news, especially in the case of component (belt and pulley) wear, is that belts
and pulleys are typically relatively easy to inspect and inexpensive to replace. The bad
news is that outside of that, they're often difficult to correct. One positive development
in recent years has been the availability of laser alignment units for belt drives for a
moderate price. Unfortunately, in more cases than not the old string & straight edge is
still the alignment method used for belt drives. The first step to identifying a belt problem
is to determine the belt speed.
2- Bearing defects
a) Abrasive damage: - Fine scratches caused by particles in the lub oil. Very common on
HFO burning engines.
b) Erosion damage: - Removal of the overlay in strips caused when the oil supply pressure
is low or rapid journal movements occur. More usual on medium speed engines.
c) Fatigue damage: - The overlay becomes detached from the lining when the bearing
load becomes too high. The bearing surface loads cracked paving.
d) Corrosion: - Discoloration and roughening of the bearing surface indicates that the oil
has become acidic.
e) Wiping: - This is overlay removal by melting wiping can be re-alignment of the bearing
to journal, but if too much metal has been removed then clearances may be affected.
3- Mechanical looseness
- Rotating looseness means that there is too much room between rotating and stationary
elements in the machine. Non rotating looseness means that the distance between two
stationary parts is too big. Both types generate extensive vibrations at 1X harmonics in all
three directions.
There are two types of mechanical looseness, first type is ‘’Rotating looseness’’
-Bearing clearance in journal bearings or rolling element bearings generates 1X
harmonics, which sometimes stretches to 10X. If the high harmonics are dominating
collisions can be suspected.
Second type is ‘’Non-rotating looseness’’
- Non rotating looseness causes the highest vibrations in the direction where the stiffness
is the smallest. The stiffness is usually least in the horizontal direction, but it depends on
the physical layout of the machine. Loose foundation can be causes by loose bolts, rust or
cracks.