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CFD Analysis 

Professional Computational Fluid Dynamics Simulation

CFD analysis services are one of the main consulting strengths of our team of specialized CFD consulting experts at our Singapore Office in BroadTech Engineering.
Computational Fluid Dynamics (CFD) simulation analysis works by giving engineers total insights into Dynamic fluid flow behaviors, such as Airflow and Thermal temperature distribution. CFD Flow analysis can be incorporated early in your engineering development process during the conceptual phase to Validate and Optimize Designs.
As CFD analysis provides a Qualitative (and occasionally Quantitative) prediction of a fluid flow behavior, our CFD consulting services allows Simulation Engineers and Scientists to perform ‘numerical experiments’ (i.e. computer simulations) in a ‘virtual flow laboratory’ to accurately simulate product design performance, Optimize and Improve Design performance, and Verify product Fluid Dynamic behavior as early as possible in the engineering development phase.

What is Computational Fluid Dynamics (CFD)

Computational Fluid Dynamics (CFD) is a highly multidisciplinary area of research which lies at the interface of Physics, Applied mathematics, and Computer science.
CFD simulation is a computational 3-dimensional Fluid Dynamics simulation analysis technology that uses numerical methods to solve and analyze the technical challenges and problems that involve precision engineering of fluid flows and mitigating thermal issues.
CFD Fluid Dynamic Analysis involves replacing Partial differential equations (PDE) systems with a set of Algebraic equations which can be solved mathematically using the digital CFD Simulation Software.

Featured CFD Analysis Case Studies

Turbulence Analysis of Antenna

Turbulence Analysis of Antenna

Our client needed to update the antennas of its first high-speed passenger train to incorporate 4G mobile coverage. Due to the physical size and design of these transmission antennas, a turbulence study was required in order to ensure that no negative aerodynamic influence reached the pantograph area on the locomotive. Different antenna design iterations were evaluated at several speed regimes, checking the pressure distribution and turbulence fields on the pantograph and their associated fluctuating aerodynamic stresses.

Turbine Discharge CFD Analysis

Turbine Discharge CFD Analysis 

Our client builds and installs small turbine systems and their associated facilities. For this project, they needed to improve the mass flow of water fluid extracted from a turbine discharge pool towards the city. The narrow space available at the discharge pool and the filter required for safety protection at the pipe entrance seriously reduced the available water output. Different options were analyzed in order to put the kynetic energy from the turbine output to work to our advantage and maximize available fluid pressure at the extraction pipe.

Features & Benefits of Computational Fluid Dynamics (CFD)

CFD Computational Fluid Analysis offers an engineering insight into fluid flow pattern behaviors that are challenging, expensive or impractical to recreate and study using traditional experimental techniques.
CFD simulation software offers many advantages such as

1. Informed Engineering Decisions

This allows design teams to make informed engineering and operational based decisions so as to create Products and Processes which are more Efficient, Integrated and optimized to Performs better-optimized performance.
The use of CFD services to analyze the development of specific engineering applications allows you to implement the best fit solution for your unique application, minimize the risk of failure, maximize performance efficiency.

2. Adaptability

The flexible option to offer easy & fast adjustment of test configuration makes it possible to save prototype testing time by having the ability to carry out parallel, Multiple-purposed model design Verification testing on practically any test configuration.
This is in contrast to Conventional single-purposed Physical testing which is usually Slow, Sequential.

3. Comprehensive & Accurate Test Input Parameters

Can Account for All Operational Environmental Conditions
Computational Fluid Analysis carried out by a CFD software offers a Realistic Quantitative simulation of fluid flow phenomena which takes into account all the desire input qualities.

Accurate Mathematical model

Simulation in a virtual time and space environment allows the creation of a Mathematical model which is High resolution and Full Scale (instead of sized-down models in physical experiments)

4. Lower Cost


1. Testing Cost

Cheaper cost of testing and validation of new innovative designs by removing the need for expensive physical fatigue testing of prototypes.
It also eliminates the need for the use of actual physical Test Equipment which is physically challenging and expensive to transport. This allows for a larger number of test simulation studies to be carried out and gives a larger collection of data points and time instants

2. Capital Cost

Gain confidence in a design concept before committing large investment financially and in terms of project resources
This help organization to effectively reducing both capital and operational costs.

3. Operational Cost

Increase overall efficiency of facility through CFD simulation of various set points and loads

5. Maximize Operation Uptime

CFD simulation analysis is able to identify and highlights any Potential issues or Failure scenario before they arise.
This allows for the understanding of effective ways to improve system redundancy so as to Maximize Operation uptime and Optimize the efficiency of system performance.
This approach often adopted by CFD companies helps to provide an effective design and gives confidence that your building facility and equipment will perform at its best.


About Us

BroadTech Engineering is a Leading Engineering Simulation and Numerical Modelling Consultancy in Singapore.
We Help Our Clients Gain Valuable Insights to Optimize and Improve Product Performance, Reliability, and Efficiency.


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CFD Analysis

1. Powerful CFD Simulation Software Tools

2. FEA Consultants with Extensive Research & Professional Experience

2. FEA Consultants with Extensive Research & Professional Experience

3. FEA projects Completed in a Timely and Cost-effective Manner

3. FEA projects Completed in a Timely and Cost-effective Manner

4. Proven Track Record

4. Proven Track Record

5. Affordable

5. Affordable

6. Full Knowledge Transfer

6. Full Knowledge Transfer

Computational Fluid Dynamics (CFD) Process

CFD is performed/carried out by means of using the following methods

1. Mathematical Model

Mathematical CFD modeling of fluid analysis challenge to be solved expressed using Partial differential equations (PDE) eg. IBVP = PDE + IC + BC

2. Discretization Process

The Discretization process involves having the PDE system mathematically transformed into a set of algebraic equations. Numerical analysis methods based on discretization includes

1. Mesh Generation

This involves decomposition of the model into Cell elements and Time instants.
The Node elements can be either Structured or unstructured, Triangular or Quadrilateral.

• Adaptive refinement of Mesh element size in Flow areas of interest
• CAD tools + grid generators (Delaunay, advancing front)

2. Space Discretization

This is the approximation of spatial derivatives based on coupled ODE/DAE systems

• high- vs. low-order approximations

3. Time Discretization

Time discretization is the approximation of temporal derivatives using Algebraic system Ax = b

• Explicit vs Implicit schemes, Stability constraints
• Local time-stepping, Adaptive time step control

3. CFD Simulation Software

Involves implementation of CFD Computer simulation software algorithm tools (Iterative solvers, Discrete function values, Pre- and postprocessing utilities) and Computer hardware to solve mathematical equations
The computing time taken for a CFD flow simulation depend on

• Choice of Numerical algorithms and Data structures
• Programming language used for coding the CFD Code (most use/adopts Fortran)
• Discretization parameters (mesh quality, mesh size, time step)
• Vectorization, Parallelization
• Run parameters and Stopping criteria
• Cost per time step and convergence rates for outer iterations
• Linear algebra tools, Stopping criteria for iterative solvers
• Computer hardware

4. Post-processing Visualization, Analysis of data

The human (simulation consultant) component input involved in this CFD simulation analysis involves stating the problems & inspection.
Post-processing of the CFD simulation results involves interpretation of the computed flow field to extract the desired information. This calls for knowledge and good judgment.

1. Calculation

This involves the calculation of Derived quantities (such as Streamfunction, vorticity) and Integral parameters (lift, drag, total mass)

2. Visualization

Visualization involves representation of numbers as visual images

– 1D data: function values connected by straight lines
– 2D data: streamlines, contour levels, color diagrams
– 3D data: cutlines, cut planes, isosurfaces, isovolumic

3. Analysis

Using Statistical tools the simulation data is Systematically Analyzed to Verify the CFD model

Call Us for a Free Consultation

Customers will be provided with fully customisable CFD reports which detail the Methodology, in-depth analysis, and recommendations.
This insight allows our customers to optimize performance and make informed engineering decisions in a scientific, proven manner.

Explore what CFD Analysis can do for your company now by calling us today at +6581822236 for a no obligation discussion of your needs.
If you have any questions our knowledgeable and friendly consultant will be happy to assist and understand more about your needs and requirements
Alternatively, for quote request, simply email us your technical specifications & requirements to info@broadtechengineering.com

Other CFD Analysis Case Studies

Simulation of Vortex-induced Vibrations (VIV) in Turbulent Flow


When fluid flows over a bluff body, vortex shed behind the body cause alternating lift force which may cause vibrations if the body is elastic. If the frequency of vibrations is equal to the natural frequency of the body, then very large amplitudes can be produced.


The objective of the project was to determine the effect of the mass of the bluff body and mass of the fluid on VIV. Ultimately, this information will be used to design a power take off for harvesting green energy from ocean tides and wind.
In this simulation, we wrote an in-house C++ code using finite volume method. Turbulence was modeled using large eddy simulation and the bluff body was marked out in the fluid flow using direct-forcing immersed boundary method.


We found that the largest amplitude of vibration is about equal to the diameter of the bluff body. There also exists a strong relationship between the amplitude of vibration and the mass of the bluff body.
In vortex induced vibration project, Fluid-structure interaction (FSI) was modeled using immersed boundary method. We also modeled turbulence using large eddy simulation in which the large eddies are solved by the flow while the small ones are modeled. The small eddies were modeled using Smagorinsky model.

Aerodynamic Analysis of UAV

1. Aerodynamic Analysis of a UAV with propeller ON/OFF conditions.
2. Estimation of Aerodynamic Loads on UAV
3. Ground Effect study on the UAV
Simulations were carried out using flow solver HiFUN and ANSYS-Fluent


1.Aerodynamic Analysis includes,
   Estimation of Aerodynamic performance characteristics at given speed (Subsonic Speed of 30-40 m/s)
2. Simulation of the UAV’s with Propellor ON/OFF conditions and also perform simulations on Propellor failure conditions.
3. Estimation of the Aerodynamic loads on UAV which will be used for structural analysis.
4. Perform static ground effect study on UAV for various ground heights and wing settings.


Grid Generation and Solver setup
1. Hybrid unstructured grids were generated for the UAV with Propeller. There are multiple zones involved in the grids namely Stationary zone and Rotational zones to simulate the propeller effects.
2. For the UAV with Propeller simulations,
Roe scheme with second-order discretization in space was used. Gradients are calculated using Green-Gauss based reconstruction procedure. S-A and SST Turbulence model was chosen. Rotating zone around the propeller was created with an optimum gap and it was assigned as a Rotational zone condition with a rotational velocity of Propeller. Also, it was simulated using rotational wall BC on the propeller.
3. For Propeller OFF condition, the Rotational velocity was specified as zero to impose the no rotation of propellers.
4. For Static Ground Effect simulations,
   Grids were generated for different heights and different pitching angles of -8degs to 18degs. These works involve combinations of grids needs to be generated. This process was completely automated to minimize the grid generation effort.
The RANS simulations were carried out with the ground as moving wall. The Moving wall boundary condition was imposed on the ground with translational velocity. The grid-independent study also performed for this case.


For Aerodynamic analysis,
1. The Aerodynamic analysis results were compared with experimental data for without propeller case.
For Propeller case, It was compared with analytical solutions available.
2. It was observed that The optimum domain distance of Rotating zone from propeller tip plays an important role while defining the rotating zone boundary condition.
3. At a higher angle of attack grid also plays an important role along with propeller rotation.


For Static Ground Effect Study,
1. The performance data were compared with analytical values.
2. The data obtaining by changing the UAV pitch angle needs to be corrected at higher alpha.
3. After the correction, The Data can be used a reference for control groups by comparing with and without ground data.

Natural Convection-driven Flow in a Glass Loop Capillary Tube


The loop in question is used for performing DNA amplification by PCR process. In this process, the reagents are heated in cycles through 3 different temperature controls optimal for various enzymatic actions that make up the PCR process. The Idea was that instead of designing three different temperature control which is expensive due to repeated heating and cooling, we could actually design a loop in which we only heat the base and cool the sides by the atmosphere. Due to natural convection, the reagents would circulate around the loop passing the reagent through different temperature zones responsible for the enzymatic action of PCR.


Our objective was to design a tube that is suitable for this process in that it contains least reagents possible since PCR reagents are very expensive, and also a tube in which flow is slow enough to allow time for PCR amplification.
In this simulation, we used Boussinesq’s approximation to cater for density variation due to the temperature difference. We used finite volume method to write an in-house C++ code do the simulation.


In our findings, the success of PCR process was affected by a number of things including the environmental temperature, the thickness of glass loop and the diameter of the loop. Through our simulation, however, we realized that it is possible to create a universal PCR environment that could successfully perform PCR by varying the angle of inclination of the loop and changing the position of the heater.

3D CFD Analysis of Components in IC engine exhaust layout using OpenFOAM

Simulation Objective: This project was done for BOSCH Ltd., Bangalore (India), where the prime objective was to analyze the flow of exhaust gases and atmospheric air in the EGR valve specifically been developed for single cylinder engines.

The methodology used:
The concept was discussed among the team of four peoples and finally Orifice-type of EGR valve concept was approved for the analysis. I was assigned to design and do CFD analysis of the concept. I have used Pro-E for CAD, ICEMCFD for meshing (tetra mesh) and OpenFOAM for CFD analysis.
Later, for post-processing, ParaView, Gnuplot and Libre office (open-source, default office program in Ubuntu OS) is used

Outcome and conclusion:
It was found that, during the exhaust stroke of an engine, when both inlet and exhaust valves are open, a pressure in the exhaust valve is very low compared to an inlet. Hence, the air was moving out of the EGR valves and was not able to mix with exhaust gases. That is why, instead of the air-exhaust mixture, only the fresh air was supplied to the engine.

What is Fluid Flow

Fluid flows can be classified into either the following flow types

• Laminar flow (slow) or Turbulent flow (fast)
• Viscous or Inviscid
• Compressible or Incompressible
• Single-phase or Multiphase flow
• Chemically inert flow systems or Reactive Flows
• Steady or Unsteady


Fluid Flow is happening all around us

It is a natural occurrence that happens in the physical environment in our day-to-day life.

• Natural meteorological phenomena (rain, wind, hurricanes, floods, fires)

• Use of HVAC system for indoor Air Heating, Air Ventilating circulation and Air Cooling of building interior environment, Automobile passenger compartments

• Assessment of Outdoor Environmental health hazards (air pollution, transport movement of air contaminants)
• Complex Thermal Heat transmission in Combustion furnaces, industrial heat exchangers, Commercial chemical reactors etc.
• Fuel Injection and Combustion in Car engines and other Propulsion systems
• Natural human body Biological processes (eg. Heart pumping of blood flow around the body, breathing and aerobic metabolic processes, digestion)
• Physical and Chemical interaction of various objects with the surrounding fluid water

Limitations of Computational Fluid Analysis Testing Methods

As a rule, CFD cannot fully replace the actual measurements completely but the amount of actual experimentation and the overall cost of testing can be significantly reduced.
The results of a CFD simulation are never designed to be a 100% representation because

1. Limitations of Mathematical modeling

The mathematical model of the analysis challenge at hand may be inadequate
The underlying assumptions mathematical model can also affect the quality of the simulation results

2. Approximate Discretization Process

The data of the input parameter may involve a certain level of guessing or inaccuracy due to the discretization process.
This can result in possible Errors due to Modeling, Discretization, Flow disturbances due to probes.

3. Constraints of Computer Processing Power

Accuracy and Speed of the simulation results is limited by the current computer processing power available

Applications of Computational Fluid Dynamics (CFD)

Some of the applications of CFD Numerical simulation analysis of fluid flow includes

• Building Designers to design building indoor living layouts for optimum Comfortable and maximise safety of occupants
• Minimize Footprint – CFD simulation allows you to Optimize the use of limited building indoor area or land space available.

This includes optimization of natural air flow to minimize of thermal hotspots in building indoor environment, such as Datacenter facility & Retail environments. This is done by using CFD thermal analysis to design the optimal layout configuration.

• Designers and engineers of vehicles to improve the Aerodynamic performance characteristics
• Chemical engineers to maximize the performance yield from their machinery from a Commercial productivity output point of view
• Petroleum engineers to devise optimal oil recovery processes and Strategies
• Medical Surgeons to accurately diagnose and cure arterial disease conditions (computational hemodynamics)
• Meteorologists to predict the weather climate conditions and issue pre-emptive warning of impending natural disasters
• Safety experts to reduce possible health hazards due to exposure to radiation and another health risk
• Military defense organizations to facilitate the engineering development of weapons and estimate extent of blast damage