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CFD Analysis 

Professional Computational Fluid Dynamics CFD Analysis 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 CFD Analysis of Antenna

Objective:
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 CFD turbulence Modeling study was required in order to ensure that no negative aerodynamic influence reached the pantograph area on the locomotive.
Approach:
For the Turbulence simulation Study, 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 CFD Research and Consultancy 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 Design 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 Flow analysis software, such as Simcenter STAR-CCM+ and Ansys Workbench Fluent offers many advantages such as

1. Informed Engineering Decisions

This allows design teams to make informed and Responsible engineering and operational based decisions so as to create Products and Processes which are more Efficient, Integrated and optimized to Performs better optimized performance.
An example where CFD have proved to be critical in ensuring low operating cost is in the area of Numerical Ship Hydrodynamics, where various Ship hydrodynamics simulations are performed to optimized the Ship Hull design to lower resistance and ensure reliable operation when subjected to green water loading.
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 and FSI Simulation 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 engineering 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.
Any example of this is in the Marine Vessel construction industry, where ship design hydrodynamics is used to validate design too big to be physically tested.

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.
An example is in the Area of Building CFD where CFD modeling is used in applications such as validation of passive ventilation Building designs, optimization of HVAC CFD analysis Simulation Studies, Data Center CFD Analysis and Wind Driven Rain Simulation, and Simulation of cooling Tower CFD Studies

5. Maximize Operation Uptime

CFD simulation analysis is able to identify and highlights any Potential issues or Failure scenario before they arise, such as ensuring the Operational Uptime of Data Center using Data Center CFD Simulation, Ventilation CFD analysis, Louver Wind Driven Rain Simulation and HVAC CFD Simulation
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.

Overview

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

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

Other CFD Analysis Case Studies

CFD Ventilation Analysis of Indoor Environment when Subjected to Various Wind Parameters

For this Building Performance Simulation project, we were appointed as the ESD consultant for performing thermal Comfort Analysis Simulation Modeling.

Objective Aim:

To use Wind Simulation analysis and Natural ventilation CFD to determine ventilation Performance in a small indoor room environment at different Wind velocities and Direction

Approach:

For this Wind Air Flow analysis and Natural Ventilation Simulation project, we Implemented turbulent flow simulation Model for Moving air entering and exiting in a small room.

Outcome:

Determined Ventilation dead zones in the room at different air Flow velocities as part of the larger goal of the ESD consultancy project to achieve Green mark platinum certification. The findings from the CFD results is used in conjunction with the HVAC CFD studies as part of the HVAC CFD Consulting project for optimizing the Data Center Air conditioning design

CFD Design Optimization of Bubble Column Reactor for Miroalgae Cultivation

Objective:

To optimize the design and operational parameters of a bubble column reactor used for cultivation of microalgae to improve its productivity.
The CFD model and methodology used is similar to that used in for Air Dispersion modeling Studies, Air Quality Modeling Consultancy Projects and Air Pollution Dispersion Model Studies

Approach:

Implemented multiphase turbulent flow approach to determine flow profiles of liquid and air. Further used the results of liquid flow profiles to track paths of microalgal cells as they move due to drag applied by moving liquid. Calculated light intensity profile (radiative heat transfer), combined it with particle tracks and used this information to calculate reactor productivity. Once this methodology was set, varied several operational (air flow rate, cell concentration etc.) and design parameters (internal structures, light incidence schemes) to determine their effect on reactor productivity.

Outcomes:

Created a Computational Fluid Analysis methodology which can be used to optimize parameters for other similar systems too. With the optimal parameters, improved the reactor productivity by 60%. Determined which parameters are more crucial than others, helpful in designing new reactor. Published one research article and one article under preparation. Successfully defended Ph.D. thesis with a very good grade.

Modeling of Mass transfer of Oxygen from Air to water in a Stirred Tank Reactor

Objective:

To model mass transfer of oxygen from air to water in a stirred tank reactor by performing Propeller CFD Simulation.

Approach:

Implemented multiphase turbulent flow CFD Computational Fluid Dynamics simulation to determine the velocity profiles and based on mass transfer models calculated the mass transfer coefficient of oxygen from air to water. Included the effect of bubble breakage and coalescence using a population balance model.

Outcome:

Created and validated an empirical model based on the CFD Propeller Simulation and Cavitation CFD results obtained from the Flow Simulation, which can further be used for predicting mass transfer coefficient at other operational conditions. Published these results in an international journal. Successfully defended master thesis with top grade.

CFD behavior Analysis of the non-dimensional Navier-Stokes equation

Simulation Objective:

The objective of the CFD Consultancy work is to analyze the behavior of the non-dimensional Navier-Stokes equation on a one-dimensional domain using our FSI Analysis Services. The exact solution is known for the structure of a cell-collocated Finite-Volume solver by imposing the velocity field constraint on a one-dimensional incompressible constraint.

Methodology :

The Navier Stokes equation is solved using the SIMPLE algorithm and a python code has been generated to automate the process. Various kinds of Fluid Flow analyses were carried out to determine the best possible factors under different conditions. The evolution of velocity and pressure residuals is studied for different discretization schemes and Reynold’s number concerning cell size. The effect of relaxation factors concerning the different number of iterations, the evolution of pressure and velocity error norms for a different number of cell numbers are also studied.

Outcome & Conclusion :

The Fluid Dynamics Simulation analysis performed by the CFD Consultant gives a clear cut idea of the suitability of the different that influence the flow concerning flow conditions. For example, the accuracy of the central scheme is high when compared to the upwind scheme during convective dominated flow but the solution is not stable. The upwind scheme gives a stable solution and converges faster but may be less accurate. Likewise, the effect of many factors concerning different flow conditions is studied. Therefore the selection of discretization schemes, relaxation factors, convergence, number of iterations, etc depends on the flow conditions and kind of results required as per the user.

Flow behavior of an Elastic and a Neo-Hookean particle in a Newtonian fluid using ABAQUS

Simulation Objective

To study the flow behavior of an elastic and a Neo-Hookean particle in a Newtonian fluid and study the effect of these deformable particles on the overall stresses and viscosity of the fluid. Such Hydrodynamic Simulation studies are commonly used in the Ship Optimization industries, specifically for Ship Trim Optimization efforts, Ship Hull Design optimization, and various Ship hydrodynamics Simulation projects.

Methodology

The geometry of the domain is prepared in Abaqus-CFD and the particle in Abaqus-Standard. A fluid-structure co-simulation boundary is created between the fluid and particle such that the velocity and traction continuity is ensured. The domain meshes and the system co-simulated the Abaqus-CFD and Abaqus-Standard models. The former is solved using the Finite Volume Method and the later using the Finite Element Method. The effect of variable shear rates and variable L/D ratios (L = length of the channel, D = diameter of the particle) are studied for initially spherical and initially ellipsoidal particles respectively.
In Abaqus-CFD, the CFL no is 0.45 and the preconditioner type is Algebraic multigrid and the solver type is conjugate gradient. The convergence criteria are 10-5 for both velocity and pressure.
In Abaqus-Standard, the linear bulk viscosity parameter was 0.06 and the quadratic bulk viscosity parameter was 0.12. Four node linear tetrahedral elements are used with dynamic explicit time steps. The time scaling factor is 0.5

Outcome & Conclusion –

The spherical particle deforms and attains a steady ellipsoidal shape with a fixed orientation angle.
The deformation increases with the increased shear rate; however, a minimum shear rate is required to deform the particle.
The larger the L/D ratio, the smaller is the deformation. In other words, the deformation is affected largely in the vicinity of the walls.
The overall viscosity of the fluid and the velocity profile around the particle changes.
The particles tend to migrate laterally towards the region of the lowest shear rate.

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.

Flow and Heat transfer characteristics of a non-newtonian fluid through a channel

Simulation objective

To compare the flow and heat transfer characteristics of a non-Newtonian fluid between two flat parallel plates with that of Newtonian fluid and further use these results for a Plate heat exchanger.

Methodology

The geometry is prepared in Ansys ICEM CFD and a grid with 25000 cells is generated and imported into Fluent Software for this Heat Exchanger Simulation. The velocity inlet and pressure outlet, as well as the constant wall temperature boundary conditions, were given, and the flow simulated using a pressure-based solver in Ansys Fluent. The pressure-velocity coupling was done using the SIMPLE algorithm and the solvers used were Standard for pressure and First Order Upwind for momentum and energy. The convergence criteria were 10-7 for velocity and 10-6 for energy.

Outcome & Conclusion

Fully developed flow is achieved earlier in the Steady State Thermal Analysis of the non-Newtonian fluid as compared to a Newtonian fluid.
The transition length is lower for lesser inlet flow velocity and gap thickness.
Temperature profiles obtained from the CFD Thermal Analysis reveal a more uniform temperature distribution for lesser inlet flow velocity and gap thickness.
Nusselt number has a higher maximum value for minimum gap thickness whereas higher value at the outlet for maximum inlet velocity and vice-versa for Prandtl number.
Thus, the heat transfer coefficient is largely affected by the non-Newtonian behavior of the fluid.

CFD Analysis of Condenser mixer

Objective:

The CFD Simulation study is aimed at achieving an optimum configuration hot and cold mixer for efficient mixing. The inefficient mixing of hot and cold fluid causes nonuniform temperature distribution over the pipes and causes thermal stresses

Methodology:

  1. To enhance the heat transfer between two fluids one can either go for active techniques or passive techniques. Since this is a parallel flow here we have chosen a passive technique for the Thermal Simulation
  2. In this CAE Simulation problem, we have considered only conduction and convection mode of heat transfer. And to achieve uniform temperature distribution at the condenser outlet without changing the size of the system, we changed the orientation of the hot fluid pipe as well as we have changed the position to achieve the fully developed condition. But this modification doesn’t give a satisfactory solution. By keeping the projection and changing the roughness of the pipe we could augment the momentum transfer but this leads to additional pressure drop. So we have introduced some holes in the inner annulus pipe where the cold fluid is flowing. This enhanced the mixing but this configuration couldn’t be manufactured as easily.so still we are working on this project to get the optimum design.
  3. The total number of mesh [tetra elements] used in the CFD Simulation is approximately 80 lakhs. And We have chosen the standard K-ω model to capture the near-wall physics. And we run the CFD Simulation for steady cases because the mass flow rate is constant.

Outcome & Conclusion: 

The minimum, maximum and average Thermal temperatures at the outlet observed as 50.6, 132.4 and 98 deg C respectively, clearly indicate that the hot and cold condensate is not mixed well, with a +34.4 / 47.4 degrees deviation to the average temperature.
Further, the cold and hot peak Thermal temperatures above create thermal stresses on the pipes downstream.
It is also observed from the CFD Simulation results that a clear asymmetric flow of hot liquid along the annulus. This contributes to the reduction of effective heat transfer.
These observations from the CFD Simulation indicates a need for the design improvements 

Integrity Evaluation of dry stored nuclear fuel using CFD thermal Simulation Analysis.

To assess the integrity of dry stored nuclear fuel through thermal prediction. To do so, a 3D model has been developed with ANSYS-CFD Premium 16.0 code.
Due to the complex geometry of the fuel assemblies, these have been approximated as porous rectangular parallelepipeds with internal heat generation.
An effective thermal conductivity and ad-hoc pressure drop have been derived.
Finally, through the use of Multiphysics Modeling, the CFD model has been Successfully validated and verified and used in different Operating conditions.
 
The Transient Thermal Analysis Simulation of experiments focused in the interaction between a vertical steam injection and a stagnant H2 rich layer in containment at Nuclear reactor in a Severe Accident. The basic outline of the experiments modeled was an upward steam injection that, once its vertical momentum is dissipated by colliding against a flat plate, erodes a lighter gas layer consisting of He and steam (the deeper in the layer, the richer in He).
The results from the Multiphase Flow Simulation show some similarities with measurements, but also differences.

Implementing SIMPLE family of CFD Algorithms

Objective

To developed computer codes to solve two-dimensional elliptic and parabolic heat transfer problems.

Methodology

– Developed finite volume based codes using Matlab to implement SIMPLE (Semi-Implicit Pressure linked equations) family algorithms to numerically solve for velocity, temperature and pressure fields in problems with rich flow physics including flow through channel, lid driven cavity and flow over a backward facing step. Compared results with literature for accuracy. A staggered grid approach was used discretize the domain and Tridiagonal Matrix Algorithm also known as Thomas algorithm was used to solve for variables iteratively.

Outcome

– independently built all three phases of solving a numerical problem (i.e. grid generation, developing discretization equations and iterative solution of equations) by developing codes in MATLAB. Compared results with literature and developed proficiency in numerical methods in heat transfer and fluid flow.

Related CFD research/ academic projects

• Studied performance of a novel refrigeration process/cycle through theoretical thermodynamic Simulation modeling and compared its performance with conventional vapor compression refrigeration cycle for various outdoor conditions and configurations. (2016)
• Worked on Particle Image Velocimetry to analyze blood flow patterns through scaled up carotid artery model using PIV technique as a project assistant at biomechanical environments lab at Texas A&M University (2014).
• Completed a certified course on Sports and building Aerodynamics by TU/ Eindhoven – Netherlands (2014).
• Presented a seminar on CFD Wind Analysis of Vertical axis wind turbine as a part of CFD Training curriculum (2014)
• Completed an introductory course on CFD, Aerodynamics and Gas Dynamics as a preparatory work related to project on Afterburner diffuser. (2013)
• Won the first place for design and fabrication of radio-controlled glider in one of the design – build competitions of a national level tech fest while representing my undergraduate institution. (2012)

CFD Aerodynamic Analysis of UAV

  1. Aerodynamic Analysis and Airflow Simulation of a UAV with propeller ON/OFF conditions.
  2. Estimation of Aerodynamic Loads on UAV using Wind Load Analysis Simulation
  3. Ground Effect study on the UAV
CFD Turbulent Flow Simulations were carried out using flow solver HiFUN and ANSYS CFD Fluent CFD Software
 

Objective

  1. Aerodynamic Analysis includes Estimation of Aerodynamic performance characteristics at a 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.

Approach

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 performed using Ansys CFD Fluent Software, Roe scheme with second-order discretization in space was used. Gradients are calculated using the Green-Gauss based reconstruction procedure. S-A and SST Turbulence model was chosen. The 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 the Propeller OFF condition, the Rotational velocity was specified as zero to impose the no rotation of propellers.
  4. For Static Ground Effect simulations performed using Ansys Mechanical CFD, Grids were generated for different heights and different pitching angles of -8degs to 18degs. These works involve combinations of grids that need to be generated. This process was completely automated to minimize the grid generation effort.
The RANS simulations were carried out with the ground as a moving wall. The Moving wall boundary condition was imposed on the ground with translational velocity. The grid-independent study also performed for this case.

Conclusions/Observations

For Aerodynamic analysis,
  1. The Aerodynamic analysis results obtained from the 3D fluid Simulation Software were compared with experimental data without the propeller case. For the Propeller case, It was compared with the analytical solutions available.
  2. It was observed that The optimum domain distance of the Rotating zone from the 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 generated from the Ansys Fluent CFX software 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 as a reference for control groups by comparing it with and without ground data.

CFD Analysis of AGARD 303 3-element airfoil system profile

Simulation Objective:

The study of the AGARD 303 profile, it is a three-element airfoil system. The Fluid Flow Simulation study is done for different wall models and using different grid densities.

Methodology:

The Airfoil Simulation analysis is carried out for total pressure coefficients along with the profile for different grid densities as part of the CFD Services rendered. The graph is plotted for pressure coefficients at slat, main and flap regions for coarse medium and fine mesh sizes. Likewise, comparisons of the Euler model with wall-models are done using the results. The influence of the type of discretization and relaxation parameters are studied for this Airflow Modeling Study and compared between them and experimental values.

Outcome & Conclusion:

The above Aerodynamics Simulation analyses gave the influence of various factors for determining the evolution of different properties around the profiles. The influence of models and discretization schemes on different regions of the profiles are plotted and analyzed.
Finally, a grid convergence study for the coefficient of lift and drag is done to study the effect of grid density and type of model.
The computational cost of different Airflow Analysis models is analysed.

Vortex Alleviation in Aircraft wings (AIRBUS Fly Your Ideas):

Objective

The objective of the CFD consulting case study was to alleviate the wing-tip vortices by jettisoning water swirl in the opposite direction. Similar to a Centrifugal Pump Impeller CFD Analysis Simulation, the Eulerian-Eulerian model of the multiphase solver in Star CCM+ is employed for the simulation. The case study was done roughly to support the Research Idea submitted to AIRBUS fly your ideas. Full scale, half-span aircraft wing (B777) given by NASA for the AIAA conference was used for the CFD simulation.

Methodology

The root-chord airfoil of the wing is aligned to the XY plane such that the flow is parallel to the X-direction with the wing-tip pointing in the Z direction. A small jet inlet facing the Z direction is made near the trailing edge of wing-tip, through which water swirl with rotational velocity component (opposite to the direction of rotation of the vortex) is jettisoned. The domain is made in cuboid shape and is sized 15 times the root-chord (15C) of the wing in the flow direction (X-axis) and 5 times the root-chord in the Y and Z directions with the wing root placed at 5C from the inlet plane of the domain. The topology is meshed using the automatic mesh generation algorithm in Star CCM+.
The hexahedral mesh cells are used with more cell concentration near the wing and relatively coarser cells at the rest of the domain. k-ɛ turbulence model is used to calculate the effect of turbulence and Y+ = 30 is used to comply with the k-ɛ turbulence model. Prism cell layers are developed to capture the effect of the boundary layer on the wing and a high density of fine grids are generated in the zone where wing-tip vortex prevails.
The fluid medium used in the domain is air while the fluid jettisoned from the wingtip is water. Velocity inlet and pressure outlet conditions are used for the inlet domain and the sides are made as symmetry planes. The jet inlet is assigned with a mass flow inlet condition. The volume fraction methodology of the multiphase solver eased the CFD simulation as it covers the full range from 0 to 1, with 0 being air and 1 being water. The time ensemble averaging of quantities nature of the solver allowed for the modeling of mixing of phases.
The unsteady case is initialized with constant air velocity and atmospheric pressure and ran for a few time steps until the vortex formation is almost steady. The water jet is then started to counter the vortex formed. The overall drag force on the wing is plotted with time and the value of drag before and after water jettisoning is compared.

Outcome & Results

The CFD Consulting study showed a significant reduction in the drag force when the wing-tip vortex is countered by water swirl. The same case is solved in OpenFOAM multiphase solver (interFoam) and the results were found to be similar both quantitatively and qualitatively.

CFD Analysis of External flow over Aerodynamic surfaces:

In my current and past works, Our CFD Consultant has done many external flow studies over aerodynamic surfaces, such as Jet Fan CFD Analysis Studies and Centrifugal Fan CFD Analysis. Our CFD Consultant investigated flow over a reentry vehicle to calculate the heat flux at various altitudes and MACH numbers. Our CFD Consultants used Ansys CFD Software for the CFD simulation. Moreover, Our CFD Consultantused UDF for the implementation of real gas effects such as dissociation.
  In my Ph.D., Our CFD Consultant was working on the simulation of ice accretion over various aerodynamic surfaces. Since shear stress and heat flux is input for the ice accretion solver, Our CFD Consultant has simulated a lot of aerodynamic surfaces using in-house and FLUENT Flow solver. Moreover, my works were not limited to two-dimensional simulations.
Our CFD Consultant has simulated a lot of test cases involving Ventilation Analysis, and Jet Fan CFD Analysis Simulation with FLUENT and FENSAP to investigate the flow and solid surface parameters. Recently, Our CFD Consultant was investigating a three-element airfoil under various icing and flow conditions. The main objective of the study was to investigate the performance degradation of the multi-element airfoil at various icing conditions. Further, Our CFD Consultant has simulated three-dimensional ice accretion as well as the Airflow simulation over wings, engine inlets, and whole airplane models.

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.

Objective

Just like a Jet Fan CFD Simulation, 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 HVAC 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.

Outcome & Conclusion

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 a vortex-induced vibration project, Fluid-structure interaction (FSI) was modeled using an immersed boundary method similar to that commonly used in Centrifugal Fan CFD Studies. 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 the Smagorinsky model.

CFD Analysis of Flow development in afterburner diffuser duct

Objective

– To study the effect of aerodynamically shaped struts on flow development in an afterburner diffuser duct of a jet engine, similar to that found in Centrifugal Pump CFD case Studies.

Methodology

– RANS based standard k-epsilon model was used to simulate flow across a 300 section of an afterburner diffuser duct of a jet engine under two cases.
(i) duct without struts (ii) duct with vertically placed NACA-00012 profiled struts.
The problem was subjected to the same boundary conditions in either of the cases and the effect of struts on flow development was studied.
CFD Heat Transfer simulations were validated against theoretical calculations as per the data handbook to ensure the accuracy of results.

Outcome & Results

– Two main conclusions of the CFD Thermal Analysis study were
(I) A significant decrease in swirl angle was observed in a situation with struts incorporated into the system – leading to much less probability of flame blow off.
(ii) Turbulent kinetic energy across the system was found to increase – which thereby ensures better mixing of fuel and air.

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

Simulation Objective:

This Engineering project was done for our Client, BOSCH Singapore. We were appointed by them as the CFD Consulting company for this project, 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.

Methodology used:

The concept was discussed among the team of four peoples and finally Orifice-type of EGR valve concept was approved for the CFD analysis.
Our CFD Consultant was assigned to design and do a CFD analysis of the concept. Our CFD Consultant has used Pro-E for CAD, Ansys ICEM CFD 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 from the Multiphysics Simulation that, during the exhaust stroke of the engine, when both inlet and exhaust valves are open, pressure in the exhaust valve is very low compared to the 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.

Optimization of Combustion performance of IC Engines using Ventilation CFD

Our CFD Consultant uses the Converge CFD Software tool.
The CFD Flow Simulation involves Numerical modeling of spray, turbulence, and chemistry.
We have worked here on several research projects and analyzed for heat transfer and CFD models validations.

Objective:

To find the pumping loss of the engine using FSI Analysis and CFD Simulation to optimize Ventilation of Engine

Approach:

We used the overset mesh technique to model the moving components such as piston, connecting rod and crankshaft.

Conclusion:

Found the pressure difference at the drain interfaces for each cylinder at the last time cycle and calculated the loss.

CFD Analysis and Simulation of internal flows of Engine Inlets:

 In addition to the external flows, Our CFD Consultant have experienced with the simulation of interval flows of engine inlets, similar to that seen in Centrifugal Pump CFD Analysis. Our CFD Consultant have simulated aircraft and rotorcraft engine inlets under various flow conditions. The main objective of the engine inlet simulations is to check the performance of engine inlets at various aerodynamic and mass flow conditions. Further, the simulations are extended with ice conditions and investigated the effect of ice on the performance of inlets.
Moreover, in my undergraduate, Our CFD Consultant investigated the secondary injection thrust vector control (SITVC) using FLUENT CFD. Hence, Our CFD Consultant is familiar with both internal and external flows. The motivation of the study is to investigate the effect of secondary jets in the main nozzle flow to get the maneuver of the rocket. Most of the rockets are using this SITVC for the direction change and rolling. In my investigation, Our CFD Consultant studied about the augmented thrust due to the injected jet. Hence, the investigation of side force generation and thrust augmentation was the objective of the project.

CHT Conjugate Heat Transfer CFD Simulation Analysis of Engine Head Block

Objective:

To find the temperatures at the critical regions of the head block using Thermal Simulation and provide data for durability analysis

Approach:

Induced data tables for HTC & temperature values of the combustion flame area through 1D analysis results and run the coolant with the water pump speed, then calculate the temperatures using Centrifugal Pump Simulation.

Outcome and Conclusion:

The detailed plot of temperatures at the head valve seat region and liner siamese region where there is a chance of high thermal stresses. Other projects involved in Hybrid motor, Transmission, Combustion, Port flow, Exhaust systems, etc.

CFD Modeling of Electro-Thermal Ice Protection System on Wind Turbine Blade

Further, Our CFD Wind Engineering Consultant has investigated Electro thermal ice protection system on a 5MW wind turbine blade using CFD Wind Flow Analysis Simulation.
The objective of this CFD Consultancy study is to design an efficient Electro-thermal ice protection system for the wind turbine using Ansys CFX. Conjugate Heat transfer simulations were involved in this study using the FENSAP package. The heater power requirements, heater length, and heating sequence were elaborately investigated.
Overall, Our CFD Consultant is familiar with internal, external flows, and thermo-fluid flows. Our CFD Consultant has a vast knowledge of FLUENT software and other necessary tools for Ansys CFD meshing (e.g. Gambit, Pointwise) and post-processing (e.g. Tecplot, Paraview).
In addition to that, Our CFD Consultant is well expertise in CFD code development and numerical modeling.