Computational Fluid Dynamics Simulation
Computational Fluid Dynamic simulation analysis is at the core of the suite of CFD services that our CFD consultants do at our Singapore offices in BroadTech Engineering.
Featured Computational Fluid Dynamics Simulation Case Studies
Computational Fluid Dynamic Analysis of Diesel Injector Nozzle
Objective: To calculate discharge coefficient & identify cavitation zone in the diesel injector nozzle. Single phase CFD simulation followed by multi-phase simulation.
Methodology: Selective catalyst reduction simulation to calculate uniformity index on a particular location. Single phase flow with structured mesh approach. Solenoid operated gas admission valve simulation. To use CFD design techniques to calculate mass flow at the outlet. Results match the test data.
Charge air cooler simulation with porosity domain. This was a challenging simulation due to convergence issues but results were having 15 % deviation.
Results: Analysis Results obtained using CFD simulation software were approximately matching the test data. Simulation Results matched with Actual data with only 5% deviation.
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Fire Safety Simulation of Turbine Enclosure Chamber
Objective: ATEX certification of turbine enclosure chamber for fire and safety.
Background: A full-scale model of enclosure chamber was considered and fluid volume was extracted from CAD file. A tet-prism mesh was considered adequate for capturing boundary layer effects and was generated using ICEM-CFD. A y+ value of 30-150 was maintained for a selection of k-epsilon turbulence model with wall functions where natural convection flow was simulated using FLUENT solver.
Results & Conclusion: A series of simulations were conducted such as cold flow, hot flow, tracer gas and gas leak analysis. Concentrations of hazardous gasses were observed and trapping zones of these gasses were identified. In order to obtain ATEX certification for safe operations containment plan was necessary. Therefore, venting of these hazardous gasses was proposed of potential problematic zones along with placements of early warning gas detectors. As a result, these enclosures were ATEX certified.
Assessment of Secondary Air System (SAS) of Ventilation Cooling Gas Turbine
Objective: Assessment of Secondary Air System (SAS) of a gas turbine for cooling ventilation and bearing load balancing.
Background: More than 50 inter turbine cavities were analyzed from various engine lines by Rolls-Royce. In all these cavities the basic geometry was developed by extracting the right features from 2D CAD and 3D features such as nozzles, boreholes, and offtakes were introduced in a periodic sector model basing on details of 3D features. The resulting periodic model was meshed using tetrahedral cells and prismatic elements were created on all the wall boundaries using ICEM-CFD. Turbulent flow was then simulated using k-epsilon turbulence model with standard wall functions in FLUENT. In order to maintain the right pressure balance in the cavity, one pressure outlet boundary condition was used with the definition of reference pressure at the boundary and then other boundary conditions were specified as pressure inlet/outlet and mass flow inlet. The compressible flow in the cavities was simulated with appropriate convergence as per the best practices and was checked once the solution was obtained. These analyses included steady and unsteady flows and depended on the nature of vortex shedding by the 3D features and also by the whirling nature of the flow.
Results & Conclusion: This was a long-term project with individual tasks ranging from 3 to 6 months. The flow analysis provides an understanding of the complex flow in high speed rotating disc where there are regions of stagnant flow. This analysis also provides an understanding of metal shielding from the hot air or if the cavities are ventilated enough to flush the oil or oil vapors as this may catch fire and could result in engine shut down. Furthermore, estimates of cooling air were made that bypasses the cavities and used for blade cooling and pressurization.
Computational Fluid Dynamic Simulation of Pipe Layout in Oil & Gas industry
Objective: Development of transfer functions for simplified pipe layout in Oil & Gas industry.
Background: A DoE approach was used to select the right set parameters and to come up with various dominant physical features of the pipes in terms of its diameter. A hexahedral mesh type was chosen that is exactly the same for all the different pipe bends. The mesh was generated with near wall mesh resolution and k-omega SST turbulence model was used for wall shear prediction to the desired accuracy. FLUENT solver was used for conducting the analysis and ICEM-CFD for grid generation.
Results & Conclusion: Most accurate loss prediction was achieved and various flow features were captured such as flow swirling and recirculation zones. This data was then used to develop transfer function that is currently used as a tool in the piping industry.
Air Encapsulation Around Ships Hull to Minimize Hydrodynamic Drag
Objective:
To provide an optimized air cushion around the ships hull to minimize skin friction drag through the use of fluid flow analysis.
Method/Approach:
a. A generic 3D model for the hull/keel of the ship was prepared in Auto Cad.
b. The mesh was prepared in Fluent mesh (tetrahedral), ensuring sufficient no of nodes (60000+) and faces.
c. In Ansys Fluent the air cavity around the hull is provided as a ‘patch’.
d. Reynolds number of lower than 1000, hence laminar fluid dynamic simulations were performed.
e. VOF (Volume of Fluid) approach is chosen from the multi-phase panel.
f. Transient fluid flow simulation is performed.
g. The CFD analysis results obtained from the CFD modeling were correlated with experimental findings and with the air cavity theory.
Conclusion:
Through the CFD flow analysis, it was found that extended air cavities across the length of the ship’s hull, with a minimal air supply (to reduce diffusion of air into water and sustain convection across it), helped lubricate ships hull and reduced hydrodynamic drag.
CO2 Dispersion from Energy System
Objective: The energy server was enclosed by building on two sides with other sides open to the road. Also, the adjoining building had few induced draft fan on the higher floor. The computational fluid dynamics simulation modeling is to address the concerns of CO2 getting trapped and sucked through the induced draft fans.
The Approach: Interaction of system exhaust, wind, adjoining building and induced draft effect of fan were studied. Wind speed and direction were varied based on prevailing conditions.
Conclusion: The predicted CO2 concentration obtained using numerical computational fluid dynamics simulation was well within limits and the dispersions did not reach the ground or accessible area of adjoining building. No additional exhaust systems were required.
Pool Fire Modelling in OpenFOAM
Predicting pool fire behavior important for safety & hazards assessments.
Good advances in turbulence & combustion modeling in pool fires. Mass burning rate key parameter
Objective:
Develop a CFD computational fluid dynamics simulation approach to predict the mass burning rate of liquid pool fires by coupling the gas and liquid phases.
Develop a sub-model for liquid fuel vaporization and implement in FireFOAM
Couple vaporization rate and radiative/convective heat feedback to predict mass burning rate
Develop a sub-model for liquid fuel vaporization and implement in FireFOAM
Couple vaporization rate and radiative/convective heat feedback to predict mass burning rate
Methodology:
Physical Models, Buoyant Flow, Turbulence (LES), Combustion (Diffusion Flame), Soot Formation and Oxidation
Radiation, Liquid Fuel Evaporation.
Heptane and Toluene fuel were tested against experiments for 30cm, 60cm and 1m pool fire.
Outcome:
Temperature and Soot Volume Fraction plot vs heights. Energy Balance of 30 cm pool fire was compared for both fuels
Radiative heat feedback was predicted and compared with experiments. The mass burning rate for both fuels and for all fire sizes was predicted and compared with experiments.
Radiative heat loss fraction was also predicted and compared with experiments.
Full SCR System Design with CFD Simulation
Objective:
Design optimization of full SCR system including the injector location, mixer, and SCR catalyst. Predict the performance parameter to optimize the design, uniformity index, droplet size and distribution and urea conversion.
Methodology:
Detailed 3D Geometry representation Turbulent flow-field
AdBlue spray dispersion/evaporation Energy Balance
Gas phase reactions SCR porous structure properties are computed and coupled to Star CCM+
Mutli-Physics computational fluid dynamics simulation Modelling of physical processes, such as Spray Dynamics, Water Evaporation , Urea Decomposition , Wall Film Formation
Outcome:
Post-process the performance parameters and analyse them to design the SCR system in an exhaust pipe of an automotive.
Under-hood Thermal – New Production Development (NPD)
Objective: Carry out virtual validation before carrying out any tests on new products. Address possible issues beforehand and minimize the number of prototype build for validation.
The Approach: Model how best the system works in the actual interactive environment. Mostly at the end of the design phase, the systems perform wells in isolation but fail when subjected to interaction effect. Evaluate the performance of heat exchangers and under hood ventilation for varied operating conditions of the cooling fan. Predict airflow and thermal distribution within the engine compartment. Emphasis on the temperature of the critical components and suggest suitable design changes to ensure their safety within intended design limits.
Conclusion: With the help of virtual validation, most of the issues were identified and reiterated with design changes to meet the design criteria. The results match closely with that of prototype results. The significant advantage is building a viable prototype with very few changes before the rollout of the final product.
Variable Geometry Turbocharger CFD Analysis
CFD Simulation for design optimization of the turbine of variable geometry turbocharger.
Objective:
To carry out turbine stage CFD analysis to predict stage performance parameters to study effect of above changes in geometry on turbine stage parameters
Deliverables
Mass flow parameter, Turbine stage isentropic efficiency, Vector plot of the flow through the vanes
Pressure distribution on the nozzle deck
Absolute vane entry angle, Absolute vane entry angle/vane exit angle, Relative wheel entry angle
Actual turbine speed (RPM) /blade tip speed (m/s)
Mach number at the nozzle throat, Loss coefficient of flow across the vanes
Temperature at the nozzle exit
Methodology:
CFX 12.1 version
3D, Steady state flow, Pressure based coupled solver
Compressible flow with heat transfer (Total Energy)
Reference pressure – 1 bar
Turbulence Model – SST K-ω
Near-wall treatment – Automatic
Discretization scheme
High Resolution for Continuity, Momentum and Energy equation
Upwind of Turbulence equations
Boundary Conditions:
Inlet Total Pressure, Outlet Static Pressure
Inlet Total Temperature
Wheel Speed, VG Opening
Fluid Properties:
Density: Ideal gas law, Viscosity: Sutherlands law
Specific heat at constant pressure
Thermal conductivity
Outcome:
Study and analyze the deliverables to optimize the design iterations.
Centrifugal Compressor CFD Computational Fluid Dynamics Simulation Analysis
Design of centrifugal compressor in a turbocharger for desired engine configuration.
Objective:
Computational fluid dynamics simulation of the compressor to study the performance parameter in order to design and match it with the engine specific needs. Generate compressor maps in order to analyze its performance at off-design points.
Methodology:
ICEM CFD: Tetrahedral mesh with prism layer to capture boundary layer
Ansys CFX Solver
3D, Steady state flow
Pressure based coupled solver
Compressible flow with heat transfer (Total Energy)
Turbulence Model – SST K
Near-wall treatment – Automatic
Discretization scheme
High Resolution for Continuity, Momentum and Energy equation
Upwind of Turbulence equations
Fluid Domain: Volute, Impeller, Diffuser
Interface Model: Frozen Rotor
Inlet: Subsonic Inlet with Total Pressure
Outlet :
Mass Flow Outlet: Surge Side, Pressure Outlet: Choke Side
Wall: Adiabatic Wall with rotational velocity for Impeller blades, shroud, and hub
Outcome:
Postprocess, study and analyze the performance parameters of the compressor for its design optimization and to predict its overall performance.
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