CFD Simulation

Professional Computational Fluid Dynamics (CFD) Simulation

CFD simulation is at the core of what we do here at our Singapore office in BroadTech Engineering.
We are a CFD company which provide a comprehensive range of CFD consulting services such as CFD flow analysis, CFD Modeling, Mechanical simulation and Digital Prototyping solution to help design engineers and Analysts make the correct engineering decisions earlier in the design development process.
This CFD consulting allows engineering companies to leverage the CFD services to validate and optimize designs way before the manufacturing phase and increases the performance efficiency.

What is CFD

CFD or computational fluid dynamics is the study of the Fluid flow of liquids and gases in and around specifically engineered objects under study. It also involves the numerical modeling and simulation of thermal behaviors.
The equations governing fluid dynamics is complex and is often unsolvable manually by hand.
However, through the use of CFD simulation software methods and Computational Fluid Analysis algorithms, it has made it possible to accurately predict the Fluid flow behavior of liquid and gases and its interaction with the engineering product designed.

Why CFD Simulation

Computational fluid dynamics or CFD analysis is an important part of the engineering design process as it helps to boost the energy efficiency of design performance, reduce the risk of failure and helps to accelerate innovation in engineering design.
By having insights into the forces that affect the fluid dynamics simulation through the use of Fluid Dynamic Analysis, you can make the critical design decisions that can significantly reduce energy consumption and improve performance efficiency

Featured CFD Simulation Case Studies

Therma Cooling System

Optimization of Thermal Cooling Systems

One of the key processes in a metal extrusion plant is the efficient thermal cooling of the extruded beams through natural convection. Our customer needed to achieve maximize the airflow while minimizing the acoustic noise footprint outside the factory. The current air intake designs were modified and optimized to guarantee uniform airflow, sound vibrational isolation and maximum cooling capacity of interior currents. Buoyant structures and wind sensitivity were analyzed to evaluate different designs of air intakes.

Thermal Comfort in Glass Facade

Thermal Comfort of Glass Facade

An in-depth thermal comfort analysis was conducted in the intermediate space of the condominium building.This space is isolated from the exterior by means of a glazed facade. Right from the beginning, It was imperative to address the greenhouse effect and the influence of interior flow currents created by wind. All must be within acceptable comfort ranges. CFD results were combined with energy simulation in order to set-up the most energy-efficient facility.

Features & Benefits of CFD Simulation

 

1. Less Reliance on Physical Prototyping

Through our CFD engineering simulation capabilities, we are able to help our clients to accurately predict the real-world performance of their various engineering design iterations.
This helps to minimize reliance on the need to fabricate and test multiple physical prototypes variants, thus helping companies to save a tremendous amount of development time and money.

2. Cutting Engineering Development Time

CFD simulation enables engineering teams the flexibility to simultaneously test design performance in multiple conditions and failure scenarios.
This helps to significantly cut down on the engineering development time and save money and resources which would otherwise be spent on testing

3. Focus on Design, We Take the Complexity out of Engineering Simulation

We help you to channel your focus on designing the product for optimum performance by taking care for you the complexity of advanced Simulation analysis and Numerical modeling methods

4. Early Validation of Engineering Design

Through the running of CFD simulation analysis during the engineering design process design issues such as miscalculations in judgment, can be identified and solved before they turn into serious problems, such as

● Building collapse due to Structural failure when subjected to wind loads
● Overheating of electronic components
● Failure of automotive car parts

The consequence of such failures can be serious, such as product recall from the market, legal lawsuits or even loss of life.

Early Identification & Highlighting of Design Errors

An accurate CFD simulation also helps to identify and highlight any occurrence of engineering design errors early in the engineering design process where the product cost is not yet locked in and allows for more flexibility for design modifications to be implemented.

5. Multiphysics Simulation

We also have the CFD software tools and capabilities to perform Multiphysics simulation to conduct a detailed analysis of Fluid flow phenomena such as

1. Heat Transfer behavior to study Thermal characteristic of Specific Designs
2. Fluid flow simulations to study accurate and detailed fluid flow behavior

Using advanced computational fluid flow simulation tools, we can accurately simulate fluid flow behaviors and patterns in various situation, such as

1. Laminar and Turbulent flow.
2. Flow of incompressible fluids moving around a physical object (such as Aeroplane wing airfoils)
3. Formation of Hollow cavitation in Fluid
4. Fluid Flow simulation which takes into account the simultaneous effects of fluid thermal behaviors, such as natural convection buoyancy and forced convection flows
5. Simulation of mold flow during Plastic injection molding process

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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Contact Us!

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CFD Simulation

1. Powerful ANSYS FEA 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

Applications of CFD Simulation

CFD analysis should be used throughout the design process to gain insight and to make good design decisions

1. Thermal prototyping

Solve and optimize design thermal performance for all modes of heat transfer (ie. Conduction, Convection, Radiation) between various medium (eg. From Solid to solid, Solid to fluid, or Fluid to Fluid)
eg. Temperature behavior in an electronics enclosure

2. Building Efficiency Design

Use CFD software and thermal modeling tools for architectural and MEP applications, such as

1. Optimization of building aerodynamics
2. Wind engineering for natural indoor ventilation
3. Optimization of the Building Mechanical, Electrical and Plumbing systems
4. Ensuring the comfortable indoor environment in a crowded building indoor environment (eg. Meeting hall)

 

3. Flow Control in Industrial Applications

Optimization of designs when you need to improve performance such as

1. Drop in pressure as fluid flows through a valley component
2. Design performance behavior in Turbulent flow conditions/scenarios
3. Distribution of Fluid flow and Thermal temperature flow.
eg. Efficient use of optimized heat sinks to eliminate the need for cooling fans in electronics.
This helps to provide a significantly smaller design form factor and increases product performance reliability.
4. Optimize Efficiency of Turbo-machinery and Combustion Engines
5. Solving of in-flight icing.

 

4. Automotive Aerodynamics

eg. Study of wind resistance effects on a car, motorcycle in motion

Types of CFD Simulation Scenarios

 

Incompressible Flow

In a majority of engineering applications, the Fluid flow involved is incompressible and turbulent, where the flow speed is below Mach 0.3. In such simulation applications, an Advanced solver is needed.

Compressible Flow

A Compressible fluid flow is where the fluid density varies with the Pressure values. Such Fluid flows are usually high speed flows with Mach numbers greater than 0.3
Examples include Aerodynamic applications such as optimization of Fluid flow over an airplane wing aerofoil and applications in industrial processes such as engineering of Fluid flow through high-performance grade valves
The simulation analysis of compressible flow takes into account the formation of shocks.
In the case of liquid, it comes in the form of water hammers.

Cavitation

Cavitation is a physical phenomenon that occurs in many high-velocity liquid flows. It occurs when vapor bubbles are formed when the liquid pressure drops below the vapor pressure of the liquid.
Prolonged cavitation have a negative effect of causing pitting and erosion in equipment, resulting in significant reduction in efficiency, costly downtime and repairs
Cavitation is common occurrence in devices, such as

1. High-performance valves
2. Flow control valves devices
3. Pumps axial fans
4. industrial mixing Propellers

Using CFD simulation, we are able to efficiently and quickly analyzed

1. Predicts the Occurrence and location of bubble formation within the flow
2. Monitor the vapor bubble to volume ratio

 

Scalar Mixing of 2 Fluids

We can also simulate the scalar mixing of two similar fluids and accurately track the variation of fluid properties, such as changes in overall density or viscosity of the fluid mixture as the scalar is added.
Using the free surface modeling capability, we are able to dynamically simulate the interface between liquids and solids
This is used for the Modeling and Study of flow phenomena in a wide range of engineering applications

1. Industrial applications, such as Mixing processes
2. Building Architectural applications, such as Tracking the distribution of air pollutants in smoke
3. Infrastructure design, such as naturally occurring flows behavior like waves sloshing and fluid spilling

Call Us for a Free Consultation

Discover what CFD Simulation can do for your company today by calling us at +6581822236 for a no obligation discussion of your needs.
If you have any questions or queries, our knowledgeable and friendly consultants will be happy to answer any of your queries and understand more about your needs and requirements

Alternatively, for quote request, simply email us your technical specifications & requirements to info@broadtechengineering.com

Other Featured CFD Simulation Case Studies

Analysis of Flue Gas Flow in The Piping of Circulating Fluidized Bed Boiler

This CFD simulation is about how to depict the flow characteristics of multiphase fluid within the pipe. And then, to design a modification of 3D piping to accommodate the separation of the small solid particles (ashes) from the gas phase along the pipe and also to direct the flow into a more laminar type. The method that was used is Lagrangian for the solid particle and the Eulerian for the gas phase in which they are applied using ANSYS CFX. The separation method has relied upon the gravitational factor and the mass difference between those two phases. After implementing modification of baffles on certain areas, a high portion of ashes can be kept in the ash pit area while the flow can be directed into a more laminar type while it was also able to be distributed in the similar amount of flow rate for all outlets.

CFD Simulation of Gas Flow on the Pipe Ejector

The simulation is about to depict the gas flow on the pipeline ejector as to show whether the gas is sucked on by the ejector or not. The method that was used is the Eulerian as it was only one phase whereas it was performed using ANSYS Fluent. The result showed that the gas was sucked in quite wholly to the ejector due to the far smaller diameter of it compared to the pipeline’s diameter whereas the velocity was constant along the pipeline up to the ejector.

Cascade Analysis of Turbine Blade Sections of Small Gas Turbine, Small Turbofan, and Turbofan Turbine

Objective: To carry out the CFD analysis of turbine blade sections and its comparison with the experimental data
Methodology: Grid generation in NUMECA’s AutoGrid5 | 3D analysis in ANSYS-CFX
Outcome: The CFD results were within acceptable limits compared to the experimental data

Conditioning Tower for a Cement Manufacturing Plant

Water was sprayed into the tower to cool and aggregate particles in the air. The problem was uneven wetting of the product at the bottom of the tower. The flow in the tower was analyzed. A simple model with particle tracking was used to determine the flow of air and water to determine how and why the water was accumulating more in one area of the tower. A range of flow correction devices was compared to determine the improvement in the air flow and water distribution. The best (and simplest) solution was presented to the client. The device was only being installed by the time I finished my term at the consultancy (part-time work), but the feedback I received indicated the device was working.

Numerical Simulation of a Dynamic/Active Heat Flux sensor on a Flat wall using Ansys (Fluent)

In this CFD simulation, a Newly developed Dynamic Heat flux sensor was developed and placed on the surface of the Wind tunnel.From the inlet side, 2m/sec to 12m/sec velocity of air was sent through the blower. The difference between Dynamic and passive Heat flux sensor is: Passive/Traditional HTS gives Local Heat transfer coefficient and surrounding temperature; Dynamic HTS gives Global Heat transfer coefficient and equivalent surrounding temperature and Experiment results were recorded and it should be validated through Numerical simulation.
ICEM CFD was used for Geometry and Meshing Purpose and Ansys (Fluent) as a solver.This is a 2-D and 3-D (Real case) Transient Numerical simulation of airflow and Heat Transfer.For Post processing, we used Matlab and Fortran 95.
Different geometry was modeled for different cases and created a Hexahedral Mesh with a better quality and less skewness.As fluid flow comes under the Laminar Flow, we also considered a turbulence flow with very less intensity about 1% and wall y+ came around 0.9.Mesh grid independence test was carried for different Nodes and considered the optimum nodes mesh for fast computation.We considered the energy models like K-epsilon, we used Enhanced wall treatment and Menter -Lechner near wall treatment (Independent of Y+ model) and K-omega SST Model.
We also created a UDF for giving some heat flux at one side up to 4sec according to the experiment.As a solver, we used Ansys Fluent and simulations ran successfully for both 2-D and 3-D cases.
3. The conclusion was the average error between the 2-D (Turbulent) and Experimental data was around 9% and between 3-D (Turbulent) and Experimental data was 8%.

Sand Erosion Modelling in the Gas Pipeline Bends

The simulation is about to depict the potential of erosion location on pipeline bends due to the existence of sand within the gas flow. The objective is to apply the best model for the pipeline bend so that the erosion area can be diminished. This was performed using STAR CCM+. Moreover, the method that was used is Lagrangian particle tracking for the sand as this was intended to show the collision area of the solid particle on the pipeline wall. Meanwhile, the Eulerian is used for the gas phase to depict it as one body of flow. The factor that determines the model selection is the curvature of pipe bend, the selection of U bend or S bend, and the pipeline diameter. Consequently, the U pipe model with 2D curvature and diameter of 25 cm was chosen as the erosion has occurred the least on this model.

Steady and Unsteady Analysis of Turbine Stage of Small Turbofan & TurboFan Engine

Objective: To carry out the unsteady simulations of turbine stage and its comparison with CFD steady analysis
Methodology: Grid generation in NUMECA’s AutoGrid5 | 3D analysis in ANSYS-CFX
Outcome: Results obtained from the unsteady analysis is within limits as compared to steady analysis results and a lot of time can be saved with steady analysis.

Flotation Tank and Flow Control Valves

A bank of settling tanks was analyzed to determine the correct sizing of flow valves and the height of the outlet back-pressure pipe for required flow characteristics between tanks. The design was approved by the time I finished my term with the company (short-term contract). No construction had started.

Hydrodynamics of a Boat Hull

I was approached by a boat builder to analyze their new design of a 52 ft catamaran motorboat. This was to determine the top speed, power requirement and other characteristics of their hull shape. Their initial hull design was not suited for the high-speed conditions they desired. So a more appropriate hull shape was proposed which met their requirements. The first boat is still under construction.

CFD Fluid Flow Analysis of Hydraulic DTH (Down the hole) Hammer Prototype

The design and numerical simulation of a wear-free fluidic switch based on the Coanda effect for a hydraulic DTH (Down the hole) hammer prototype. The traditional DTH hammer prototypes have around 40-45 parts enclosed within the hammer casing for efficient operation. the major drawback, however, is if one of the components within the hammer fails, the complete hammer assembly has to be opened and the part has to be replaced. The need to reduce the number of moving parts within the assembly is of utmost importance. The fluidic switch assembly was designed in the Siemens Unigraphics NX 10 Cad software and the numerical simulation was carried out in the Ansys CFX simulation software. The major part of the analysis is the extraction of the fluid volume through the hammer assembly. this was accomplished in the Ansys design modeler. A sensitivity analysis was carried out in order to establish the final design of the fluidic switch which can be incorporated into the hammer casing.

3D CFD analysis of Components in IC Engine Exhaust Layout using OpenFOAM

 

Field of Work: Transient Thermal Analysis
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 the engine, when both inlet and exhaust valves are open, the 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.
Finally, it is established that spring-loaded elbow type EGR valve can perform better than the newly-designed Orifice-Type EGR valve.

Let us quickly touch on the fundamental Methodology of Engineering Simulation and Computational Fluid Dynamics (CFD) mean and how they fit into your engineering development workflow processes.

What is Engineering Simulation

Engineering Simulation is an integral and core part of the digital prototyping process. Fundamentally the 3d CAD model of your product concept design is your digital prototype.
It is from this prototype model that critical engineering design information is verified, Tested and Validated along each of the engineering development function in the company, from Manufacturing to Production and finally to Sales and Marketing

Engineering simulation takes place predominantly in the early Test and Validation phase of the digital prototyping process, during which critical questions need to be answered. This includes questions such as:

– Can the design withstand the loading forces? Will the design break?
– How light can the design be made while optimizing it for maximum strength
– What is the physical performance like when the temperature changes

 


 

Why Engineering Simulation

Engineering Simulation allows companies to develop better products quicker and at a cheaper rate

1. Save Time & Money

Traditionally, questions concerning a design performance have been answered through the Building and Testing a large number of physical prototype iterations which is an extremely Costly and Time-consuming process.
By leveraging on engineering simulation, you can test digital prototypes in a virtual environment, thus helping to save time and money as fewer physical prototypes are needed for testing.

2. Early Engineering Insights

Engineering simulation provides Accurate and Reliable results early in the design development process to help companies make better-informed engineering decisions to optimize their products.
It also allows Failure modes to be identified and Defects to discovered early in the engineering design life-cycle where there is flexibility for corrective modifications allows changes to be implemented relatively inexpensively.
This helps tremendously in the creation of higher quality products and prevents costly product recalls when the product is sold.

3. Accelerated Testing Cycle & Rate of Innovation

In a virtual simulation environment, designers and engineers have the freedom to test and Explore more what-if scenarios because engineering simulation is not constrained by physical size, cost, or external environmental conditions.
As the performance of specific Engineering designs when subjected to specific external conditions can be accurately predicted, it helps to accelerate the design testing cycles involved in optimizing the Materials and Design features.

4. Complete Picture

Through the use of CFD simulation analysis, it is able to give a complete view of the fluid flow behavior.
This accurate engineering insight helps to facilitate questions and critical thinking which is important for driving innovation.
This is in contrast to the individual testing of each iteration of physical prototypes, which only provides discrete pieces of test data

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