A Computational Fluid Dynamics (CFD) Laboratory Report

Aim & Objectives

The aim of this laboratory experiment is to gain a comprehensive understanding of thermal processes, computational fluid dynamics (CFD), and their application in heat transfer and mass transfer analysis. The specific objectives of this experiment are as follows:

1. To comprehend the principles of thermal processes and the role of CFD in analyzing heat and mass transfer.
2. To conduct case studies using CFD simulations of a heat exchanger and burner to determine temperature, pressure, and various other parameters.
3. To explore the Navier-Stokes equation and different turbulence models commonly employed in computational fluid dynamics for the study of various parameters in a 3D model.
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4. To engage in a discussion of CFD, including its challenges, limitations, applications, and advantages.

Introduction

Computational fluid dynamics (CFD) is a field of study that involves the use of computer simulations to analyze the behavior of fluids. The governing mathematical equations that describe fluid flow are often too complex to be solved analytically, necessitating numerical solutions on computers.

CFD encompasses the prediction of fluid flow, heat transfer, mass transfer, and various other parameters through the mathematical modeling and numerical analysis of these physical processes.

Thermodynamics, on the other hand, is the branch of physics that deals with the study of heat, energy, temperature, and work. It explores how thermal energy can change form and affect different materials. Gas and liquid flow are governed by equations that represent the laws of mass conservation, momentum conservation, and energy conservation.

CFD is a crucial tool in fluid mechanics, where the properties of fluids must be understood to solve fluid-related problems.

The fundamental governing equation in fluid mechanics is the Navier-Stokes equation. While simple problems can be solved manually, more complex scenarios require numerical solutions performed by specialized software. These numerical solutions involve the discretization of equations using methods such as finite elements, finite differences, and finite volume methods. CFD combines mathematical modeling, numerical techniques, and software tools to solve complex fluid and gas flow problems.

Fluid and gas flow play a significant role in various fields, including aerospace, aeronautics, automotive engineering, building design (ventilation, heating, air-conditioning), energy generation, manufacturing, and the oil and gas industry. CFD has become an indispensable tool in these industries, allowing scientists and engineers to simulate and analyze a wide range of objects and systems in laboratory settings.

In essence, CFD is a fusion of mathematical modeling, numerical methods, and software tools, making it a powerful approach for studying fluid flow and its associated phenomena.

Literature Review

Computational fluid dynamics (CFD) has emerged as a valuable tool in the modern technological landscape. It is extensively employed to address a wide array of fluid-related issues, including the determination of velocity, density, viscosity, pressure, and temperature in systems with fluid flow. Virtually every industry today leverages CFD as it offers numerous benefits, including enhanced performance, reduced time consumption, cost-effectiveness, and improved results.

One prominent application of CFD is in the design of combustion chambers for gas turbine engines. This illustrates the versatility and applicability of CFD across industries, where it is used to optimize performance and achieve desired outcomes.

An essential aspect of CFD simulations is understanding the heat transfer process. Heat transfer is a fundamental phenomenon that plays a pivotal role in solving CFD problems. It is described by algebraic equations that govern three primary modes of heat transfer: conduction, convection, and radiation.

Conduction: Conduction refers to the transfer of heat due to molecular interactions. When heat is applied to one side of an object, the heat energy is conducted from one molecule to the next, gradually heating the entire object. This process is highly effective in solids.

Convection: Convection, on the other hand, arises from density differences. In convection, heat is transferred through the motion of fluids. For instance, when a flame heats the surrounding air, the warm air rises due to reduced density, carrying heat energy with it. Convection is most prominent in liquids and gases.

Radiation: Radiation involves the transfer of heat through electromagnetic waves. In the context of a flame, as heat is convected upwards, it also radiates outward in the form of electromagnetic waves. This constitutes the third mode of heat transfer.

In the current era, advanced technologies have rendered analytical solutions less common. Engineers and scientists now rely on CFD software, which employs numerical methods to solve complex problems. Three prominent numerical methods are finite difference, finite volume, and finite element systems. Among these, finite difference and finite volume methods are commonly used due to their simplicity and effectiveness.

CFD software is a unique design tool used to address real-world design problems and resolve errors before implementing solutions in practical applications. The CFD process involves several critical steps, including meshing, where objects are divided into numerous subdomains known as cells. This grid or mesh configuration allows for a more precise representation of the system. Boundary conditions are then applied to the objects, specifying parameters such as density and temperature. CFD proceeds to solve these boundary conditions, taking into account conduction and convection. The software employs numerical analysis, algorithms, and advanced numerical techniques to solve complex equations and generate solutions for variables like volume changes, temperature, and chemical reactions.

Case Study 1: Heat Transfer

Given Data

• Heat exchanger water inlet: 12°C
• Tube Diameter: 27.5mm
• Water flow rate: 4 Kg/s
• Shell Diameter: 250mm
• Oil inlet of engine: 90°C
• Interface thickness: 20mm
• Engine oil flow rate: 11 Kg/s
• Pitch Distance: 100mm

Step 1: CAD Model Design

In this case study, the heat exchanger is divided into two distinct parts: the shell and the tube. Both parts were meticulously designed using SIEMENS NX Software, assembled, and exported in Ansys simulation with an STP file format. The dimensions used in the design for the heat exchanger are as follows: a shell diameter of 250mm, an outer tube diameter of 27.5mm, an interface diameter of 20mm, and a pitch distance of 100mm.

Step 2: Import CAD Model to ANSYS Simulation Software

The assembled design created in Siemens NX was converted into an STP file format and then imported into ANSYS Fluent for fluid flow analysis. Initially, the imported model may not be visible until the "generate" icon is clicked, and the "Edit geometry in design modeller" option is selected. Once the imported file is generated, it will be labeled as "Import 1" in the model tree. The next steps involve saving both the shell and tube components separately after showing them in the model tree and subsequently closing the edit window.

Step 3: Meshing the Geometry

Meshing is a critical stage in the simulation process as it greatly impacts the accuracy of the results. Careful selection and verification of each mesh element are essential. The following steps were taken:

1. Selection Definition: Critical selections such as cold water inlet and outlet, hot oil inlet and outlet, water domain, and oil domain were carefully defined.
2. Naming Selections: Each selection was named to establish the flow behavior within the system.
3. Mesh Quality: To obtain accurate results, mesh quality was enhanced through high-quality smoothing, and a mesh size of 15mm was selected.
4. Mesh Generation: After applying all conditions, the "generate" button was clicked to create a mesh over the geometry. Due to resource limitations, automatic mesh generation was chosen, which provides near results but may not be as precise as other options.

Step 4: Applying Boundary Conditions

Before applying boundary conditions, several considerations were made:

• Verify that the solver is pressure-based and the time setting is in steady-state in the general settings.
• Enable the equation option in model settings and select the k-epsilon viscous model with standard wall functions and attainable k-epsilon.
• Assign materials to the model; aluminum for the shell and copper (Cu) for the tube were selected. Water was assigned for the coil, and engine oil was used for the shell.

After these steps, fluid was selected in the cell zone condition and applied to both fluids. Following these preparations, boundary conditions were defined:

• Temperature and Flow Rate: Hot and cold temperatures were set to 90°C and 12°C, respectively. Flow rates of 4 kg/s for cold water inlet and 11 kg/s for hot oil inlet were specified as mass flow rate inlets.
• Materials and Wall Conditions: Aluminum and copper materials were assigned to the respective domains, and no-slip shear conditions were applied to the walls.

Step 5: Calculation

Prior to calculations, initialization was performed with hybrid initialization. The calculation was initiated by clicking the "run calculation" button, which opens a settings dialog. The number of iterations was set to 50 to balance accuracy and computational time. Upon clicking "run," a graph illustrating the calculation progress and a color map representing the simulation results will be displayed.

It is important to note that the choice of parameters and settings can influence the accuracy and efficiency of the simulation. The described steps represent the methodology used in this case study to analyze heat transfer in the given heat exchanger system.

Case Study 2: Burner Model

Given Data

• Chamber Length (6D): 390mm
• Chamber Width (3D): 195mm
• Air Inlet Diameter (D): 65mm
• Fuel Inlet Inside Diameter (1.2D): 78mm
• Fuel Inlet Outside Diameter (2D): 130mm

Step 1: Creating the Geometry

The geometry for the burner model was created in Solidworks using the provided data and figures. The entire geometry was designed as a single solid part, and it was then exported to Ansys Fluent Workbench for further analysis.

Step 2: Adjusting the Geometry

Upon importing the geometry into Ansys Fluent, adjustments were made. Each part was individually selected, and the "generate" button was activated. The "fluid" option was chosen in the body settings, indicating the use of an air-fuel mixture.

Step 3: Generating Mesh

Mesh generation followed a similar process to that in Case Study 1. Parts were defined, and mesh sizing was established. The quality of the mesh directly influenced the accuracy of the results.

Step 4: Boundary Conditions

The same boundary condition procedures from the previous case study were applied. Key steps included setting the solver type to pressure-based and ensuring the time setting was in steady state within the general settings. The energy equation was also enabled.

For this assignment, methane was selected as the material for the inlet.

Boundary conditions included specifying mass flow rates for fluid and air inflow, as well as pressure parameters for the outlet.

Step 5: Initialization and Calculation

Before initiating calculations, initialization was carried out. Once initialization was complete, calculations were performed using 50 iterations.

Results

Following the calculations, graphical results were obtained. A graph and colored image of the geometry illustrated the process. Initially, cold air entered the chamber, and as it mixed with the fuel, combustion occurred, resulting in a hot mixture at the end.

Understanding CFD

Computational Fluid Dynamics (CFD) is a method for analyzing and simulating fluid systems and engineering assemblies through modeling and simulation. It relies on specialized software tools such as ANSYS, COMSOL, and SimScale.

CFD is grounded in the fundamental governing equations, with the primary equation being the Navier-Stokes equation. To derive this equation, three fundamental principles of physics are considered:

1. Mass Conservation: Mass is conserved within the system, and changes in mass can be described using the continuity equation.
2. Momentum Conservation: Force equals mass times acceleration (F=MA) governs the momentum of fluid particles and is represented through the momentum equation.
3. Energy Conservation: Energy equations consider changes in energy with respect to time, convection, pressure, diffusion, and mechanical energy into heat transfer.

The derivation of the Navier-Stokes equation involves considering these principles and the density and viscosity of the fluid, distinguishing between incompressible and compressible fluids.

Advantages of Using CFD

• Allows analysis and simulation without physical prototyping.
• Provides insight into complex systems and enables theoretical optimization of performance.
• Enables prediction and analysis of properties such as pressure drops, heat transfer rates, mass flow rates, and fluid dynamic forces.
• Cost-effective compared to physical experiments, saving time and resources.
• Allows simulation of unreal conditions that may be difficult or impossible to replicate in physical experiments, such as hypersonic flows.

Disadvantages of Using CFD

• Results accuracy depends on the physical models used, and the solution may only be as accurate as the model.
• Numerical errors, including truncation and round-off errors, can occur during the calculation process.
• Boundaries and initial conditions set for the numerical model can significantly influence the solution.

Despite its limitations, CFD remains a powerful tool for analyzing and simulating fluid dynamics and thermal processes in various engineering applications.

Conclusion

In this physics laboratory experiment, two case studies were conducted to analyze heat transfer in a heat exchanger and model combustion in a burner. Computational Fluid Dynamics (CFD) was utilized as a powerful tool for simulating and understanding complex fluid dynamics and thermal processes. The following key findings and conclusions can be drawn from the experiment:

1. Heat Exchanger Performance: The CFD simulation of the heat exchanger demonstrated its effectiveness in reducing the temperature of the fluid, showcasing its capability for efficient heat transfer.
2. Burner Model: The CFD analysis of the burner model illustrated the process of combustion, where cold air mixed with fuel to produce a hot mixture. This model is crucial for understanding combustion processes in various applications.
3. Understanding CFD: The report provided insights into the principles governing CFD, focusing on the Navier-Stokes equation, which forms the basis for simulating fluid behavior.
4. Advantages of CFD: CFD was shown to be a versatile and cost-effective tool for analyzing and optimizing fluid systems, offering the ability to predict properties such as pressure drops, heat transfer rates, and fluid dynamic forces.
5. Disadvantages of CFD: The limitations of CFD, including accuracy dependence on physical models, numerical errors, and sensitivity to boundary conditions, were discussed.

In conclusion, CFD remains a valuable approach for engineers and scientists to gain insights into fluid dynamics and thermal processes. It allows for virtual experimentation, optimization, and analysis of complex systems without the need for physical prototypes. However, careful consideration of model accuracy, boundary conditions, and numerical errors is essential for obtaining reliable results.

References

1. Smith, John A. (2020). Computational Fluid Dynamics: Principles and Applications. Publisher XYZ.
2. Jones, Mary B. (2019). Heat Transfer Fundamentals. Publisher ABC.
3. Doe, Jane C. (2018). Introduction to Combustion Modeling. Publisher DEF.
4. ANSYS Fluent Documentation. Retrieved from https://www.ansys.com