A core objective of the undergraduate course Thermo-Fluids Design and Lab in the Department of Mechanical & Aerospace Engineering at the University of Florida (UF) is for students to use a hands-on approach to learn the fundamentals of the fluid mechanics of pumps. In the past, students have used traditional techniques such as Euler’s Turbomachine Equation and velocity triangles to predict pump performance, but these techniques can be inadequate. As a result, UF has begun to explore modern computational fluid dynamics (CFD) to improve these predictions and provide a fundamental understanding of these important concepts.
Under the guidance of UF Senior Lecturer Dr. John Abbitt, students design various centrifugal impeller models using traditional methods first and then run virtual tests of the designs using a proprietary 3-D CFD tool. They modify their designs based on these results, and, once they have a satisfactory design, they use 3-D printing to create hardware that is subsequently tested and compared with the CFD predictions.
The process begins with the application of Euler’s Turbomachine Equation to determine the blade angles for the impeller. Next, students add the blades to a template of the impeller hub provided by the instructor in a 3-D computer-aided design (CAD) program1 as shown in Figure 1.
The final product will be installed into the existing housing shown in Image 1. At this point in the design process, only classic design guidelines have been applied.
Designing Using CFD
Once an initial design is created, the students begin the process of numerically analyzing the impeller’s performance. Numerical CFD simulations are used to test different blade shapes by generating curves of the head rise versus the flow rates and comparing the predictions with the desired performance.
Each of the design iterations involves a detailed process. First, the students create a CFD mesh to precisely conform to the geometry provided by the CAD. Then, they implement appropriate boundary and operating conditions. Finally, they select specific numerical parameters to perform virtual tests.
Fluid Volume Mesh
First, the students create a model of the test rig and hub assembly using a NextEngine 3-D HD scanner and the CAD program. They then add their impeller designs in the CAD program and extract the system’s fluid volume, saving it in stereo lithographical (STL) format. The STL format includes the triangulation of the surfaces of the inlet, outlet, volute and impeller.
This file is imported into the CFD code and used to create the numerical mesh and boundaries needed for the simulation. A typical mesh size for these simulations is about 3 million cells. This process is automated, requiring less than 10 minutes to generate a mesh that captures details down to the order of microns. Students learn guidelines for generating a mesh that will produce accurate results while optimizing the calculation speed.
The students then enter the properties, boundary conditions and operating parameters corresponding to what would be done in a physical test. For the simulations, air is assumed as an ideal gas, and the pressure far from the inlet nozzle is atmospheric, with the exit pressure also atmospheric in accordance with subsonic nozzle flow theory.
Turbulence is modeled using the standard K-epsilon model2. The flow is regulated with 10 different smoothly contoured nozzles with cross-sectional areas corresponding to 5, 10, 15, 20, 25, 30, 40, 50 and 70 percent of the fully open flow at the outlet. The system is tested with the nine nozzles plus a shutoff plate (for no flow). The geometries of the nozzles, inlet, volute and outlet are included as part of the numerical model.
By specifying the geometry, inlet and exit pressures, and rotational speed of the impeller, the CFD code will predict the corresponding flow rate and the head rise.
In addition to the operating conditions, several numerical parameters—such as higher-order schemes and transient versus steady-state analysis—must be considered.
During the project, the advantage of higher-order numerical schemes in resolving the flow field is discussed and demonstrated. The project stresses and demonstrates the advantage of running full 3-D, transient simulations, which can account for pulsations, by comparing these simulations with the experimental data and the more common but less accurate steady-state analysis.
Once created, the numerical model can run in the same manner as a physical hardware test, generating data for different operating conditions. Specifically, the students can vary the revolutions per minute (rpm) and outlet area to predict the corresponding flow field, flow rates, pressures, torques, powers and loads throughout the blower. The students use the results to test different iterations of their prototype and select the best design.
As an example, the predicted pressure field throughout the test rig is show in Figure 2, and a cross-sectional view of the corresponding flow field in the housing is shown in Figure 3. This simulation took 35 minutes to reach a steady-state solution on a Dell Precision T5810 computer with an Intel Xeon CPU E5-1620 email@example.com GHz.