Annular Jet Pump CFD Simulation, ANSYS Fluent Training
Annular Jet Pump CFD Simulation, ANSYS Fluent Training
- Upon ordering this product, you will be provided with a geometry file, a mesh file, and an in-depth Training Video that offers a step-by-step training on the simulation process.
- For any more inquiries regarding the product, please do not hesitate to reach out to us at info@CFDLAND.com or through our online support assistant.
€140.00 Original price was: €140.00.€99.00Current price is: €99.00.
The annular jet pump is a super clever device that moves fluids without any spinning parts or motors! This amazing fluid pumping technology uses a fast-moving stream of water or air (called the primary flow) to pull along and push a slower secondary flow, just like how a fast train creates wind that pulls leaves along with it. First of all, the special annular design means the high-speed jet comes in as a ring shape around the outside, which works much better than older straight-line jets. Additionally, the motive fluid rushes through a carefully shaped nozzle and creates a powerful suction effect that can pull liquids from wells or tanks without needing electricity. Moreover, the heart of the jet pump is the mixing chamber where fast and slow flows come together and share energy through momentum transfer – this is like a fast-running person grabbing someone’s hand and pulling them along! Furthermore, because they have no moving parts to break, annular pumps last much longer than regular pumps in dirty or sandy water. The special throat section and diffuser parts help convert speed energy back into pressure energy, making the whole system more efficient. Most importantly, these simple but powerful pumps work great for many jobs like lifting water from wells, mixing chemicals, boosting flow in pipes, and even creating vacuum for scientific equipment. The current CFD simulation relies on a valid reference paper entitled “ Parameter Analysis and Optimization of Annular Jet Pump Based on Kriging Model”.
- Reference [1]: Xu, Kai, et al. “Parameter analysis and optimization of annular jet pump based on kriging model.” Applied Sciences21 (2020): 7860.
- Reference [2]: Xu, Kai, et al. “Multi-objective optimization of jet pump based on RBF neural network model.” Journal of Marine Science and Engineering2 (2021): 236.
Figure 1: Schematic drawing of an annular jet pump
Simulation Process
Figure 2 shows the annular jet pump calculation domain. To reduce the calculation cost, the 2D axisymmetric model was adopted. It is discretized by 390307 quadrilateral cells (structured grid). The standard wall function and the realizable k–ε model can accurately simulate annular jet pump flow details and calculate the performance index. These settings are all set regarding the reference paper.
Figure 2: 2D axisymmetric domain
Post-processing
The effect of turbulent mixing is influenced by the jet pump structure parameters determining the jet pump performance. Dimensionless parameters, efficiency η and pressure ratio h, are introduced to study the jet pump performance. Their equations are (reference paper):
Given the reported efficiency of 0.115 (11.5%), this suggests that there’s significant room for optimization while the pump is operational. The relatively low efficiency might be due to energy losses during mixing, wall friction, or suboptimal geometry design. Further analysis and potential design modifications could be explored to improve the pump’s performance.
Looking at the velocity patterns shows us how the annular jet pump works its magic! The speed starts low at the inlets but then zooms up to maximum velocity of 1.4 m/s right at the narrow ring-shaped opening. This happens because the flow must speed up when squeezing through a smaller space, following the continuity equation: Q = V × A (flow rate equals velocity times area). Once the fast-moving primary flow shoots out from the ring gap, it creates a cone-shaped stream that pulls in the slower secondary flow around it. The most amazing part is how the high-speed flow spreads out from the walls toward the center as it moves through the mixing chamber. Also, notice how the flow gradually slows down in the diffuser section on the right side, where the pipe gets wider again. This slowing down is super important because it converts speed energy back to pressure energy following Bernoulli’s principle: P₁ + ½ρv₁² + ρgh₁ = P₂ + ½ρv₁² + ρgh₂. The conversion from high velocity (around 1.4 m/s) to lower velocity (about 0.3-0.5 m/s) at the outlet is what creates the pumping effect and makes the whole system work!
Figure 3: Velocity distribution in annular jet pump
The turbulence kinetic energy picture tells us where all the mixing and energy transfer happens in our jet pump! The turbulence stays very low in both inlet sections but then suddenly jumps up right after the annular nozzle where the fast and slow flows meet. We captured peak turbulence values of approximately 0.09 m²/s² in the key mixing regions, which shows exactly where the fast primary flow is grabbing and pulling the slower secondary flow. This turbulence is calculated using the formula k = ½(u’² + v’² + w’²), where u’, v’, and w’ represent the speed fluctuations in different directions. The highest turbulence appears in a cone-shaped region just downstream of the nozzle, marking the shear layer where fast and slow fluids rub against each other. Furthermore, notice how the turbulence gradually decreases as the flow moves toward the outlet, showing that the mixing becomes more complete and the flow more uniform. This perfect pattern of turbulence is exactly what we want in a good jet pump design – strong mixing where the flows first meet, then gradually calming down as the combined flow moves through the diffuser to build up pressure while maintaining good flow stability and pumping efficiency.
Figure 4: Turbulence kinetic energy distribution reaching approximately 0.09 m²/s² in the mixing region
We pride ourselves on presenting unique products at CFDLAND. We stand out for our scientific rigor and validity. Our products are not based on guesswork or theoretical assumptions like many others. Instead, most of our products are validated using experimental or numerical data from valued scientific journals. Even if direct validation isn’t possible, we build our models and assumptions on the latest research, typically using reference articles to approximate reality.
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You can load geometry and mesh files, as well as case and data files, using any version of ANSYS Fluent.
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