Spiral Heat Exchanger CFD Simulation Considering Heat Transfer Coefficient, ANSYS Fluent Training
Spiral Heat Exchanger CFD Simulation Considering Heat Transfer Coefficient, ANSYS Fluent Training
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€160.00 Original price was: €160.00.€75.00Current price is: €75.00.
The small shape and excellent heat transfer of the Spiral Heat Exchanger make it a thermal management breakthrough. The spiral design uses two concentric spiral flow channels to efficiently exchange heat between two fluids without many tube passes, unlike shell and tube exchangers. This novel design improves heat transfer surface area while reducing pressure drop, improving thermal performance and energy efficiency. Spiral Heat Exchangers are helpful for chemical processing, food and beverage production, and HVAC systems due to their adaptability.
According to the reference paper entitled “Effect of employing a new biological nanofluid containing functionalized graphene nanoplatelets on thermal and hydraulic characteristics of a spiral heat exchanger [1]”, we conducted a CFD simulation, modelling spiral heat exchanger considering Heat transfer coefficient. The figure portrays a schematic of a 3D model of the spiral heat exchangers:
- Reference [1]: Bahiraei, Mehdi, Hamid Kiani Salmi, and Mohammad Reza Safaei. “Effect of employing a new biological nanofluid containing functionalized graphene nanoplatelets on thermal and hydraulic characteristics of a spiral heat exchanger.” Energy conversion and management180 (2019): 72-82.
- Reference [2]: Zhang, Yanfeng, et al. “Numerical study on heat transfer enhancement in capsule-type plate heat exchangers.” Applied Thermal Engineering108 (2016): 1237-1242.
Figure 1: Geometrical configuration of spiral heat exchanger
Simulation Process
The geometry consists of three zones. Two stands for cold and hot liquid and the third one is dedicated to the copper wall of heat exchanger. Approximately 1 million elements are used to fill the computational domain with high-quality grid. The hot and cold fluids` temperature is 350 and 280K, respectively. We hope to see significant performance due to the use of copper walls. Two important output parameters, including Delta(T-LMTD) and heat transfer coefficient, are calculated based on the given equations:
Post-processing
With temperatures ranging from 280K to 350.5K, the temperature distribution image shows a very good heat transfer pattern across the spiral shape. The contour plot shows a smooth and steady change in temperature from the center to the spiral on the outside. This means that the hot and cold fluids are exchanging heat in the best way possible. The simulation, which uses about 1 million high-quality grid elements, shows that the copper wall structure makes thermal conductivity much better. In the transition zones between the spiral channels, the temperature gradient is especially clear. This is where the hot fluid (entering at 350K) successfully transfers heat to the cold fluid (entering at 280K), giving them exit temperatures of 333K and 296.5K, respectively.
Figure 2: Temperature field in spiral heat exchanger
The thermal performance metrics show that the exchanger works well; a Log Mean Temperature Difference (LMTD) of 53.42K shows that it has a lot of temperature-driving capacity. The heat transfer value of 102.8 W/m²K shows that the design is very good at exchanging heat, which is especially noticeable given how small the spiral is. The temperature contour also shows how well the concentric spiral flow lines work at increasing the surface area for heat transfer while reducing pressure losses. This is shown by the smooth changes in temperature that can be seen in the volume rendering, especially where the hot and cold fluid lines are next to each other and only the copper wall separates them. The design is even more efficient because the temperatures are spread out evenly, which means there is little thermal resistance and the heat transfer area is used to its best.
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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