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Heat Transfer Simulation
Simulating shell-and-tube heat exchangers In this study , a shell-and-tube heat exchanger was simulated under various flow rates using M-Star CFD on an NVIDIA RTX 3090 GPU . Three different grid resolutions were tested to balance accuracy and computational cost . The intermediate resolution proved to be the optimal choice , achieving results within 10 % of experimental data while maintaining reasonable runtimes . To ensure accurate predictions , a “ wall function ” model was applied . This method smooths boundary layer interactions and reduces numerical artifacts associated with traditional grid-aligned boundary conditions . The results were benchmarked against experimental data and demonstrated excellent agreement for both pressure drop and heat transfer coefficient predictions . A fixed flow rate of 0.00222 m ³/ s was specified at shellside inlet and a 0 psig pressure boundary condition was prescribed at the shellside outlet . Water with a kinematic viscosity of 1e – 6 m 2 / s and a density of 1000 kg / m 3 was used for the fluid properties . All simulations were performed on an NVIDIA RTX 3090 GPU , with each simulation running for a total of 10 seconds , discarding the first 5 seconds to eliminate initial transients during startup . A time-averaged analysis was then performed over the remaining 5 seconds .
In addition to these numerical studies , the intermediate lattice size was chosen to evaluate the entire range of volumetric flow conditions experimentally reported by Chen et al ., 2019 . Initially 3 m 3 / h , increasing 1 m 3 / h every 5 s until reaching 7 m 3 / h .
Key findings The results of the pressure drop in the shell side of the heat exchanger are presented below . 1 . Pressure drop : Simulations using the wall function model closely matched experimental values across a range of flow rates , outperforming traditional gridaligned and interpolated boundary conditions . This is critical for ensuring realistic energy requirements in industrial systems .
2 . Heat transfer : The wall function model also excelled in predicting heat transfer coefficients , showing deviations of less than 10 % from experimental values at higher flow rates . The approach effectively captures local heat transfer variations , offering deeper insights into exchanger performance .
3 . Local heat transfer coefficients : One standout feature of M-Star CFD is its ability to resolve local heat transfer coefficients across the entire surface of the heat exchanger . This provides engineers with detailed insights into where heat transfer is most efficient and where potential bottlenecks exist . By visualizing these
Numerical and experimental shellside pressure drop . Numerical and experimental heat transfer coefficients .
Local heat transfer coefficient ( Flow = 3 m 3 / hour ). Local heat transfer coefficient ( Flow = 4 m 3 / hour ). www . heat-exchanger-world . com Heat Exchanger World March 2025
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