2014
DOI: 10.1016/j.apm.2014.04.051
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A fast running numerical model based on the implementation of volume forces for prediction of pressure drop in a fin tube heat exchanger

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Cited by 10 publications
(5 citation statements)
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“…Due to the limitations of FEM-based methods (geometry preparation, meshing, computational burden or software licenses among others) or the limitations of lumped parameter methods (poor discretization or not considering the temperature dependency of the cable parameters), to overcome these drawbacks, it is highly appealing to develop fast and accurate transient models [ 23 ], if possible based on model reduction methods [ 24 ].…”
Section: Introductionmentioning
confidence: 99%
“…Due to the limitations of FEM-based methods (geometry preparation, meshing, computational burden or software licenses among others) or the limitations of lumped parameter methods (poor discretization or not considering the temperature dependency of the cable parameters), to overcome these drawbacks, it is highly appealing to develop fast and accurate transient models [ 23 ], if possible based on model reduction methods [ 24 ].…”
Section: Introductionmentioning
confidence: 99%
“…Geometrical structure of a heat exchanger is mostly compact and complex, which makes discretization of such domain and further computations problematic. This applies in particular to small but important elements, like finned pipes, in terms of heat transfer and pressure drop [20][21][22][23].…”
Section: Introductionmentioning
confidence: 99%
“…A commercial finite volume methodbased code, CFX, was used to model the convective heat transfer in a representative elementary volume for fin and tube heat exchanger. Applying a finite element simulation in COMSOL, a fast running numerical model for prediction of pressure drop in a fin tube heat exchanger was developed by Rezk and Forsberg [13]. Taler and Ocłoń [14] correlated air-side heat transfer results based on the CFD modeling for plate fin and oval tube heat exchangers.…”
Section: Introductionmentioning
confidence: 99%