A validated CFD model of plain and serrated fin-tube bundles

Lindqvist, Karl; Næss, Erling

doi:10.1016/j.applthermaleng.2018.07.060

Cited by 23 publications

(13 citation statements)

References 17 publications

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“…In the context of fin-tube bundles, CFD models can provide heat transfer and pressure drop coefficients in a consistent and time efficient manner. Comparisons with experimental data has shown good agreement, close to or within the experimental uncertainty, for a wide range of geometries [15]. CFD models are also able to provide data for extreme geometries that may not be possible to manufacture and test experimentally, but still add valuable data in the correlation development process.…”

Section: Data Source Experimental Correlation or Cfdmentioning

confidence: 63%

“…Numerical simulations in this work followed the methodology described in a previous article [15], where thorough validation with experimental data are given. The main characteristics of the numerical model are as follows:…”

Section: Numerical Modelmentioning

confidence: 99%

“…A limitation of the current study is that the correlation accuracy is restricted to the accuracy of the numerical model. The numerical model is successfully validated over a large range of geometric parameters for which experimental data exist [15]; Future directions of this work should therefore include experimental investigations of previously untested geometries indicated by the correlations, such as at the case study optimum indicated in this work.…”

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confidence: 98%

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A Machine Learning Approach to Correlation Development Applied to Fin-Tube Bundle Heat Exchangers

et al. 2018

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Heat exchanger designers need reliable thermal-hydraulic correlations to optimize heat exchanger designs. This work combines an adaptive sampling method with a Computational Fluid Dynamics (CFD) simulator to obtain increased accuracy and validity range of heat transfer and pressure drop predictions using a limited number of data points. Correlation efficacy was evaluated based on a steam generator case study. The sensitivity to the design parameters was analyzed in detail. The RMSE (root mean square error) of the developed correlations were reduced, through CFD sampling, from 28% to 15% for pressure drop, and from 33% to 25% heat transfer, compared to regression on experimental data only. The best reference correlations have RMSE values of 43% and 33% on pressure drop and heat transfer, respectively, on an independent validation set. Indeed, a radically different fin-tube geometry was suggested for the case study, compared to results using the Escoa correlations.The developed correlations show good to excellent agreement with trends in the CFD model. The quantitative error of predicted heat transfer and pressure drop coefficients at the case study optimum, however, was as large as those of the Escoa correlations. More data are likely needed to improve accuracy for compact heat exchanger designs further.

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Section: Data Source Experimental Correlation or Cfdmentioning

confidence: 63%

Section: Numerical Modelmentioning

confidence: 99%

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confidence: 98%

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A Machine Learning Approach to Correlation Development Applied to Fin-Tube Bundle Heat Exchangers

et al. 2018

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“…These, in turn, are calculated using equations from literature (e.g., [28] in the case of plain tubes or [29] if the tubes are finned) depending on the actual bundle geometry and flow conditions. Additional information regarding validation of the commonly used empirical equations for estimation of heat transfer coefficient in the case of plain and serrated fins can be found, for instance, in [30]. One could also use the correlations from [31], which have been obtained via the machine learning technique.…”

Section: Of 20mentioning

confidence: 99%

Nonlinear Finite Element Analysis-Based Flow Distribution and Heat Transfer Model

et al. 2020

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A new strategy for fast, approximate analyses of fluid flow and heat transfer is presented. It is based on Finite Element Analysis (FEA) and is intended for large yet structurally fairly simple heat transfer equipment commonly used in process and power industries (e.g., cross-flow tube bundle heat exchangers), which can be described using sets of interconnected 1-D meshes. The underlying steady-state model couples an FEA-based (linear) predictor step with a nonlinear corrector step, which results in the ability to handle both laminar and turbulent flows. There are no limitations in terms of the allowed temperature range other than those potentially stemming from the usage of fluid physical property computer libraries. Since the fluid flow submodel has already been discussed in the referenced conference paper, the present article focuses on the prediction of the tube side and the shell side temperature fields. A simple cross-flow tube bundle heat exchanger from the literature and a heat recovery hot water boiler in an existing combined heat and power plant, for which stream data are available from its operator, are evaluated to assess the performance of the model. To gain further insight, the results obtained using the model for the heat recovery hot water boiler are also compared to the values yielded by an industry-standard heat transfer equipment design software package. Although the presented strategy is still a “work in progress” and requires thorough validation, the results obtained thus far suggest it may be a promising research direction.

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“…Although limited when it comes to condensation hoods, the literature describes profusely the unit processes regarding other applications and appliances. The most important phenomena in terms of the condensation efficiency are: the model of condensation of the air-steam mixture coupled with the species transportation process [4][5][6][7][8], the heat transfer in externally-finned pipes with plain circular fins [9][10][11][12][13][14], and also tube bundle configuration analysis [15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Development of a Condensation Model and a New Design of a Condensation Hood—Numerical and Experimental Study

et al. 2021

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The development of a numerical model and design for the innovative construction of a heat exchanger (HE) used in a condensation hood (being a part of the combi-steamer) are described in this work. The model covers an air-steam flow, heat transfer, and a steam condensation process. The last two processes were implemented with the use of an in-house model introduced via User Defined Functions (UDF). As the condensate volume is negligible compared to the steam, the proposed model removes the condensate from the domain. This approach enabled the usage of a single-phase flow for both air and steam using a species transport model. As a consequence, a significant mesh and computation time reduction were achieved. The new heat exchanger is characterised by reorganised fluid flow and by externally finned pipes (contrary to the original construction, where internally finned pipes were used). This allowed a reduction in the number of the pipes from 48 to 5, which significantly simplifies construction and manufacturing process of the HE. The redesigned HE was tested in two cases: one simulating normal working conditions with a combi-steamer, the other with extremely high heat load. Measurement data showed that the numerical model predicted condensate mass flow rate (3.67 g/s computed and 3.56 g/s measured) and that the condensation capability increased at least by 15% when compared to the original HE design.

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A validated CFD model of plain and serrated fin-tube bundles

Cited by 23 publications

References 17 publications

A Machine Learning Approach to Correlation Development Applied to Fin-Tube Bundle Heat Exchangers

A Machine Learning Approach to Correlation Development Applied to Fin-Tube Bundle Heat Exchangers

Nonlinear Finite Element Analysis-Based Flow Distribution and Heat Transfer Model

Development of a Condensation Model and a New Design of a Condensation Hood—Numerical and Experimental Study

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