Development, verification and application of a new model for active nucleation site density in boiling systems

Li, Quan; Jiao, Yongjun; Avramova, Maria; Yu, Ji-Guo; Chen, Jie; Hou, Jason

doi:10.1016/j.nucengdes.2017.12.027

Cited by 46 publications

(20 citation statements)

References 14 publications

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“…The new model is based on a parametric analysis of existing experimental data and developed as a function of three crucial parameters relevant to the nucleation site density: wall superheat, system pressure, and contact angle. Li et al' model is applicable in a wide range of pressures: 0.101 MPa~ 19.8 MPa [24]. As shown from Figure 2, the nucleation site density model predicted by Li et al' model [24] are in good agreement with the published experimental data [25] compared to the Hibiki-Ishii' model.…”

Section: Data-driven Nucleation Site Density Closuresupporting

confidence: 66%

“…Li et al' model is applicable in a wide range of pressures: 0.101 MPa~ 19.8 MPa [24]. As shown from Figure 2, the nucleation site density model predicted by Li et al' model [24] are in good agreement with the published experimental data [25] compared to the Hibiki-Ishii' model. Another key advantages of Li et al' model is that there are no artificial limiters of superheat temperature.…”

Section: Data-driven Nucleation Site Density Closuresupporting

confidence: 66%

“…A data-driven nucleation site density model has been recently developed by Li et al [24] and preliminarily applied in CFD simulations of subcooled boiling in a vertical heated tube. The new model is based on a parametric analysis of existing experimental data and developed as a function of three crucial parameters relevant to the nucleation site density: wall superheat, system pressure, and contact angle.…”

Section: Data-driven Nucleation Site Density Closurementioning

confidence: 99%

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Toward Industrial Applicability of DNB Predictions in CFD With Improved Wall Boiling Models

Feng

Skirpan

Baglietto

2020

Volume 1: Beyond Design Basis; Codes and Standards; Computational Fluid Dynamics (CFD); Decontamination and Decommissioning; Nu

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The design of Pressurized Water Reactor (PWR) fuel has to rely on costly prototypical experimental campaigns, due to the inherent limitations of legacy lumped-parameter thermal-hydraulics codes. By resolving the fine spatial scales, computational fluid dynamics (CFD) methods offer the opportunity of delivering improved fuel design, taking full advantage of three-dimensional mixing and turbulence control, but must extend their predictive capabilities to multiphase conditions up to DNB, where the maturity and accuracy of the methods is still developing. In this paper, the closures developed within the Eulerian-Eulerian two-fluid model framework are assembled and extended to a general boiling formulation to deliver prediction of DNB at reactor conditions. The classic heat flux partitioning approach is advanced through selection of optimal closures for interaction length scale, nucleation site density, and bubble departure diameter, and further extended though the addition of a consistent DNB detection criterion, to reflect the near wall two phase characteristics. Assessment is performed at 138 bar against the experimental dataset for vertical pipe, where the inlet subcooling ranges from 1 to 150 K and the mass flux varies from 600 kg/(m2.s) to 2650 kg/(m2.s). The presented closures demonstrate consistent agreement with the experimental data, in particular in light of the calibration free application, while further work is ongoing to close the remaining gap and support the introduction of further modeling improvements.

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Section: Data-driven Nucleation Site Density Closuresupporting

confidence: 66%

Section: Data-driven Nucleation Site Density Closuresupporting

confidence: 66%

Section: Data-driven Nucleation Site Density Closurementioning

confidence: 99%

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Toward Industrial Applicability of DNB Predictions in CFD With Improved Wall Boiling Models

Feng

Skirpan

Baglietto

2020

Volume 1: Beyond Design Basis; Codes and Standards; Computational Fluid Dynamics (CFD); Decontamination and Decommissioning; Nu

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“…In the FY19 model, active NSD is estimated by the modified Li et al model. 17 Li et al's NSD model strives to account for the system pressure, surface characteristics, and wall superheat when NSD is correlated based on empirical data with a wide range of operating pressure conditions illustrated in Fig. 3.…”

Section: Iiia Active Nucleation Site Densitymentioning

confidence: 99%

Progress Toward Simulating Departure from Nucleate Boiling at High-Pressure Applications with Selected Wall Boiling Closures

Kim

Johns

Yoo

et al. 2020

Nuclear Science and Engineering

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Recently, a Eulerian-based two-fluid computational fluid dynamics (CFD) framework with a wall heat flux partitioning approach has been intensively investigated for departure from nucleate boiling (DNB) simulation under the U.S. Department of Energy-funded Consortium for Advanced Simulation of Light Water Reactors (CASL) program. Understanding of the DNB characteristics over a range of pressurized water reactor-like operating conditions and accurate prediction of boiling crisis in the nuclear power system have been grand challenges because of the large impact of DNB on reactor safety and operational economics. The ultimate goal of this task in the CASL program is to introduce a robust multiphase CFD-based DNB modeling framework that is capable of characterizing an entire boiling history in which the wall boiling mode experiences the following through multiple stages of heat transfer mode: (1) single-phase convective heat transfer, (2) nucleate boiling heat transfer, and (3) identification of the departure of nucleate boiling. To validate the CASL boiling model, we have benchmarked simulated DNB over three different flow channel configurations (pipe flow, 5 × 5 fuel bundle with mixing vane tests, and 5 × 5 fuel bundle without mixing vane tests) against experimental measurements, and the validation result with open literature is reported. The DNB detection criteria in the simulation are checked by monitoring the peak wall temperature, wall dryout factor, and net energy balance. In addition to the DNB performance test, some preliminary sensitivity results on closure model selection are reported to address the prediction capability of local void profile against measurements. The boiling simulation tested in this study exhibits a maximum deviation of 24% from the measured DNB value in a high-pressure (i.e., 138 bars) subcooled pipe flow test. The ranges of operating conditions are as follows: 1650 to 2650 kg/m 2 •s for mass flux and 8.5 to 96 K for subcooled inlet temperature. The deviation is even reduced to 7% when the subcooled temperature is less than 40 K. Besides accuracy, base practice guidelines for DNB detection criteria are tested by monitoring three simulation variables: (1) maximum wall temperature, (2) wall dryout factor (i.e., K-value), and (3) energy balance. Numerical robustness of DNB simulation is largely achieved in most of the validation test except for a few high subcooled test cases.

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“…For instance, the gas-liquid subcooled boiling could occur in the first loop of the nuclear power plant (NPP) which highly affects the reactor safety and efficiency [5]. Especially, the phenomenon of the departure from nucleate boiling (DNB) relates with the critical heat flux (CHF), and the validations of the improvement on the CHF in the design of the nuclear power plant are expensive and time-consuming [6].…”

Section: Introduction 1gas-liquid Subcooled Boiling Flowmentioning

confidence: 99%

Evaluation on Coupling of Wall Boiling and Population Balance Models for Vertical Gas-Liquid Subcooled Boiling Flow of First Loop of Nuclear Power Plant

Liu

2021

Energies

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An accurate prediction of the interphase behaviors of the vertical gas-liquid subcooled boiling flow is meaningful for the first loop of a nuclear power plant (NPP). Therefore, the interphase behaviors including the bubble size distribution in the first loop of the NPP are analyzed, evaluated, and validated using various wall boiling models coupled with the population balance model (PBM) kernels in this paper. Firstly, nondimensional numbers of the first loop of the NPP and DEBORA (Development of Borehole Seals for High-Level Radioactive Waste) experiment test cases are analyzed with approximation. Secondly, five active nucleation site density models Nn coupled with the PBM kernel combination, four kernel combinations (C1~C4) with the Nn models are calculated and analyzed. Lastly, various behaviors including the bubble size distribution Sauter mean diameter (SMD) dp, void fraction α, gas superficial velocity jg, and liquid superficial velocity jl are compared and validated with the experimental data of the DEBORA-1 (P = 2.62 MPa). The results indicate that the two Nn models are suitable for the calculations of thefirst loop of the nuclear power plant. For instance, for the bubble size distribution SMD dp, the specified Nn model with C1 (maximum relative error 9.63%) has relatively better behaviors for the first loop of the NPP. Especially, the combination C1 is applicable for the calculation of the bubble size distribution dp, void fraction α and liquid superficial velocity jl while C4 is suitable for the calculation of the gas superficial velocity jg. These results can provide guidance for the numerical computation of the subcooled boiling flow in the first loop of the NPP.

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Development, verification and application of a new model for active nucleation site density in boiling systems

Cited by 46 publications

References 14 publications

Toward Industrial Applicability of DNB Predictions in CFD With Improved Wall Boiling Models

Toward Industrial Applicability of DNB Predictions in CFD With Improved Wall Boiling Models

Progress Toward Simulating Departure from Nucleate Boiling at High-Pressure Applications with Selected Wall Boiling Closures

Evaluation on Coupling of Wall Boiling and Population Balance Models for Vertical Gas-Liquid Subcooled Boiling Flow of First Loop of Nuclear Power Plant

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