Comparative analysis of correlations for calculating subcooled boiling heat transfer

Agafonova, N. D.; Gotovskii, M. A.; Paramonova, I. L.

doi:10.1134/s0040601506020091

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Consortium for Advanced Simulation of LWRs Simplified 1D two-phase flow models employed in nuclear thermal hydraulic system codes such as RELAP5 and TRACE need closure relations for flow pattern transition, drag force, interfacial heat transfer, and wall heat flux partition [29]. In these models, the boiling heat transfer coefficient is normally determined with empirical/semi-empirical correlations, many of them were surveyed by Guglielmini et al [30] and Agafonova et al [31].…”

Section: 3)mentioning

confidence: 99%

Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study

Bui¹,

Dinh²,

Williams³

2013

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A ABSTRACTIn addition to a validation data plan for quantification of data needs and strategy for data collection and characterization [1] [2], development of advanced techniques for calibration and validation of complex multiscale, multiphysics nuclear reactor simulation codes are a major component of the CASL VUQ plan.Advanced modeling of LWR systems normally involves a range of physicochemical models describing multiple interacting phenomena, such as thermal hydraulics, reactor physics, coolant chemistry, etc., which occur over a wide range of spatial and temporal scales. To a large extent, the accuracy of (and uncertainty in) overall model predictions is determined by the correctness of various sub-models, which are not conservation-laws based, but empirically derived from measurement data. Such sub-models normally require extensive calibration before the models can be applied to analysis of real reactor problems.This work demonstrates a case study of calibration of a common model of subcooled flow boiling, which is an important multiscale, multiphysics phenomenon in LWR thermal hydraulics. The calibration process is based on a new strategy of model-data integration, in which, all sub-models are simultaneously analyzed and calibrated using multiple sets of data of different types. Specifically, both data on large-scale distributions of void fraction and fluid temperature and data on smallscale physics of wall evaporation were simultaneously used in this work's calibration.In a departure from traditional (or common-sense) practice of tuning/calibrating complex models, a modern calibration technique based on statistical modeling and Bayesian inference was employed, which allowed simultaneous calibration of multiple sub-models (and related parameters) using different datasets. Quality of data (relevancy, scalability, and uncertainty) could be taken into consideration in the calibration process.This work presents a step forward in the development and realization of the CIPS Validation Data Plan [3] [1] at the Consortium for Advanced Simulation of LWRs to enable quantitative assessment of the CASL modeling of Crud-Induced Power Shift (CIPS) phenomenon, in particular, and the CASL advanced predictive capabilities, in general.This report is prepared for the Department of Energy's Consortium for Advanced Simulation of LWRs program's VUQ Focus Area. E EXECUTIVE SUMMARYThis milestone supports a case study of calibration and validation of a realistic and relatively complex subcooled flow boiling model, with the objective to develop recommendations on CASL-wide Model Calibration, Validation, and Uncertainty Quantification efforts. The SFB model utilized a common description of multiphase flow as inter-penetrating continua with conservation laws applied to each phase as a separate field. Small-scale physics related to thermal hydrodynamic inter-phase and flow-wall interactions were represented by various empirical/semi-empirical closure sub-models. In this SFB modeling, the sub-model of wall evaporation, which relied on...

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Section: 3)mentioning

confidence: 99%

Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study

Bui¹,

Dinh²,

Williams³

2013

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“…These data were used in the development of phenomenological analytical models as described in [19] [46], which can be used in CMFD codes as closure models. Plant measurements and observations (PMOs) are mostly at the large scale, integralphysics level.…”

Section: Review Of Experimental and Dns Data Relevant To Subcooled Flmentioning

confidence: 99%

Quantification of Data Needs, Data Collection and

Bui¹,

Dinh²

2013

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Further to the development of a model analysis framework suitable for calibration and validation of complex multivariate multiphysics models detailed in [1], this report presents an approach to data collection and characterization which can work in parallel with the above-mentioned model analysis framework and support the calibration and validation of the case-study subcooled flow boiling model presented in [1].This work presents a step forward in the development and realization of the "CIPS Validation Data Plan" [2][3] at the Consortium for Advanced Simulation of LWRs (CASL) to enable quantitative assessment of the CASL modeling of CrudInduced Power Shift (CIPS) phenomenon, in particular, and the CASL advanced predictive capabilities, in general.Advanced modeling of LWR systems normally involves a range of physicchemical models describing multiple interacting phenomena, such as thermal hydraulics, reactor physics, coolant chemistry, etc., which are usually constrained by the lack of data suitable for model validation and calibration. The necessary employment of different modeling approaches in the advanced LWR modeling practice further complicates the situation, since each modeling approach has a unique requirement of validation data. The development and validation of closure model of wall heat transfer process employed in the subcooled flow boiling modeling, for instance, may require data of microscopic physics, i.e. wall heat flux partitioning, bubble nucleation, growth and detachment dynamics, etc.[4], which can hardly be obtained for reactor-prototypical conditions.Although the model analysis framework proposed in [1] is designed to be robust enough to deal with a wide range of measurement data of different quality and availability, a strategy for data collection, data validation and data characterization is still needed which has been detailed in [3]. This work presents an implementation of that strategy for a case-study calibration/validation of a subcooled flow boiling model. The lesson learnt and implication to CIPS modeling and the overall CASL VUQ effort will also be discussed. EXECUTIVE SUMMARYThis milestone supports a case study on development, testing and application of a strategy, methods and associated infrastructure for validation data support that enables assessment of CASL-developed predictive capability for Crud-Induced Power Shift (CIPS) challenge problem as formulated in a previous report for CASL.VUQ.VVDA.P4.02 [3]. Subcooled flow boiling (SFB) prediction is selected as a capability for which data collection, characterization and integration (model calibration) be performed, with the objective to develop recommendations on a CASL-wide Validation Data Process.This milestone focuses on quantification of data needs, data collection and characterization, preparing the ground for the SFB model calibration and validation. The selected test case (simulation of subcooled flow boiling) is an important capability for CIPS prediction, whose development has been hampered by validation data ch...

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A comparative analysis of the calculation methods of the heat emission during heating water with underheating

et al. 2014

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Comparative analysis of correlations for calculating subcooled boiling heat transfer

Cited by 3 publications

References 6 publications

Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study

Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study

Quantification of Data Needs, Data Collection and

A comparative analysis of the calculation methods of the heat emission during heating water with underheating

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