Simulation of subcooled flow instability for high flux research reactors using the extended code ATHLET

Hainoun, A.; Schaffrath, A.

doi:10.1016/s0029-5493(00)00410-6

Cited by 17 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, since void fraction was not directly measured, but determined from the resulted beam intensity which changes as a result of absorption in accordance with the following correlation [24] , where I 0 is the initial beam intensity, μ w,f are the linear absorption coefficients in wall and fluid, and l w,f are the path lengths though wall and fluid, the measurement error may vary greatly as a result of "error propagation" (see section 3.1), and additional uncertainty is introduced from errors in estimating above parameters. Complicating the matter further, in the plane shown in Figure 3.4.1, the portions of gamma beam absorbed in walls and in fluid vary greatly depending on the direction of each beam path and it is difficult to precisely determine the average (over channel cross-section) void/fluid volume fraction based on the integral measurement of beam intensity provided by the detector.…”

Section: Example Of Quantification Of Data Needs Data Classificationsupporting

confidence: 65%

Quantification of Data Needs, Data Collection and

Bui¹,

Dinh²

2013

View full text Add to dashboard Cite

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...

show abstract

Section: Example Of Quantification Of Data Needs Data Classificationsupporting

confidence: 65%

Quantification of Data Needs, Data Collection and

Bui¹,

Dinh²

2013

View full text Add to dashboard Cite

show abstract

“…The power plants' safety is largely based on simulation [5]. Nowadays, the bestestimate nuclear system codes such as TRAC [6], RETRAN [7], RELAP5 [8,12], ATHLET [9], CATHARE [10], and APROS [11] are widely used to investigate the thermal-hydraulic characteristics of nuclear power plants either during steady-state operation or accidental transients and simulate the overall behavior of the installation (pumps, piping, heat exchangers, tanks, valves, control loops, etc. ).…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of the Accidental Transient of an Industrial Steam Boiler

Cheridi¹,

Chaker²,

Loubar³

2019

Heat and Mass Transfer - Advances in Science and Technology Applications

View full text Add to dashboard Cite

Numerical simulation allows a better understanding of thermal-hydraulic phenomena that can take place in thermal installations. It is a capital contribution, especially in accident situations. The code RELAP5/Mod3.2 makes it possible to predict the thermal-hydraulic behavior of these installations during the normal and accidental operations. The present chapter focuses on accidental transient modeling and simulation of an industrial steam boiler by the code RELAP5/Mod3.2. This steam boiler is radiant type, high power, natural circulation, and a single drum. The model of the boiler developed for the RELAP5/Mod3.2 code encompasses the entire installation. The control loop of the water level in the steam drum and the superheated steam temperature are also included in the model. The qualification process of the steam boiler model is based on the steam boiler operation data under steady-state operating conditions. The comparative study shows that the theoretical results of the code RELAP5 are in good agreement with the operating data of the installation. To evaluate the behavior and response of the boiler in accident situations, the loss of feedwater following pump power loss, with and without protective operations, was simulated.

show abstract

“…(Babelli & Ishii, 2001) presented a procedure for predicting the OFI in down ward flows at low-pressure and low-flow conditions. (Hainoun & Schaffrath, 2001) developed a model permitting a description of the steam formation in the subcooled boiling regime and implemented it in ATHLET code to extend the code's range of application to simulate the subcooled flow instability in research reactors. (Li et al, 2004) presented a three dimensional two-fluid model to investigate the static flow instability in subcooled boiling flow at low-pressure.…”

Section: Introductionmentioning

confidence: 99%

Flow Instability in Material Testing Reactors

El-Morshedy¹

2012

Nuclear Reactors

View full text Add to dashboard Cite

Simulation of subcooled flow instability for high flux research reactors using the extended code ATHLET

Cited by 17 publications

References 5 publications

Quantification of Data Needs, Data Collection and

Quantification of Data Needs, Data Collection and

Numerical Simulation of the Accidental Transient of an Industrial Steam Boiler

Flow Instability in Material Testing Reactors

Contact Info

Product

Resources

About