Abstract

Determination of the local void fraction in BWRs from in-core neutron noise measurements requires the knowledge of the axial velocity of the void. The purpose of this paper is to revisit the problem of determining the axial void velocity profile from the transit times of the void between axially placed detectors, determined from in-core neutron noise measurements. In order to determine a realistic velocity profile which shows an inflection point and hence has to be at least a third order polynomial, one needs four transit times and hence five in-core detectors at various axial elevations, whereas the standard instrumentation usually consists only of four in-core detectors. Attempts to determine a fourth transit time by adding a TIP detector to the existing four LPRMs and cross-correlate it with any of the LPRMs have been unsuccessful so far. In this paper we thus propose another approach, where the TIP detector is only used for the determination of the axial position of the onset of boiling. By this approach it is sufficient to use only three transit times. Moreover, with another parametrisation of the velocity profile, it is possible to reconstruct the velocity profile even without knowing the onset point of boiling, in which case the TIP is not needed, although at the expense of a less flexible modelling of the velocity profile. In the paper the principles are presented, and the strategy is demonstrated by concrete examples, with a comparison of the performance of the two different ways of modelling the velocity profile. The method is tested also on velocity profiles supplied by system codes, as well as on transit times from neutron noise measurements.

Highlights

  • Ever since early work in the mid-70’s on the in-core neutron noise in BWRs revealed that direct information on the local two-phase flow fluctuations can be obtained through the local component of the neutron noise (Wach and Kosály, 1974; Behringer et al, 1979), it was thought that such measurements could be used to determine the local void fraction in the core

  • To date no routine method exists for extracting the local void fraction in BWRs from measurements

  • Unlike in the method suggested by Loberg et al (2010), in which the void fraction is extracted from the neutron energy spectrum, our suggestion was to utilise the information content in the measured neutron noise by the four axially displaced LPRM detectors in the same detector string, which constitute the standard instrumentation

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Summary

Introduction

Ever since early work in the mid-70’s on the in-core neutron noise in BWRs revealed that direct information on the local two-phase flow fluctuations can be obtained through the local component of the neutron noise (Wach and Kosály, 1974; Behringer et al, 1979), it was thought that such measurements could be used to determine the (axially) local void fraction in the core. It was suggested that one could use, in addition to the four standard LPRMs (Local Power Range Monitors), an additional TIP detector (Transverse In-core Probe), by placing the TIP at an axial position either between the four LPRMs, or outside these, i.e. in a position different from those of the LPRM positions, and determine the transit time between the TIP and the nearest LPRM This approach was tried in measurements, performed in the Swedish Ringhals-1 BWR (Dykin et al, 2014). For simplicity these profile types will be referred to as ‘trigonometric’’ In this case not even the onset point of the boiling needs to be known; determination of the void profile is possible based on solely of the three measured transit times with the standard instrumentation, without the need for using a TIP detector at all. The focus of the investigation is to see which method can reconstruct the known transit times better, and which inversion method is more robust and convergent

Characteristics of the velocity profile
Possible analytical forms
Construction of a simple non-polynomial velocity profile
The unfolding procedure
Trigonometric profile
Polynomial profile
Significance of choosing the right type of profile
Test with Ringhals-1 data
Conclusions
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