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Technical Brief

Analysis of Filtered Thermal-Fluid Video Data From Downward Facing Boiling Experiments

[+] Author and Article Information
Chi-Shih Jao

Department of Electrical Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: cxj36@psu.edu

Faith R. Beck

Department of Mechanical and Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: frb115@psu.edu

Nurali Virani

General Electric Global Research Center,
Niskayuna, NY 12309
e-mail: nurali.virani88@gmail.com

Fan-Bill Cheung

Fellow ASME
Department of Mechanical and
Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: fxc46@psu.edu

Asok Ray

Fellow ASME
Department of Mechanical and
Nuclear Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: axr2@psu.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received October 5, 2017; final manuscript received February 16, 2018; published online March 27, 2018. Assoc. Editor: Sergey Nersesov.

J. Dyn. Sys., Meas., Control 140(7), 074502 (Mar 27, 2018) (7 pages) Paper No: DS-17-1506; doi: 10.1115/1.4039470 History: Received October 05, 2017; Revised February 16, 2018

During severe accidents in a nuclear power plant, in-vessel cooling may be required to mitigate the risk of vessel failure in the event of core meltdown and subsequent corium contamination. This cooling technique, known as in-vessel retention (IVR), entails flooding the reactor cavity with water. If the temperatures are sufficiently high, IVR may cause downward facing boiling (DFB) on the outer surface of the reactor pressure vessel (RPV), which gives rise to two-phase thermal-hydraulic phenomena. The regimes in DFB may range from film boiling to nucleate boiling, where the efficiency of cooling varies immensely between these two. In the DFB geometry under consideration (i.e., a hemispherical vessel), the collected signals/images are heavily contaminated by unavoidable noise and spurious disturbances, which hinder the extraction of pertinent information, such as film thickness and the boiling cycle. This paper proposes a wavelet-based filtering of sensor measurements for denoising of the nonstationary signals with the future objective of estimating the thickness of vapor films in real time, as needed for process monitoring and control. The proposed concept has been validated with experimental data recorded from a pool boiling apparatus for physics-based understanding of the associated phenomena.

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References

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Figures

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Fig. 1

The pool boiling apparatus: (a) schematic diagram of the experimental apparatus and (b) measurement angles ϕ

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Fig. 2

(a) Raw and detected edge images, (b) geometry of the vessel for vapor film extraction, and (c) schematic of IA vibration

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Fig. 3

Profiles of vapor film thickness estimation at 97 °C bath temperature. The thick vertical lines indicate the time epoch (i.e., 9.2 s) at which the signal behavior changes significantly.

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Fig. 4

Multiresolution analysis of signals in the first 6000 frames. The Wavelet basis db45 has been used for MRA: (a) ϕ = 42 deg, (b) ϕ = 28 deg, (c) ϕ = 14 deg, and (d) ϕ = 0 deg.

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Fig. 5

Schematic representation of the recursive filtering process

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Fig. 6

Profile of a typical IA signal

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Fig. 7

Filtered signals of vapor film thickness. The thick vertical lines in the two bottom plots indicate the time of thermocouple quench.

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Fig. 8

Filtered signals (ϕ = 28 deg) at different bath temperatures

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