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Critical heat flux acoustic detection: Methods and application to ITER divertor vertical target monitoring
Fusion Engineering and Design 88 (2013) 1722–1726
Contents lists available at ScienceDirect
Fusion Engineering and Design journal homepage: www.elsevier.com/locate/fusengdes
Critical heat flux acoustic detection: Methods and application to ITER divertor vertical target monitoring X. Courtois a,∗ , F. Escourbiac b , M. Richou a , V. Cantone a , S. Constans c a b c
CEA, IRFM, F-13108 Saint-Paul-Lez-Durance, France ITER Organization, Route de Vinon sur Verdon, F-13115 Saint-Paul-Lez-Durance, France AREVA-NP, Le Creusot, France
a r t i c l e
i n f o
Article history: Received 14 September 2012 Received in revised form 22 February 2013 Accepted 26 February 2013 Available online 23 March 2013 Keywords: Acoustic Critical heat flux Plasma facing component
a b s t r a c t Actively cooled plasma facing components (PFCs) have to exhaust high heat fluxes from plasma radiation and plasma–wall interaction. Critical heat flux (CHF) event may occur in the cooling channel due to unexpected heat loading or operational conditions, and has to be detected as soon as possible. Therefore it is essential to develop means of monitoring based on precursory signals providing an early detection of this destructive phenomenon, in order to be able to stop operation before irremediable damages appear. Capabilities of CHF early detection based on acoustic techniques on PFC mock-ups cooled by pressurised water were already demonstrated. This paper addresses the problem of the detection in case of flow rate reduction and of flow dilution resulting from multiple plasma facing units (PFU) which are hydraulically connected in parallel, which is the case of ITER divertor. An experimental study is launched on a dedicated mock-up submitted to heat loads up to the CHF. It shows that the measurement of the acoustic waves, generated by the cooling phenomena, allows the CHF detection in conditions similar to that of the ITER divertor, with a reasonable number of sensors. The paper describes the mock-ups and the tests sequences, and comments the results. © 2013 Elsevier B.V. All rights reserved.
1. Introduction In the harsh tokamak environment, a good optimised design does not totally prevent PFC from unexpected high heat fluxes (HHF) during plasma operation. Strong material damages can result, up to a very detrimental water leakage in the vacuum vessel which would lead to costly damages and long break for repairing. Thus means of PFC monitoring are mandatory for the success of a safe and reliable operation of a W divertor as foreseen in ITER. In this context, abnormal surface heating due to localised peaked heat fluxes can occur and cause a strong temperature increase of the PFC. According to the duration and area of the unexpected HHF event, the PFC cooling can then evolve from the regular subcooled nucleate boiling regime to the CHF at the cooling tube wall, and cause its burnout. Since PFC temperature measurements by means of thermocouples or infrared (IR) radiation may give delayed data on such event, due to the thermal time constant of the component, experimental acoustic studies have been performed on PFC mock-ups submitted to HHF, and proved that CHF early detection is possible using acoustic sensors. Another advantage of acoustic measurement is
∗ Corresponding author. Tel.: +33 4 42257411; fax: +33 4 42254990. E-mail address: [email protected] (X. Courtois). 0920-3796/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fusengdes.2013.02.149
the wave propagation which makes possible to monitor several PFU with one sensor, whereas a thermocouple is a very local measurement. The IR temperature monitoring drawback is the high uncertainty due to metallic surfaces issues (low and variable emissivity, and high parasitic reflexions).
2. Objective However, some concerns need to be solved before a possible application in ITER. On each of the 54 divertor cassettes (Fig. 1), the vertical targets (2 inner + 2 outer) put together 8–11 PFUs which are hydraulically connected in parallel. The problem is to determine how to monitor the divertor with a minimum number of sensors cautiously located, given that one sensor per PFU is not achievable. Past experiments [1–3] showed that the boiling sounds in cooling channels mainly propagate through the water rather than the structures. Thus, the acoustic waves propagation will be disturbed when the flow coming from the PFUs submitted to the CHF will be mixed with the flow coming from the other PFUs connected in parallel. This phenomenon, called flow dilution effect, will probably alter the CHF detection capabilities. The issue of flow dilution effect is studied by means of an experimental study, which was performed in the frame of the Site Support Agreement No. 9 between ITER Org. and the CEA/IRFM.
X. Courtois et al. / Fusion Engineering and Design 88 (2013) 1722–1726
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Fig. 3. CuCrZr test section and its swirl.
Fig. 1. ITER divertor cassette body.
3. Mock-up and test section description 3.1. Hydraulic mock-up HHF tests are performed under various flow conditions on a dedicated mock-up (Fig. 2). The test section represents a single PFU submitted to an abnormal HHF while the by-pass simulates a variable number of PFUs with a regular cooling regime, i.e. without HHF. Valves, diaphragm and flow metres make flow variation between the test section submitted to HHF and the by-pass, and create the flow dilution effect. The acoustic sensors which equip the mock-up are piezoelectric accelerometers. They measure the acoustic waves transmitted from the fluid to the structure. The sensor no. 2 is the reference sensor for this study. It will measure the acoustic waves generated by the cooling phenomena in the test section, propagating through the water, and mixed with the non-heated flow. 3.2. HHF test section The test section (Fig. 3) made of CuCrZr is designed to simulate the thermal behaviour of an outer vertical target
Fig. 4. Sketch of the CuCrZr equivalent monoblock under CHF, for nominal flow conditions (§5.1).
(OVT) of ITER divertor. The channel tube and the swirl tape (turbulence promoter) have exactly the same geometry as a real OVT monoblock [4]. The external dimensions are adapted with thermal simulation to reproduce the same wall heat flux (WHF) profile along the channel circumference when the CHF is expected (Fig. 4), while the surface temperature is kept lower than the CuCrZr melting. This ensures the same thermo hydraulic and acoustic phenomenology development in the water channel. The thermal simulations [5] are performed using ANSYS FE calculation, with SIEDER TATE and THOM modified CEA laws for the heat transfer coefficients, and TONG75 CEA correlation for the CHF estimation. Four identical test sections are manufactured. The swirl is inserted very tightly in the tube, so that any swirl vibrations are measurable when the water flows in it. 4. CHF acoustic detection principle Acoustic detection consists in analysing the sounds coming from the cooling regimes (Fig. 5) measured by the sensors. The sound looks like a Gaussian noise, and is composed of various sources: - Hydraulic turbulences, varying with flow speed, Re number... - Boiling sounds: steam bubbles growth and collapse. - Resonance phenomena in the water, and/or in the diphasic fluid when the steam ratio is high, i.e. near the CHF. - Other parasitic sources: pump, EB impact...
Fig. 2. Mock-up.
Fig. 5. Cooling regimes of a PFC submitted to HHF.
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Table 1 CHF tests matrix. Test number
#0
#1
#2
#3
#4
Test section flow rate (m3 /h) By-pass flow rate (m3 /h) Dilution ratio
1–3.9 0 1
2.8 2.8 2
2.7 10.8 5
1.4 12.6 10
0.7 12.6 19
A dedicated signal processing allows to identify some of the acoustic signatures of the above mentioned phenomena, and in particular when the WHF approaches the CHF. Fig. 6. Sensor 2 background noise PSD (EB gun off).
5. Tests description 5.1. Test facility The test campaign was performed in the HHF test facility FE 200, at AREVA Le Creusot. An Electron Beam (EB) gun is used as heating source, which simulates the plasma thermal load to test the power handling capabilities of the test section. 5.2. Tests parameters The nominal flow conditions are: 90 ◦ C, 3.0 MPa at the test section outlet, and flow rate 3.7 m3 /h (axial speed = 9 m/s). The flow speed of 11 m/s required by ITER is reduced in order to comply with the water loop pump capabilities in terms of flow and pressure drop. The HHF is applied on 5 consecutive blocks (20 cm2 ), with increasing power steps. Each step lasts 30 s and is followed by a 30 s standby. The absorbed HHF is controlled by thermocouples at the mock-up inlet and outlet (thermal balance). The EB sweeping uses a random scanning mode instead of the standard TV screen mode, to avoid a periodic excitation of the surface. As a drawback, the power deposition profile is Gaussian shaped. The EB is stopped when the surface temperature suddenly rises. The CHF occurrence is validated by the surface temperature profile inversion measured by an IR camera: the block centre is colder than the sides under regular cooling regime (Fig. 4), but becomes hotter when the CHF occurs, due to the lack of heat exchange with the vapor at the centre of the tube.
metres make a disturbing noise in almost all the frequencies. The tests #2–#4 are particularly disturbed due to the valve 1 which has to be almost closed for the high dilution ratios. The EB impact also contributes to the background noise, increasingly with the HHF, but is less sensitive on sensor 2 which is far from the heated surface. However, some variations can be detected when the HHF is increased. On the example shown on the time–frequency plot (Fig. 7), one can note the rise of a spectral energy, despite a constant hydraulic noise around 400 Hz, which vanishes when the HHF decreases, and arises again just before the CHF occurrence. As a result, this event is certainly linked to the approach of the CHF. Such acoustic forerunner was already observed in past experiments [1–3], within the range 200–800 Hz, and seems to vary according to the hydraulic scheme of the mock-up. This phenomenon was explained by probable resonances or stationary waves in the two-phases zone. When the test #0 (no dilution) is reproduced with flow rates up to ¼ of the nominal one, the CHF forerunner is still observable. This allows high dilution effect to be studied with a total flow rate acceptable for the water loop pump. A frequency band analysis is performed close to the frequency of the obvious CHF forerunner, but slightly switched to avoid the hydraulic noise. A 200–333 Hz band-pass filter is applied on the time signal, and the root mean square (RMS) is calculated and plotted on Fig. 8. This acoustic CHF forerunner is present whatever the dilution ratio. Furthermore, it is very interesting for the following reasons:
5.3. Tests frame Five tests are presented (Table 1), with various dilution ratio: The increasing flow dilution ratio implies a high total flow rate (test section + by-pass flow). Thus, the test section flow rate is reduced to comply with the water loop pump capabilities. The test #0 is performed beforehand with various flow rates and no dilution to make sure that the phenomenology is the same with flow reduction only. Acoustic signals sampled at 52 kHz are recorded during the tests, and then post treated. 6. Results and comments 6.1. Frequency analysis A frequency analysis is used first to analyse the acoustic signals content. The power spectral density (PSD) is calculated in the 0–20 kHz range using the classical fast Fourier transform (FFT), together with a Hanning windowing, and the Welch’s time averaged method. At first glance, the background noise is rather high (Fig. 6). As expected, the turbulences due to the valves, tube bends and flow
Fig. 7. Time–frequency plot for test #2, sensor no. 2. Scale = −50 (black) to −20 (white) dB; 0 dB = 1 g2 /Hz.
X. Courtois et al. / Fusion Engineering and Design 88 (2013) 1722–1726
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Fig. 8. Sensor 2 RMS level in the 200–333 Hz band compared with absorbed HHF. (1 mg = 0.01 m/s2 ).
• A threshold of about 30 mg can alert a high level of HHF, independent of the flow rate, which means that the indicator is most likely linked to the boiling phenomena occurring inside the channel. • If one zooms in the last step of each step, when the HHF is suddenly applied with a level higher than the CHF, the delay for the acoustic phenomenon to occur and be detected is about one or two seconds. • When the HHF is progressively increased (this is what is simulated step by step during the tests), the threshold gives enough margin before the CHF. The threshold level is a compromise between the safety margin to the CHF and the risk of false detection, and will have to be studied on tests performed on a scale-one mock-up simulating the exact divertor geometry. • The sensor 2 is the one where this indicator is the most relevant. The parasitic EB impact propagates mainly in the solid structure, and highly disturbs the sensor 1 while the sensor 2 is more sensitive to the phenomena occurring and propagating in the fluid.
6.2.2. Singularities orders analysis calculated with a wavelets transform It provides information on the kind (or order) of sound singularities caused by the growth and collapse of bubbles. The Fig. 9 shows that low orders vary significantly when approaching the CHF during test #1. However, this event is reproduced only on the #2 test, but not on the others, probably due to the parasitic noise (needle valve after the test section almost closed). 6.2.3. Envelope detection calculated with the Hilbert transform The aim is to identify phenomena of low energy like bubbles detachment rate or bubbles collapse rate (some tens of Hz), which are of too low energy to be measured by classical methods (FFT), but which can modulate high frequency boiling signals. It has been successfully used to detect CHF in past experiments,
6.2. Other signal processing Some other signal processing techniques which showed in past experiments [1,2] interesting variations before the CHF occurrence are applied on the signals. 6.2.1. Statistical analysis It consists in calculating the Skewness and the Kurtosis (respectively the third and fourth normalised moments), which characterise the signal samples distribution shape. No relevant statistical indicator variations, correlated with CHF occurrence, have been noted here.
Fig. 9. Test #1 singularities orders analysis.
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but there is no evidence in the present experiment of any CHF forerunner. Finally, the high background noise generated by the mock-up hydraulic components certainly obscures most of the above mentioned acoustic indicators. 7. Conclusion and perspectives The CHF tests campaign demonstrates that CHF acoustic forerunners exist and could be observed at a dilution ratio up to ∼20. The most relevant indicator is an increase of acoustic level in a narrow frequency band 200–333 Hz. This indicator is remarkable since it is independent of flow speed, flow dilution and the level of HHF which causes the CHF. Some others indicators seem to be there, but they remain questionable. The high background noise generated by the mock-up hydraulic components probably obscures some of them. The fact that the most interesting precursory indicator is revealed on the outlet sensor, far from the test section, is very promising. It is then meaningful to equip the divertor with a reasonable number of sensors (typically one per each IVT and OVT). A remote sensor will also be probably less sensitive to the plasma/surface interaction. The hydraulic configuration (channels geometry, fluid speed, pressure and temperature. . .) is the most important parameter to take into account for CHF acoustic detection. The hydraulic configuration determines as well the boiling phenomena, the way they produce acoustic energy, and the hydraulic noise which can obscure
the latter. As a consequence, the results of the present study must not be taken as the definition of a definitive CHF forerunner. It just demonstrates that CHF acoustic monitoring is possible, even with a highly disturbing noise and flow rate variations. To go further, testing a full scale PFC under representative hydraulic conditions is mandatory. Initially, hydraulic tests would enable noise comparison (level, frequencies) to present tests. Then HHF tests, with a representative sensor (location, technology), would confirm the main results of this study, and the definition of some indicators to survey during plasma operation. The plasma/wall interaction will also have to be taken into account since it could produce disturbing noise similarly as the EB impact on the copper test section. Dedicated tests in a facility featuring plasma/surface interaction would be welcome. Finally, a monitoring system based on acoustic measurements will involve a “learning period” to observe and understand phenomena and adjust the indicators to monitor. References [1] X. Courtois, A. Durocher, F. Escourbiac, J. Schlosser, R. Mitteau, M. Merola, R. Tivey, Physica Scripta T128 (2007) 189–194. [2] X. Courtois, F. Escourbiac, A. Durocher, B. Riccardi, M. Boinet, M. Merola, Proceedings of the 12th NURETH International Meeting, Pittsburgh, 2007. [3] K. Ezato, S. Suzuki, M. Dairaku, M. Akiba, Fusion Engineering and Design 83 (7–9) (2008) 1097–1101. [4] T. Hirai, Engineering of In-vessel Components for ITER, PFMC-13 Rosenheim Germany, Physica Scripta, submitted for publication. [5] M. Richou, Thermal Analysis for Acoustic Detection Precursor – Design Definition, Contract CEA/IO SSA No. 9, IRFM Report SIPP/GCECFP/NTT-2011I0000349144, 2011.
Contents lists available at ScienceDirect
Fusion Engineering and Design journal homepage: www.elsevier.com/locate/fusengdes
Critical heat flux acoustic detection: Methods and application to ITER divertor vertical target monitoring X. Courtois a,∗ , F. Escourbiac b , M. Richou a , V. Cantone a , S. Constans c a b c
CEA, IRFM, F-13108 Saint-Paul-Lez-Durance, France ITER Organization, Route de Vinon sur Verdon, F-13115 Saint-Paul-Lez-Durance, France AREVA-NP, Le Creusot, France
a r t i c l e
i n f o
Article history: Received 14 September 2012 Received in revised form 22 February 2013 Accepted 26 February 2013 Available online 23 March 2013 Keywords: Acoustic Critical heat flux Plasma facing component
a b s t r a c t Actively cooled plasma facing components (PFCs) have to exhaust high heat fluxes from plasma radiation and plasma–wall interaction. Critical heat flux (CHF) event may occur in the cooling channel due to unexpected heat loading or operational conditions, and has to be detected as soon as possible. Therefore it is essential to develop means of monitoring based on precursory signals providing an early detection of this destructive phenomenon, in order to be able to stop operation before irremediable damages appear. Capabilities of CHF early detection based on acoustic techniques on PFC mock-ups cooled by pressurised water were already demonstrated. This paper addresses the problem of the detection in case of flow rate reduction and of flow dilution resulting from multiple plasma facing units (PFU) which are hydraulically connected in parallel, which is the case of ITER divertor. An experimental study is launched on a dedicated mock-up submitted to heat loads up to the CHF. It shows that the measurement of the acoustic waves, generated by the cooling phenomena, allows the CHF detection in conditions similar to that of the ITER divertor, with a reasonable number of sensors. The paper describes the mock-ups and the tests sequences, and comments the results. © 2013 Elsevier B.V. All rights reserved.
1. Introduction In the harsh tokamak environment, a good optimised design does not totally prevent PFC from unexpected high heat fluxes (HHF) during plasma operation. Strong material damages can result, up to a very detrimental water leakage in the vacuum vessel which would lead to costly damages and long break for repairing. Thus means of PFC monitoring are mandatory for the success of a safe and reliable operation of a W divertor as foreseen in ITER. In this context, abnormal surface heating due to localised peaked heat fluxes can occur and cause a strong temperature increase of the PFC. According to the duration and area of the unexpected HHF event, the PFC cooling can then evolve from the regular subcooled nucleate boiling regime to the CHF at the cooling tube wall, and cause its burnout. Since PFC temperature measurements by means of thermocouples or infrared (IR) radiation may give delayed data on such event, due to the thermal time constant of the component, experimental acoustic studies have been performed on PFC mock-ups submitted to HHF, and proved that CHF early detection is possible using acoustic sensors. Another advantage of acoustic measurement is
∗ Corresponding author. Tel.: +33 4 42257411; fax: +33 4 42254990. E-mail address: [email protected] (X. Courtois). 0920-3796/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fusengdes.2013.02.149
the wave propagation which makes possible to monitor several PFU with one sensor, whereas a thermocouple is a very local measurement. The IR temperature monitoring drawback is the high uncertainty due to metallic surfaces issues (low and variable emissivity, and high parasitic reflexions).
2. Objective However, some concerns need to be solved before a possible application in ITER. On each of the 54 divertor cassettes (Fig. 1), the vertical targets (2 inner + 2 outer) put together 8–11 PFUs which are hydraulically connected in parallel. The problem is to determine how to monitor the divertor with a minimum number of sensors cautiously located, given that one sensor per PFU is not achievable. Past experiments [1–3] showed that the boiling sounds in cooling channels mainly propagate through the water rather than the structures. Thus, the acoustic waves propagation will be disturbed when the flow coming from the PFUs submitted to the CHF will be mixed with the flow coming from the other PFUs connected in parallel. This phenomenon, called flow dilution effect, will probably alter the CHF detection capabilities. The issue of flow dilution effect is studied by means of an experimental study, which was performed in the frame of the Site Support Agreement No. 9 between ITER Org. and the CEA/IRFM.
X. Courtois et al. / Fusion Engineering and Design 88 (2013) 1722–1726
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Fig. 3. CuCrZr test section and its swirl.
Fig. 1. ITER divertor cassette body.
3. Mock-up and test section description 3.1. Hydraulic mock-up HHF tests are performed under various flow conditions on a dedicated mock-up (Fig. 2). The test section represents a single PFU submitted to an abnormal HHF while the by-pass simulates a variable number of PFUs with a regular cooling regime, i.e. without HHF. Valves, diaphragm and flow metres make flow variation between the test section submitted to HHF and the by-pass, and create the flow dilution effect. The acoustic sensors which equip the mock-up are piezoelectric accelerometers. They measure the acoustic waves transmitted from the fluid to the structure. The sensor no. 2 is the reference sensor for this study. It will measure the acoustic waves generated by the cooling phenomena in the test section, propagating through the water, and mixed with the non-heated flow. 3.2. HHF test section The test section (Fig. 3) made of CuCrZr is designed to simulate the thermal behaviour of an outer vertical target
Fig. 4. Sketch of the CuCrZr equivalent monoblock under CHF, for nominal flow conditions (§5.1).
(OVT) of ITER divertor. The channel tube and the swirl tape (turbulence promoter) have exactly the same geometry as a real OVT monoblock [4]. The external dimensions are adapted with thermal simulation to reproduce the same wall heat flux (WHF) profile along the channel circumference when the CHF is expected (Fig. 4), while the surface temperature is kept lower than the CuCrZr melting. This ensures the same thermo hydraulic and acoustic phenomenology development in the water channel. The thermal simulations [5] are performed using ANSYS FE calculation, with SIEDER TATE and THOM modified CEA laws for the heat transfer coefficients, and TONG75 CEA correlation for the CHF estimation. Four identical test sections are manufactured. The swirl is inserted very tightly in the tube, so that any swirl vibrations are measurable when the water flows in it. 4. CHF acoustic detection principle Acoustic detection consists in analysing the sounds coming from the cooling regimes (Fig. 5) measured by the sensors. The sound looks like a Gaussian noise, and is composed of various sources: - Hydraulic turbulences, varying with flow speed, Re number... - Boiling sounds: steam bubbles growth and collapse. - Resonance phenomena in the water, and/or in the diphasic fluid when the steam ratio is high, i.e. near the CHF. - Other parasitic sources: pump, EB impact...
Fig. 2. Mock-up.
Fig. 5. Cooling regimes of a PFC submitted to HHF.
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Table 1 CHF tests matrix. Test number
#0
#1
#2
#3
#4
Test section flow rate (m3 /h) By-pass flow rate (m3 /h) Dilution ratio
1–3.9 0 1
2.8 2.8 2
2.7 10.8 5
1.4 12.6 10
0.7 12.6 19
A dedicated signal processing allows to identify some of the acoustic signatures of the above mentioned phenomena, and in particular when the WHF approaches the CHF. Fig. 6. Sensor 2 background noise PSD (EB gun off).
5. Tests description 5.1. Test facility The test campaign was performed in the HHF test facility FE 200, at AREVA Le Creusot. An Electron Beam (EB) gun is used as heating source, which simulates the plasma thermal load to test the power handling capabilities of the test section. 5.2. Tests parameters The nominal flow conditions are: 90 ◦ C, 3.0 MPa at the test section outlet, and flow rate 3.7 m3 /h (axial speed = 9 m/s). The flow speed of 11 m/s required by ITER is reduced in order to comply with the water loop pump capabilities in terms of flow and pressure drop. The HHF is applied on 5 consecutive blocks (20 cm2 ), with increasing power steps. Each step lasts 30 s and is followed by a 30 s standby. The absorbed HHF is controlled by thermocouples at the mock-up inlet and outlet (thermal balance). The EB sweeping uses a random scanning mode instead of the standard TV screen mode, to avoid a periodic excitation of the surface. As a drawback, the power deposition profile is Gaussian shaped. The EB is stopped when the surface temperature suddenly rises. The CHF occurrence is validated by the surface temperature profile inversion measured by an IR camera: the block centre is colder than the sides under regular cooling regime (Fig. 4), but becomes hotter when the CHF occurs, due to the lack of heat exchange with the vapor at the centre of the tube.
metres make a disturbing noise in almost all the frequencies. The tests #2–#4 are particularly disturbed due to the valve 1 which has to be almost closed for the high dilution ratios. The EB impact also contributes to the background noise, increasingly with the HHF, but is less sensitive on sensor 2 which is far from the heated surface. However, some variations can be detected when the HHF is increased. On the example shown on the time–frequency plot (Fig. 7), one can note the rise of a spectral energy, despite a constant hydraulic noise around 400 Hz, which vanishes when the HHF decreases, and arises again just before the CHF occurrence. As a result, this event is certainly linked to the approach of the CHF. Such acoustic forerunner was already observed in past experiments [1–3], within the range 200–800 Hz, and seems to vary according to the hydraulic scheme of the mock-up. This phenomenon was explained by probable resonances or stationary waves in the two-phases zone. When the test #0 (no dilution) is reproduced with flow rates up to ¼ of the nominal one, the CHF forerunner is still observable. This allows high dilution effect to be studied with a total flow rate acceptable for the water loop pump. A frequency band analysis is performed close to the frequency of the obvious CHF forerunner, but slightly switched to avoid the hydraulic noise. A 200–333 Hz band-pass filter is applied on the time signal, and the root mean square (RMS) is calculated and plotted on Fig. 8. This acoustic CHF forerunner is present whatever the dilution ratio. Furthermore, it is very interesting for the following reasons:
5.3. Tests frame Five tests are presented (Table 1), with various dilution ratio: The increasing flow dilution ratio implies a high total flow rate (test section + by-pass flow). Thus, the test section flow rate is reduced to comply with the water loop pump capabilities. The test #0 is performed beforehand with various flow rates and no dilution to make sure that the phenomenology is the same with flow reduction only. Acoustic signals sampled at 52 kHz are recorded during the tests, and then post treated. 6. Results and comments 6.1. Frequency analysis A frequency analysis is used first to analyse the acoustic signals content. The power spectral density (PSD) is calculated in the 0–20 kHz range using the classical fast Fourier transform (FFT), together with a Hanning windowing, and the Welch’s time averaged method. At first glance, the background noise is rather high (Fig. 6). As expected, the turbulences due to the valves, tube bends and flow
Fig. 7. Time–frequency plot for test #2, sensor no. 2. Scale = −50 (black) to −20 (white) dB; 0 dB = 1 g2 /Hz.
X. Courtois et al. / Fusion Engineering and Design 88 (2013) 1722–1726
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Fig. 8. Sensor 2 RMS level in the 200–333 Hz band compared with absorbed HHF. (1 mg = 0.01 m/s2 ).
• A threshold of about 30 mg can alert a high level of HHF, independent of the flow rate, which means that the indicator is most likely linked to the boiling phenomena occurring inside the channel. • If one zooms in the last step of each step, when the HHF is suddenly applied with a level higher than the CHF, the delay for the acoustic phenomenon to occur and be detected is about one or two seconds. • When the HHF is progressively increased (this is what is simulated step by step during the tests), the threshold gives enough margin before the CHF. The threshold level is a compromise between the safety margin to the CHF and the risk of false detection, and will have to be studied on tests performed on a scale-one mock-up simulating the exact divertor geometry. • The sensor 2 is the one where this indicator is the most relevant. The parasitic EB impact propagates mainly in the solid structure, and highly disturbs the sensor 1 while the sensor 2 is more sensitive to the phenomena occurring and propagating in the fluid.
6.2.2. Singularities orders analysis calculated with a wavelets transform It provides information on the kind (or order) of sound singularities caused by the growth and collapse of bubbles. The Fig. 9 shows that low orders vary significantly when approaching the CHF during test #1. However, this event is reproduced only on the #2 test, but not on the others, probably due to the parasitic noise (needle valve after the test section almost closed). 6.2.3. Envelope detection calculated with the Hilbert transform The aim is to identify phenomena of low energy like bubbles detachment rate or bubbles collapse rate (some tens of Hz), which are of too low energy to be measured by classical methods (FFT), but which can modulate high frequency boiling signals. It has been successfully used to detect CHF in past experiments,
6.2. Other signal processing Some other signal processing techniques which showed in past experiments [1,2] interesting variations before the CHF occurrence are applied on the signals. 6.2.1. Statistical analysis It consists in calculating the Skewness and the Kurtosis (respectively the third and fourth normalised moments), which characterise the signal samples distribution shape. No relevant statistical indicator variations, correlated with CHF occurrence, have been noted here.
Fig. 9. Test #1 singularities orders analysis.
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but there is no evidence in the present experiment of any CHF forerunner. Finally, the high background noise generated by the mock-up hydraulic components certainly obscures most of the above mentioned acoustic indicators. 7. Conclusion and perspectives The CHF tests campaign demonstrates that CHF acoustic forerunners exist and could be observed at a dilution ratio up to ∼20. The most relevant indicator is an increase of acoustic level in a narrow frequency band 200–333 Hz. This indicator is remarkable since it is independent of flow speed, flow dilution and the level of HHF which causes the CHF. Some others indicators seem to be there, but they remain questionable. The high background noise generated by the mock-up hydraulic components probably obscures some of them. The fact that the most interesting precursory indicator is revealed on the outlet sensor, far from the test section, is very promising. It is then meaningful to equip the divertor with a reasonable number of sensors (typically one per each IVT and OVT). A remote sensor will also be probably less sensitive to the plasma/surface interaction. The hydraulic configuration (channels geometry, fluid speed, pressure and temperature. . .) is the most important parameter to take into account for CHF acoustic detection. The hydraulic configuration determines as well the boiling phenomena, the way they produce acoustic energy, and the hydraulic noise which can obscure
the latter. As a consequence, the results of the present study must not be taken as the definition of a definitive CHF forerunner. It just demonstrates that CHF acoustic monitoring is possible, even with a highly disturbing noise and flow rate variations. To go further, testing a full scale PFC under representative hydraulic conditions is mandatory. Initially, hydraulic tests would enable noise comparison (level, frequencies) to present tests. Then HHF tests, with a representative sensor (location, technology), would confirm the main results of this study, and the definition of some indicators to survey during plasma operation. The plasma/wall interaction will also have to be taken into account since it could produce disturbing noise similarly as the EB impact on the copper test section. Dedicated tests in a facility featuring plasma/surface interaction would be welcome. Finally, a monitoring system based on acoustic measurements will involve a “learning period” to observe and understand phenomena and adjust the indicators to monitor. References [1] X. Courtois, A. Durocher, F. Escourbiac, J. Schlosser, R. Mitteau, M. Merola, R. Tivey, Physica Scripta T128 (2007) 189–194. [2] X. Courtois, F. Escourbiac, A. Durocher, B. Riccardi, M. Boinet, M. Merola, Proceedings of the 12th NURETH International Meeting, Pittsburgh, 2007. [3] K. Ezato, S. Suzuki, M. Dairaku, M. Akiba, Fusion Engineering and Design 83 (7–9) (2008) 1097–1101. [4] T. Hirai, Engineering of In-vessel Components for ITER, PFMC-13 Rosenheim Germany, Physica Scripta, submitted for publication. [5] M. Richou, Thermal Analysis for Acoustic Detection Precursor – Design Definition, Contract CEA/IO SSA No. 9, IRFM Report SIPP/GCECFP/NTT-2011I0000349144, 2011.