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JET operating experience: Global analysis of tritium plant failure
Fusion Engineering and Design 85 (2010) 1396–1400
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JET operating experience: Global analysis of tritium plant failure T. Pinna a,∗ , G. Cambi b , S. Knipe c , JET-EFDA Contributors a
ENEA FPN-FUSTEC Via E.Fermi 45, 00044 Frascati, Rome, Italy University of Bologna, Via Irnerio 46, 40126 BO, Italy c JET, Culham Science Centre, Abingdon, Oxfordshire OX14 3DB, UK b
a r t i c l e
i n f o
Article history: Available online 28 April 2010 Keywords: Failure rates Fusion machines JET Tritium system
a b s t r a c t The objective of the activity was to build up an overall data collection about the existing experience on the performances and management of the system dedicated to handle the tritium at the Joint European Torus (JET). At first, the analysis performed in 2002 on data related to JET Active Gas Handling System (AGHS) failures was reviewed considering failures and system updating occurred in the AGHS between 2002 and 2006. Main reliability parameters associated to the components (i.e.: failure rate and the corresponding standard errors and confidence intervals) were estimated by means of investigation on failure modes of components and, where possible, causes and consequences of the failures. About 460 failures/malfunctions on a set of more than 6200 components, operating for about 215,000,000 h, were pointed out since 1995 up to 2006. By the comparison between this statistical assessment and the old one performed in the 2002 it is possible to note, apart few cases, the slight increase of failure rate values because of a slight deterioration of components, due to the ageing. The evaluated failure rates were also compared with failure rates existing in literature for similar applications (e.g.: nuclear power plants, tritium processing laboratories). A good agreement between the values from the different sources came out. Second step of the work was the detailed analysis of some relevant maintenance operations performed to repair significant failures in the plant. Unavailability of components and systems, possible impact on workers’ doses and possible environmental releases related to the maintenance activities were scrutinized. The investigation highlights the very low consequences for workers in terms of doses and the negligible effects on environmental releases. The investigation also highlights essential key elements of procedures undertaken to perform maintenance on the AGHS. © 2010 Elsevier B.V. All rights reserved.
1. Introduction The tritium system is one of the most important parts of deuterium/tritium (D/T) fusion machines from the radiological point of view. A large experience on this type of system comes from the CANadian Deuterium Uranium (CANDU) fission power plant reactors, but also from tritium laboratories and fusion experimental reactors. Particularly for the latter, the Joint European Torus (JET) is the most important source of information. It is essential for creating a consistent operating experience databank useful for the International Thermonuclear Experimental Reactor (ITER) tritium system construction, management and Occupational Radiation Exposure (ORE) forecast. The JET started operating in 1983 and was the first fusion facility in the world to achieve a significant production of controlled fusion power (nearly 2 MW) with a D/T experiment.
The objective of the activity described in this paper was to collect and analyse data about the existing experience on the performances and management of the JET tritium systems named Active Gas Handling System (AGHS). A first data collection and analyses were already performed in 2002 for this system [1,2] and now it is updated considering last failures and operating conditions, as well as enreached by new type of information. Similar data collection and analyses were also performed in the past for other JET systems, such as the Vacuum, the Ion Cyclotron Resonance Heating (ICRH), the Neutral Beam Injector (NBI) and the Power Supply (PS) Systems. Data from the Tritium Laboratory of Karlsruhe (TLK) were also collected and analysed. All those data and the related analyses have been presented in some ENEA technical reports and publications [1–4]. 2. Applied methodology
∗ Corresponding author. E-mail address: [email protected] (T. Pinna). 0920-3796/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.fusengdes.2010.03.062
The same methodology used for the 2002 analysis has been here applied. A summary description is given in the following.
T. Pinna et al. / Fusion Engineering and Design 85 (2010) 1396–1400
The data retrieval follows sequential steps:
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3. JET AGHS data for reliability analysis
(a) The achievement of a general understanding about the information, available in the plant files, on component failures at the overall plant system level. (b) The collection of all the information available about single component malfunctions and failures of the system under investigation. (c) The identification of failure causes, consequences and maintenance actions, if possible. (d) The identification of the complete ‘reference set’ of components of which the faulted components are a subset. Operating life, for components in continuous operation, and/or operating demands, for components in intermittent operations, have been determined. Process and instrumentation diagrams (P&ID), design documents and drawings have been analysed. For component failure during operation, statistical data, such as failure rate , standard error s.e. (), lower L and upper U limits of the 90% confidence interval and mean time between failures (MTBF) and mean number of demands between failures (MDBF) have been calculated assuming the constant failure rate model, USNRC [5]. As a result of the work, statistical data are provided together with the collected practical information acquired from the experience gained operating the system analysed.
The AGHS has been designed and installed for JET operation with D/T plasma. It was installed from 1990 to 1991; its main function is the supplying of D and T gases into the plasma and the extraction and separation of hydrogen isotopes from the Torus exhaust so that tritium and deuterium can be recycled. Tritium was introduced to AGHS on 12 June 1995. 3.1. Data collection Data related to AGHS operations and to the component failures were got partly from AGHS staff and partly by looking at the system log-books (hand-written). All the data have been successively recorded in an Excel spreadsheet. The information investigated on failures/malfunctions concerns the identification of failed components, failure modes and, where possible, causes and consequences of the failures. To perform statistical analysis, the whole sets of components affected by failures/malfunctions were also identified. Components were classified and counted in order to find out their amount, related operating hours and related demands to operate (for components operating in intermittent way). About 6200 components, operating for about a total of 215,000,000 h were identified in AGHS. 3.2. Overview on identified failures The analysis performed in 2002 on data related to JET AGHS failures was reviewed considering failures and system updating
Table 1 Statistics on AGHS components made by operating hours and failure modes. Component
Failure mode
No. of faults
Failure rate, (1/h)
s.e. () (1/h)
L (90%) (1/h)
U (90%) (1/h)
MTBFa (h)
Amplifier Ancillary power supply Blower Blower Catherometer Chiller water Chiller water Controller Distributed control unit Fan of electronic board Filter Fire detection system Heater Heater Heater Indicator Indicator Ionization chamber Radiation monitor (room) Radiation monitor (stack) Rupture disc Site PS (from national grid) Site PS (from national grid) Switch Thermoresistance Transducer Transducer Transformer (high voltage) Transmitter Uninterruptable PS Uninterruptable PS Vacuum pump Vacuum pump Vacuum pump Vacuum pump Vacuum pump Valve Valve Valve
Erratic/No Output Loss of power Failure to run Failure to start Erratic/No Output Alarm/Erratic Alarm Failure to operate Erratic/No Output Erratic/No Output Failure to run Blocked Spurious alarm Failure to operate Loss of power Overtemperature Erratic/No Output Leak-External Erratic/No Output Erratic/No Output Erratic/No Output Premature opening Loss of power Overvoltage Failure to operate Erratic/No Output Erratic/No Output Leak Loss of power Erratic/No Output Alarm/Erratic Alarm Loss of power Alarm/Erratic Alarm Leak-External Failure to run Failure to start Failure to stop Failure to operate Leak-External Leak-Internal
17 29 13 5 2 17 22 8 24 3 1 18 3 2 2 60 2 3 5 4 1 3 1 8 1 14 1 2 8 5 5 5 1 37 6 1 47 54 2
5.5E−6 7.1E−4 3.3E−5 1.3E−5 1.3E−5 4.2E−4 5.4E−4 3.3E−6 1.0E−5 2.0E−6 2.1E−6 4.4E−4 5.3E−7 3.5E−7 3.5E−7 2.1E−6 7.1E−8 1.7E−6 5.0E−5 4.0E−5 5.9E−7 3.0E−5 1.0E−5 1.9E−7 7.9E−7 2.3E−6 1.6E−7 1.4E−5 8.1E−7 5.0E−5 5.0E−5 2.8E−5 7.6E−7 2.8E−5 4.6E−6 7.6E−7 6.3E−7 7.2E−7 2.7E−8
1.3E−6 1.3E−4 9.1E−6 5.6E−6 9.3E−6 1.0E−4 1.1E−4 1.2E−6 2.1E−6 1.2E−6 2.1E−6 1.0E−4 3.0E−7 2.5E−7 2.5E−7 2.7E−7 5.0E−8 9.6E−7 2.3E−5 2.0E−5 5.9E−7 1.7E−5 1.0E−5 6.9E−8 7.9E−7 6.1E−7 1.6E−7 9.6E−6 2.9E−7 2.3E−5 2.3E−5 1.2E−5 7.6E−7 4.6E−6 1.9E−6 7.6E−7 9.2E−8 9.8E−8 1.9E−8
3.5E−6 5.1E−4 1.9E−5 5.0E−6 2.3E−6 2.7E−4 3.6E−4 1.6E−6 7.0E−6 5.5E−7 1.1E−7 2.8E−4 1.4E−7 6.2E−8 6.2E−8 1.7E−6 1.3E−8 4.5E−7 2.0E−5 1.4E−5 3.0E−8 8.3E−6 5.2E−7 9.7E−8 4.1E−8 1.4E−6 8.4E−9 2.4E−6 4.0E−7 2.0E−5 2.0E−5 1.1E−5 3.9E−8 2.1E−5 2.0E−6 3.9E−8 4.9E−7 5.7E−7 4.8E−9
8.2E−6 9.7E−4 5.2E−5 2.7E−5 4.1E−5 6.2E−4 7.7E−4 5.9E−6 1.4E−5 5.2E−6 9.9E−6 6.5E−4 1.4E−6 1.1E−6 1.1E−6 2.6E−6 2.2E−7 4.3E−6 1.1E−4 9.2E−5 2.8E−6 7.8E−5 4.8E−5 3.5E−7 3.8E−6 3.6E−6 7.8E−7 4.3E−5 1.5E−6 1.1E−4 1.1E−4 5.9E−5 3.6E−6 3.7E−5 9.0E−6 3.6E−6 8.0E−7 9.1E−7 8.4E−8
1.8E+5 1.4E+3 3.0E+4 7.9E+4 7.6E+4 2.4E+3 1.9E+3 3.0E+5 9.9E+4 4.9E+5 4.8E+5 2.3E+3 1.9E+6 2.8E+6 2.8E+6 4.7E+5 1.4E+7 6.0E+5 2.0E+4 2.5E+4 1.7E+6 3.3E+4 9.9E+4 5.1E+6 1.3E+6 4.4E+5 6.1E+6 7.4E+4 1.2E+6 2.0E+4 2.0E+4 3.6E+4 1.3E+6 3.5E+4 2.2E+5 1.3E+6 1.6E+6 1.4E+6 3.7E+7
a
Mean time between failures.
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T. Pinna et al. / Fusion Engineering and Design 85 (2010) 1396–1400
Table 2 Statistics on some AGHS components made by operating cycles (open/close or turn on/off) and failure modes. Component
Class type
Failure mode
No. of faults
No. of components in AGHS
Total no. of demands
1/Demand pD
s.e. (pD )
pDL (90%)
pDU (90%)
Valve
General type
Failure to operate
47
2124
725,035
6.5E−5
9.5E−6
5.0E−5
8.3E−5
Valve Valve Valve
Air actuated Air actuated Air actuated
Failure to open/close Leak-External Leak-Internal
31 2 2
601 601 601
295,481 295,481 295,481
1.0E−4 6.8E−6 6.8E−6
1.9E−5 4.8E−6 4.8E−6
7.6E−5 1.2E−6 1.2E−6
1.4E−4 2.1E−5 2.1E−5
Valve Valve
Solenoid Solenoid
Failure to open/close Leak-External
8 52
646 646
419,351 419,351
1.9E−5 1.2E−4
6.7E−6 1.7E−5
9.5E−6 9.7E−5
3.4E−5 1.6E−4
Valve
Manual
Failure to open/close
0
732
10,203
9.0E−5
9.4E−5
0.0E+0
2.3E−4
All failure modes Failure to operate Loss of power Overtemperature
7 3 2 2
131 131 131 131
56,025 56,025 56,025 56,025
1.2E−4 5.4E−5 3.6E−5 3.6E−5
4.7E−5 3.1E−5 2.5E−5 2.5E−5
5.9E−5 1.5E−5 6.3E−6 6.3E−6
2.3E−4 1.4E−4 1.1E−4 1.1E−4
Heater Heater Heater Heater
Table 3 Statistics by type and failure modes of indicators in AGH system. Component
Class type
Failure mode
No. of faults
No. of components in AGHS
Total run time (h)
Failure rate, (1/h)
s.e. () (1/h)
L (90%) (1/h)
U (90%) (1/h)
MTBF (h)
Indicator Indicator Indicator Indicator Indicator Indicator Indicator Indicator Indicator Indicator
General type General type Flow Humidity Level Pressure Temperature Temperature Tritium Tritium
Erratic/No Output Leak-External Erratic/No Output Erratic/No Output Erratic/No Output Erratic/No Output Erratic/No Output Leak-External Erratic/No Output Leak-External
60 2 3 1 2 11 17 1 26 1
653 653 54 6 18 239 161 161 43 43
28,251,072 28,251,072 3,133,800 594,576 683,184 9,533,544 6,950,488 6,950,488 2,062,888 2,062,888
2.1E−6 7.1E−8 9.6E−7 1.7E−6 2.9E−6 1.2E−6 2.4E−6 1.4E−7 1.3E−5 4.8E−7
2.7E−7 5.0E−8 5.5E−7 1.7E−6 2.1E−6 3.5E−7 5.9E−7 1.4E−7 2.5E−6 4.8E−7
1.7E−6 1.3E−8 2.6E−7 8.6E−8 5.2E−7 6.5E−7 1.6E−6 7.4E−9 8.8E−6 2.5E−8
2.6E−6 2.2E−7 2.5E−6 8.0E−6 9.2E−6 1.9E−6 3.7E−6 6.8E−7 1.7E−5 2.3E−6
4.7E+5 1.4E+7 1.0E+6 5.9E+5 3.4E+5 8.7E+5 4.1E+5 7.0E+6 7.9E+4 2.1E+6
occurred in the AGHS between 2002 and 2006. As a result, about 460 failures/malfunctions were pointed out since 1995 up to 2006. More precisely, 131 failures/malfunctions were related to the period 1995–January 2002 and 326 failures/malfunctions were related since February 2002 up to September 2006. Generally speaking, the most part of them do not affect the JET operations. 3.3. Reliability analysis on AGHS failures For component failed during operation, statistical data, such as failure rate , standard error s.e. (), lower L and upper U limits of the 90% confidence interval and mean time between failures (MTBF) and mean number of demands between failures (MDBF) are usually calculated [5] assuming the constant failure rate model. In such a case, as a sample, is evaluated applying the point estimate model (Poisson or exponential models) through the number of observed failures N, over time T of component operating expe-
rience, i.e. by the formula = N/T. The application of the Poisson model is considered appropriate when the total number of failures N is increasing linearly versus the component total operating time. For component operating on demand, failure probability on demands pD are commonly determined [5] on the base of the estimated amount of “calls in operation” (demands), considering the binomial model. The related standard error s.e. (pD ), and the lower pDL and upper pDU limits of the 90% confidence interval, have been calculated, too. Details about the data collected and the data elaboration are given in [6]. Few samples of the results pointed out by this work is presented in Tables 1–4. Statistics on AGHS components made by operating hours and failure modes are listed in Table 1. Statistics on valves and heaters made by operating cycles and failure modes are listed in Table 2. Statistics by type and failure modes of indicators are
Table 4 Statistics by failure modes of ancillary systems in AGHS plant. Component
Failure mode
No. of faults
Total run time (h)
Failure rate, (1/h)
s.e. () (1/h)
L (90%) (1/h)
U (90%) (1/h)
MTBF (h)
Ancillary power supply (PS) system
Loss of power
29
40,872
7.1E−4
1.3E−4
5.1E−4
9.7E−4
1.4E+3
Chiller water system Chiller water system
Alarm/Erratic Alarm Failure to operate
17 22
40,872 40,872
4.2E−4 5.4E−4
1.0E−4 1.1E−4
2.7E−4 3.6E−4
6.2E−4 7.7E−4
2.4E+3 1.9E+3
Fire detection system
Spurious Alarm
18
40,872
4.4E−4
1.0E−4
2.8E−4
6.5E−4
2.3E+3
Radiation monitor (room control) Radiation monitor (stack control)
Erratic/No Output Erratic/No Output
5 4
99,096 99,096
5.0E−5 4.0E−5
2.3E−5 2.0E−5
2.0E−5 1.4E−5
1.1E−4 9.2E−5
2.0E+4 2.5E+4
Site PS (from national grid) Site PS (from national grid)
Loss of power Overvoltage
3 1
99,096 99,096
3.0E−5 1.0E−5
1.7E−5 1.0E−5
8.3E−6 5.2E−7
7.8E−5 4.8E−5
3.3E+4 9.9E+4
Transformer (high voltage)
Loss of power
2
594,576
3.4E−6
2.4E−6
6.0E−7
1.1E−5
3.0E+5
Uninterruptable PS system Uninterruptable PS system
Alarm/Erratic Alarm Loss of power
5 5
99,096 99,096
5.0E−5 5.0E−5
2.3E−5 2.3E−5
2.0E−5 2.0E−5
1.1E−4 1.1E−4
2.0E+4 2.0E+4
T. Pinna et al. / Fusion Engineering and Design 85 (2010) 1396–1400
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tion of failures have been scrutinized. The following maintenance activities have been selected to be studied in detail: replacing of the Emergency Detritiation System (EDS) butterfly valve; repairing of the plant Uninterruptible Power Supply (UPS); re-routing of Mechanical Forevacuum (MF) pipework to substitute large scroll vacuum pump; removing of the failed large scroll vacuum pumps and their substitution with new screw vacuum pumps; inspection of large scroll pump; replacing of perforated EDS bellows; replacing of blocked EDS filter. Every maintenance activity on failed or obsolete components had dedicated worker procedures carefully prepared to avoid or limit worker exposures, environmental releases, system and plant outages. Detailed data are reported in [6] and some considerations deduced from the analysis of those maintenance activities are given in the following. 4.1. Time spent for AGHS maintenance activities About the time spent in the various phases of maintenance:
Fig. 1. AGHS reliability data: comparison between 1995–2006 and 1995–2002 results.
listed in Table 3. Statistics by failure modes of AGHS plant ancillary systems are listed in Table 4. 3.4. Discussion about AGHS reliability results 3.4.1. Comparison with previous AGHS reliability results For the most part of components, failure rates were presented also in [1,2] where the operating experience considered was between 1995 and January 2002. The comparison of the new failure rates with the previous ones shows, apart few cases, a slight deterioration of components with their age, because of the increasing of failure rate values (see Fig. 1). 3.4.2. Comparison between obtained statistical and literature data The evaluated failure rates were also compared with failure rates existing in literature for similar applications (e.g.: nuclear power plants, tritium processing laboratories). The result showed a good agreement (see Fig. 2 in [7]) between the values from the different sources (see e.g. [8–10]). That enforces the usefulness of the obtained data in evaluating reliability parameters to support the safety assessment and to analyse availability/reliability of fusion machines/plants and tritium laboratories.
(a) Even if disturbances in the process parameters was noted, in some cases, the failure detection took 2 or 3 days. (b) Generally speaking, for important maintenance operations the planning of the intervention took weeks and also months, particularly for large components and breaching of process lines. Some times, decisions to postpone maintenance to planned main plant shutdown period were taken, when it was possible. (c) The procuring of components sometimes took months. A suitable strategy of spare parties could have been reduced highly the time spent for this issue. (d) Time to start the work after failure did not take less than some weeks and, clearly, it depended from time required to plan the intervention and time to procure components. (e) Time to perform the first breach after starting of the work took from 1 day to some months, depending from the complexity of the preparatory work (e.g.: set of working area with scaffolding, tools, tents, isolators, radiation monitors, etc.) and decontamination of components to be maintained (e.g.: purging of components and process lines, as well as checking of the contamination levels). (f) Time required to conclude breaching conditions, usually, took days (from 1 to 15 days according to the complexity of the operations). (g) Also leak tests and activities devoted to eliminate leaks took from few days to some weeks. Summarizing, maintenance activities requiring the breaching of the tritium process lines necessitated of a time of the order of magnitude of months to perform the overall work of medium and high complexity, as the removal of large size components. Minor maintenance activities in terms of breaching the process lines required working time on the order of few weeks. Consequently, outage of the system was also on the order of months, with the exception of minor activities for which the outage of the system was for few weeks. 4.2. Worker and public safety effects of AGHS maintenance activities
4. Analysis of relevant JET AGHS maintenance operations Some of the most important failures in the plant, which required significant maintenance operations have been investigated in detail. Unavailability of components and system, possible impact on doses to the workers, possible environmental releases related to the failures and possible plant modifications to prevent repeti-
For four of the maintenance activities analysed, minor worker doses have been recorded. All these activities necessitated breaching of tritium process lines. The collective doses assumed by “authorized radiological workers” for each activity was very low, on the order of tens of Sv. The average values of worker dose rate for the opening of the tritium process lines results 0.13 Sv/person-
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T. Pinna et al. / Fusion Engineering and Design 85 (2010) 1396–1400
h. The most exposed workers were fitters. The mean dose rate for fitters was 0.22 Sv/person-h. Data on internal and external doses to workers operating in the AGHS building J25 have been provided by JET Operator. External dose are measured by dosimeters and internal doses by bioassay measurements. Data on radioactive release to stack from tritium plant (building J25) have been also provided by JET Operator. Those data refer to weekly releases in HTO and HT forms: partial, for each form, and total MBq values have been provided. Total releases from J25 in 5 years of operations result of 0.3 TBq of HTO and 2.2 TBq of HT. These releases are usually not related to maintenance activities. Only for three of the eight maintenance activities analysed the weekly stack release curves have small peaks of the order of 1–10 GBq, corresponding to 0.2 mg in the HTO form or 0.04 mg in HT form at maximum in correlation to the maintenance periods. 5. Main outcomes from JET tritium plant components failures and operating experience Data on operating experience of JET AGHS have been deeply searched and assessed. In about 11 years of system operations, about 460 failures/malfunctions on a set of more than 6200 components have been identified. The largest number of failures/malfunctions concerned “external leaks” and “fail to operate” of air actuated valves and solenoid valves. For them, a program of preventive maintenance started in 2001 after 6 years of operation. Important in terms of amount of malfunctions were also “Erratic/No Output” of instrumentation and electronic components due to: ammeter failures for tritium indicators and ionization chambers; electrochemical cell “Exhausted” for humidity indicator; filament failure for catherometer; amplifier, thermocouples, pressure and flow indicators, sensors, switches, probe and transducers faults; control units failures. Particularly, to avoid one of the possible causes of the last ones failures, a dedicated preventative maintenance program started after 2 years of operation to replace every 12 months cooling fans of electrical boards. Three of the five large scroll vacuum pumps (capacity: 150–600 m3 /h), installed in the plant, stopped and then they were removed, respectively after about 29,000, 22,000 and 24,000 h of operating life. Build up of debris inside the pump was observed on failed pumps. The pumps have been replaced with screw vacuum pumps, which for their part also experienced several failures due to problems in the electric circuits, in their instrumentation and control equipment and in supplying N2 gas. Other failures concerned: metal bellow, rotary vane and turbo-molecular vacuum pumps; blowers; radiation monitors; no-return and pressure regulator valves; oil pumps; power supply systems (grid, UPS and ancillary); air cooling system, chiller system and fire detection system. A detailed analysis of the most complex maintenance activities experienced in the AGHS has been done too. For them, it results that to perform the overall work of a maintenance programme takes time of the order of magnitude of weeks or months according to the relevance of the activity. Consequently, the outage of the sub-system under maintenance is also in the order of few weeks or months. For four of these major maintenance activities requiring breaching of tritium process lines, it results a mean value of total dose to workers of 0.13 Sv/person-h, according to
the health physics detection. From the analysed tritium environmental releases no clear correspondence has been identified with maintenance activities requiring breaching of tritium process lines. Some small peaks on stack releases have been found only during the periods of three maintenance activities. These peaks are on the order of 10 GBq. 6. Conclusions Main reliability parameters associated to the JET tritium plant components have been estimated. The failure rates and the failure probabilities on demand evaluated are in very good agreement with the corresponding ones existing in literature for similar applications (e.g.: nuclear power plants). The data obtained could be very useful to evaluate reliability parameters in support of safety assessment and for availability/reliability analyses of fusion machines/plants and tritium laboratories. Failure rates estimated in a previous assessment done in 2002 have been compared with the new ones. By these data it is possible to note, apart few cases, a slight deterioration of components with their age, because the increasing of failure rate values. From the analysis of the most complex maintenance activities experienced in the AGHS it has pointed out that the outage of the sub-system under maintenance is of the order of few weeks or months. For four of the major maintenance activities requiring breaching of tritium process lines, it results a mean value of total dose to workers of 0.13 Sv/person-h, according to the health physics detection. Some small peaks of about 10 GBq on stack releases have been found only during the periods of three maintenance activities. Therefore the environmental release related to maintenance activities can be considered negligible. Acknowledgments The work was possible thanks to the collaboration of the AGHS JET staff and to the support of the European Fusion Development Agreement (EFDA) Close Support Unit at JET. References [1] T. Pinna, G. Cambi, A. Lo Bue, C. Rizzello, Collection and analysis of data related to fusion machines (JET and TLK) operation experience on component failure, ENEA FUS-TN-SA-SE-R-058, February 2003. [2] T. Pinna, et al., Collection and analysis of data related to fusion machines (JET and TLK) operating experience on component failure, Fusion Eng. Des. 75–79 (2005) 1199–1203. [3] T. Pinna, G. Cambi, F. Gravanti, Collection and analysis of component failure data from JET systems: neutral beam injectors and power supply, Nuclear Fusion 47 (2007) S453–S457. [4] G. Cambi, T. Pinna, M. Angelone, Data collection on component malfunctions and failures of JET ICRH System, Fusion Eng. Des. 83 (2008) 1874–1877. [5] USNRC, PRA procedure guide: a guide to the performance of probabilistic risk assessments for nuclear power plants, Final Report, NUREG/CR-2300, January 1983. [6] T. Pinna, G. Cambi, S. Knipe, JET operating experience: global analysis of tritium plant failure, ENEA FUS-TN-SA-SE-R-193, June 2008. [7] T. Pinna et al., Operating experiences from existing fusion facilities in view of ITER safety and reliability, this conference. [8] L.C. Cadwallader, Comparison of tritium component failure rate data, Fusion Sci. Technol. 47 (May (4)) (2005) 983–988. [9] L.C. Cadwallader, Failure rate data for glovebox components and cleanup systems at the tritium systems test assembly, J. Fusion Energy 12 (1–2) (1993) 47–51. [10] L.C. Cadwallader, Vacuum component reliability estimates for experimental fusion facilities, Fusion Technol. 26 (3 (Pt 2)) (1994) 1021–1024.
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Fusion Engineering and Design journal homepage: www.elsevier.com/locate/fusengdes
JET operating experience: Global analysis of tritium plant failure T. Pinna a,∗ , G. Cambi b , S. Knipe c , JET-EFDA Contributors a
ENEA FPN-FUSTEC Via E.Fermi 45, 00044 Frascati, Rome, Italy University of Bologna, Via Irnerio 46, 40126 BO, Italy c JET, Culham Science Centre, Abingdon, Oxfordshire OX14 3DB, UK b
a r t i c l e
i n f o
Article history: Available online 28 April 2010 Keywords: Failure rates Fusion machines JET Tritium system
a b s t r a c t The objective of the activity was to build up an overall data collection about the existing experience on the performances and management of the system dedicated to handle the tritium at the Joint European Torus (JET). At first, the analysis performed in 2002 on data related to JET Active Gas Handling System (AGHS) failures was reviewed considering failures and system updating occurred in the AGHS between 2002 and 2006. Main reliability parameters associated to the components (i.e.: failure rate and the corresponding standard errors and confidence intervals) were estimated by means of investigation on failure modes of components and, where possible, causes and consequences of the failures. About 460 failures/malfunctions on a set of more than 6200 components, operating for about 215,000,000 h, were pointed out since 1995 up to 2006. By the comparison between this statistical assessment and the old one performed in the 2002 it is possible to note, apart few cases, the slight increase of failure rate values because of a slight deterioration of components, due to the ageing. The evaluated failure rates were also compared with failure rates existing in literature for similar applications (e.g.: nuclear power plants, tritium processing laboratories). A good agreement between the values from the different sources came out. Second step of the work was the detailed analysis of some relevant maintenance operations performed to repair significant failures in the plant. Unavailability of components and systems, possible impact on workers’ doses and possible environmental releases related to the maintenance activities were scrutinized. The investigation highlights the very low consequences for workers in terms of doses and the negligible effects on environmental releases. The investigation also highlights essential key elements of procedures undertaken to perform maintenance on the AGHS. © 2010 Elsevier B.V. All rights reserved.
1. Introduction The tritium system is one of the most important parts of deuterium/tritium (D/T) fusion machines from the radiological point of view. A large experience on this type of system comes from the CANadian Deuterium Uranium (CANDU) fission power plant reactors, but also from tritium laboratories and fusion experimental reactors. Particularly for the latter, the Joint European Torus (JET) is the most important source of information. It is essential for creating a consistent operating experience databank useful for the International Thermonuclear Experimental Reactor (ITER) tritium system construction, management and Occupational Radiation Exposure (ORE) forecast. The JET started operating in 1983 and was the first fusion facility in the world to achieve a significant production of controlled fusion power (nearly 2 MW) with a D/T experiment.
The objective of the activity described in this paper was to collect and analyse data about the existing experience on the performances and management of the JET tritium systems named Active Gas Handling System (AGHS). A first data collection and analyses were already performed in 2002 for this system [1,2] and now it is updated considering last failures and operating conditions, as well as enreached by new type of information. Similar data collection and analyses were also performed in the past for other JET systems, such as the Vacuum, the Ion Cyclotron Resonance Heating (ICRH), the Neutral Beam Injector (NBI) and the Power Supply (PS) Systems. Data from the Tritium Laboratory of Karlsruhe (TLK) were also collected and analysed. All those data and the related analyses have been presented in some ENEA technical reports and publications [1–4]. 2. Applied methodology
∗ Corresponding author. E-mail address: [email protected] (T. Pinna). 0920-3796/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.fusengdes.2010.03.062
The same methodology used for the 2002 analysis has been here applied. A summary description is given in the following.
T. Pinna et al. / Fusion Engineering and Design 85 (2010) 1396–1400
The data retrieval follows sequential steps:
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3. JET AGHS data for reliability analysis
(a) The achievement of a general understanding about the information, available in the plant files, on component failures at the overall plant system level. (b) The collection of all the information available about single component malfunctions and failures of the system under investigation. (c) The identification of failure causes, consequences and maintenance actions, if possible. (d) The identification of the complete ‘reference set’ of components of which the faulted components are a subset. Operating life, for components in continuous operation, and/or operating demands, for components in intermittent operations, have been determined. Process and instrumentation diagrams (P&ID), design documents and drawings have been analysed. For component failure during operation, statistical data, such as failure rate , standard error s.e. (), lower L and upper U limits of the 90% confidence interval and mean time between failures (MTBF) and mean number of demands between failures (MDBF) have been calculated assuming the constant failure rate model, USNRC [5]. As a result of the work, statistical data are provided together with the collected practical information acquired from the experience gained operating the system analysed.
The AGHS has been designed and installed for JET operation with D/T plasma. It was installed from 1990 to 1991; its main function is the supplying of D and T gases into the plasma and the extraction and separation of hydrogen isotopes from the Torus exhaust so that tritium and deuterium can be recycled. Tritium was introduced to AGHS on 12 June 1995. 3.1. Data collection Data related to AGHS operations and to the component failures were got partly from AGHS staff and partly by looking at the system log-books (hand-written). All the data have been successively recorded in an Excel spreadsheet. The information investigated on failures/malfunctions concerns the identification of failed components, failure modes and, where possible, causes and consequences of the failures. To perform statistical analysis, the whole sets of components affected by failures/malfunctions were also identified. Components were classified and counted in order to find out their amount, related operating hours and related demands to operate (for components operating in intermittent way). About 6200 components, operating for about a total of 215,000,000 h were identified in AGHS. 3.2. Overview on identified failures The analysis performed in 2002 on data related to JET AGHS failures was reviewed considering failures and system updating
Table 1 Statistics on AGHS components made by operating hours and failure modes. Component
Failure mode
No. of faults
Failure rate, (1/h)
s.e. () (1/h)
L (90%) (1/h)
U (90%) (1/h)
MTBFa (h)
Amplifier Ancillary power supply Blower Blower Catherometer Chiller water Chiller water Controller Distributed control unit Fan of electronic board Filter Fire detection system Heater Heater Heater Indicator Indicator Ionization chamber Radiation monitor (room) Radiation monitor (stack) Rupture disc Site PS (from national grid) Site PS (from national grid) Switch Thermoresistance Transducer Transducer Transformer (high voltage) Transmitter Uninterruptable PS Uninterruptable PS Vacuum pump Vacuum pump Vacuum pump Vacuum pump Vacuum pump Valve Valve Valve
Erratic/No Output Loss of power Failure to run Failure to start Erratic/No Output Alarm/Erratic Alarm Failure to operate Erratic/No Output Erratic/No Output Failure to run Blocked Spurious alarm Failure to operate Loss of power Overtemperature Erratic/No Output Leak-External Erratic/No Output Erratic/No Output Erratic/No Output Premature opening Loss of power Overvoltage Failure to operate Erratic/No Output Erratic/No Output Leak Loss of power Erratic/No Output Alarm/Erratic Alarm Loss of power Alarm/Erratic Alarm Leak-External Failure to run Failure to start Failure to stop Failure to operate Leak-External Leak-Internal
17 29 13 5 2 17 22 8 24 3 1 18 3 2 2 60 2 3 5 4 1 3 1 8 1 14 1 2 8 5 5 5 1 37 6 1 47 54 2
5.5E−6 7.1E−4 3.3E−5 1.3E−5 1.3E−5 4.2E−4 5.4E−4 3.3E−6 1.0E−5 2.0E−6 2.1E−6 4.4E−4 5.3E−7 3.5E−7 3.5E−7 2.1E−6 7.1E−8 1.7E−6 5.0E−5 4.0E−5 5.9E−7 3.0E−5 1.0E−5 1.9E−7 7.9E−7 2.3E−6 1.6E−7 1.4E−5 8.1E−7 5.0E−5 5.0E−5 2.8E−5 7.6E−7 2.8E−5 4.6E−6 7.6E−7 6.3E−7 7.2E−7 2.7E−8
1.3E−6 1.3E−4 9.1E−6 5.6E−6 9.3E−6 1.0E−4 1.1E−4 1.2E−6 2.1E−6 1.2E−6 2.1E−6 1.0E−4 3.0E−7 2.5E−7 2.5E−7 2.7E−7 5.0E−8 9.6E−7 2.3E−5 2.0E−5 5.9E−7 1.7E−5 1.0E−5 6.9E−8 7.9E−7 6.1E−7 1.6E−7 9.6E−6 2.9E−7 2.3E−5 2.3E−5 1.2E−5 7.6E−7 4.6E−6 1.9E−6 7.6E−7 9.2E−8 9.8E−8 1.9E−8
3.5E−6 5.1E−4 1.9E−5 5.0E−6 2.3E−6 2.7E−4 3.6E−4 1.6E−6 7.0E−6 5.5E−7 1.1E−7 2.8E−4 1.4E−7 6.2E−8 6.2E−8 1.7E−6 1.3E−8 4.5E−7 2.0E−5 1.4E−5 3.0E−8 8.3E−6 5.2E−7 9.7E−8 4.1E−8 1.4E−6 8.4E−9 2.4E−6 4.0E−7 2.0E−5 2.0E−5 1.1E−5 3.9E−8 2.1E−5 2.0E−6 3.9E−8 4.9E−7 5.7E−7 4.8E−9
8.2E−6 9.7E−4 5.2E−5 2.7E−5 4.1E−5 6.2E−4 7.7E−4 5.9E−6 1.4E−5 5.2E−6 9.9E−6 6.5E−4 1.4E−6 1.1E−6 1.1E−6 2.6E−6 2.2E−7 4.3E−6 1.1E−4 9.2E−5 2.8E−6 7.8E−5 4.8E−5 3.5E−7 3.8E−6 3.6E−6 7.8E−7 4.3E−5 1.5E−6 1.1E−4 1.1E−4 5.9E−5 3.6E−6 3.7E−5 9.0E−6 3.6E−6 8.0E−7 9.1E−7 8.4E−8
1.8E+5 1.4E+3 3.0E+4 7.9E+4 7.6E+4 2.4E+3 1.9E+3 3.0E+5 9.9E+4 4.9E+5 4.8E+5 2.3E+3 1.9E+6 2.8E+6 2.8E+6 4.7E+5 1.4E+7 6.0E+5 2.0E+4 2.5E+4 1.7E+6 3.3E+4 9.9E+4 5.1E+6 1.3E+6 4.4E+5 6.1E+6 7.4E+4 1.2E+6 2.0E+4 2.0E+4 3.6E+4 1.3E+6 3.5E+4 2.2E+5 1.3E+6 1.6E+6 1.4E+6 3.7E+7
a
Mean time between failures.
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Table 2 Statistics on some AGHS components made by operating cycles (open/close or turn on/off) and failure modes. Component
Class type
Failure mode
No. of faults
No. of components in AGHS
Total no. of demands
1/Demand pD
s.e. (pD )
pDL (90%)
pDU (90%)
Valve
General type
Failure to operate
47
2124
725,035
6.5E−5
9.5E−6
5.0E−5
8.3E−5
Valve Valve Valve
Air actuated Air actuated Air actuated
Failure to open/close Leak-External Leak-Internal
31 2 2
601 601 601
295,481 295,481 295,481
1.0E−4 6.8E−6 6.8E−6
1.9E−5 4.8E−6 4.8E−6
7.6E−5 1.2E−6 1.2E−6
1.4E−4 2.1E−5 2.1E−5
Valve Valve
Solenoid Solenoid
Failure to open/close Leak-External
8 52
646 646
419,351 419,351
1.9E−5 1.2E−4
6.7E−6 1.7E−5
9.5E−6 9.7E−5
3.4E−5 1.6E−4
Valve
Manual
Failure to open/close
0
732
10,203
9.0E−5
9.4E−5
0.0E+0
2.3E−4
All failure modes Failure to operate Loss of power Overtemperature
7 3 2 2
131 131 131 131
56,025 56,025 56,025 56,025
1.2E−4 5.4E−5 3.6E−5 3.6E−5
4.7E−5 3.1E−5 2.5E−5 2.5E−5
5.9E−5 1.5E−5 6.3E−6 6.3E−6
2.3E−4 1.4E−4 1.1E−4 1.1E−4
Heater Heater Heater Heater
Table 3 Statistics by type and failure modes of indicators in AGH system. Component
Class type
Failure mode
No. of faults
No. of components in AGHS
Total run time (h)
Failure rate, (1/h)
s.e. () (1/h)
L (90%) (1/h)
U (90%) (1/h)
MTBF (h)
Indicator Indicator Indicator Indicator Indicator Indicator Indicator Indicator Indicator Indicator
General type General type Flow Humidity Level Pressure Temperature Temperature Tritium Tritium
Erratic/No Output Leak-External Erratic/No Output Erratic/No Output Erratic/No Output Erratic/No Output Erratic/No Output Leak-External Erratic/No Output Leak-External
60 2 3 1 2 11 17 1 26 1
653 653 54 6 18 239 161 161 43 43
28,251,072 28,251,072 3,133,800 594,576 683,184 9,533,544 6,950,488 6,950,488 2,062,888 2,062,888
2.1E−6 7.1E−8 9.6E−7 1.7E−6 2.9E−6 1.2E−6 2.4E−6 1.4E−7 1.3E−5 4.8E−7
2.7E−7 5.0E−8 5.5E−7 1.7E−6 2.1E−6 3.5E−7 5.9E−7 1.4E−7 2.5E−6 4.8E−7
1.7E−6 1.3E−8 2.6E−7 8.6E−8 5.2E−7 6.5E−7 1.6E−6 7.4E−9 8.8E−6 2.5E−8
2.6E−6 2.2E−7 2.5E−6 8.0E−6 9.2E−6 1.9E−6 3.7E−6 6.8E−7 1.7E−5 2.3E−6
4.7E+5 1.4E+7 1.0E+6 5.9E+5 3.4E+5 8.7E+5 4.1E+5 7.0E+6 7.9E+4 2.1E+6
occurred in the AGHS between 2002 and 2006. As a result, about 460 failures/malfunctions were pointed out since 1995 up to 2006. More precisely, 131 failures/malfunctions were related to the period 1995–January 2002 and 326 failures/malfunctions were related since February 2002 up to September 2006. Generally speaking, the most part of them do not affect the JET operations. 3.3. Reliability analysis on AGHS failures For component failed during operation, statistical data, such as failure rate , standard error s.e. (), lower L and upper U limits of the 90% confidence interval and mean time between failures (MTBF) and mean number of demands between failures (MDBF) are usually calculated [5] assuming the constant failure rate model. In such a case, as a sample, is evaluated applying the point estimate model (Poisson or exponential models) through the number of observed failures N, over time T of component operating expe-
rience, i.e. by the formula = N/T. The application of the Poisson model is considered appropriate when the total number of failures N is increasing linearly versus the component total operating time. For component operating on demand, failure probability on demands pD are commonly determined [5] on the base of the estimated amount of “calls in operation” (demands), considering the binomial model. The related standard error s.e. (pD ), and the lower pDL and upper pDU limits of the 90% confidence interval, have been calculated, too. Details about the data collected and the data elaboration are given in [6]. Few samples of the results pointed out by this work is presented in Tables 1–4. Statistics on AGHS components made by operating hours and failure modes are listed in Table 1. Statistics on valves and heaters made by operating cycles and failure modes are listed in Table 2. Statistics by type and failure modes of indicators are
Table 4 Statistics by failure modes of ancillary systems in AGHS plant. Component
Failure mode
No. of faults
Total run time (h)
Failure rate, (1/h)
s.e. () (1/h)
L (90%) (1/h)
U (90%) (1/h)
MTBF (h)
Ancillary power supply (PS) system
Loss of power
29
40,872
7.1E−4
1.3E−4
5.1E−4
9.7E−4
1.4E+3
Chiller water system Chiller water system
Alarm/Erratic Alarm Failure to operate
17 22
40,872 40,872
4.2E−4 5.4E−4
1.0E−4 1.1E−4
2.7E−4 3.6E−4
6.2E−4 7.7E−4
2.4E+3 1.9E+3
Fire detection system
Spurious Alarm
18
40,872
4.4E−4
1.0E−4
2.8E−4
6.5E−4
2.3E+3
Radiation monitor (room control) Radiation monitor (stack control)
Erratic/No Output Erratic/No Output
5 4
99,096 99,096
5.0E−5 4.0E−5
2.3E−5 2.0E−5
2.0E−5 1.4E−5
1.1E−4 9.2E−5
2.0E+4 2.5E+4
Site PS (from national grid) Site PS (from national grid)
Loss of power Overvoltage
3 1
99,096 99,096
3.0E−5 1.0E−5
1.7E−5 1.0E−5
8.3E−6 5.2E−7
7.8E−5 4.8E−5
3.3E+4 9.9E+4
Transformer (high voltage)
Loss of power
2
594,576
3.4E−6
2.4E−6
6.0E−7
1.1E−5
3.0E+5
Uninterruptable PS system Uninterruptable PS system
Alarm/Erratic Alarm Loss of power
5 5
99,096 99,096
5.0E−5 5.0E−5
2.3E−5 2.3E−5
2.0E−5 2.0E−5
1.1E−4 1.1E−4
2.0E+4 2.0E+4
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tion of failures have been scrutinized. The following maintenance activities have been selected to be studied in detail: replacing of the Emergency Detritiation System (EDS) butterfly valve; repairing of the plant Uninterruptible Power Supply (UPS); re-routing of Mechanical Forevacuum (MF) pipework to substitute large scroll vacuum pump; removing of the failed large scroll vacuum pumps and their substitution with new screw vacuum pumps; inspection of large scroll pump; replacing of perforated EDS bellows; replacing of blocked EDS filter. Every maintenance activity on failed or obsolete components had dedicated worker procedures carefully prepared to avoid or limit worker exposures, environmental releases, system and plant outages. Detailed data are reported in [6] and some considerations deduced from the analysis of those maintenance activities are given in the following. 4.1. Time spent for AGHS maintenance activities About the time spent in the various phases of maintenance:
Fig. 1. AGHS reliability data: comparison between 1995–2006 and 1995–2002 results.
listed in Table 3. Statistics by failure modes of AGHS plant ancillary systems are listed in Table 4. 3.4. Discussion about AGHS reliability results 3.4.1. Comparison with previous AGHS reliability results For the most part of components, failure rates were presented also in [1,2] where the operating experience considered was between 1995 and January 2002. The comparison of the new failure rates with the previous ones shows, apart few cases, a slight deterioration of components with their age, because of the increasing of failure rate values (see Fig. 1). 3.4.2. Comparison between obtained statistical and literature data The evaluated failure rates were also compared with failure rates existing in literature for similar applications (e.g.: nuclear power plants, tritium processing laboratories). The result showed a good agreement (see Fig. 2 in [7]) between the values from the different sources (see e.g. [8–10]). That enforces the usefulness of the obtained data in evaluating reliability parameters to support the safety assessment and to analyse availability/reliability of fusion machines/plants and tritium laboratories.
(a) Even if disturbances in the process parameters was noted, in some cases, the failure detection took 2 or 3 days. (b) Generally speaking, for important maintenance operations the planning of the intervention took weeks and also months, particularly for large components and breaching of process lines. Some times, decisions to postpone maintenance to planned main plant shutdown period were taken, when it was possible. (c) The procuring of components sometimes took months. A suitable strategy of spare parties could have been reduced highly the time spent for this issue. (d) Time to start the work after failure did not take less than some weeks and, clearly, it depended from time required to plan the intervention and time to procure components. (e) Time to perform the first breach after starting of the work took from 1 day to some months, depending from the complexity of the preparatory work (e.g.: set of working area with scaffolding, tools, tents, isolators, radiation monitors, etc.) and decontamination of components to be maintained (e.g.: purging of components and process lines, as well as checking of the contamination levels). (f) Time required to conclude breaching conditions, usually, took days (from 1 to 15 days according to the complexity of the operations). (g) Also leak tests and activities devoted to eliminate leaks took from few days to some weeks. Summarizing, maintenance activities requiring the breaching of the tritium process lines necessitated of a time of the order of magnitude of months to perform the overall work of medium and high complexity, as the removal of large size components. Minor maintenance activities in terms of breaching the process lines required working time on the order of few weeks. Consequently, outage of the system was also on the order of months, with the exception of minor activities for which the outage of the system was for few weeks. 4.2. Worker and public safety effects of AGHS maintenance activities
4. Analysis of relevant JET AGHS maintenance operations Some of the most important failures in the plant, which required significant maintenance operations have been investigated in detail. Unavailability of components and system, possible impact on doses to the workers, possible environmental releases related to the failures and possible plant modifications to prevent repeti-
For four of the maintenance activities analysed, minor worker doses have been recorded. All these activities necessitated breaching of tritium process lines. The collective doses assumed by “authorized radiological workers” for each activity was very low, on the order of tens of Sv. The average values of worker dose rate for the opening of the tritium process lines results 0.13 Sv/person-
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h. The most exposed workers were fitters. The mean dose rate for fitters was 0.22 Sv/person-h. Data on internal and external doses to workers operating in the AGHS building J25 have been provided by JET Operator. External dose are measured by dosimeters and internal doses by bioassay measurements. Data on radioactive release to stack from tritium plant (building J25) have been also provided by JET Operator. Those data refer to weekly releases in HTO and HT forms: partial, for each form, and total MBq values have been provided. Total releases from J25 in 5 years of operations result of 0.3 TBq of HTO and 2.2 TBq of HT. These releases are usually not related to maintenance activities. Only for three of the eight maintenance activities analysed the weekly stack release curves have small peaks of the order of 1–10 GBq, corresponding to 0.2 mg in the HTO form or 0.04 mg in HT form at maximum in correlation to the maintenance periods. 5. Main outcomes from JET tritium plant components failures and operating experience Data on operating experience of JET AGHS have been deeply searched and assessed. In about 11 years of system operations, about 460 failures/malfunctions on a set of more than 6200 components have been identified. The largest number of failures/malfunctions concerned “external leaks” and “fail to operate” of air actuated valves and solenoid valves. For them, a program of preventive maintenance started in 2001 after 6 years of operation. Important in terms of amount of malfunctions were also “Erratic/No Output” of instrumentation and electronic components due to: ammeter failures for tritium indicators and ionization chambers; electrochemical cell “Exhausted” for humidity indicator; filament failure for catherometer; amplifier, thermocouples, pressure and flow indicators, sensors, switches, probe and transducers faults; control units failures. Particularly, to avoid one of the possible causes of the last ones failures, a dedicated preventative maintenance program started after 2 years of operation to replace every 12 months cooling fans of electrical boards. Three of the five large scroll vacuum pumps (capacity: 150–600 m3 /h), installed in the plant, stopped and then they were removed, respectively after about 29,000, 22,000 and 24,000 h of operating life. Build up of debris inside the pump was observed on failed pumps. The pumps have been replaced with screw vacuum pumps, which for their part also experienced several failures due to problems in the electric circuits, in their instrumentation and control equipment and in supplying N2 gas. Other failures concerned: metal bellow, rotary vane and turbo-molecular vacuum pumps; blowers; radiation monitors; no-return and pressure regulator valves; oil pumps; power supply systems (grid, UPS and ancillary); air cooling system, chiller system and fire detection system. A detailed analysis of the most complex maintenance activities experienced in the AGHS has been done too. For them, it results that to perform the overall work of a maintenance programme takes time of the order of magnitude of weeks or months according to the relevance of the activity. Consequently, the outage of the sub-system under maintenance is also in the order of few weeks or months. For four of these major maintenance activities requiring breaching of tritium process lines, it results a mean value of total dose to workers of 0.13 Sv/person-h, according to
the health physics detection. From the analysed tritium environmental releases no clear correspondence has been identified with maintenance activities requiring breaching of tritium process lines. Some small peaks on stack releases have been found only during the periods of three maintenance activities. These peaks are on the order of 10 GBq. 6. Conclusions Main reliability parameters associated to the JET tritium plant components have been estimated. The failure rates and the failure probabilities on demand evaluated are in very good agreement with the corresponding ones existing in literature for similar applications (e.g.: nuclear power plants). The data obtained could be very useful to evaluate reliability parameters in support of safety assessment and for availability/reliability analyses of fusion machines/plants and tritium laboratories. Failure rates estimated in a previous assessment done in 2002 have been compared with the new ones. By these data it is possible to note, apart few cases, a slight deterioration of components with their age, because the increasing of failure rate values. From the analysis of the most complex maintenance activities experienced in the AGHS it has pointed out that the outage of the sub-system under maintenance is of the order of few weeks or months. For four of the major maintenance activities requiring breaching of tritium process lines, it results a mean value of total dose to workers of 0.13 Sv/person-h, according to the health physics detection. Some small peaks of about 10 GBq on stack releases have been found only during the periods of three maintenance activities. Therefore the environmental release related to maintenance activities can be considered negligible. Acknowledgments The work was possible thanks to the collaboration of the AGHS JET staff and to the support of the European Fusion Development Agreement (EFDA) Close Support Unit at JET. References [1] T. Pinna, G. Cambi, A. Lo Bue, C. Rizzello, Collection and analysis of data related to fusion machines (JET and TLK) operation experience on component failure, ENEA FUS-TN-SA-SE-R-058, February 2003. [2] T. Pinna, et al., Collection and analysis of data related to fusion machines (JET and TLK) operating experience on component failure, Fusion Eng. Des. 75–79 (2005) 1199–1203. [3] T. Pinna, G. Cambi, F. Gravanti, Collection and analysis of component failure data from JET systems: neutral beam injectors and power supply, Nuclear Fusion 47 (2007) S453–S457. [4] G. Cambi, T. Pinna, M. Angelone, Data collection on component malfunctions and failures of JET ICRH System, Fusion Eng. Des. 83 (2008) 1874–1877. [5] USNRC, PRA procedure guide: a guide to the performance of probabilistic risk assessments for nuclear power plants, Final Report, NUREG/CR-2300, January 1983. [6] T. Pinna, G. Cambi, S. Knipe, JET operating experience: global analysis of tritium plant failure, ENEA FUS-TN-SA-SE-R-193, June 2008. [7] T. Pinna et al., Operating experiences from existing fusion facilities in view of ITER safety and reliability, this conference. [8] L.C. Cadwallader, Comparison of tritium component failure rate data, Fusion Sci. Technol. 47 (May (4)) (2005) 983–988. [9] L.C. Cadwallader, Failure rate data for glovebox components and cleanup systems at the tritium systems test assembly, J. Fusion Energy 12 (1–2) (1993) 47–51. [10] L.C. Cadwallader, Vacuum component reliability estimates for experimental fusion facilities, Fusion Technol. 26 (3 (Pt 2)) (1994) 1021–1024.