Transcript IEA ESE Task 5 Failure Rate Database Status and Work Program

Impact of Reliability,
Availability, Maintainability,
and Inspectability (RAMI)
Lee Cadwallader
Fusion Safety Program
ARIES-Pathways Project Meeting,
GIT, Atlanta, GA, December 12-13, 2007
What is RAMI?
Availability, A
Annual plant operating hours ∕ 8760 hr
Reliability, R
Probability of a
system running
correctly over its
assigned run time
Maintainability, M
Probability of returning
failed system to service
in a fixed time interval, or
avg time to 100% repair
Inspectability, I
Productive time lost
or gained due to test
and inspection
requirements
Design in inherent R
What is not there
can’t fail
Weakest link of chain
Parallel strand of rope
Contractors vs permanent
staff
Maintenance staff size,
training
Spare parts stock on hand
Regulations vs good
practice
Inspections & tests
requiring extra outage
time vs those that don’t
All of the “-ilities” Lead to Availability
•
High plant availability produces profitable revenue or meets the
facility mission.
•
Fusion experiments track “mission availability” which is actual
operating hours compared to funded operating hours in the calendar
year. Tokamaks are 60-80% mission available over 8 or 10 hour days
of perhaps ~20 weeks/year. This is ~11% calendar availability. Such
availabilities are early in a technology development path.
•
US fission power plants are reaching ~90% and higher calendar
availability per year. The Westinghouse AP-1000 “Generation III”
design expects to exceed 93% annual availability because its
simplified design uses fewer parts than existing plants and specifies
off-the-shelf components of proven reliability.
•
Utility companies are interested in low O&M costs and high
availability to maximize their profit. To be economically competitive,
fusion has a strenuous goal to reach.
•
Reliability tends to have the most crucial influence on availability;
reliability is inherent in the plant systems. If systems are continually
breaking down then availability can never be high.
There are Several Means to Estimate Reliability
•
•
•
Infer component failure rates from similar equipment that has already
been operating in a similar environment; this is very lost cost and
fast, but not always highly accurate.
– Fission reactor data
– Accelerator data
– Aerospace data
Analyze component failures from tokamak operating experiences
– There is a modest IEA task under way to do this work for fusion
components
Present tokamaks and fusion experiments are not power plants; they
may be mature in age but not in technologies used, so their data are
not always what is needed. Nonetheless, most technology
development activities use the data from the present level to apply to
the next plateau or stairstep in technology advance.
Selected component failure data have been analyzed
and compared between fusion facilities - and between
fusion experiments and accelerators
•
Analyses have been completed in the US, Europe, and Japan. We are
slowly growing our own failure rate data base for next step machines.
•
Component failure rates compare with fair to good results thus far
What are the fusion data telling us so far?
Where are we? What is our goal?
•
Abdou suggested some top-down system availability
apportionments, 97.8% availability for 6 major fusion power plant
systems, such as plasma heating, vacuum, fueling. This was
based on a plant overall availability of only 75% and BOP A = 85%,
to match other power plant technologies. These values set the
fusion reactor “island” requirement at A = 88%.
•
More recently, Waganer pointed out that fusion has not set an
official power plant availability goal. He suggested a 90% overall
plant goal for ARIES-AT.
•
Since our competition has improved, fusion power plant
availability should be over 90% and fusion system availabilities
need to be higher, ~99%.
•
For a 95% available fusion power plant, each of ~10 major systems
must have an availability of 99.5%. The system failure rates
should be less than 1E-04/hour. Along the power plant path, the
ITER goal is A=25%, so major systems should be 87% available, or
system failure rates of ~5E-04/h.
System Failure Rate (/hr)
1.00E-05
10-5
Preliminary system
failure rate goal for a
fusion power plant
1.00E-04
10-4
Preliminary system
failure rate goal for ITER
1.00E-03
10-3
1.00E-02
10-2
λ > 1E-01
1.00E-01
10-1
ICH
ECH
NBI
Vacuum Small TF Power
PF
Pumping Vacuum Supplies Power
Vessel
Supplies
Leaks
DIII-D Tokamak Systems
Component Testing can also Develop Failure Rates
•
•
Testing must be performed in the most similar environment possible.
Making a fusion environment is difficult & costly, e.g., CTF, IFMIF
– Margin tests are used to determine the safety, or design, margin in a
component, e.g., SNL HHF testing
– Life tests are used to determine basic reliability in the service
environment, e.g., ORNL Large Coil Task
To find a component failure rate, test components in the most demanding
aspects of the service environment. The larger the sample, the better the
results. Use as many units as affordable, as long as possible, until the units
fail.
•
Few agencies can afford to produce a hundred or more units, set up testing
stands for them, and then perform ten thousand hours (or more) of testing.
•
Instead, accelerated life tests are used - subjecting components to more
harsh environments than expected service. Usually, overstress tests are
used and results are extrapolated to normal service. Accelerated tests can
reduce the need to tens of units for a few hundred or a thousand hours of
testing. An example is light emitting diodes (LEDs), a traditional test was
1,000 units for a year at room temperature, but an accelerated test is 32
units for 720 hours at temperatures up to 200ºC.
The ITER Tokamak Cooling Water System (TCWS) A&M
•
A success story is the ITER TCWS. In the CDA and early EDA, there
were 10 cooling loops in the TCWS; the original idea was to make sure
the walls would never melt. This meant high capital cost, very large
floor space for equipment mounting and maintenance access, and
more maintenance time for 10 pumps, sets of valves, HXs,
instruments, etc.
•
The TCWS designers, with inputs from safety personnel, were able to
safely reduce the design to 3 cooling loops.
•
•
– Pump failure rates in the 1-10k gpm size range typically have little
difference (< 20%) compared to the 10-25k gpm size range.
– Pipe failure rates decreased with reduction in footage
Reduction placed a safety burden on the VV; inventory from an invessel LOCA of one large loop caused very high pressure in the
vessel. This was solved by adding a steam pressure suppression
tank, a passive system with a low failure rate.
ORNL RAMI analysis is reviewing the idea of one extra, standby
coolant pump plumbed in to the 3 FW/BKT loops to enhance system
availability. An alternative is to specify 3 oversized pumps so that 2
pumps can provide the necessary flow in 3 loops.
Availability Impacts
•
•
Availability is the key to profitable plant operations. Assume fusion
energy becomes a base-load, central station power plant technology
(i.e., > 200 MWe), and no government subsidies will be given to favor
“green” technology, then:
– Fusion will have to compete against present coal-fired plants that
are reaching availability, A = 87% and higher, and new clean coal
plants purported to reach A ≥ 90%.
– Generation III fission plants that expect A = 93% and higher
– Generation IV fission plants (e.g., PRISM, IRIS, PBMR), with 18- or
24-month fuel cycles that refuel in less than 20-day outages or
refuel on-line, are predicting A = 93% to 95%.
There are always unplanned power plant outages: lightning strikes,
plant switchyard and electrical grid equipment faults, animal
encroachment in switchyard equipment, tree growth onto power
lines, plant equipment faults, control computer hardware or software
faults, instrumentation faults, and human errors. Even well
designed, well operated plants can typically lose 1% to 2.5% or more
availability due to these types of events each year.
Availability Impacts
•
•
ARIES-CS estimated 1,230 hours, or a 51-day scheduled outage,
for wall module changeout every 3 years.
– Fusion walls must become more durable, or changeouts must
be performed more quickly, for power plant competitiveness.
– Ideally, a fusion wall changeout session would be less time
than an LWR refueling outage (~ 20 days every 1.5 or 2 years)
We have serious competition that has already established itself in
the power generation field. Economics is driving all forms of
power generation to be more efficient. Fission and coal have
increased their availability > 15% in the past 20 years.
References
•
M. A. Abdou and the APEX Team, “Exploring Novel High Power Density Concepts for Attarctive Fusion Systems,” Fusion
Engineering and Design, 45 (1999) 145-167.
•
E. M. Blake, “U.S. capacity factors: Leveling off at last,” Nuclear News, 49 (May 2006) 26-31.
•
L. Cadwallader, data reports and papers on DIII-D data analyses.
•
R. Caplen, A Practical Approach to Reliability, Business Books Limited, London (1972).
•
M. D. Carelli et al., “The design and safety features of the IRIS reactor,” Nuclear Engineering and Design, 230 (2004) 151-167.
•
S. Ciattaglia et al., “Availability of Present Fusion Devices,” 21st SOFE, Knoxville, TN, September 26-29, 2005.
•
A. Koster et al., “Pebble-bed modular reactor: a generation IV high-temperature gas-cooled reactor,” Proceedings of the Institution
of Mechanical Engineers, Part A: Journal of Power and Energy, 218 (2004) 309-318.
•
W. G. Ireson, C. F. Coombs Jr., R. Y. Moss, Handbook of Reliability Engineering and Management, 2/e, McGraw-Hill, New York
(1996).
•
North American Electric Reliability Corporation, Generating Availability Data System (GADS), 2002-2006 data, www.nerc.com.
•
T. L. Schultz, “Westinghouse AP1000 advanced passive plant,” Nuclear Engineering and Design, 236 (2006) 1547-1557.
•
L. M. Waganer and the ARIES Team, “ARIES-AT maintenance system definition and analysis,” Fusion Engineering and Design,
80 (2006) 161-180.
•
L. M. Waganer, R. J. Peipert-Jr., X. R. Wang, and S. Malang, “ARIES-CS Maintenance System Definition and Analysis,” rev 4,
January 2007.
•
W. Zhao and E. A. Elsayed, “A general accelerated life model for step-stress testing,” IEE Transactions, 37 (2005) 1059-1069.