Fuel Failure
Detection
By David Smith, Entergy.
David Smith
David Smith is a
Senior Staff Engineer
at Entergy in the
Fuels Department.
He has a BS in
Nuclear Engineering
from the Missouri
University of Science
and Technology and
a MS of Engineering
Management from
George Washington
University.
This Top Industry Practice Award was a
2013 Process Award Winner.
The team members who participated
included:
David Smith, Fuels & Analysis
Engineer; Scott Stanchfield, Supervisor,
Engineering, Fuels & Analysis; George
Rorke, Senior Staff Engineer, Fuels
& Analysis; Jeffery Goldstein, Fleet
Chemistry Manager; Fred Smith,
Manager, Fuels & Analysis, Entergy.
Summary
The nuclear industry did not have
a reliable process to confidently detect
very tight Boiling Water Reactor fuel
failures during normal operations. Classic
identifiers, i.e., Xenon-138/Xenon-133
ratios and others were not consistent,
early and accurate indicators of such fuel
failures.
As a result, steps could not be taken to
prevent further fuel damage during normal
power movements of a
power plant which could
ultimately require a
costly mid-cycle outage.
Improvement
The Entergy Nu-
clear Fleet Fuels &
Analysis group devel-
oped a correlation mod-
el to flag fuel failure by
using BWR historical
data from the industry,
including Entergy data. This model specifi-
cally used data from Exelon units at Quad
Cities-1 and LaSalle-2 along with Entergy’s
River Bend, Grand Gulf, Vermont Yankee,
Pilgrim and James A. FitzPatrick stations.
The correlation model uses off-gas
data during power changes to flag a fuel
failure.
Validation
The Entergy correlation model
predicted a fuel failure at Exelon’s Quad
Cities which was later actually found.
The Entergy correlation was in
agreement with a later fuel failure declared
for Exelon’s LaSalle-2.
The correlation was applied to
Entergy’s Pilgrim Nuclear Station in April
2011. It added confidence that the fuel
cycle was failure free. Uncertainty existed
due to the Quad Cities and LaSalle-2
fuel failure experience. The correlation
predicted a failure-free cycle for Pilgrim
which was later verified.
Due to ambiguous data gathered at
Grand Gulf during June and July 2011,
Grand Gulf performed a down-power
to employ the new correlation, which
successfully identified a fuel failure. This
permitted the site to perform a timely
power suppression test to locate the region
of the failure and to insert control blades
in this region to protect the failure from
added stresses relating to future power
maneuvers.
Fuel Failure Impacts
In-house calculations for degraded
failures note ALARA impacts in the
millions of dollars. Fuel failure impacts
are also responsible for mid-cycle outage
durations of 6-10 days.
With the fuel failure correlation
model, damage is predicted. With this
knowledge, actions can be taken to
minimize risk of further fuel damage and
large cracks in fuel structures which would
ultimately result in a shutdown.
By detecting the fuel failure, the
failure could be power-suppressed so
that further degradation is avoided. Fuel
failure degradation can result in very
high background radiation activities and
the need of a possible mid-cycle outage.
Information from the correlation model
will reduce the challenge of a needed
forced-outage to remove the failed bundle.
Entergy shared the correlation model
approach during industry fuel performance
meetings: International Fuel Performance
Conference in New Orleans on June 2011
and at the EPRI meeting in July 2011.
INPO noted that Entergy’s use of
the correlation model, early detection of
a fuel failure, and prompt suppression of
the failure was an industry “beneficial-
practice” during a recent visit to Grand
Gulf Nuclear Station.
Safety
Nuclear safety is greatly enhanced by
the implementation of this new correlation
model.
There is a reduction in radioactive
release and elimination of risk
evolutions for forced down power.
42
NuclearPlantJournal.com Nuclear Plant Journal, March-April 2014
