471st Advisory Committee on Reactor Safeguards (ACRS) - April 6, 2000
UNITED STATES OF AMERICA
NUCLEAR REGULATORY COMMISSION
ADVISORY COMMITTEE ON REACTOR SAFEGUARDS
***
471ST ADVISORY COMMITTEE ON
REACTOR SAFEGUARDS (ACRS)
U.S. Nuclear Regulatory Commission
11545 Rockville Pike, Room T-2B3
Two White Flint Building North
Rockville, Maryland
Thursday, April 6, 2000
The committee met, pursuant to notice, at 8:30
a.m.
MEMBERS PRESENT:
DANA A. POWERS, ACRS Chairman
GEORGE APOSTOLAKIS, ACRS Vice-Chairman
THOMAS S. KRESS, ACRS Member
MARIO V. BONACA, ACRS Member
JOHN J. BARTON, ACRS Member
ROBERT E. UHRIG, ACRS Member
WILLIAM J. SHACK, ACRS Member
JOHN D. SIEBER, ACRS Member
ROBERT L. SEALE, ACRS Member
GRAHAM B. WALLIS, ACRS Member
ALSO PRESENT:
JOHN T. LARKINS, ACRS Executive Director
MEDHAT EL-ZEFTAWY, ACRS Staff
HOWARD J. LARSON, ACRS
MICHAEL T. MARKLEY, ACRS Staff
NOEL F. DUDLEY, ACRS Staff
PAUL A. BOEHNERT, ACRS Staff
SAM DURAISWAMY, ACRS Staff
CAROL A. HARRIS, ACRS/ACNW Staff
PATRICK W. BARANOWSKY, NRR
STEVEN E. MAYS, NRR
. C O N T E N T S
NUMBER PAGE
1 OPERATING EXPERIENCE RISK ANALYSIS
BRANCH PROGRAM OVERVIEW 308
2 COMMENTS ON APPENDIX 2.B. "STRUCTURAL
INTEGRITY SEISMIC LOADS" 380. P R O C E E D I N G S
[8:30 a.m.]
CHAIRMAN POWERS: The meeting will now come to
order. This is the second day of the 471st meeting of the
Advisory Committee on Reactor Safeguards.
During today's meeting the committee will consider
the following: special studies for risk-based analysis of
reactor operating experience; a report of the Materials and
Metallurgy and Thermal Hydraulic Phenomena Subcommittees,
future ACRS activities, report of the Planning and
Procedures Subcommittee, reconciliation of ACRS comments,
recommendations, proposed ACRS reports.
The meeting is being conducted in accordance with
the provisions of the Federal Advisory Committee Act. Mr.
Sam Duraiswamy is the Designated Federal Official for the
initial portion of the meeting.
We have received no written statements or requests
for time to make oral statements from members of the public
regarding today's session.
A transcript of a portion of the meeting is being
kept and it is requested that the speakers use one of the
microphones, identify themselves and speak with sufficient
clarity and volume so that they can be readily heard.
I do want to bring to your attention that
subsequent to our discussion of the spent fuel pool accident
risk for decommissioning plants on Wednesday, April 5th,
2000, the Nuclear Energy Institute has provided comments on
this matter via an e-mail to Dr. El-Zeftawy. Nuclear Energy
Institute comments have been distributed to the members this
morning. They will be made part of the record of our
meeting.
CHAIRMAN POWERS: I also will remind members that
it is time for your ethics training and we have set it up so
that you can quickly go down, grab some lunch, come back up
here, and Mr. Szabo will come in and give us the ethics
instructions that we need to keep ourselves on the right
side of the legal requirements.
That does mean, however, that I am going to be
holding schedules fairly tightly in today's presentations
and discussions, so that we can meet, as scheduled, Mr.
Szabo.
Do any of the members have comments they want to
make before we begin today's proceedings?
DR. SEALE: Have we seen that e-mail from NEI?
CHAIRMAN POWERS: You have a copy in front of you.
DR. SHACK: About an eighth of an inch thick.
DR. SEALE: Oh, good.
CHAIRMAN POWERS: Seeing no additional comments, I
will move on to the provisions of the agenda.
Our first topic is special studies for risk-based
analysis of reactor operating experience.
Dr. Bonaco, I believe you will lead us through
this?
DR. BONACA: Yes. Good morning.
We met with the Operating Experience Risk Analysis
Branch on December 15th, and we had an overview of the
program that they have put forth and we heard about the
improved availability of different sources that is a major
improvement in the availability of information that comes
and is being used by this branch now.
We also heard about a number of the activities
that they support with this information. We believe that
meeting and its presentations were very informative. We
also believe that some of the programs that these activities
support are very important to the future of the agency,
particularly to risk-informing the regulations and because
of that we invited the branch to come and give an overview
to the whole committee.
We asked them to put particular emphasis on the
activities they support, although it is very important that
we understand what the databases are and how they gather the
information. It is also very important to understand who
the users are and the community they support and activities
they support and I believe that the presentation this
morning will be focused on those items, so with that I will
let Mr. Baranowsky to give us an overview.
MR. BARANOWSKY: Okay. For the record, I am
Patrick Baranowsky, Chief of the Operating Experience Risk
Analysis Branch, and I have Steven Mays here, who is the
Assistant Branch Chief, and thank you.
We did give our presentation to the subcommittee
in December on this, and it was about a half a day long, so
I have cut this down and tried to put some more information
in here on some of the uses of the work that is conducted in
my branch.
The first viewgraph I have here talks about the
purpose of this presentation, which is to give you the
overview of the activities, discuss our role in the
regulatory process, and provide some typical results of the
kinds of things that we finally performed, this risk-based
analysis of reactor operating experience. Why don't we just
go on to the next viewgraph?
Yesterday we talked about risk based performance
indicators and what we have in front of you here is a chart
which shows how all the activities that are conducted in my
branch are organized logically and hierarchically, and
information from one set such as the data flows into
analysis of special areas where we do industry-wide
analyses, such as system reliability, component and
initiating events. That information can then be used for
plant-specific type analyses with some enhancements or it
supports things like the Accident Sequence Precursor Program
methods and models, and all of these things can be pulled
together and have been pulled together as we discussed
yesterday as elements or at least learning exercises, if you
will, as to how we might go about constructing
plant-specific, risk based performance indicators.
One other point I want to make is that in addition
to each of these elements providing information that flows
up this chart. There is also a horizontal utilization of
the information at each level as we go along here, so
various NRC activities that are interested in the more raw
data that might come out of either LERs or the EPIX system,
which we will talk about in a minute, can have access to
those data sources, and they do.
We get many queries for each of those data
systems, plus the industry-wide analysis have results that
in and of themselves are important that get fed into the
regulatory process either for generic issues or for risk
inspections and things like that, and of course the Accident
Sequence Precursor Analysis Program provides insights on the
most significant events that occur, some of which result in
fairly immediate regulatory actions or they could result in
information notices after some deliberate study, and then
finally we have the risk based performance indicators, which
we discussed yesterday.
DR. APOSTOLAKIS: Bob, the box there says operator
error probability studies.
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: We haven't discussed this, have
we?
MR. BARANOWSKY: Correct, and that is more of a
place-holder than anything else.
There is another branch that has the primary
responsibility for the operator error studies.
We put it in there just for completeness and we
tried to factor in whatever we learned from other sources on
that into these programs, but I guess it's stashed in this
particular block to show that we are --
DR. APOSTOLAKIS: I don't recall it being part of
the Human Performance Program we saw yesterday. I mean that
is the other branch.
MR. BARANOWSKY: Yes, that's Jack Rosenthal's
branch.
DR. APOSTOLAKIS: Jack Rosenthal's. I don't
remember.
CHAIRMAN POWERS: My recollection is he had
something on this subject, but it seems to me you also made
the point that the latent errors outweighed the active
errors by four to one.
DR. APOSTOLAKIS: Right.
CHAIRMAN POWERS: And I am wondering if this --
DR. SEALE: At least.
CHAIRMAN POWERS: I mean it is labelled operator
error. What about the latent errors?
MR. BARANOWSKY: Okay, that is a good point. We
can pick that up right noww.
We think that the studies that we perform on
reliability of component systems, initiating events and
common cause failure capture the human error input to the
availability of those functions or the likelihood of those
initiators because that is just a causal factor and what we
end up doing is collecting the data and performing analysis
that allows us to organize that information in terms of its
impact on systems, so it doesn't show up as a human
performance analysis per se, but we know that it is an
important contributor and it shows up in our various system
and components studies.
CHAIRMAN POWERS: The guys that are doing --
looking and trying to model human performance need a
database on latent errors as much as they need one on active
errors, don't they?
MR. BARANOWSKY: Yes, and I would say we are not
producing that database and that is probably being done by
the other branch, but if they want to have a perspective on
the risk significance of those errors and how they fit in to
impact on safety functions, they can go and look at any of
these results, and that is what I mean by a cross,
horizontal utilization of this particular information.
DR. APOSTOLAKIS: So you are really proceeding
forward --
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: -- given that there is an error,
what happens next.
MR. BARANOWSKY: Right.
DR. APOSTOLAKIS: And the other branch will
investigate the causes of the error.
MR. BARANOWSKY: Right.
DR. APOSTOLAKIS: Or the latent part.
MR. BARANOWSKY: Right. If you want to make
corrections to the root causes, then that is the level that
you have to work on, and what we try to do is provide the
risk perspective as to what is important.
So there's really two aspects of it. Once you
know what is important, then you can spend your resources
making the fix. I would not want to go the other way
around, which is the traditional intuitive way.
DR. SEALE: Are you going to tell us what you are
going to do or what you are doing to validate or verify the
breadth of applicability of your SPAR models?
MR. BARANOWSKY: I will talk a little bit about
it. I wasn't going to cover it in too much detail because
it is just one fairly modest piece part here, but I can talk
a little bit about it.
DR. SEALE: But it is kind of crucial.
MR. BARANOWSKY: Yes. We have some activities
ongoing. I will go over that.
DR. SEALE: Okay.
MR. BARANOWSKY: It's a little later on.
We do have the fundamental mission of performing
this analysis and when we do it, especially our intention
has been over about the last year to make sure that our work
supports the four safety goals of maintaining safety,
improving regulatory effectiveness and efficiency, reducing
unnecessary burden, and improving public confidence.
Now originally I looked at, oh, gee, let me see if
I can pull out specific sub-bullets on each one of these
things, but what I found was that most of the activities
that we do support these things across the board.
As an example, when we find what is important and
insights on incidence or in special studies, that
information could go towards maintaining safety by
providing, say, an information notice that would go out to
licensees on the insights. It could affect regulatory
efficiency by providing insights on how to focus either a
risk informed inspection or determining if a generic issue
that has been or is being implemented is showing
improvements that were forecast when the issue was claimed
to be resolved, for instance, and we have done those kinds
of analyses on station blackout or ATWS and things like
that.
Reducing unnecessary burden -- again, if you
focus, as I said earlier, on the important factors before
you go into the root causes, that is sort of the optimum way
of determining how to expend your resources on things.
Lastly, I think, improving public confidence -- we
do provide a relatively independent cut, what we think the
operating experience is showing. We also take a look at how
the operating experience supports or has differences with
respect to licensee PRAs, and we have several examples in
the studies that we have done on systems, initiating events,
and also on the Accident Sequence Precursor Program.
CHAIRMAN POWERS: We have an industry that is
producing a variety of analytic tools to assist them during
periods of low power operation and shutdown, particularly
shutdown, configuration analysis and what-not.
We have a large number of events that take place
during those periods of shutdown.
Do you do comparisons between those models and
these events?
MR. BARANOWSKY: There aren't too many shutdown
models --
CHAIRMAN POWERS: Well, industry seems to have a
proliferation of them.
MR. BARANOWSKY: Okay. Well, I am not too
familiar with them --
DR. SEALE: Maybe that is the reason he asked the
question.
CHAIRMAN POWERS: Maybe.
MR. BARANOWSKY: If they have a proliferation of
shutdown models, I am not familiar with them.
CHAIRMAN POWERS: They've got EOS and they've got,
what is it? -- ORAM.
MR. BARANOWSKY: Oh, okay.
CHAIRMAN POWERS: And they have got --
DR. APOSTOLAKIS: Sentinel.
MR. BARANOWSKY: Okay, I'm sorry --
CHAIRMAN POWERS: San Onofre --
MR. BARANOWSKY: -- these are the risk management
models. I am thinking of something different like a
shutdown PRA.
CHAIRMAN POWERS: Well, Seabrook claims to have a
shutdown PRA. South Texas, SONGS.
MR. BARANOWSKY: I am familiar with the software
packages that you mentioned and that they are using those
for risk management type decisions.
DR. SEALE: And apparently very effectively, and
it would be nice to know are there special elements in those
packages that contribute to that effectiveness.
CHAIRMAN POWERS: Well, I wonder how effective
they are because I seem to see an awful lot of incidents
occurring during low power and shutdown operations.
MR. BARANOWSKY: That is an interesting point.
That's one that we haven't looked at that I know of.
MR. BARTON: I think what we are seeing is the
human element of it.
DR. SEALE: Yes.
MR. BARTON: You look at configuration and the
defense-in-depth and the risk analysis. That seems to all
be in place, but then somebody goes and screws it up, and
that is what we are seeing, I think, in the shutdown.
DR. BONACA: I think what we are seeing is also
the acceleration of the shutdown for refueling activities.
That is really where the challenge comes from the human
factor in many ways, and that challenges any ability of
predicting.
MR. BARANOWSKY: We do have a couple of things
that relate to that area.
One is that we still are doing Accident Sequence
Precursor Analysis including shutdown events. The Wolf
Creek blowdown event was done under the Accident Sequence
Precursor with insights from the shutdown there.
There was a similar event that occurred recently
at Waterford which we are analyzing. In addition, we have
been pushing in the EPIX database to get unavailability
information on key components and stuff at shutdown as part
of the EPIX database.
So we're putting that kind of stuff in place, and
we recently did an analysis of the kinds of events that
involve loss of offsite power, loss of heat removal, loss of
level control in events for NRR for their uses in their
shutdown significance determination process model.
So we are involved at that level of trying to
gather the information, put information available for people
to do that, but our Branch isn't doing the development of
shutdown models in that case right now, although we do have
an ongoing task in SPAR model development, which Pat will
talk about later to try to figure out what kind of SPAR
models we need to have for our regulatory uses. So we are
involved in it.
DR. APOSTOLAKIS: How do you do the accident
sequence precursor analysis for a shutdown event if you
don't have a model?
MR. BARANOWSKY: We develop models on the basis of
what the particular event is on each case that comes up, and
we use information that -- for example, there are shutdown
models that were put together for the shutdown rulemaking
that was done, and we used that and general PRA practice to
develop the strategies to deal with those things.
We documented those in the Wolf Creek analysis,
and there was one documented in the Vogel analysis when they
had the offsite power mid-loop event, so we do it on a
somewhat ad hoc basis, but we still do it.
DR. POWERS: How do you -- you construct these ad
hoc models, and I know you're extremely skilled, but surely
you're not the only people in the world that can produce
error-free models on a demand basis.
What I'm struggling with is, we have so much
trouble with getting risk models that have been around a
long time to be accurate and have great fidelity to the
plant. How do you do it on an ad hoc basis and have any
assurance that the product you get is -- or the predictions
you get out of the model are of useful quality?
MR. BARANOWSKY: The reason that it works for us
is that the models are very limited. We don't have to go
and search for all the possibilities and put them in some
sort of pecking order, which is what you do when you're
developing the full-blown PRA. We already have enough
information that tells us what functions and systems have
been impacted.
And then we ask ourselves, what are the ways that
one can find success paths beyond that?
It's a much simpler problem. It's an order of
magnitude simpler, to be honest with you.
DR. SEALE: But aren't you flying blind, in a way?
The utility is using some sort of management program, ORAM
or something like that --
MR. BARANOWSKY: Right.
DR. SEALE: -- when it does its planning. It has
a Wolf Creek or a Waterford or whatever, and they used
something like that, I assume, in leading up to that and
somehow there was a failure.
Somehow you didn't catch that particular problem
and they got themselves into the corner where that happened.
It strikes me that that's a whole ensemble of questions that
ought to be followed pretty carefully, if you really want to
find out whether or not these management models are being
useful.
MR. BARANOWSKY: I think we're not really making
the assessment of whether the management models are useful.
That's a point that is probably worth us thinking about,
because when we look at the full power PRAs, we say to
ourselves, are they capturing what they're seeing in the
operating experience, or not?
In many cases, we find that at least on the
failure mode level, things that are not being captured, and
sometimes at a higher functional level.
When it comes to the shutdown models, we have less
access to the specific types of models that they are using.
ORAM and RISKMAN and all that stuff, those are tools. When
I say model, I mean the model for Waterford that has all the
logic in it. We don't have their shutdown model that
they're using, if they are processing it with RISKMAN or
whatever.
So it's a little bit more difficult for us to make
the comparison of the shutdown analysis that we do with the
way that they did their analysis.
Probably the only way that that could be done
right now is if an augmented inspection team went out and we
asked them to look at the model and compare it to what we
found in our own risk analysis.
It's an interesting thought. I just hadn't -- I
don't think we thought about that before.
DR. APOSTOLAKIS: As a point, I don't think that
the PRA would have included in it, what happened at Wolf
Creek. It's something that normally we don't investigate,
and this Committee, in a letter in the past has asked the
ATHENA people to think about how normal operations can lead
to initiating events.
DR. SEALE: Well, yes.
DR. APOSTOLAKIS: This particular event, I don't
think would --
DR. SEALE: Well, the Committee has recognized the
fact that the big problem with shutdown operations is that
they are so diverse that it's impossible, practically, to
have a stylized system like a PRA that would cover
everything.
And yet there's a regulatory responsibility that
exceeds the scope of the models that are being used, and I
think this is a legitimate set of questions that ought to be
asked.
DR. BONACA: One other thing, at least for some
examples I have seen of some events that took place, was a
typical event was, they predicted what was supposed to
happen, and then changes were made to the schedule just at
the last minute.
There were a lot of changes of those schedules,
and there was even some assessment from some PRA person that
said, well, it looks okay. But there wasn't a full
quantification or an evaluation of new possibilities
introduced by the new schedule, and that's really what came
out.
And so that's why they couldn't predict what
happened, because --
DR. APOSTOLAKIS: Again, it depends on what you
mean by "what happened."
MR. BARTON: You have an event, is what he's
saying.
DR. BONACA: You have an event in the original
evaluation with the timing and the activities that were
planned. It couldn't have happened.
But then because there were changes to the
schedules and to the activities and they were put in
different orders --
DR. APOSTOLAKIS: I think that the way PRA is used
in managing the shutdown risk is really to prohibit or to
not allow certain configurations. I think it's a high level
use.
It doesn't go down to details like how this was
initiated. And I don't think the state of the art allows
you to figure out some of these, to predict some of these
things -- some of these, but some others are there.
It's really a combination of defense-in-depth
ideas, and PRA insights. Basically what they are saying is
that if I'm in this configuration, do I have alternate means
of achieving certain functions?
And some of the insights come from the PRA, others
from just experience, defense-in-depth and so on. I don't
think there is any detailed analysis.
But even that is very, very useful. There is no
question about it.
MR. BARANOWSKY: I may be jumping the gun a little
bit here, but since we're on this, I might as well get to
it. You know, we are finding that 15 or 20 percent of the
accident sequence precursors don't look like what we see in
the PRAs.
But that the implied core damage frequency is
about what we would expect.
DR. APOSTOLAKIS: I mean, you have to be careful
when you say that.
MR. BARANOWSKY: I am careful.
DR. APOSTOLAKIS: Parts of it are not in the PRA.
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: Typically what I think is not in
the PRA is the detailed manner in which something evolved,
like take TMI, for example. I mean, ultimately it was a
small loca, right? But the details of how that happened,
the valve getting stuck open and so on, was not in the PRA.
But at some point, you do get into the PRA. Isn't
that true?
MR. BARANOWSKY: Sure. But the point is this; that
you can't make detailed procedural corrections on some of
these things that you can't forecast very well.
MR. BARTON: Right, true.
MR. BARANOWSKY: That means you're going to have
some residual level of risk and error, and the question
becomes, is that an acceptable thing? I think we have
evidence that will probably add a reasonable residual level
of risk.
DR. APOSTOLAKIS: Yes.
DR. BONACA: What I meant to say before is that if
you look at a shutdown, typically the issue you are dealing
with is the removal and restoration of certain systems from
service.
The order in which you do that is a fundamental
issue, because it allows us to assess, in fact, what
equipment you have available, and what equipment you have to
restore first in order to cope with certain conditions.
Now, if you have pressures on the outage that will
force this order to be continuously changed, and we seek
this more and more with the faster shutdowns taking place,
then you are challenging the ability or predicting because
you are just simply -- then there are these screw-ups, as we
call them.
But really they're not screw-ups; they're the
consequence of not allowing people the proper process, and
it becomes very hard to make those predictions.
MR. BARANOWSKY: Okay, the next chart I have is --
DR. SHACK: You can come back tomorrow if you
finish this one.
MR. BARANOWSKY: I'm going to get through on time.
This is some of the uses that these programmed
elements -- some of the things that these programmed
elements are used for. I took the programmed elements and
put them on the left-hand side.
Originally, we were going to try to take each one
of these uses on the right side and say, well, which of
these program elements are used there?
And then we realized, they're pretty much all
used, when we started going through it, so I had a redundant
chart put together.
And one way or another, all of these program
elements on the left side of this chart -- data sources,
reliability studies, common cause failure, ASP, risk-based
performance indicators -- fit into a number of these
applications that are listed on the right side.
Risk-informed inspections, that's an area that
we're working pretty hard right now with NRR to get common
cause failure, system and initiating events insights into
what they're inspecting when they do the risk-informed
inspections.
The operational events: NRR has, for instance, a
daily cut at what's important, and so does the operations
center, and we work both with them, and, in addition,
provided tools for them to perform those analyses.
They review various licensee applications. Many
times, they will go to the system studies or initiating
events, and see what it says about that plant versus what
the licensee's claiming on that thing, and really so on and
so on as I go down here.
It's really pretty much the same; they're looking
at either the methods or the insights that are derived from
each of these areas for application to analysis or for
judging whether an application by a licensee has covered as
best we understand today, the insights from the operating
experience. And so this is sort of the list that we were
able to come up.
DR. BONACA: Just one note, during the
presentation in December, you showed us a SMUG group.
MR. BARANOWSKY: Yes. I'm going to cover that.
DR. BONACA: I think that would be interesting to
the Committee to have an actual owners group there that is
driving the --
MR. BARANOWSKY: I actually have these kinds of
groups on a lot of the activities that we undertake when
we're trying to produce a product that has usage in NRR and
the Regions.
We get someone from NRR and usually a
representative for two or more of the Regions to get on some
sort of a users group. And the philosophy is that they have
to define what they need before we can produce it.
It's like ordering a car; you've got to tell me a
little bit about it first.
Okay, so the first level of risk-based analysis of
operating experience elements that we have is the
operational data. And I have three of them highlighted here
because they're the primary three that we use:
The sequence coding of search system captures LER
information. There are over 47,000 LERs coded in there.
And it's a pretty significant source of information for us,
NRR, our contractors, and it's fairly trustworthy in terms
of the quality.
It's been maintained and coded consistently, and
licensees report information in a fairly consistent manner.
But as you know, it's more at the system level or higher
level of events and it doesn't capture component and
train-like information.
So, the reporting system that used to capture that
was called the NPRDS, the Nuclear Plant Reliability Data
System, and that is now defunct. And replacing it is the
Equipment Performance and Information Exchange System that
INPO is developing.
It's been under development for a few years. It's
actually operation now, but I wouldn't say it's at a high
enough quality level that we could go in and extract the
data and use it primarily because of our concern about the
completeness of the data, and maybe some errors in the way
it's been coded in there, but mostly the completeness.
MR. SIEBER: Did the NPRDS old data go into EPIX?
MR. BARANOWSKY: No, the old data has been
archived and can be extracted using software that's
available, but this is quite a different system, and it
would cost a horrendous amount of money to backfit it.
MR. SIEBER: Okay.
DR. POWERS: If I wanted to know something about
the frequency of fires at a particular site or industrywide,
which of the datasets do I go to to interrogate?
MR. BARANOWSKY: Okay, we have some special
studies. I'm not sure how that shows up on here, but we did
-- have done one on fire, and we're probably going to update
that.
There is also some proprietary fire data at EPRI,
I believe, which sometimes we negotiate to get them to let
us use, which includes information of lower significance
incidents at plants than are normally reported through LERs.
But through LERs, we can get all the fires that
meet the reporting requirements, which I think are the ones
that are greater than ten minutes in duration where the
affect the safety function in some way.
And those we have available and update -- I think
we do it in our initiating event report, right?
MR. MAYS: Yes.
MR. BARANOWSKY: Yes.
DR. POWERS: The people that do fire risk analysis
are put in the position frequently of having to extrapolate
a database to get a fire big enough to pose some threat to
the plant.
Is the database that one derives from the LERs,
suitable for that extrapolation, since it reports only fires
that meet a reporting criterion, missing some kinds of
fires? So I'm wondering if that affects an extrapolation.
MR. BARANOWSKY: You can get the number of large
fires, but as you said, there aren't that many, and certain
ones that affect numerous or even more than one train of
safety systems are rare or probably nonexistent.
MR. BARTON: Really rare, yes.
MR. SIEBER: Yes.
MR. BARANOWSKY: I guess that's a good insight
that we're getting, and that is that some of the Appendix R
protective features seem to have worked in reducing both the
frequency and the consequence of fires, at least that's the
result of the study that we completed a couple of years ago
showed.
I don't know that there has been any indication
that it's changed since then, although there has been
interest in folks in NRR for us to update that work, people
that are working on new fire protection rules and so forth.
DR. POWERS: It seems to me that we're getting a
mixed message here. When I look at some of the preliminary
information that has been released on the IPEEEs, I see
fairly -- what strikes me as surprisingly high core damage
frequencies, given that I have Appendix R and all this
restriction, in fact, despair of ever seeing a fire big
enough to affect more than one train.
But it just doesn't seem -- the two results just
don't seem to square with each other.
MR. BARANOWSKY: Yes. We've talked about trying
to take the fire data and comparing it with the IPEEEs.
I think when we first started doing this, we
didn't have all the IPEEEs, for one thing.
MR. MAYS: Plus, the bigger thing we found was
that there weren't so many differences between what we were
reviewing in the fire frequencies; the big differences are
in the assumptions about the ability to detect and suppress
before you get to a big enough fire to have the adverse
consequences.
So we don't have a lot of data on detection and
suppression capabilities, so our ability to compare
operating experience to what's in those PRAs is very limited
by that.
And I think that's where the big gap is, quite
frankly. If you look at a fire PRA, it compares the
frequency of the fire, the probability of non-detection and
suppression, and the probability that the remaining system
is not affected would work. It's that middle block where
there is the limit on our operating experience capability to
review.
DR. APOSTOLAKIS: There is one more, although I
agree with you that that's a major one. But also the
probability that the fire will become large enough, that's
something that --
MR. MAYS: Yes, the loading in the area is the
deterministic part of that.
DR. APOSTOLAKIS: Yes.
MR. MAYS: The thing we've seen is that at the
larger scope level, the bigger picture, since other than the
Brown's Ferry fire, we haven't had a fire that both causes a
trip and takes out more than one train of anything. We
haven't seen that.
We've seen a couple of fires since then that would
cause a trip and take out one train, but not two.
So at the high level, from a performance
standpoint, we're not seeing degraded performance at that
level.
What we're seeing in the IPEEEs, I think, is cases
of particular plant configurations that are more susceptible
than others.
For example, the IPEEE on Quad Cities had a major
fire area where feed pumps, which have large oil reservoirs,
if a fire were to start in that area, there was also cabling
in that area that would affect offsite power, that would
affect DC power, that would affect AC power and would affect
HPSI and RCSI.
Well, that's kind of a plant-specific
configuration thing for which operating experience data is
not likely to be able to detect, and that's the reason why
you need to go do a fire vulnerability study in the first
place.
DR. POWERS: I guess my point that I'm making in
an elliptic fashion is that I think this is a part of basic
data, more boxes that need to show up at this level here,
and not only the database that you mention on detection and
suppression. I think there's a database that's needed on
fire effects.
And I think we've got extremely conservative
approaches to that which say that essentially a fire in a
fire area takes out anything that you might want in the area
in the worst possible way.
MR. MAYS: That's the assumption.
DR. POWERS: We just don't have a lot of data to
tell us about that sort of thing, whereas I see a
proliferation of data on fire frequencies. There is an
insurance industry one; there's one sitting up in
International, and I don't see people setting up databases
that say things like what a fire affects.
I see people struggling with what you've talked
about, suppression and detection, because you don't want to
start the clock on those things.
MR. MAYS: It's the denominator problem.
DR. APOSTOLAKIS: I really don't know what that
database would be.
MR. BARANOWSKY: Well, I'm not sure that we're the
right people to put the database together. I think that one
of the points I would like to make is, remember, when we
talk about EPIX, we're not putting the database together.
Actually, the main tool that we have is the next
one that I was going to talk about, which is the Reliability
and Availability Data System. We pull information out of
these databases. I mean, we're the primary contact, maybe,
with INPO for access to EPIX, but they're the ones that are
designing it and filling it.
We're just saying we need these pieces and parts
of data, and we pull that out and put it into our
Reliability and Availability analysis system.
DR. BONACA: But I had a question on that.
Yesterday when you showed us the RBPI process, you showed us
in the chart, a main new element.
MR. BARANOWSKY: Right.
DR. BONACA: And the element ran right though
EPIX.
MR. BARANOWSKY: Correct.
DR. BONACA: In fact, I had a question on that
because you're telling us that by next August or so you'll
have already some deliverable, but now you're telling us
that EPIX is not usable yet.
MR. BARANOWSKY: Correct. That is an issue.
There are a couple of aspects of EPIX that are probably
worth noting:
One is the business that it's not fully supported
at this point by all the utilities. The second one is that
it has some limitations in it that require us to do
extrapolations and estimations that we think would be better
done if they would provide the information directly to us.
We're not getting all the demands for all the
systems that we need in order to estimate the demand failure
rates, for instance, and so we have to make some
extrapolations.
And it's the same thing for some of the down time
on some of the equipment.
DR. APOSTOLAKIS: Is it because they don't collect
the information or they don't release it.
MR. BARANOWSKY: No. The licensees collect all
this information from what I can tell. They don't have it
in the form that fits in EPIX.
And what INPO is trying to do is put together some
processors that will allow licensees to collect the
information the way they do, but according to the definition
rules that everybody agrees are correct, what's a failure,
what's a demand, and then have it in any form they want and
let the processor pull it altogether into a common form
that's called EPIX.
And if that can happen, that can be done fairly
efficiently.
DR. BONACA: In December, we talked about the need
for having proper definitions of these terms, and also the
importance for the industry to provide the information that
you need for this kind of work.
MR. BARANOWSKY: It's about a half-FTE per plant
to support this kind of data need that we're talking about.
DR. APOSTOLAKIS: Are you providing input to the
INPO people as to what your needs are?
MR. BARANOWSKY: Yes, there are two groups. There
is a working group which we provide technical input to, that
works with folks from the utilities who say they have needs
for certain things, and we identify ours.
And there is an Executive Oversight Group that
Bruce Boger from NRR is the primary member and I'm the
backup, I guess you would say, sort of the technical arm,
who are looking over the Technical Working Group's proposals
to make sure that they make practical sense.
DR. APOSTOLAKIS: Okay.
MR. BARANOWSKY: And that's ongoing over the next
couple of months. We expect to come to some resolution.
The important thing will be whether or not NEI and
INPO can get the utilities to buy into making this a
complete database. We could probably live with it without
it being perfect, but it can't be one of these things where
it's supported 50 percent by one utility, and 20 and 100 by
another. It won't work.
DR. BONACA: That's right.
DR. APOSTOLAKIS: Exactly.
DR. BONACA: But there is a wealth of information
there, potentially.
MR. BARANOWSKY: By the way, even if it's only
partially supported, there's a wealth of information there.
DR. BONACA: Right now, however, the fidelity of
it, so far as --
MR. BARANOWSKY: Well, for doing quantitative
analysis, it's a little difficult if the variation in
reporting of information is very wide. I certainly couldn't
make performance indicators that made any sense.
DR. APOSTOLAKIS: Now, who decides what is a
failure? Is it the licensee?
MR. BARANOWSKY: Yes, but the big thing is
definitions. We have common -- we have people working on
definitions, sometimes page after page, depending on the
type of system and component.
DR. APOSTOLAKIS: That's the most difficult part
of data collection.
MR. BARANOWSKY: I know. People think data
collection is just put it into a spreadsheet, but that's not
it.
DR. APOSTOLAKIS: So are you going to have a
chance in the future to confirm that what they're doing is,
in fact, reasonable?
MR. BARANOWSKY: Yes, that's a good point. There
are two ways that it will be confirmed. One is, INPO goes
out to the plants themselves, and looks for consistency with
the way they're collecting data with regard to the rules.
The second thing is, if these performance
indicators that we were talking about yesterday become
reality and we use that data, then our own V&V activities
will look at the fidelity of the data also.
DR. BONACA: I thought that in December you
committed to write the white paper that, in fact, Dr.
Apostolakis was recommending, where you would identify some
of these definitions, as well as the kind of raw data that
has to be collected to --
MR. BARANOWSKY: Actually, we talked about writing
a paper on reliability and availability, and we have started
doing that and have got a pretty good cut at it.
DR. APOSTOLAKIS: Let me give you an example now
that I remember. Many, many years ago we were collecting
data on fires.
And at one facility there was a cabinet which
switch gears that had had five fires within a few weeks.
And finally the utility did a more serious investigation and
they concluded that there was a common cause that was
causing these fires, so they just replaced the whole thing.
Now, what kind of data do we have here? We have
zero fires, as they claimed, because they replaced it? In
other words, the database should have nothing?
We have five or we have one?
MR. BARANOWSKY: The right thing is to capture the
information in a database accurately, and don't confuse the
analysis of the data with the factual.
DR. APOSTOLAKIS: Let's say that something like
that happens again. Will that information reach you or you
will just see one fire in five weeks?
MR. BARANOWSKY: These are the kinds of things
that a technical group argues about.
DR. APOSTOLAKIS: Okay, because that's an
extremely important point, of course.
MR. BARANOWSKY: I completely agree.
DR. APOSTOLAKIS: And the typical attitude from
the licensees, at least at that time, was that we fixed the
problem so it can't happen again; therefore, it shouldn't be
part of the database, which, of course, in a bigger scale we
saw in the ATWS controversy with the German failure, the
Kahl reactor. Was there one failure to scram or not?
MR. BARANOWSKY: But if the data was collected in
a factual manner, I wouldn't want to conclude that the data
was wrong, as much as maybe the analysis or the inference
from the analysis might be questionable.
DR. APOSTOLAKIS: But you really have to go into
the rationale sometimes.
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: Just the numbers don't do it.
MR. BARANOWSKY: That's why these people need over
and over.
Okay, let me just mention one more thing about
RADS. I think that's going to be a fairly interesting
analysis system. Just by itself, it's going to provide some
interesting component, train, and system reliability results
of both generic and plant-specific nature.
The analytics are pretty much done on that. What
we're doing now is testing it, using what we know is
slightly faulted data, but at least we're seeing if all the
routines work on it.
DR. APOSTOLAKIS: But you have seen a lot of PRAs,
you and Steve, done by different people and so on.
Overall, based on your vast experience in
analyzing data, could you say that the distributions for
failure rates that people are using in their PRAs are
reasonable, consistent with operating experience?
MR. BARANOWSKY: In fact, that's sort of what
we're going to be showing you. We have two viewgraphs here.
DR. APOSTOLAKIS: Okay.
MR. BARANOWSKY: In fact, the next area that I
wanted to talk about was reliability studies, but it's
really this middle band of industrywide analyses and the
first is reliability studies and initiating events, in which
we're trying to use as much as possible, actual demands,
failures, unavailabilities, analyze trends, quantify
uncertainties, compare findings with what's in the PRAs,
which is what you just said, and identify either
plant-specific or industrywide insights to feed back into
the regulatory process.
And compare with regulations like station blackout
and ATWS to see if the analyses indicate that the risks are
as we've stated they were going to be in some of the backfit
analyses that we did. So let's go to that chart on the
Summary of System Reliability Study Results.
These are reliability systems that we have
performed reliability and unavailability analyses on, and
what this chart shows of course is the name of the system
and the dates from which we collected the data, the mean
unreliability, which from a terminology point of view it's
probably what we are referring to as unavailability before
but it is like unreliability on demand, if you will.
Whether the unplanned demand trends are going down
or undetectable -- as you can see for most of them the
unplanned demands are going down, and these are unreportable
LER demands, okay?
Failure rates -- whether they are declining,
increasing or we couldn't tell, about half of them seemed to
be declining in failure rate.
Is there a trend in the unreliability? In most
cases, we can't tell. Now one of the reasons we can't tell
is this is not a data rich system that we are working with
on the LERs, even though we spanned five years, so from a
performance indicator point of view the LERS aren't going to
really let us see plant performance changes in a timely
manner, and we wouldn't be able to satisfy the criteria we
talked about yesterday.
DR. BONACA: But wouldn't you have to have, for
example, a common cause failure of a HPSI system to have an
LER?
MR. BARANOWSKY: No.
DR. BONACA: If you have an individual train
failure, it's not being reported.
MR. BARANOWSKY: No, but you probably get a
reactor trip or --
DR. BONACA: I see.
MR. BARANOWSKY: -- or a couple of failures
reported, maybe one train failed and one had a degradation.
How for HPSI, which is the BWR high pressure coolant
injection system, it is a single train system so whenever it
actuates or fails it is reported.
MR. BARTON: Right.
DR. BONACA: All right.
MR. BARANOWSKY: But for auxiliary feedwater, that
is another story. We have to go to places where they had
initiation of auxiliary feedwater. Luckily we had quite a
few of those, or maybe not luckily but --
[Laughter.]
MR. BARANOWSKY: -- in the data we had quite a few
and we could get a pretty good picture on auxiliary
feedwater systems.
Now in the interest of time I am not going to run
through --
DR. APOSTOLAKIS: Let me understand this.
Consistency with PRAs --
MR. BARANOWSKY: I'm sorry.
DR. APOSTOLAKIS: -- let's take the HPSI. The PRA
is three times lower than operating experience.
MR. BARANOWSKY: Right.
DR. APOSTOLAKIS: Which PRAs are these?
MR. BARANOWSKY: Several of them.
DR. APOSTOLAKIS: Really?
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: And if they report a
distribution, what do you mean "lower" -- the whole
distribution is --
MR. BARANOWSKY: No, we looked at whether or not
our mean was outside of their 90 percent bounds or whether
their mean was outside our 90 percent bounds. We had pretty
wide bounds, by the way.
DR. APOSTOLAKIS: You are also saying that the
failure rate is going down --
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: -- with the operating
experience. Is it possible that the PRA guys had tremendous
foresight and eventually it will stabilize three times lower
than the current operating experience?
MR. BARTON: I doubt it.
MR. MAYS: I think what we found in that case,
George, was something that we do on all these operating
event studies that was a critical thing. We looked at the
unplanned demands, which were more like the real demands for
these things to work under accident conditions, and what we
found was that in some cases the test demands that were
being done were showing a different failure probability than
the unplanned demands were, and what the people at an
individual plant were doing was using their test demands to
figure out their probabilities because they didn't have
access to all of the other information from all the other
plants.
So we have seen in some cases where we couldn't
pool the test demands and the unplanned demands because they
belonged to a statistically different population and that
was probably the basis for why they were using the numbers
that they were using and were coming up with lower failure
probabilities in their PRA.
DR. APOSTOLAKIS: Because I find that a bit
surprising. The PRAs I am familiar with, the distributions
were based on plant-specific data --
MR. MAYS: But I mean it's like the nature of the
test demands were not producing the same kind of results as
the nature of the unplanned events.
DR. APOSTOLAKIS: Which brings us back to the
earlier point --
MR. BARANOWSKY: That was true on diesel
generators --
DR. APOSTOLAKIS: -- what is a demand and what is
a failure are the key issues here.
MR. BARANOWSKY: Right. The definitions are not
the same so what happens is a licensee comes in and says
this tech spec should be approved because I have got data
that shows it is, and the NRC says well, I don't agree with
you -- so what we are trying to do is bring this all
together, so that the facts aren't argued about anymore.
DR. APOSTOLAKIS: I wonder whether a statement PRA
is three times lower than operating experience is really
valid because there may be cases when this is not valid at
all.
I mean right now there is a difference. I think
that is the accurate statement between your views and their
views.
MR. BARANOWSKY: Yes, I think that's true. That
is a fair point.
DR. APOSTOLAKIS: Because, you know, again there
was Zion and Indian Point that I am very familiar with.
They spent tremendous amounts of time and dabates and all
that as to what is a failure and what is a demand and those
are reflected in the distributions, so that would probably
be unfair to those guys to say that.
MR. BARANOWSKY: To some extent it might be, but
to be honest with you, we've had some phone calls from
utilities that we have talked to and they usually come
around to our way of thinking. Moreover, this stuff has
gone to the owners groups and we take the owners groups'
comments and we factor them in. We don't poo-poo them, and
now they are going and CE and Westinghouse in particular are
trying to standardize amongst their groups, and they are
using these reports as a baseline.
DR. BONACA: And some of it will in fact have to
do with what they call what, I mean if they count in a
different way than you count?
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: Yes.
DR. BONACA: It is going to give you different
numbers, and that is again one of the fundamental issues
here of people, what kind of counting they do.
MR. BARANOWSKY: Well, if we can get more data
from EPIX I think this problem will go away for sure.
DR. APOSTOLAKIS: Now when you say failure rate
trend is down, and yet on the left you say that the mean
unreliability is .07, was that calculated using methods that
assume a constant unreliability?
MR. BARANOWSKY: I think so.
DR. APOSTOLAKIS: So --
MR. MAYS: But we went back and tested --
DR. APOSTOLAKIS: What?
MR. MAYS: We went back and tested over time on a
year by year basis based on the data to see whether we were
seeing a change in the unreliability associated with that.
When we said the failure rate trend here was going down, we
listed in that column all the failures that were reported
whether or not those were the failures that were grouped
together with the demand, so there's a little bit of a
difference there.
DR. APOSTOLAKIS: No, but my point is if you know
that the failure rate is going down, maybe in your
statistical calculations for the numbers that should be part
of the calculations.
MR. MAYS: Yes, we would go back and check to see
whether that was a factor in the calculations and do that.
We did that as part of the analysis.
MR. SIEBER: Has anybody taken this reliability
dataset and put it into something like a SPAR model to
see --
MR. MAYS: Yes.
MR. SIEBER: -- see what the change in risk would
have been? What does the change in risk look like for
various reactor types?
MR. MAYS: Well, we haven't gone back and compared
the various reactors at that level.
We have used this information as input into the
SPAR models --
MR. SIEBER: Right.
MR. MAYS: -- and when we do things with the SPAR
models such as accident sequence precursor analysis, those
all go to the licensees for their comparison with their
PRAs. We get information back from them about how well our
SPAR models match up with their PRAs and where the
differences are, so we found that the SPAR models have been
pretty consistent with the plant PRAs but maybe for
different reasons.
Maybe we have higher failure probabilities in some
systems but they have higher initiating events, so some of
it is, you know, they may agree with the bottom line but
agree for different reasons.
MR. SIEBER: Yes, it comes out in the wash.
MR. BARANOWSKY: Yes, but the important thing for
us is to also have some insights that have to do with modes
and causes so we are trying to be as careful as we can with
the data available about whether or not we are getting phony
insights or real ones.
MR. SIEBER: This phenomenon is not introducing a
systematic bias into the system of reported risk numbers,
CDF type numbers, that the industry is using, right? -- just
because of the data?
MR. MAYS: We haven't done that level of analysis
of all the PRAs. First off, these comparisons here were
made against the IPEs. Subsequently there have been numbers
of changes to the IPEs and to the way plants operate, since
8820 was put out.
MR. SIEBER: Right.
MR. MAYS: So this was just our first cut to say
do we have a huge difference or a little difference, and
what is the nature of it, so that when we deal with plants
on an individual basis we will be able to focus on where the
potential differences are.
MR. SIEBER: I asked the question because you
could have -- the Commission has a set of safety goals or
safety goal policy. Maybe they would come up with a risk
goal policy. The question is how reliable is the data in
the models, both from the NRC standpoint and from the
licensees' standpoint to be able to stand up against a risk
goal policy statement.
MR. BARANOWSKY: I think what we have seen here is
that the PRAs don't have substantial differences from our
own independent analysis looking at it with some different
tools. A factor of three on this system, higher. I can go
down here to diesel generator failure to run, which is
important in the blackout sequences, and the utilities are
using conservative failure to run rates.
We have pretty good statistical information that
says they are using very high failure to run rates, so if
they have some that are higher, some that are lower, but
generally with one or two exceptions on a system basis they
are all pretty much in the ballpark.
I am not sure that the insights are exactly the
same. I know on auxiliary feedwater systems we didn't think
they were modeling some of the suction path potential
failure modes that could cause AFW to become unavailable.
MR. MAYS: We saw a similar thing on HPI. When
you get very redundant trains, the things that are going to
dominate the unreliability are not train level faults. They
are going to be things that go back to where the trains
connect like the suction sources.
We did see, for example, in the high pressure core
spray system the PRA numbers and our numbers matched up
pretty well, but their numbers were -- excuse me, in the
isolation condenser -- their numbers were based on failure
of the return valve to open, and our experience was -- the
causes of failure was inappropriate isolation of the suction
line, so while we got about the same number, we got
completely different causes.
DR. BONACA: Okay. We need to move on. We have a
little bit less than 20 minutes.
MR. BARANOWSKY: Okay, let me move to -- let's
just mention quickly the initiating events, I think. Do you
have that one?
MR. MAYS: I've got it.
MR. BARANOWSKY: So we did do a fairly extensive
updating of initiating events that have been pretty much
used by everyone in the PRAs and we found that, as you
wouldn't be surprised, that the initiating event frequencies
are declining pretty much across the board by about a factor
of four to six lower than the IPEs and there are a number of
them, over half I think, that show statistically significant
declines in their frequencies, and that the risk significant
initiators like the loss of feedwater and I think the small
LOCAs and things like that --
MR. MAYS: Loss of heat sink.
MR. BARANOWSKY: -- loss of heat sink, they were
declining at a faster rate than the average, say, drop in
reactor trips or something like that.
The other thing that we did was take a look at the
data on loss of coolant frequencies for small, medium and
large breaks, and we looked at some worldwide data including
work that was done by SKI, and working with our piping and
fracture mechanics experts both at the labs and at NRC,
concluded that the failure rates for pipe break type LOCAs,
not transient-induced ones, are conservative, and we have
now come up with a lower failure rate, which we think is
still conservative but in light of the uncertainty it is
about as far as we are going to go until I think we have a
more extensive analysis by the piping and fracture mechanics
people on this.
DR. APOSTOLAKIS: But this is different from the
other kind of work that you are doing in the sense that you
also did calculations.
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: I mean you didn't base it on any
experience or --
MR. BARANOWSKY: Well, we did actually. We --
DR. APOSTOLAKIS: What, a large LOCA?
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: The only experience is zero.
MR. BARANOWSKY: But no, what we did is we took
worldwide experience and working, as I said, with the piping
and fracture mechanics folks, the whole power industry, if
you will, we asked what is the applicability of this and how
can we translate that information to use it as sort of a
prior information, if you will, for the nuclear industry.
DR. APOSTOLAKIS: That is not the same as
collecting failure data for components.
MR. BARANOWSKY: It is not the same, you're right,
and if we did collect it like you said, well, then we
wouldn't be able to say anything.
DR. APOSTOLAKIS: Well, it is consistent.
If you say zero failures over, you know, two,
three, four thousand reactor years, it is consistent with
the current estimates, but you are saying the current
estimates are high anyway.
MR. BARANOWSKY: Our job is to analyze operating
experience any way we can. We don't have to use one
technique.
DR. APOSTOLAKIS: Yes, but this is not operating
experience. It is --
MR. BARANOWSKY: Yes, it is.
MR. MAYS: Not quite, George, because what we did
was when we have a situation like aux feedwater we had zero
failures in a thousand demands for aux feedwater. We didn't
stop there and say therefore the probability is some big
number with uncertainty.
We went down in the aux feedwater study and said
we know information about failures in the aux feedwater
system that we can put together logically in a model to
develop the probabilities.
In a similar way, for large LOCAs and for medium
LOCAs, what we did is we went back to the basic of how does
a break occur from the fracture mechanics and physics.
We went back and said, well, the first thing you
do to break a pipe, you have got to get a crack that goes
through a wall, and then the crack has to grow, and those
things have probabilities and things associated with them,
so what have got data on was the through-wall cracks, the
natures, the causes and the frequencies of the through-wall
cracks and then applying the understanding from fracture
mechanics in a conservative way went from the frequency of
through-wall cracks to the frequencies of pipe breaks in the
same way that we went from the frequency of AFW pumps not
working to the AFW system not functioning.
DR. APOSTOLAKIS: So you had --
MR. BARANOWSKY: So we used a similar operating
experience technique.
DR. APOSTOLAKIS: So you had evidence --
MR. BARANOWSKY: Right.
DR. APOSTOLAKIS: -- on the crack level.
MR. BARANOWSKY: Absolutely. They have a great
database.
DR. APOSTOLAKIS: The models themselves evolve
too, don't they? They improve. The models themselves?
MR. BARANOWSKY: The models have improved
significantly from what we knew 10, 15 years ago.
DR. APOSTOLAKIS: So how much -- what is the large
LOCA frequency now?
MR. BARANOWSKY: It is close to --
MR. MAYS: We had two values, one for PWRs and
BWRs and they were in the 10 to the minus 5 range.
DR. APOSTOLAKIS: One order of magnitude.
MR. MAYS: Yes.
DR. APOSTOLAKIS: And the small LOCA?
MR. BARANOWSKY: About 10 to the minus 3 for a
small LOCA.
DR. APOSTOLAKIS: Another order of magnitude.
MR. BARANOWSKY: Now the transients --
MR. MAYS: It's still about at 10 to the minus
2-ish.
The ones where you have transients and stuck-open
PORV or something like that, those are still in about the
nine, ten to the minus 3 I believe was the number that we
came up with for those.
DR. APOSTOLAKIS: So ultimately it will tell us h
ow the core damage frequency trends in time, based on all
this information? You will do something like that?
MR. BARANOWSKY: Well, the only thing we have to
show something like that is really the ASP results.
DR. APOSTOLAKIS: And what are the insights from
there?
MR. BARANOWSKY: Apparently the risk is declining
in time and may be --
DR. APOSTOLAKIS: Well, that would be an extremely
useful insight.
Don't do it as a side --
MR. MAYS: No, that is in the ASP report as well
as in the ASP SECY paper we sent up every year.
The frequency of ASP events in each of the bins,
10 to the minus 5, 4, 3 have been going down in a
statistically significant fashion and continue to decrease.
The rate at which precursors in the 10 to the
minus 3 or greater range occur is about one every three
years or so and so that seems to be kind of the residual
level at which we are seeing those, and if you look at the
core damage index for comparison with PRAs as a rough
approximation of core damage frequency, you are seeing
reasonable agreement between what those are.
DR. APOSTOLAKIS: Is there a single document where
you guys put your insights regarding risk and these trends
and document them a little bit?
MR. BARANOWSKY: No.
DR. APOSTOLAKIS: Wouldn't that be a very useful
thing to have?
MR. BARANOWSKY: Yes. In fact, that is sort of my
last viewgraph that I am going to mention that a little bit.
DR. APOSTOLAKIS: That really would be great.
MR. BARANOWSKY: Why don't we just flip, go to
ASP.
I am going to skip the common cause failure --
DR. APOSTOLAKIS: Yes, we have seen this. We have
used it in our letters.
MR. BARANOWSKY: Actually Steve has already talked
about -- let's go to --
MR. MAYS: Evaluation of trends in ASP?
DR. APOSTOLAKIS: 14?
MR. BARANOWSKY: Yes, 14. There is a slight error
in this viewgraph. This 10 to the minus 3 over here should
not be there.
DR. APOSTOLAKIS: It should not be there.
MR. BARANOWSKY: Right. What we do with the ASP,
every year we put out a report to the Commission as
requested and we identify the insights from the current year
and also the trends.
As Steve said, the trends are going on in all the
bins except the 10 to the minus 3 bin, which means 10 to the
minus 3 -- greater ASP results. But we are pretty sure it
is going to show a statistically significant decline after
we finish the 1999 events because we don't believe there are
any 10 to the minus 3 events in 1999.
We have preliminary results or at least review of
all the events that have occurred. They are not all
finalized but they all seem to be less than 10 to the minus
4.
In the year 2000 we have some 10 to the minus 4s
already so, you know, you can't get too cocky just because
you seem to have a slight decline in that group.
That doesn't mean that it has gone away, and we
have had a couple of interesting events already in the year
2000.
Let's see -- what else do I want to say? Oh, and
the best we can tell, the occurrence rate of these accident
sequence precursors matches up with what we would expect
with the CDFs predicted in the IPEs, so even though some
differences exist in the modes and causes, and I think I
have a couple listed --
DR. APOSTOLAKIS: I am trying to digest this first
comment. What you are saying is, in the first bullet, that
most of these ASPs are going down, except the bad ones.
MR. BARANOWSKY: Right.
DR. APOSTOLAKIS: So the frequency of real
screw-ups has not been changed.
MR. BARANOWSKY: It is a low frequency.
DR. APOSTOLAKIS: Why is that?
MR. BARANOWSKY: Well, that is because they don't
have as much experience.
DR. APOSTOLAKIS: Ah.
MR. BARANOWSKY: If you look at all these
declines, you see a learning exercise going on, and the more
information you can get to people about what is not good,
the more likely they are to make some corrections, so we
very rarely get information on these 10 to the minus 3s, but
we are getting some, and we are starting to feed that back
into the system and I think we are going to see some
dropping off here.
Now people are aware of things like Wolf Creek.
Let's have the next viewgraph -- also LaSalle, where they
had a failure mode of the service water system that I would
have never thought about, which they were pumping these
concrete sealants, just loading it into the system --
MR. BARTON: Through the floor.
MR. BARANOWSKY: Who would have thought of that?
That is just not anywhere, but now it is in our common cause
failure database. That is another reason why we are,
sometimes we had some differences with licensees. Until
recently the common cause failure data base wasn't made
available to the industry. We had industry. We had it but
it wasn't made available, so we could do pretty good common
cause failure analysis.
DR. APOSTOLAKIS: I don't know what kind of
information you are going to give them to reduce that. I
mean the Wolf Creek event is a rare event. It is not
something we see all the time, and what are they going to
learn from that? That when you make changes in your work
plans, make sure that somebody knows? Well, they are
supposed to do that anyway, so how would that affect the
CCDP?
MR. BARANOWSKY: I think it just gives a
heightened focus on these kinds of things. We know all this
stuff. There is nothing that occurs -- we are not supposed
to pump sealant into things without knowing where it is
going. I knew that. You knew that. But so did they. They
did it.
DR. APOSTOLAKIS: But that is what worries me. I
mean okay, higher sensitivity? All right.
MR. MAYS: The point is this, George. If you look
at the PRAs as a predictive model --
DR. APOSTOLAKIS: Which I don't. Which I don't.
MR. MAYS: If you were to look at the PRAs, it
says this is a measure of the baseline risk.
DR. APOSTOLAKIS: Yes, that's good.
MR. MAYS: Okay? Then the Accident Sequence
Precursor Program would say, well, take one step back from
core damage frequency based on that model. How often should
I see things that are getting me close to core damage
frequency?
The ASP program is a way of measuring whether the
expected non-core damage frequency events from your PRA are
occurring at a rate that is comparable to what your PRA
would have predicted, and what we are seeing is that in
large part that is true. There may be some differences in
the particular modes, and the more that information gets fed
back to the licensees the better position they are in to
make the frequency of them happen less.
It won't mean they will go away. It means that we
can get an opportunity to reduce the occurrence rate and
that is what we are seeing.
MR. BARANOWSKY: And that seems to be happening.
DR. APOSTOLAKIS: No, but I am still trying to
understand what it means that the really bad events have an
almost constant rate of occurrence while the others are
declining. There must be some fundamental reason -- maybe
the latent error business. I don't know.
MR. BARANOWSKY: I don't know. There is not
enough of them for us to draw a conclusion yet.
DR. APOSTOLAKIS: Yes. No, I understand that.
MR. BARANOWSKY: Let me briefly mention the work
that we did on D.C. Cook, which of course you all are aware
of we had significant issues with.
We performed a special ASP study on that because
of the heightened public awareness and the Commission's
concern about Cook and analyzed all the licensees in the
NRC's inspection findings and we came up with 141 issues,
which we analyzed individually and integrally, and as a
result so far we have determined one of these issues
produces a conditional core damage probability of greater
than 10 to the minus 6, which is the ASP criteria. That
involves a high energy line break that has the potential for
causing loss of component cooling water trains which could
lead to a reactor coolant pump seal LOCA and you wouldn't
have a high pressure injection available without component
cooling water trains.
There's four others that could meet the criteria
for being a precursor. They are being sent out to the
licensee for review and comment and to NRR to make sure that
the facts that we have are correct on them.
If they are, then these four would also be. They
are also high energy line breaks, but this could affect
either AFW trains, vital AC buses, or emergency diesel
generators, ultimately leading to blackout type sequences,
pressure locking in some motor operated valves required for
recirculation functions, and two seismic issues.
One has to do with the potential for failing
emergency service water due to inadequate anchorages that
were found, and the other one has to do with the failure of
block walls that were put up, I think for fire protection
but I am not sure, which could fall down on equipment
because they weren't seismically designed. They are trying
to determine how bad the damage would be if those block
walls fell down, but any of those could be up in the 10 to
the minus 4 range of the Accident Sequence Precursor
Program.
We should be done with that analysis in about
another month. As I said, we are going to the licensees for
comments now.
DR. APOSTOLAKIS: That is a probability, 10 to the
minus 4.
MR. BARANOWSKY: Those are conditional --
DR. APOSTOLAKIS: CCDPs.
MR. BARANOWSKY: -- CCDPs and since they are over
one year, they are like the CDF. That is in essence what
the CDF was at that plant for the time period these
conditions existed.
DR. APOSTOLAKIS: But it wouldn't really be right
to compare it with a goal of 10 to the minus 4. They are
two different things.
MR. BARANOWSKY: I am not sure about that, to be
honest with you, because I mean if a plant takes away a
system and it doesn't exist, and the core damage frequency
is above the goal with that system not being there, and it
operates like that --
DR. APOSTOLAKIS: For how long?
MR. BARANOWSKY: A year, two years, three years --
for that period of time, I question whether they were --
DR. APOSTOLAKIS: You are right.
MR. BARANOWSKY: Okay. So I think that is a
pretty significant finding.
DR. APOSTOLAKIS: Yes.
MR. BARANOWSKY: SPAR model development. This is
what we talked about.
We are working on several areas to develop
accident sequence precursor models but these are the
standardized plant analysis risk models. They are really
fairly simplified in comparison to what the licensees have
in their PRAs, although they are getting more complete every
time we work on them.
We have established this SPAR Model Users Group
called SMUG which has both NRR and Regional folks on it.
[Laughter.]
MR. BARANOWSKY: And we are trying to detail out
exactly what kind of models and capability are required for
regional analysis, NRR analysis, or just to perform ASP
calculations.
This would Support things like the Significance
Determination Process and so forth. And at this point we
have a pretty good step-up on doing all the Level 1 models
for the plants, I forget how many we have done so far. We
have Rev. 2 SPAR models for every plant. We are working on
improvements to those in Rev. 3, for which I believe we
have --
MR. MAYS: Nineteen.
MR. BARANOWSKY: Nineteen. Nineteen of those
initials models completed, and we are doing them at a rate
of about 20 a year.
DR. POWERS: When you produce a model, one of
these SPAR models for a plant, is there the capability to do
uncertainty analysis on the results?
MR. BARANOWSKY: Yes. It is included.
DR. BONACA: In the December meeting, you, at some
point, mentioned that you would consider doing a systematic
comparison of the SPAR models with the IPEs.
MR. BARANOWSKY: Oh, yeah, that is what you
wanted. We were talking about validation. In fact, there
is a couple of things going on with validation. One is we
do compare with the IPEs and ask ourselves why there is any
differences in our SPAR models.
The second thing is there is a simplified
checklist type of screening tool that has been put together
for the Significance Determination Process that NRR is
trying to validate, and we are tagging along on those
validation get-togethers with the licensees and asking
questions that allow us to clarify some concerns that we had
about SPAR model details.
And then, lastly, we are looking at whether or not
we need to have even more thorough, maybe multi-day plant
visits working with the resident inspectors to get even more
accurate information into the SPAR models. So that last
part is still a little bit up in the air, but we are doing
the first two things. And that's -- I think we will have a
pretty good simplified model. It won't be able to do
everything in a licensee's PRA, but it will be easy to use
and the assumption will be standardized, which is important
for making comparisons.
DR. APOSTOLAKIS: Now, the issue of peer review
has come up in the past of these models. Do you plan to do
anything about it?
MR. BARANOWSKY: Well, I don't know about peer
review in the sort of traditional sense that we would do it
for a PRA.
DR. APOSTOLAKIS: No, no. But some independent
evaluation, some kind of an independent evaluation.
MR. BARANOWSKY: Yeah, I don't know that we had
plans to do that.
DR. APOSTOLAKIS: Do you think that that is
something that you may consider?
MR. BARANOWSKY: It is probably something we
should think about.
DR. APOSTOLAKIS: Okay.
MR. BARANOWSKY: These models are different and
simpler than the PRAs, and I don't want to try and say they
are a PRA, but within their limitations, they should produce
consistent results.
DR. APOSTOLAKIS: No, but it would be nice to know
that, say, a couple of practitioners, say, from the industry
spend some time actually looking at it.
MR. BARANOWSKY: Yeah. It might not be. I think
maybe we would put together some kind of a report describing
this.
DR. APOSTOLAKIS: Some group.
MR. BARANOWSKY: And we are sending them to all
the licensees, too.
MR. MAYS: Right. The licensees, now that they
have known we have these, have been asking for us copies of
them at an increased rate, and they are indicating,
depending, of course, on their PRA sophistication and desire
to do that, we are finding more and more licensees want to
see what we have in our model so they can understand the
difference between ours and theirs.
And when they give us feedback, as we did through
the ASP program, about, well, we have this system or this
capability, or something that you don't have modeled, and we
would go back and verify that, we would change the model.
DR. APOSTOLAKIS: Eventually, your models will be
PRAs, won't they?
MR. BARANOWSKY: Well, they are PRAs.
DR. APOSTOLAKIS: Why not?
MR. BARANOWSKY: They are PRAs.
DR. APOSTOLAKIS: Steve, why not?
MR. MAYS: I am not sure what you mean by the
statement, they are. I mean they are risk assessments. The
question is, at what level of detail and to what
thoroughness and completeness are they relative to what is
the plant's --
DR. APOSTOLAKIS: But I mean you are not making
some of the very drastic assumptions that were being made in
this program 15 years ago.
MR. MAYS: Absolutely not.
DR. APOSTOLAKIS: Like the operator will do this
or that.
MR. MAYS: We have found that these are more
consistent and/or realistic in terms of PRA sequences,
numbers and contributors than what was done before. And
that is one of the goals, is to make it a more realistic
process.
MR. BARANOWSKY: They are primarily standardized,
to be honest with you.
DR. BONACA: That is why how it compares with the
IPE is important, because you may find that one system you
did not model makes a big difference.
DR. APOSTOLAKIS: Yes.
DR. BONACA: If you don't find that, then, you
know, that confirms that your modeling is adequate enough,
even if it is at a high level. So I think that that kind of
comparison is most useful because it speaks about the
structure and the level of details you have to go to.
MR. MAYS: The other thing that it is very useful
for is when we get licensee applications under Reg. Guide
1.174, for example. That is going to be based on some PRA
result. The key thing about these that will be good is we
can compare our results independently with theirs, and
instead of going back and having to review their entire PRA
in its entirety, down to the last level of detail, we can
use our information, which is going to be based on operating
experience and standardized ways of looking at risk
sequences, and say our assessment is different from yours in
this way, and we can go focus on where the differences are,
rather than having to spend, in an efficiency standpoint,
going out and looking at everything that they did.
DR. APOSTOLAKIS: But in that context then, I mean
you told us that you will develop SPAR models for low power
and shutdown models?
MR. MAYS: That is correct.
DR. APOSTOLAKIS: So would you be then --
DR. POWERS: I guess I don't understand that. I
think that when your management discusses this with the
Commission, they say you have all the capability you need.
MR. BARANOWSKY: Well, they are probably thinking
that when we have these models in place.
DR. POWERS: Oh, forward-looking individuals. I
hadn't thought of that possibility.
MR. BARANOWSKY: Our management is
forward-looking.
DR. APOSTOLAKIS: So, Pat, would you then say that
these models could be good enough to given to senior reactor
-- what do we call them?
MR. BARANOWSKY: Absolutely.
DR. SHACK: SRAs.
MR. BARANOWSKY: They are on the SMUG group. They
are on the SMUG group.
DR. APOSTOLAKIS: They are SMUG group.
MR. BARANOWSKY: They are some of the people who
are telling us what capabilities they need.
DR. APOSTOLAKIS: So the agency is in the process
of developing these tools?
DR. BONACA: Oh, yes.
MR. BARANOWSKY: Right, we are. And I think there
is a big difference between, you know, no knowledge and
perfect knowledge, and what we are is in the middle and
moving.
DR. APOSTOLAKIS: Who told us yesterday that
incorrect knowledge is worse than no knowledge.
DR. POWERS: Their sister organization.
MR. BARANOWSKY: No, we are not saying incorrect.
We are saying if you have some knowledge, and you understand
its limitations, that is better than having no knowledge.
DR. SHACK: Which your sister organization said,
too.
MR. BARANOWSKY: Good. Why don't we go to the
last viewgraph because I don't think we need to say any more
about risk-based PIs, which we covered yesterday, and I
wasn't going to.
DR. APOSTOLAKIS: That's fine.
MR. BARANOWSKY: I need to tell you sort of where
we are heading with this stuff. We are going to try and
streamline the things that we do and make more current and
consolidate the work on initiating events, system and
component reliability studies, common cause failure analyses
and so forth, mainly because we went through a learning
exercise in producing this stuff the first time around or
so,, and now we see that there is a way to bring this stuff
together and still get system component and common cause
failure insights out, but probably integrated them a little
bit better. So that will be an efficiency type thing.
The other thing, we want to make ASP more current.
Sometimes now it takes six months to get an ASP result out,
because it needs to be more coordinated with the revised
reactor oversight process, where they are making findings,
and, in particular, the Significance Determination Process.
DR. APOSTOLAKIS: Good.
MR. BARANOWSKY: And I can tell you the reason why
it usually takes a long time to do the ASP results, usually
the ones that we, ourselves, get tagged with doing, there is
a lot of questions about the engineering capability of
equipment or the thermal-hydraulic response of the plants.
The ones that are easy, where the equipment was broken and
fell on the floor, and you just punch a little button on the
SPAR models and make it fail, I can do those in, you know,
30 seconds. But going and figuring out whether a pump that
had a degraded condition would have actually provided enough
flow to satisfy the thermal-hydraulic requirements in a
plant, that sometimes can take months.
So it is going to be difficult to get this to be
too fast if we don't have those kind of capabilities worked
into the system in some way.
Then we want to try and prepare this annual report
which --
DR. APOSTOLAKIS: Which we discussed earlier,
right? This could be the insights and the transient risk.
The report we --
MR. BARANOWSKY: Annual report?
DR. APOSTOLAKIS: Yes.
MR. BARANOWSKY: Yes.
DR. APOSTOLAKIS: Good.
MR. BARANOWSKY: And we would pull it all together
also.
DR. APOSTOLAKIS: Yes.
MR. BARANOWSKY: Instead of having it in four or
five different locations and reports produced throughout the
year. We might still produce individual reports, but we
would have one report. I don't want to say it is reviving
the old AEOD annual report, because it would be a little
different, but it is along that idea. Again, we would like
to try and make that a current kind of thing, not be years
old.
DR. APOSTOLAKIS: When do you think you are going
to have this one?
MR. BARANOWSKY: I think the first cut at it will
come around March of 2001. Well, the reason is we can't
make all this stuff current until then. There is a lot of
work to take these system initiating event studies and bring
them into some currency.
DR. APOSTOLAKIS: When you say we, how many people
are involved in this?
MR. BARANOWSKY: Well, that is the other problem.
DR. POWERS: Well, I think that is really a
management issue.
DR. APOSTOLAKIS: I know, but it is information.
MR. BARANOWSKY: We have like --
DR. POWERS: I am going to give you some
information, that I will take the time from now on out of
your hide.
MR. BARANOWSKY: We have 12 staff and $4 million
in contractors. And we won't be able to do all this stuff
in a timely manner that I am listing here, because budgets
keep on changing. I have had some staff reductions. But we
will do as much as we can.
SPAR model, we identified what we wanted to do
that. We want to implement the databases and continue
developing the risk-based PIs.
You also made some suggestions on looking at
licensee shutdown analyses, risk analyses and comparing
them, and some comparisons with fires. I am putting those
down as --
DR. APOSTOLAKIS: Seismic?
MR. BARANOWSKY: Seismic. All possibilities,
questions whether we have the resources to do these things,
or whether it would be so spread out in time it wouldn't be
worth doing. We would make that decision to.
DR. APOSTOLAKIS: Peer review, think about the
peer review.
MR. BARANOWSKY: All these things are in the
hopper, but I have limited resources. I have the smallest
branch in the Office of Research. Thank you very much.
DR. BONACA: Thank you. Any other questions?
DR. APOSTOLAKIS: I just want to say that I always
enjoy the presentations of those guys, it is always
informative.
DR. BONACA: Well, I think this is most of the
intelligence that comes within the staff. Not because the
rest of the staff is unintelligent, just because it is a lot
of information that comes from operating experience which is
so important.
Okay. With that, thank you, and I will give it
back to the chairman.
DR. POWERS: Thank you. I will echo my
appreciation of the presentation.
DR. SEALE: High information density.
DR. POWERS: I think it, however, has raised more
possibilities for work than the smallest branch in Research
can tolerate.
At that point, I will recess for 12 minutes.
[Recess.]
DR. POWERS: We will come back into session. I
want to begin immediately with seeing if any members have
feedback they would like to offer Mario Bonaca in preparing
a letter on the material we have just heard.
I have provided Mario some comments. My comments
are, I see needs for more and different databases than the
agency has. I see this as yet another indication that the
agency needs to completely redo its PRA implementation plan
in the light of the rapid progress that we are making toward
risk-informed regulation. I think updating the existing
plan is no longer sufficient, that we need to take a broad
and holistic look at the entire plan so that we have a
comprehensive development of the kinds of materials that
these gentlemen, Mr. Mays and Mr. Baranowsky, told us about
today.
I also find it striking that the SPAR users
groups, including the senior reactor analysts, are asking
them to develop their models to include low power and
shutdown assessment capabilities at the same the management
is telling the Commission that they have all the models they
need in this area. I think that is a striking difference in
opinion.
I ask are there other members that have comments
they would like to have included in this -- or considered
for inclusion in the report on this work we have just heard
about?
Dr. Apostolakis, you made mention of points on
peer review.
DR. APOSTOLAKIS: Yes.
DR. POWERS: Anything else that you think needs to
be commented on?
DR. APOSTOLAKIS: I think we should say something
to the effect that this is one of the most useful activities
of the agency.
MR. BARTON: That would be nice.
DR. POWERS: I think we ought to hearken back, I
can remember, since I have been on the committee, Professor
Seale hammering on people that mining the operational
database is going to be the source of information that is
unavailable from other sources. Is that roughly correct,
Bob?
DR. SEALE: Yes.
DR. POWERS: And I think we might just point out
in our letter that this has been a long-time interest in the
committee, of mining the operational database for things to
compare against PRAs and have some validity to the PRAs.
And that might be an excellent lead-in to, I
think, another point that Professor Apostolakis suggested,
that there be some sort of a summary report on this
comparison.
DR. APOSTOLAKIS: Yes. And it is something we
suggested in the past, and I am not sure anything has
happened, is, again, I don't think that the community out
there at large is really aware of the work that these guys
are doing, and taking advantage of it.
Now, I don't know what they can do. I mean they
do go out and present papers and all that.
DR. BONACA: I tried already to have a draft which
is complimentary enough, and I tried to strength that
portion upfront of the importance. Really, this is the
lifeblood of the agency, I mean.
DR. APOSTOLAKIS: Yes.
DR. BONACA: And that is why, you know, I keep
harping on EPIX, because they keep saying we are going to do
these wonderful things, and then if you look at the chapter
from yesterday, there was -- it ran right through EPIX. And
without it, there is not going to be any of these wonderful
things they want to do.
DR. SEALE: I think you want to be very careful
when you say that though.
DR. BONACA: Oh, yes.
DR. SEALE: We want to say it -- you want to point
out that the people who are in the dark are the rest of the
agency. It is not the utilities, the utilities are
following this EPIX data very closely. They know what it is
in there. Is the rest of the agency that doesn't know what
is in there. And I think when we say, you don't know it, it
is an agency problem more than industry problem.
DR. BONACA: No, I agree with that. And one
comment I would like to make, Dana, would be your comment on
a different type of database is well taken. I wonder if
this is the place to make it. You know, if I look at the
thrust of your comment, really, it is more on the PRA
implementation plan needs a rework, and maybe, my suggestion
would be that we put this comment in the letter that we have
next month. I believe we have a presentation on the PRA
implementation plan. Because if we put it, you know,
narrowly in this letter, it undermines to some degree the
other message we are trying to give, that these people are
important, what they do, it is important.
I don't know if you have any thoughts about that,
but I am afraid that putting it here, it will somewhat
undermine the interaction they are having right now with
INPO to strength the quality of EPIX.
DR. POWERS: Of course I am never opposed to the
idea of focus leads to resolution, as opposed to having a
shotgun approach, and, so, I am perfectly willing to defer
to your judgment on that matter.
I think it is -- I am concerned about whether we
are having the strong support information and technology
development that this move toward risk-informed regulation
is going to take. I think that when we look at things like
performance indicators and Significance Determination
Processes, you see a crude nature to them at this juncture.
We have the hopes that they improve with time. And if we
don't have strong support efforts going on to develop
technology and develop better indicators, and develop better
processes, those things may become entrenched and they can't
be changed. So I am concerned about that.
But I offer you my comments simply for
consideration, and if you think it is better to wait till
another time, I think that is fine.
DR. BONACA: I can weave in the need for
consideration of an expanded database without reference to
the PRA implementation plan. I would like to stay away from
it right now as far as that portion. But let me see what I
can do.
DR. POWERS: Well, I defer to your best judgment
on that matter.
Any other comments?
[No response.]
DR. POWERS: Seeing none, I think at this point we
can go off the transcript.
[Whereupon, at 10:18 a.m., the open portion of the
meeting was concluded.]
Page Last Reviewed/Updated Tuesday, July 12, 2016
Page Last Reviewed/Updated Tuesday, July 12, 2016