Forsmark 1 & 2 bwr stability benchmark,nea/nsc/doc(99)9
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NUCLEAR ENERGY AGENCY
NUCLEAR SCIENCE COMMITTEE
FORSMARK 1 & 2 BWR STABILITY BENCHMARK
Time Series Analysis Methods for Oscillations during BWR Operation
Summary Record of the First Meeting
Consejo de Seguridad Nuclear, Madrid
18th and 19th February 1999
Document complet disponible sur OLIS dans son format d’origine
Complete document available on OLIS in its original format
NUCLEAR SCIENCE COMMITTEE
FORSMARK 1 & 2 BWR STABILITY BENCHMARK
Time Series Analysis Methods for Oscillations during BWR Operation
The meeting was opened by the chairman, J.M. Conde Lopez, who welcomed participants to the
meeting on behalf of the Consejo de Seguridad Nuclear, who co-sponsored the benchmark and washosting the workshop. E. Sartori welcomed participants on behalf of the OECD/NEA.
In all, seventeen participants from eight countries and thirteen organisations attended. The
interest in the benchmark and in the meeting was somewhat larger: some interested parties were unable toattend because of other commitments (see Annex 1, for the list of participants)
The agenda was reviewed; the details including presentations are provided as Annex 2. The list
of papers distributed at the meeting is provided as Annex 3.
G. Verdú, co-ordinator of the benchmark study, recalled the objectives of the benchmark
and the meeting: the purpose of this benchmark is the intercomparison of the different time seriesanalysis methods that can be applied to the study of BWR stability, and is a follow-up activity of theRinghals 1 Stability Benchmark organised by the NSC in 1996.
While the Ringhals 1 Stability Benchmark included both time domain and frequency domain
calculation models to predict stability parameters, the new activity is focused in the analysis of time seriesdata by means of noise analysis techniques in the time domain.
The first goal is to determine, if possible, the main stability parameters from the neutronic
signals time series with enough reliability and accuracy. Typically, the main stability parameters areassumed to be the decay ratio (DR) and the frequency of the oscillation. However, there is also thepossibility of considering other parameters that can provide valuable information of the stability of theneutronic time series.
For the purpose of analysing the effects of all these parameters, the participants in this
benchmark were asked to provide a short description of the methodology used for the analysis of the timeseries, to provide information on the codes used with enough detail to identify the sources of
discrepancies. In addition participants were asked to describe their experience with the data and otherinformation to help the analysis of the results globally and to draw conclusions.
The data used in this benchmark were obtained during several stability tests performed at the
Swedish BWR reactors Forsmark 1 and 2, in the period 1989 to 1997. And were released by Pär Lansakerof Forsmarks Kraftgrupp AB.
Test Problems Considered
Two kinds of power oscillations have been observed in BWRs: in-phase (core-wide) oscillations,
where all the core oscillations are in phase, and out-of-phase, where one half of the core oscillates out ofphase of the other part. The oscillations are studied using LPRM and APRM signals. Thus, the oscillationdetection algorithms are important to detect and classify the instabilities of the neutronic power signal.
The database is divided into six cases, the sampling rate of all the time series being 25 Hz,
decimated to 12.5 Hz. No filter was applied to the signals and the DC-component has not been subtracted.
• CASE 1
This case contains the neutron flux signals measured during several tests. The objectiveof the case is to study several signals ranging from stable to quasi-unstable conditions.
The signals are standard measurements with no distortions, and should be fairly easy to evaluate.
Data contains measured APRM (Average Power Range Monitor) signals from stability tests.
The results for this case will be the DRs and oscillation frequencies associated with the APRMsignals taken during 14 different tests.
Each time series has about 4000 points, the range of DR being from 0.4 till 0.8. The objective ofthis case is the comparison among the different methods applied to obtain the stabilityparameters.
The preliminary results provided for the DR and the fundamental frequency for this case areshown in tables 2 and 3. Taken as a reference the mean values, the following conclusions can beobtained
− The UPV-AR methodology is dependent on the model order. AR methodologies based on an
average among different orders or the plateau methodology are more stable.
− The UPV-Dynamics reconstruction method generally overestimates the DR.
− For the methods based on a fit for the impulse response it was found that JAERI’s group
method has a stable behaviour and the method used by TU DELFT gives deviating DRs forsome of the cases.
− The PSU group and the Tsukuba University group use AR methods that generally
− The Reduced-order Method, based on the LAPUR code, provides different results from the
other contributors. This could be due to the lack of an accurate input model for the Forsmarkreactor.
− As the main conclusion for this case we have that case 1 corresponds to a stable
configuration of the reactor. The results for the fundamental frequency are quite uniform,and there is a large dispersion for the DR values.
• CASE 2
This case addresses the importance of the time duration of measured data.
The objective of this case is to study the variability of the DR and the oscillation frequency withthe measurement time duration. There are two long time series to analyse, l1 and l2. Each onehas about 14000 points, and will be divided into blocks of approximately 4000 and 2000 points.
The results for the short time series will be compared with the original long series results.
The preliminary results provided for this case are shown in tables 5 and 6. From these results thefollowing conclusions can be drawn:
− For Signals l1 and l2 the frequency is approximately constant for the different segments.
− For Signal l1 the DR depends on the segment of the signal analysed. The first part of the
signal (s1) corresponds to a more stable configuration than the other segments(s2, s3, s4).
− For Signal 12 the DR remains approximately constant along all the segments.
− Signal 11 presents a slow transient and the results provided for this signal have larger
dispersion than the ones provided for Signal l2, which is practically stationary.
− It is clear that at least for Signal l1 the DR is time dependent.
• CASE 3
APRM data for this case contain more than one natural frequency of the core. The data alsocontain peaks of other frequencies due to the actuation of the pressure controller. One case hastwo frequencies close to each other. Cases with more than one natural frequency make theanalysis much more difficult.
This case contains five measurements contaminated with influences from the plant controlsystems. In this case, the time series have a bad behaviour, and consequently the standardstability parameters are not clear.
The preliminary results provided for this case are shown in tables 7 and 8. From these results thefollowing conclusions can be obtained:
− For this case the UPV group has found some problems to determine the fundamental
− The other contributors give homogenous results for the frequency of the neutronic signals.
− The typical dispersion for the values of the DR appear. For example, the values provided for
the DR in test 3 range from 0.1 to 0.6.
− The signal conditions can play an important role to resolve the stability information.
• CASE 4
This case contains a mixture between a global oscillation mode and a regional (half core)oscillation. The case consists of APRM and LPRM (Local PRM) signals coming fromone test.
The LPRM positions in the core are as follows:
The locations corresponding to the different numbers used to label the tables are the following:
The time series have a good behaviour. In this case, it is interesting to study the interrelationsbetween APRM and LPRM signals.
The preliminary results for this case are shown in tables 9 and 10. From these tables thefollowing conclusions are obtained:
− There is not a large dispersion for the values of the DR in this case because the configuration
of the reactor is more unstable, that is the DR is high ( ≅ 0.8).
− There is a half of the reactor (locations 23 and 9) where the DR is high and the other half
(locations 31 and 11) where the DR is lower. The upper part of the reactor seems to be morestable than the lower part.
− Spectral analysis of the signals indicates that there is a phase shift between the LPRM at
radial locations 23 and 11, and locations 23 and 31, but the out-of-phase oscillation is nottotally developed.
− To make a more accurate regional analysis more information is needed, e.g. more LPRM
signals, the operating conditions for this case and nuclear cross-sections. Nevertheless, forthis case the Siemens group provides regional decay ratio calculations obtained fromdiagonal LPRMs.
• CASE 5
This case is focused on the analysis of two APRM-signals obtained during a small plant transientthat resulted in a bad behaviour of the signals. In this case, it is important to analyse the firstdominant poles of the transfer function obtained from the time series. Note that this is a non-stationary case and the auto-regressive methods have a limited validity.
The preliminary results for this case are shown in tables 11 and 12. For this case the followingconclusions can be obtained:
− For APRM 1 signal considered as a whole, the results are quite uniform, the DR is near 1,
and the results for the frequency are near 0.5 Hz.
− If the signal is divided in two or three records, the first part corresponds to a limit cycle, and
− For the APRM 2 the results of all the contributors are quite similar. The signal can also be
divided in two or three parts, the first part of the signal being more stable than the second.
− We can surmise that when the DR is high the methodology seems to work even for small
− For cases with mild transient, the transient portion of the signal, which must correspond to a
time-varying decay ratio, was shown to have an averaged decay ratio bounded by the steadystate points before and after the transient portion. This gives confidence that some methodsretained importance for monitoring purposes.
• CASE 6
The LPRM positions in the core for case 6 are the following:
The locations corresponding to the different numbers used to label the tables are:
This test case shows local (channel) oscillations.
The data contains APRM and LPRM signals from two tests that were performed closeto each other, both in time and in the operating conditions.
Test 1 (case 6.1) is the same as Case 1.8, and the measurement is taken from Forsmark 1.
The second test (case 6.2) clearly shows local oscillations.
The preliminary results for this case are shown in tables 13, 14, 15 and 16. The followingconclusions can be obtained:
− This is a stable case where the typical dispersion for the values provided for the DR are
observed while the results for the frequency are more accurate.
− The LPRM signal at location 11 has a higher DR than the one corresponding to the APRM
− The APRM signal corresponds to an almost unstable situation (DR>0.9) and the results for
− It is observed that half of the reactor is oscillating and the other half is stable.
− The channels with radial locations 26, 11, 6, 24 are almost unstable. It seems that half of the
reactor is oscillating and the other half is stable.
− There is a kind of local oscillation but there is no phase shift between the LPRMs signals.
Clearly this case is not an out-of-phase oscillation
− Case 6.2 corresponds to a ‘strange’ oscillation where some channels oscillate and other
channels are stable. Dr. Hennig has proposed a possible explanation of this case based on theassumption of unseated channels in the core.
Presentation by Participants
Participants presented their results. The corresponding papers and copies of viewgraphs
containing the relevant details are listed in Annex 3. Table 1, summarises the methods used byparticipants.
Table 1. The methods used in the solutions provided
Method Country Organisation
A general discussion followed. The conclusions for the different cases are summarised in a previousparagraph.
Review of Summary Conclusions
Lessons learned on the performance of different approaches and determination of uncertainties
were debated. The questions raised were summarised by G. Verdú and discussed. The answers providedby participants were summarised by D. Ginestar. The expert views are as follows:
Questions Raised / Answers
1. Which is the best definition of Decay Ratio (DR)?
For Noise Analysis it is the decay ratio associated with the least stable or dominant pole. Thedefinition is clear for a second order system.
2. Which are the best methods for calculating the DR?
Several methods were used in this study: AR method, AR method plus Impulse Response, Auto-correlation, Recursive Autocorrelation methods, ARMA, LAPUR, Power Spectrum Estimation. At theForsmark NPP stability monitors have been used for over 10 years and the uncertainty in the DR
range 0.5 – 0.6 is smaller than 0.1. Obviously experience of the operator in using such a monitor atthe plant is required. In other ranges the uncertainty can be higher. Measurements in a steady statecondition, extracting signals for a given time interval and analysing them, leads to smalluncertainties. The methodology for determining the uncertainty has to be defined and the model ordershould be known (but this is not always certain). What really matters is the DR after manoeuvring andthe amplitude of the oscillation. Often oscillations are not stationary, the ‘decay ratio’ for thesesignals is not well defined but the determination of frequency (Fourier analysis) is quite accurate. Forthe determination of decay ratios the asymptotic part of the transformation function should be used.
This is a suggested pragmatic approach.
3. Is it possible to have reliable methods for determining DR automatically, independently of the
It is possible. This has been demonstrated at Forsmark where the same method is used and compared
in the monitoring and off-line. Also the Siemens experience affirms this answer. No filtering is
required and once experience has been gained it works well. Signal conditioning has to be plant
dependent. The experts tune it to the plant, then it can be run automatically.
4. What is the influence of the time duration in the estimation of DR?
An accurate auto-correlation function is required first based on the AR model. A heuristic type ofalgorithm is normally used. The duration depends on the value of DR (about inversely proportional toit). For power spectral density between 4000 and 10000 points are required).
5. Is it of interest to determine the DR in a transient? Is the calculation reliable?
It is of interest - because the method follows the trend and makes the DR derived acceptable.
6. What happens if the signal contains more than one natural frequency? Which DR is the true
The interesting information for the operator is: oscillations driven by a noise source, disturbances in
the system. Oscillations by themselves do not imply instability if driven by an external source. The
stability characteristics of the reactor need to be known; the amplitudes are easy to extract.
7. Is it possible to determine DR of an out of phase oscillation?
This is possible for DR up to 0.7
± 0.1 and if enough LPRM signals per plane are provided. Becausethere are many ways of doing it wrong and only a few to do it right, it depends on the expertise of theanalyst, or the sophistication of the monitoring algorithm.
8. Can we provide an accurate limit to the stable behaviour of the reactor core?
This depends on the uncertainty. The real margin should be determined on power. Frequency domaincodes can determine it; they are efficient but not sufficient. The ‘decay ratio’ is a measure of linearstability and should therefore not be used as the only indicator of BWR stability
. The Siemens groupdisagrees with this affirmation, and the say that there is no need for non-linear considerationwhatsoever.
The Next Phase
The possibility to add an additional phase was debated. The possibilities would be to;
revisit the solutions in the light of what was presented and discussed at the meeting
repeat some precise cases with more data
It was agreed that the major objective, namely the verification as to what extent different
methods give the same answer was met. The applicability and reliability of the different methods wereinvestigated. Additional data would not be more helpful for the signal analysis. In practice analysts haveonly a small set of data available and not the full picture. The six cases chosen to be studied are relativelydifficult and are really addressing the limits of the methods. Use of a full set of data could be the subjectof a different study involving reactor physics. It has therefore been agreed that new solutions would beaccepted, but those submitted would not be revised.
The schedule for submission of new results, the publication of results, the presentation at
conferences and reporting to CSNI PWG2 was agreed on. This summary will form the basis for the reportto the NEA NSC.
The proposed outline of the final report is provided as Table 2.
Table 2. Proposed Outline of Forsmark 1 & 2 Benchmark Report
ForewordExecutive SummaryContributions & Acknowledgements (Chair, Co-ordination, Participation, Editing)(a) Introduction(b) Objectives(c) Description of Cases(d) Summary Table on Participants and Methods Used(e) Comparison of Results (sorted by method and case)(f) Discussion of Results(g) Conclusions
Annex 1: Full Address of ParticipantsOther Annexes: Special Analyses Made by Participants; Details about Methods UsedReferences____________________________________________________________________
The agreed actions and timetable are provided as Annex 4.
The NEA Secretariat expresses thanks to the Consejo de Seguridad Nuclear for hosting the
workshop, for the hospitality provided, and for the competent expertise made available.
Table 3. Preliminary results for the DR. Case 1.
Table 4. Preliminary results for the fundamental frequency. Case 1.
Table 5. Preliminary results for the DR. Case 2.
Table 6. Preliminary results for the fundamental frequency. Case 2.
Table 7. Preliminary results for the DR. Case 3
Table 8. Preliminary results for the fundamental frequency. Case 3.
Table 9. Preliminary results for the DR. Case 4.
lprm.10 0.703 0.707 0.711 0.757 0.712 0.500 0.670 0.750 0.730 0.749 0.751 0.710 0.756
lprm.11 0.634 0.635 0.650 0.749 0.767 0.880 0.710 0.770 0.760 0.714 0.678 0.670 0.788
lprm.12 0.709 0.709 0.733 0.787 0.517 0.270 0.450 0.580 0.560 0.677 0.677 0.710 0.654
lprm.13 0.767 0.771 0.771 0.835 0.821 0.870 0.770 0.810 0.830 0.737 0.787 0.700 0.833
lprm.14 0.739 0.742 0.740 0.817 0.813 0.880 0.750 0.810 0.800 0.728 0.767 0.700 0.823
lprm.15 0.646 0.657 0.657 0.691 0.788 0.870 0.760 0.800 0.800 0.790 0.740 0.690 0.783
lprm.16 0.675 0.668 0.670 0.699 0.801 0.880 0.800 0.800 0.810 0.796 0.690 0.680 0.771
lprm.17 0.833 0.834 0.836 0.838 0.861 0.900 0.830 0.850 0.860 0.854 0.838 0.810 0.862
lprm.18 0.819 0.817 0.821 0.877 0.843 0.880 0.820 0.850 0.850 0.845 0.829 0.810 0.857
lprm.19 0.813 0.814 0.813 0.886 0.628 0.850 0.450 0.800 0.790 0.785 0.812 0.800 0.787
lprm.20 0.721 0.720 0.701 0.757 0.695 0.840 0.670 0.750 0.740 0.756 0.767 0.700 0.769
lprm.21 0.666 0.672 0.661 0.771 0.766 0.880 0.670 0.770 0.760 0.770 0.738 0.670 0.791
lprm.22 0.583 0.569 0.569 0.702 0.360 0.860 0.380 0.390 0.360 0.422 0.517 0.490 0.447
Table 10. Preliminary results for the fundamental frequency. Case 4.
lprm.10 0.527 0.526 0.520 0.522 0.530 0.360 0.495 0.530 0.530 0.527 0.526 0.526 0.529
lprm.11 0.524 0.523 0.523 0.518 0.521 0.470 0.520 0.520 0.520 0.522 0.514 0.514 0.519
lprm.12 0.541 0.540 0.540 0.542 0.534 0.290 0.495 0.530 0.530 0.531 0.536 0.536 0.497
lprm.13 0.491 0.490 0.490 0.505 0.508 0.460 0.520 0.510 0.510 0.504 0.498 0.498 0.506
lprm.14 0.492 0.493 0.493 0.506 0.508 0.470 0.495 0.510 0.510 0.505 0.501 0.501 0.508
lprm.15 0.503 0.502 0.502 0.497 0.513 0.460 0.495 0.510 0.510 0.513 0.506 0.506 0.507
lprm.16 0.496 0.496 0.501 0.522 0.517 0.470 0.495 0.520 0.520 0.520 0.504 0.504 0.516
lprm.17 0.485 0.485 0.485 0.500 0.496 0.480 0.495 0.490 0.490 0.494 0.490 0.490 0.494
lprm.18 0.486 0.486 0.486 0.487 0.492 0.460 0.495 0.490 0.490 0.495 0.490 0.490 0.494
lprm.19 0.492 0.492 0.492 0.499 0.496 0.450 0.495 0.500 0.500 0.497 0.495 0.495 0.497
lprm.20 0.497 0.497 0.495 0.478 0.508 0.440 0.495 0.500 0.500 0.500 0.502 0.502 0.516
lprm.21 0.502 0.501 0.500 0.518 0.513 0.470 0.495 0.510 0.510 0.511 0.507 0.507 0.510
lprm.22 0.530 0.531 0.530 0.557 0.540 0.450 0.495 0.530 0.550 0.512 0.526 0.526 0.523
Table 11. Preliminary results for the DR. Case 5.
Table 12. Preliminary results for the fundamental frequency. Case 5.
Table 13. Preliminary results for the DR. Case 6.1.
Table 14. Preliminary results for the fundamental frequency. Case 6.1
Table 15. Preliminary results for the DR. Case 6.2.
Table 16. Preliminary results for the fundamental frequency. Case 6.2.
In tables 3-16 above, we have used the following notation:
UPV standard AR .M2:
UPV Full SVD AR.M3:
UPV Truncated SVD.M4:
UPV Dynamics reconstruction.M5:
Pennsylvania State University: AR.M6:
Pennsylvania State University: LAPUR code.M7:
University of Tsukuba.M8:
PSI: ARMA model (Plateau method)M9:
Also, we note that the method M6 (LAPUR code) is not a signal analysis method. Furthermore someparticipants also provided standard deviation estimates. This is an important aspect of the Benchmark;these results will be presented in the final report.
List of Participants
MOJUMDER, Soma Tel: +49 (9131) 18 7536
SIEMENS AG/KWU Fax: +49 (9131) 18 5243
KWU NBTT Eml: [email protected]
POHLUS, Joachim Tel: +49 (089) 3200 4542 Institut fur Sicherheits- Fax: +49 (089) 3200 4300 technologie (ISTec) GmbH, Eml: [email protected]
Abteilung Diagnose Forschungsgelaende 85748 GARCHING
KONNO, Hidetoshi Tel: +81 (298) 53 5016
Inst. of Information Sciences Fax: +81 (298) 53 6471
& Electronics Eml: [email protected]
University of Tsukuba
* ROSTON, Graciela Beatriz Tel: +81 22 217 7907 Quantum Science & Energy Engineering Fax: +81 22 217 7907 Tohoku University Eml: [email protected]
Aramaki-Aza, Aoba, Aoba-ku SENDAI 980-77
* SUZUDO, Tomoaki Tel: +81 (29) 282 6077 Control and AI Laboratory Fax: +81 (29) 282 6122 Dept. of Reactor Engineering Eml: [email protected]
JAERI Shirakata Shirane 2-4, Tokai-mura Naka-gun, Ibaraki-ken 319-1195
TAKEUCHI, Yutaka Tel: +81 44 288 8131 TOSHIBA Corporation Fax: +81 44 270 1808 Nuclear Engineering Lab.
Eml: [email protected]
Systems Analysis & Mech. Eng.
4-1 Ukishima-cho Kawasaki-ku KAWASAKI 210
NUÑEZ-CARRERA, Alejandro Tel: +52 2 590 8113
Comision Nacional de Seguridad Nuclear Fax: +52 5 590 6103
y Salvaguardias Eml: [email protected]
Dr. Barragan Num. 779
Col. Narvarte C.P. 03020
DE KRUIJF, Willy J.M. Tel: +31 15 278 6594
Interfaculty Reactor Institute Fax: +31 15 278 6422
Reactor Physics Department Eml: [email protected]
2629 JB Delft
CONDE LOPEZ, José M. Tel: +34 91 346 02 53
Head, Nuclear Engineering D. Fax: +34 91 346 05 88
Consejo de Seguridad Nuclear Eml: [email protected]
Justo Dorado, 11
GINESTAR, Damian Tel: +34 96 387 7635/7630 Universidad Politecnica de Valencia Fax: +34 96 387 7639 Dept. Ingenieria Quimic y Nuclear Eml: [email protected]
Camino Devera, 14 P.O. Box 22012 46022 VALENCIA
NAVARRO, Joaquin Tel: Departamento de Ingenieria Quimica y Nucl Fax: +34 96 387 76 39 Universidad Politecnica Eml: Campus Camiro de Vera P.O. Box 22012 46071 VALENCIA
* PALOMO, Maria José Tel: Departamento de Ingenieria Fax: +34 (6) 387 76 39 Quimica y Nuclear Eml: Universidad Politecnica P.O. Box 22012 46071 VALENCIA
RECIO SANTAMARIA, Manuel Tel: +34 91 346 02 10 Nuclear Engineering Dept. Fax: +34 91 346 05 88 Consejo de Seguridad Nuclear Eml: [email protected]
Justo Dorado, 11 28040 MADRID
REY GAYO, Jose Maria Tel: +34 91 346 02 15 Nuclear Engineering Dept. Fax: +34 91 346 05 88 Consejo de Seguridad Nuclear Eml: [email protected]
Justo Dorado, 11 28040 MADRID
VERDÚ, Gumersindo Tel: +34 96 387 76 30 Departamento de Ingenieria Quimica y Nucl Fax: +34 96 387 76 39 Universidad Politecnica Eml: [email protected]
Campus Camiro de Vera P.O. Box 22012 46071 VALENCIA
LANSAKER, Pär Tel: +46 173 81543
Vattenfall Fax: +46 173 81697
Forsmarksverket Eml: [email protected]
HENNIG, Dieter Tel: +41 (56) 310 41 67
Systems Engineering Fax: +41 (56) 310 23 22
Paul Scherrer Institut Eml: [email protected]
CH-5232 VILLINGEN PSI
UNITED STATES OF AMERICA
CECEÑAS-FALCON, Miguel Tel: +1 814 231 0581
Nuclear Engineering Fax: +1 814 865 8499
The Pennsylvania State University Eml: [email protected]
231 Sackett Building
University Park, PA 16802
FARAWILA, Yousef M. Tel: +1 (509) 375 8720 Siemens Power Corporation Fax: +1 (509) 375 8402 Nuclear Division Eml: [email protected]
SPC 2101 Horn Rapids Road RICHLAND, WA 99352-0130
* MARCH-LEUBA, Jose A. Tel: +1 423 574 5571 OAK RIDGE NATIONAL LABORATORY Fax: +1 423 576 8380 PO BOX 2008 MS6010 Eml: [email protected]
OAK RIDGE TN 37831-6010
SARTORI, Enrico Tel: +33 (0)1 45 24 10 72
OECD/NEA Data Bank Fax: +33 (0)1 45 24 11 10
Le Seine-Saint Germain Eml: [email protected]
12 boulevard des Iles
* regrets for not having been able to attend
1. General Items
1.3 Review and Approval of Agenda (J.M. Conde)
2. Forsmarks 1 & 2 Benchmarks
2.1 Summary Introduction to the 6 Test Cases (G. Verdú, P. Lansaker)
2.2 Review of Submitted Results and First Draft Report (G. Verdú, D. Ginestar)
2.3 Presentation by Participants (D. Hennig, Y. Farawila, H. Konno, J. Navarro, W. de Kruijf Y. Takeuchi, M. Ceceñas, A. Nuñez, J. Pohlus)
3. Review of Summary Conclusions
3.1 Lessons learned: performance of different approaches determination of uncertainties (G. Verdú, P. Lansaker, D. Ginestar, and all other participants)
3.2 Conclusions and Recommendations on methods (J. Conde, D. Ginestar …)
4. Next Phase
4.1 Schedule for Submission of Revised Results
4.2 Publication of Results, Presentation at Conferences Reporting to CSNI PWG2
5. Reporting to NSC
List of Distributed Papers
1. Agenda2. List of Participants3. Summary Introduction to the 6 Test Cases (G. Verdú)4. Review of Submitted Results (G. Verdú)5. Comparison of the Results Provided for the Forsmark Stability Benchmark. Some Comments
6. Graphs Comparing the Results (G. Verdú)7. Results obtained at Penn State University Using Auto-regressive Models (M. Ceceñas)8. First Results (A. Nuñez)9. Preliminary Results (W.J.M. de Kruijf)10. Time Series Data Analysis Results (Y. Takeuchi, S. Kanemoto, H. Miyamoto)11. Time Series Analysis for BWR Stability Studies (D. Hennig)12.
The Physical Mechanism of Core-wide and Local Instabilities at the Forsmark-1 BWR(G. Analytis, D. Hennig, J. Karlsson)
13. Application of Noise Analysis for the Study of Core Local Instabilities at Forsmark-1 (R. Oguma –
distributed and commented by P. Lansaker)
14. Localisation of a Channel Instability in the Forsmark-1 BWR (J. Karlsson, I. Pazsit – distributed and
15. Forsmark Benchmark Report (H. Konno)16. Parametric Stochastic Stability and Decay Ratio for a Stochastic Non-Linear BWR Model Below the
Hopf Bifurcation (H. Konno, S. Kanemoto, Y. Takeuchi)
17. UPVM Methodologies and Results (J. Navarro)18. The First Results (T. Suzudo)
Prepare draft summary of meeting (E. Sartori, G. Verdú, J.M. Conde)
Submit draft paper about status of benchmark for M&C’99 (G. Verdú)
Provide comments/amendments to summary. Participants should look at theconclusions and comment so that the consensus view can be extracted (All)
Distribute summary to participants, NSC and PWG2 (E. Sartori)
Deadline for submitting new, additional results. (All)
Prepare first draft of report for circulation to participants (G. Verdú)
Submit paper on results of benchmark to M&C’99 (G. Verdú)
Distribute ‘Final Draft’ of Report for final comments and approval(G. Verdú, E. S.)
End of final report editing and formatting submission to printing (E. Sartori)
For September 2000: Paper preparation and presentation of final benchmark results at Physor’2000
Submit draft article to NSE or Nuclear Technology
Psicothema 2008. Vol. 20, nº 4, pp. 812-817 Chronic sildenafil (Viagra) administration reduces anxiety in intact and castrated male rats Abdel A. Solís, José A. Bethancourt* and Gabrielle B. Britton*Universidad de Salamanca and * Instituto de Investigaciones Científicas y Servicios de Alta TecnologíaEpidemiological research indicates that sildenafil (Viagra) abuse is associated with i
Assessing the Potential Value of Rare Metals in Urban Mines: A Comparative Look at Korea and Japan By JUNG Ho-Sung Co-authored by KIM Hwa-Nyeon and CHOI Myeong-Hae September 2011 I. The Rise of Rare Metals Rare metals refer to metals which are scarce in the earth’s crust, or which are scarce because they are difficult to extract and process. Rare metals are also met