STATE OF ‘J!RE ART On

REACTUR HOISE ARALPSIS

NEACRP-A-699

P. Bernard Commissariat a l*Rnergie Atomique, Cd&ache

D. Fry Oak Ridge National Laboratory, oak Ridge

D. Stegemann Techniscnen Universitaet Hannover, Hannover

H. van Dam Interuniversitair Reactor Instituut, Delft

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INTRODUCTION

Reactor Noise Techniques have seen important developments and appli- cations over the past few years. Some of the main reasons for this is that they can give important and interesting information with non-intrusive techniques, generally using "passive listening" techniques, which means that the reactor canbe operatedwithoutconstraints whentakingnoise measurements.

The aims oftheapplication of reactor noise techniques are:

. To monitor the reactor components: verification of conformity with 0 expected status, detection and diagnosis of anomalies.

. To determine physical parameters and/or general dynamics characteristics of the reactor.

. To contribute complementary information for characterising the status of the plant under normal or abnormal operation.

At the recent SMORN-IV meeting in Dijon, a number of recommendations to the Nuclear Energy Agency were formulated by the participants. It was proposed to:

. Draft a State of the Art report including an analysis of trends and make recommendations to the various sectors of the reactor noise community.

. Setupnewnoisebenchmarkproblems.

. Assess possible ways to use the establishedmechanisms and facilities providedbythe NRA Data Bank.

This report'is the result of the work of a task force sponsoredby The NRA Committee on Reactor Physics (NEACRP).

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Benchmarks

{a) Artificial Anomaly

The Dutch group at Interuniversity Reactor Institute has proposed to co-ordinate a new artificial noise benchmark consistingofa synthetic System. It Will contain two or three noise sources and three output Variables.

The systemwillcontain a subsystem simulating dampedoscillations.

The output signals willcontaintwoparts:

. The first part refers to a Wormal~~ operation condition and iS meant for checking FFT and MAR methods. In particular, it will aim at identifying subsystem transfer functions and noise contribution ratios. Special attention will be paid to the influence of analysis conditions like sampling rate, filtering and model order on MAR-analysis.

. In the second part there will be at some time point a transition to qtabnormalW behaviour, where the parameters of the oscillation subsystem and perhaps a noise source strength will change. This pert will be used to assess the merits of anomaly recognitionmethods.

lb) Real Anomaly

In order to supplement this benchmark on anomaly detection, the NRAis asking laboratories possessing a recording containing a real reactor aIIOmly

a to draw up the specifications for such abenchmark and to be prepared to analy- se the contributions. The anomaly should preferably be the result of a loose partinaPWR or BWR.

xc) SMORR-IV Benchmark

Laboratories interested in obtaining an analog or digital copy of the taps used for the previous benchmarks can contact the N8A Data Bank. The recordings are made available for laboratories wishing to compare their methods with the results of the previous benchmarks. The full report of the SMORN-IV benchmark Will be published in mid-1985 under the reference NRA'ZRP-L-283.

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,

The NEA Data Bank can help in the supply of tested codes; used in noise analysis such as:

. Fast Fourier Transforms

. Auto Regression

. statistical tests

. Graphics for spectra representation

. Automatic (peak) characterisation of Spectra.

State of the art

The present document is divided into six chapters:

. Loose-parts detection andacoustic monitoring

. Thermal hydraulics surveillance

. Flow measurements

. Vibration monitoring

. Surveillance systems and evaluation methods

. System dynamic analysis

Each chapter summarizes the current Situation innoise ,aIIalySiS tech- niques with emphasis on the following aspects:

. physical quantities considered

. possible anomalies involved * sensors used for the detection . conditions of applications

The remainder of each chapter discusses future trends and recommendations.

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1 LOOSE-PARTS DFTECTION AND ACOUSTIC MONITORING

This chapter deals with the detection of (1) loose parts within the plant primary and SeCOndary cooling systems and (2)leaks, both frOmValVeS and pipes.

PHISICAL OUANTITIES

Acoustic noise sensed by externally mounted accelerometers or high- frequency (up to 500 kHx) acoustic sensors is used routinely to detect 1OOSe objects in nuclear plant primary and secondary Cooling systems. The objects may be parts from the plant's own internal components or may be foreign parts that were inadvertently left in the system during COnStrUCtiOn, refuelling, or maintenance activities. Impacting of loose reactor internal structures against adjacent structures canalsobe detectedby acoustic noise monitoring. The objective of loose-part monitoring is to detect the presence of a 1OOSe part or structure, the energy with which it is impacting, its size, and its location. There are many documentedcases systems (LPMSs) have provided early warning of mechanical failures and have thereby benefitted both plant safety and operability. The sizes of loose or detached objects detected successfully range from 50 g to tens of kg and include nuts,

bolts, and retaining pins: steam generator tube plugs; surveillance specimen holders; thermal sleeves; andmiscellaneous hand tools, welding rods, brackets andspacers.

Acoustic noise has alsobeen used to detectandquantify leakagetothe outlet side of closed valves, to the environment (steam packing leaks), and from cracks in coolant piping. The relative rate of leakage is strongly correlatedwiththetotal rms magnitude of the acoustic signal.

The application of acoustic noise for the detection of pipe leaks has not been as successful as for valves. One reason is because for valves the potential leak locations are known in advance (thereby providing a basis for choosing sensor locations), but are unpredictable in the case of pipe leakage, thus making it difficult to install enough sensors to achieve reliable detection. Equally important is the problem of maintainability of the acoustic sensors, since these need to be mounted directly to the pressure boundary and are therefore subjected to both high temperatures and radiation, and are generally inaccessible except during outages.

Acoustic signals are analysed for their relative times of arrival with respect to Signals received from other sensors, for their frequency spectra, and their amplitudes to determine the location, mass, and impact energy of a loose part or structure and to locate and quantify coolant leakage. On-line calibration by controlled impacts as well as theoretical prediction of Waveform properties and transmission properties of the internal structures are used to interpret the acoustic signals. The acoustic-wave and Hertz theories are employed in data interpretation.

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POSSIBLE ANOMALIES IN~~LVEJI

Particular safetyconcernsidentifiedwithloose parts are:

. Failure or weakening of reactor coolant systemcomponents, duetoloss or loosening of one or more key parts or fasteners;

. Damage to or material wear of portions of the coolant system (particularly steam generator tubes), due to frequent impacting or abrasionby an otherwise non-critical loose object;

. Threat of fuel cladding failure due to overheating resulting frompos- sible fuel assembly flow blockage caused by loose objects;

. Threat of control rod jamming (failure to insert upon command);

. Personnel hazard associated with increased levels of radioactive crud in the primary system, resulting from the gradual disintegration of loose parts and subsequent irradiation by passagethroughthereactor core.

For example, loose parts have occasionally caused significant damage to the primary-side inlets of steam generator tubes, thereby inducing cracking which may lead to primary-to-secondary leaks and consequent transfer of radioactivity to the environment. Loose structures such as instrument tubes in BWRs and thermal shields in PWRs have likewise caused impact damage to fuel boxes and core support structures, respectively, with concomitant safety and operational consequences.

Leaking PWR pressuriser reliefvalvesandBWRsafety relief valves are undesirable conditions in operating plants. If not detected at an early stage, these leaks can lead to abnormal loss of reactor coolant and damage to these safety-related Valves. Prompt detection of pipe leaks can prevent more serious failure of coolant piping and subsequent loss of reactor cooling and permit repairstobe performed duringscheduledplantoutages.

SENSORS USED FOR DETECTION

Loose-part monitoring is achieved by mounting accelerometers (frequency response to 30 kHz) at locations on the exterior surfaces of the primary and secondary coolant systems where loose parts Willnaturallytendto collect due to coolant flow forces. Special accelerometers that are designed for the high temperature and radiation environment of nuclear systems are commercially available.

Both accelerometers and so-called acoustic emission sensors (frequency response to 500 kRz) have been used successfully for valve leak detection. The latter sensor type iS normally used in conjunction with an acoustic waveguide which allows the sensor to be placed a short distance from the component and thereby in an environment of which it is more tolerant.

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CONDITIONS OF APPLICATION

For reliable loose-part monitoring, attention should be given to sensor mounting techniques which are robust and achieve good aCOUStiC coupling, and to extensive calibration at the time of installation by Using simulated loose parts of known energy, size and location. Multiple sensors are requiredtolocate a loose part accurately. Normally, three or fOUr sensors are used for locating, but a recently proposed metnod employing Only two sensors has been used successfully under certain conditions. Background noise at all plant operating conditions, especially those encountered during plant startup, must be measured to provide abasis for selectingalarmthresholds.

Valve leak detection requires that an accelerometer or acoustic emission sensor be located on or near the valve. For quantifying leak rate, it is necessary to know if the leaking fluid is water, steam, or a two-phase mixture. Low-freguenty (<l kRx) noise is usually eliminated with a high-pass filter to prevent false alarms fromnormal plantbackgroundnoise attributable to coolantflowandrotating machinery.

FUTURETRENDS

Although the theory of 1OOSe parts is continuing to advance, more fundamental studies are neededtoimprovethe understanding of acoustic signal transmissionthrough in-vessel structures and the role of water damping. This understanding should lead to improved methods for the determination of the mass and location of loose parts. Further research will improve the ability to monitor for loose parts during plant startup, at which time it is particularly important to detect any foreign objects inadvertently left in the system duringrefuellingandmaintenance activities.

An important future trend is in the direction of more intelligent monitoring (based on the methods of artificial intelligence) to provide on-line, machine-aided interpretation anddiagnosis of loose parts.

RRCOtR.lRRDATIONS

Utilities

Utilities should establish improved communications (perhaps by means of periodic workshops) with regard to their loose-part experiences, both to improve their ability to diagnose loose parts and to provide a forum for encouraging all plant owners to utilixe the best available loose-part detection technology so as to improve plant safety andavailability.

Plant owners need to make a commitment to loose-part monitoring by upgrading existing systems and by establishing comprehensivetrainingin LPMS technology for all plant personnel involved.

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Manufacturers of LPMSs shouldbe encouraged to refine their product to include technological advancements; in particular, the addition of diagnostic capabilities and improved calibration schemes to minimize radiation exposure to personnel and to improve the reproductivity of calibration. They should also improve training programs, with more emphasis placed on the diagnosis of loose parts when alarms occur.

Plant manufacturers should integrate loose-partmonitoringinto plant design by providing specifications on sensor locations andbuilt-in capability for proper sensor mounting.

R&D Organisations

Future research and development in loose-part monitoring will focus on improving the theory of acoustic signaltrensmissionandthe frequency COntent of signals as a function of loose part size, shape, and impact energy (Hertz theory). This will include benchmark experiments on mass and location determination as well as establishment of criteria for alarm thresholds and diagnosis of loose parts.

R&D in valve and pipe monitoring will focus on establishing quantita- tive relationships between leak rate and sound level or other properties of acoustic emission. Crack/leak geometry, pressure differential, single-phase and two-phase mixtures, and proximity of the sensor to the source of the leak will all require exploration.

A major thrust of future development will be in the area of automated on-line diagnosis of loose-part and pipe-leak situations, using schemes based on artificial intelligence and expert systems -that provide access to the combined knowledge and experience of acoustic noise diagnostic experts worldwide.

Committee on Reactor Physics

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NEACRP should compile a compendium of examples of SUCCeSSfUl loose-part diagnoses (including actual data) and organise workshops both to encourage communication between manufacturers, R&D organizations, and utilities and to develop guidelines for SUCCeSSfUl loose-part monitoring programs. The guidelines should emphasize improved training of plant personnel in the methods for calibrating loose-pert systems andinthe interpretation of signals and diagnosis of the situation when alarms occur.

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2 THERM&L HYDRAULICS SURVEILLANCE

2.1 BWR T?lE%MAL mDRAULICS SURVEILLANCE

In BWR noise analysis two areas can be distinguished: incore measurements and system analyses. The first is focussed on the two-phase flow characteristics in the core, the latter aims at 'an analysis of the dynamics of the complete reactor loop.

2.1.1. Incoremeasursmnts

The measurement of two phase flow Velocities with inCOre neutron detectors is nowadays a well-established technique. There are, however, remaining difficulties in the interpretation of the results which hamper the application of this technique for verification of thermal hydraulic calcu- lations, in particular calculations withadvanced subchannelanalysis codes of steam velocities, void fraction profile and flow pattern. There is a continuing discussion on the type of perturbation velocity being measured (e.g. volumetric flux density or kinematic wave Velocity), which may depend on the type of two phase flowregime. In additiontothis the contributions of the different subchannels surrounding the detector position, to the detector signals are an important issue. These contributions are not only relatedtothe detector 'field of view' but also to the effective noise source strengths in the subchannels. An important issue with respect to anomaly detection is the effective noise source strength for different flow patterns. There areindica- tions that noise sources innormally Operating fuel bundles will dominate over the noise from a bundle with a highly anomalous thermal hydraulic condition leading to a flow of more or less pure steamor small droplets. This may endan- ger the feasibility of the noise method for detection of local anomalies in two phase flow.

The recent introduction of gamma-sensitive incore detectors with a ~larger field of view than thermal neutron detectors will certainly provide :additional information about two-phase flow distributions around detector ~positions. In view of the complicated two-phase flow patterns.in BWR fuel bundles, the guantitativeinterpretationin an absolute sense willcontinueto be difficult. On the other hand, the use of noise data in acomparative way is a Useful way of monitoring two-phase flow and undoubtedly has development potential.

A technique has been developed for extracting information about core dynamics from the radial dependence of low frequency coherence of neutron detector signals; it has been applied in a few BWR's and provides a means for on-line monitoring of the at-power reactivity transfer function. The infor- mation obtainedinthis way about the sensitivity volume of incore detectors at low frequencies is of relevance for the detectability of local anomalies in a reactor core by using LPRMdetectors.

The technique for assessing core stability (see also chapter 6) from neutron PSD resonance parameters is presently a mature method; used in an increasing number of surveillance systems. The same applies to detection of instrument tube vibrations and of bypass coolant boiling, which items were of practical importance some years ago.

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2.1.2. Svstm analysis

System analysis of BWR loops on the basis of noise measurements has made considerable progress in recent years and has proven to be a valuable technique for monitoring process parameters. There is a great incentive to use noise analysis instead of deterministic reactor dynamic tests, because the former do not interfere with normal plant operation, which gives the possibility of continuous surveillance, and the dynamic information extends to significantly high frequencies; inmany cases dynamic tests require permission from safety authorities: For preparation and realization much time is needed and assistance of specially trained personnel is indispensable.

Process signals of special interest for analysis are: neutron flux, core coolant flow, reactor vessel pressure and feedwater flow. The signals to be recorded can normally be obtained from the plant instrumentation. Neutron flux is monitored viathein-core detectors, whichprovideinformationonboth local and global conditions (LPRM, APRM). Steamdome pressure is monitoredvia pressure sensors, steam flow to the turbine Via flow sensors in the individual steam lines, the method for measurements of core coolant flow depends on the particular BWR design.

Systemanalyses aim at obtaining quantitative information on:

. process parameters

. strengths of noise sources and their contributions to noise in process variables

. transfer functions of subsystems, including process control systems

It shouldbe kept in mind that many process sensors are dynamic systems in themselves which gives a filtering of the real process variables; it also implies that the proper operation of a sensor can be monitored by noise analysis. There are also examples of detectionof interchanged junctions (e.g. of a large number of in-core detectors) by noise analysis.

The analysis of a multivariable system on the basis of noise signals is performed with standard FFT- and AR-methods. For complicated systems with feedback loops the latter seem to be indispensable. In the application to real physical systems sometimes problems are encountered, reflected in the non perfect diagonalization of the noise source matrix, which occurs when a particular signal transfer path is considerably faster than (other ones. In this case small sampling intervals and high model orders are needed: research to overcome these problems is under way.

System noise analysis on BWR loops has improved our insight into the relevant processes and there is an economic incentive for continuation. Because of the combinedeffectof several uncertainties, Operatingmargins are often set very conservatively. This means that room for uprating exists. Safe uprating must be based on additionalthermalhydraulic information such as can be obtainedfromnoise analysis. Monitoring of core stability is of highimpor- tance in the uprating but has for BWR's a particular significance. Several incentives exist for operating BWR's at reduced coolant flow; this saves both neutrons and pumping power, and improves both operational flexibility and xenon override capability. However, operation at reduced flow impairs core

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stability to some extent; thus it becomes of interest to determine as accurately as possible the actual stability margins. From the point of View of safety, operation at natural circulation should be included in such analysis. (See also Chapter 6)

2.1.3. Futuredevelouments and recommendations

knowledge about two phase flow conditions in BWR's shouldbe improved by the combined application of advanced thermal hydraulics codes and incore noise measurements. The latter could preferable make use of both neutron and gamma detectors. From the methodological point of view, measurements in full Scale fuel bundles under variable and well-known conditions are to be preferred, but are perhaps not realixable or at least very costly. Although the results of steam velocity measurements in an absolute sense may be questionable, they can be very useful in a relative sense, for instance in correlating steam velocities with power density distributions and monitoring if Velocity changes are consistent with other operational changes. In this respect, the development of techniques for sufficiently accurate velocity measurements in short time intervals, in the order of a few tenths of asecond, can be useful. In addition to tests of core stability inaglobal sense, based on measurement of damping ratios, the monitoring of velocity fluctuations may be useful in assessing channel stability.

Not particular for BwR's but of more general relevance is the further exploration of AR techniques and the formulation of criteria for proper appli- Cation. The investigationof its potentialities for failure detection andiso- lation should be continued. A properly defined noise benchmark, based on a synthetic system, canbe very helpful in this respect.

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2.2 PWR THERMAL HYDRAULICS SURVEILLANCE

In PWR thermal hydraulic SUrVeillance two major areas ofresesrchand development work can be distinguished:

. Surveillance of the reactor related to reactor core thermal hydraulics

. Surveillance of the complete primary system to detect changes in the thermal hydraulic behaviour of the components.

PHYSICAL OIJANTITIES

Available for operational analysis and surveillance are:

. neutron noise

. temperature noise . pressure noise

In the area of surveillance of reactor thermal hydraulics particular effort is visible in detection and interpretation of subcooled boiling. The activities range from experimental investigations to detect subcooledboiling by local neutron noise analysis and acoustic methods along with the development of thermal hydraulic non-equilibrium models and coupled neutron-thermal hydraulic models. Further cross-correlation of core outlet temperature noise with incore-neutron noise is used to estimate the incore coolant velocity.

In the area of surveillance of the primary system considerable effort has been given to a better understanding of pressure fluctuations. Coolant pumps and turbulent flow give, amongst other sources, rise to pressure fluc- tuations in the form of standing waves whose characteristic wavelengths or frequencies depend on the geometry of tubes and primary system components as well as on pressure and compressibility of the coolant. To interpret the autopower spectral density of pressure fluctuations in different positions of the primary system new models have been developed particularly to identify characteristic frequencies caused by a special component. Changes of dominant frequencies occur due to steam and gas content in tubes and the other components of the primary system. Encouraging results have been obtained particularly for tubes and pressurizers.

The influence of thermal hydraulic parameters on the dynamic behaviour of PWR's is also of great interest to identify the origin of resonance frequencies (fuel elements, core barrel, standing waves, etc.) and to normalime the actual spectra. This means correction of measured dominant frequencies taking into account the influence of the temperatures of coolant and materials.

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POSSIBLE ANOMLIES INVOLVED

Surveillance of reactor core thermal hydraulics, measuring coolant velocities, NRMS-values of core outlet temperatures and detecting lOCal subcooledboilingis ofinterestbecause of the followingpcSSible anomalies:

. incore flow blockages

. localised power skews

. hot spots

. boiling crisis

Surveillance of the primary system, in particular by detecting changes in dominant frequencies of pressure noise, has the following airs:

. information concerning thermalhydraulic conditions in Components of the primary system. Gas contents, boiling and steam in piping and other components influence strongly the velocity of sound andbythis dominant frequencies of standingpressurewaves.

. information about the mechanical performance of the primary circuit components, in particular pumps, core barrelandpiping.

SENSORS USED ?wRDErEcTION

For tne investigation of subcooled boiling incore neutron detectors (normally self-powered neutron detectors) are used in the frequency range up to 50 Hz. Coolant flow velocities are being measured by cross correlation of incore neutron detectors and thermocouples at core outlet. Of vital importance for these measurements is the correct knowledge of the thermocouple time response. Pressure fluctuationstransducersare used fortheanalysis of pres- sure noise; typical frequency range is up to 20 Hz. Due to limited access in some cases the transducers had to be connectedtothe component under investi- gation by tubes (sensing lines) which act as a resonance system themselves which can lead to misinterpretation of dominant frequencies. Special care must be giventothese phenomena.

FUTURE TRENDS

In reactor core thermal hydraulics further investigations are necessary for detection and interpretation of subcooled boiling. This is certainly true for stochastic model development as well as for experimental research (bubble size, bubble life time, bubble frequency) under PWR condi- tions. In primary systemsurveillance by pressure noise further improvement of models and particularly their verification in PWR systems seems necessary in order to correlate, in an unequivocal manner, dominant frequencies andsystem components.

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REClB!MERDATIONS

Committee on Reactor Phvsics

NEACRP could serve as a coordinating committee to establish guidelines and standards for the application of surveillance techniques using noise analysis. There are areas, such as mechanical vibrations and loose part monitoring, where the establishment of guidelines or standards may be easier right now than in reactor thermal hydraulics or pressure noise analysis. It should be kept in mind, however, that these activities wouldbe of along range nature, anyway.

General

Surveillance methods for components of the secondary system of PWR, such as steam-turbines and condensers, should be included in ths researchand development activities, if noise analysis techniques are applied.

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2.3 LWBR THERMOHYDRAULICS SURVEILLANCE

Seven SMORN-IV papers dealt with experimental (power rectors and loops) and theoretical developments (stochastic models, noise data treatment)...

The sensors that are usedinthese developments are:

. Neutron detectors

. Temperature sensors (thermocouples) measuring sodium or fuel (Only applicable on test facilities) temperature

. Acoustic detectors

The aim of the developments concernedeither

. Subsystem properties investigations and parameters determination (fuel/coolant heat transfer and time constant, fuel-clad elongation, sodium flow rate)

. CL- continuous monitoring of commercial (present or future) LMFBR:

- Sodium boiling detection (neWrOn. temperature and acoustic sensors)

- FlOW reduction Or blockage (outlet thermocouples) - Time constant surveillance of outlet thermocouples.

Concerning continuous monitoringinlarge LMFBR:

. Acoustic monitoring would be sensitive to bubbles duetoboiling or to fission gas after severe accidental transient. There will be some problems to be solved in using the SCOUStiC nOiSS teChXIi.qUe in large power LMFBRs, for sodium boiling detection, for the fOIloWing main reasons:

- Lowboilingnoisetobackground noise ratio

- Likely several (or many) sensors for monitoring the whole core.

l Neutron noise techniques should be sensitive to boiling and could be used for on-line boiling detection and monitoring. Some limitation for the application of this technique is duetothe fact that it may not be very sensitive, because :

- The sodium void coefficient is rather small and changes with the void location inside the core, and the reactivity weight of aunit volumebubbleis small, comparedtothe core size.

- The Campbelling Noise on the neutron detectors iS high, due to their low efficiency (low counting rate of the neutron detectors thatarelocatedrather far from the core).

. Flow blockage monitoring could be performed using outlet thermocouple noise monitoring. The accuracy of the methodwouldhavetobe compared to the classical method (comparisonofthe DCthermocouple signalto a

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threshold). The time constant of the thermocouple appears to be an important parameter for noise measurement purposes.

. Outlet thermocouple time response can be monitoredusingthermocouple and power signals. This could be of interest because thermocouples signals are usedinthe fast core protection system 1

RECt3lMENDATIONS

It would be interesting for future orientations to have some more quantitative information on one hand of the possible sensitivity limits of monitoring technique using noise methods, and on the other hand on the cost/benefitaspectofthe use of on-line noise monitoring. More precisely:

. Concerning boiling detection and monitoring:

- R&D organisations should contribute to a guantitative determination of the sensitivity limits, response time and appli- cation conditions of on-line boiling monitoring using acoustic methods or neutron noise method (when using present neutron detectors or detectors with an improved efficiency (more sensi- tive detectors, more detectors, detectors nearer to the core.. . )) .

- With this information, manufacturers and utilities should evaluate the interest (benefits andcosts) of Using ,the techniques in operating LMFBR.

. Concerning flow blockage monitoring, R&D organisations should make a quantitative evaluation of the sensitivity limits and response time of the flow blockage monitoring using On-line analysis of outlet thermocouple fluctuations, and compare it to the classical method (comparison of the DCthermocouple signal to a threshold).

1 Let us note that the fuel assemblies of the Super Phenix core Will be

fittedwithintrinsic thermocouples (large bandwidth).

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3 PLWIMEASEEEMEETS

All methods of flow measurement, except one, deal with the transit time correlation technique , wnere the transit time of the flow between fixed detector positions is measured. One of the primary goals of the flow measurement methods is to measure the coolant velocity withoutdirectcontact with the fluid.

PHYSICAL OUAETITIES

Steam-velocity determination is the major aim in boiling water reactors for core surveillance and thermal hydraulic model comparison. Due to the fact that this topic is discussed in detail in the chapter on BWB-thermal hydraulics surveillanceitwillnotbe treated here.

Coolant flow in the primary circuit of aPWEwas successfully measured using the Nitrogen-16 activity noise analysis technique. The better the mixing of the coolant at the core outlet, the better the accuracy which canarrive at values of less than 2 percent. Coolant flow velocity of water in large diameter pipes can also be measured using ultrasonic cross correlation technique. Both methods have the advantage to measure the flow rate without contact to the coolant thus avoiding penetrations through the tube and pressure drop in the tube.

Coolant flow measurements in sodium cooled reactors by applyingtran- sit time correlation techniques has the aim to facilitate or even better to avoid the recalibration of electromagnetic flowmeters. Here appreciable progress has been made. Systematic error sources, which can occur, have been identified very clearly. For practical application great care is therefore necessary to take these results into consideration in order to avoid inaccurate flowrate measurements.

POSSIBLE AEOMALIES IEVOLVED

The coolantflowcanbe perturbedbythree basic anomalies:

. failure of driving force, e.g. pump failures . obstacles in the flow channel, e.g. partial or complete blockage . loss of coolant by leaks

SENSORS USED FOR DETECTION

For steam velocity measurements incore neutron detectors are used in the frequency range up to 50 Hz. Nitrogen-16 activity noise analysis uses detector-pairs sensitive to gamma radiation.

Ultrasonic emitters and receivers are used for measuring water flowratebythe cross correlation technique.

Induced voltage fluctuations for sodium flow rate measurements are measured by electrodes outside and inside the cooling channels whereas sodium-steel thermocouples (frequency range up to a few KHz) have been usedto measure sodium flowrate by temperature noise.

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FUTURETRENDS

The development and application of flow measurement methods applying noise analysis will certainly benefit from the progress in microelectronics for on-line data analysis and evaluation. Together with the advantage to reduce pressure dropinthe tubes andinthe majority also to avoid penetration of the cooling channel they have a great potential for practical'use.

RECOMMENDATIONS

Guidelines and standards should be established for application of flowrate measurements for nuclear power plants based on noise or correlation techniques.

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4 VIBRATION MONITORING

4.1 INTRODUCTION

4.1.1 TvDeof reactors

SMORN-IV papers on vibration monitoring dealt with:

. LMPBR (4 papers)

. No paper on BWR

. PWR (including VVRtype reactors) (22 papers).

With regard to PWR, there exist differences between the designs of the several reactors (different manufacturers, different designs in the Series). Nevertheless, the qualitative behaviour of the phenomena and the field of application seem to be similar, and does not allow us to distinguish between the different types of PWRinthe presentation hereafter.

The SMORN-IV papers concerning vibrationmonitoringcanbe classified into:

. Investigations and developments on operating PWRand/or experience of automatic or systematic monitoring

. Analytical developments

- On experimental facilities (loops, mockup) Theoretical

4.1.2 Sensors

The main sensors used for vibration analysis and (continuous) monitoring in nuclear reactors are:

. Accelerometers, strain or displacement sensors

. Rx-vessel (excore) and incore (mobile or fixed neutron detectors)

. Pressure sensors

4.1.3 Phvsical uhenomene and DerzUneterS. end Dossible anomalies that can be monitor4

Physical phenomena are vibrations of in-vessel components (internal structures, fuel, control rods) pump movement (shaft and body), steam generator body.

These phenomenaare observed:

. On mechanical sensors (accelerometers)

. Onneutron sensors, throughamechanicsto neutronics relationship

. On pressure fluctuations: hydroacoustic transmission of vibration acting as a driving source.

The anomalies that are related to these phenomena are abnormal vibrations of internal structures and components due to abnormal additional

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driving Sources or to abnormal changes in the mechanical tightening conditions of the vibrating systems.

4.2 STATE OF THE ART

4.2.1PWR vibrationmonitorinq

4.2.1.AComoonents and generalframeof vibrations monitorinq

The maincomponents whose vibrations or rotation can be monitoredare:

Vessel Core barrel Upper structures Thermal shield Control rods Fuel assemblies Detectors (and detectors' guide tubes) Primary pumps Steam generator body

In most types of PWRs, the normal vibratory behaviour of vessel and in-vessel components seem to havebeenthoroughly investigated (calculations, loop experiments, start-up tests with in-vessel temporary instrumentation).

Developments (loops and calculation) have also been achieved to characterize the vibratory behaviour of the vesselandin-vessel components in case of anomaly (loosening of hold-down spring, thermal shield flexure broken), in order to know the noise Signatures in case of anomaly.

It seems important to note that, according to operating (or loop simu- lation) experience, normal vibratory behaviour of internal Structures belong to a rather broad domain:

. For instance, 0, 1 or several contacts may exist on the! radial keys, that change the main pendulum-type motion frequency (contacts on the radial keys are often observed in operating PWRs and are generally considered as normal phenomena).

. Operating parameter changes may induce changes in vibratory signatu- res (extended core cycle duration: "stretch-out" conditions).

Vessel and internal structure Vibrations are induced by the downward water pressure fluctuations, and characterized by typical mode shapes frequency and damping, particularly:

. Pendulum-likemotion of the Vessel l Pendulum-likemotion of the core barrel . Shell mode of core barrelandthermal shield..

These developments mainly concern vessel and internal structures but such programs do not seem to have been performed in depth on fuel assemblies, control rods, incore neutron detector guide tubes.

Concerning fuel assembly vibrations, it seems that investigations havetobe continuedin ordertoidentify precisely:

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. The normal driving sources (lower core plate vibrations and/or upgoing water pressure fluctuations and/or upper core plate vibrations)

. The abnormal driving sources (baffle jet, abnormal Cross flows)

. The influence of the contacts between fuel assemblies

. The typical signatures of fuel assembly vibratory behaviour in case of abnormal tightening conditions.

In operating PwRs, as it is not possible to set mechanical sensors on the in-vessel components, the aim of continuous (or periOdiC) reactor noise monitoring is to obtain precise enough information about the vibratory behaviour of the components concerned, using available sensors.

4.2.1.B Vibration monitoring using vessel mechanical sensors (accele- rometers...

These sensors are sensitive to the vibrations of the reaCtOr Vessel and would allow a guantitative monitoring. They are also influenced by the vibrations of:

. Core barrel

. Primary pumps (shaft and body)

. Steam generator body (small)

and could give information for a qualitative monitoring.

4~.2.1.CVibrations monitoring using ex-vessel (excore) neutrondetectors

These detectors are quite sensitive to core barrel andthermalshield (andvessel) vibrations.

As longasthe core canbe consideredas:

. Rigidly vibrating in phase and with the same amplitude with core barrel pendulum-like motion

. Motionless for the core barrelandthermalshield shell modes,

then it is possible to get a quantitative interpretation andcharacterisation of amplitude of core barrel and thermal shield vibration, using neutronic scale factors (neutron fluctuation to vibration amplitude relationship), and obtain an efficientmonitoringof internal structures vibrations.

Actually, the excore neutron detectors are also sensitive to fuel assembly vibrations (lst, 2nd and higher beammodes) and interpretation of the participation of the fuel assemblies to the pendulum-like motion of the core barrel does not seem to be identical in different papers. The neutronic effect has been evaluated by some authors, but a conclusion does notseemto have been definitely reached.

It iS also quotedinthe papers that the core barrel (andbaffle) shell modes could induce peripheral fuel assembly motion (see also next item).

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No experience of controlrodvibration detection has been presented in the papers.

4.2.1.0 Vibrationmonitoring usingincore neutron detector

These detectors are sensitive to the vibrations of the fuel assemblies and the detector itself. It is usually assumed that the detector is motionless when the assembly vibrates, and the neutronics to assembly vibratory displacement is generally interpreted in connection with the macroscopic flux radial gradient.

Normal beam modes of fuel assemblies are observed on incore spectra. Interpretation of the spatial dependence of the fluctuations (axial and radial) are presented in some papers and shouldbe deepened.

Examples of anOmaly detection have been presented in connection with baffle jetting and unusual cross flow phenomena.

4.2.1.E Vibrationmonitoring usingpressure fluctuations

When the pressure sensors have the convenient properties (dynamics, frequency band, location), the pressure fluctuations can give information for monitoring of vibrations of:

. Core barrel

. Primary pumps

The main freqUenCy on the spectra are related to s&Ming waves, in connection with the soundvelocity.

This aspect istreatedin part2 (reaCtOrthermohydraulic!s and thermal fuels behaviour surveillance).

4.2.13 Primarvoumomecbanical sensors

These can provide information for monitoring

. Primary pump body vibration

. Shaft vibration

4.2.2 LMFBR Vibration Monitoring

Four papers dealt with this topic, and presented experience with PHENIX, JOYO, PFR, FFTF.

Main noise sources, andassociatedmonitoredphenomenaare:

. Control rod vibrations, mainly observed at JOY0 (strong fluctuations on the MARK II core), PHRNIX, and FFTF. They induce global reactivity fluctuations.

. Fuel assembly vibrations mainly observed on PFR.

. Noise in transmission of neutron to the detector.

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Some authors indicated that the low level of counting rate of the neutron detector was a problem for the accuracy of the monitoring.

4.3 RDlARRS. FUTURE TRENDS AND RECCMIERDATIONS

As a general remark, it is important, for vibration monitoring purposes, to finalize noise investigations and developments to get Clear interpretation and models that can be interpreted in terms of technological aspects, inorderto have:

. Well defined criteria for detection and diagnosis of anomalies

. Decision rules for what to do in case of detectedanomaly

On-vessel mechanical senSors (accelerometers) are adequate sensors for vessel vibration monitoring and can bring qualitative complementary information on internal Structure vibrations.

Pressure fluctuations can also bring some qualitative complementary information on vibration of reactor vessel, internal StrUctUreS, coolant pumps (shaft and body), body of steam generator.

Em-vessel (excore) neutron detectors fluctuations can bring the most complete information for internal structures vibrations. There exist several examples of anomaly detections. It seems important to note that the normal signatures can belong to several different classes (changes in contact on radial keys, change of operating conditions) and that an automatic system shouldincludethis in the classification criteria.

Rccomendation for RSDOrsanizations A complementary effort on the evaluation of the participation of the fuel assemblies to the internal structure vibratory displacements, and esti- mation of the corresponding neutronics (space time effect), indicates that this monitoring method has reachedmaturityandcanbe used for continuous monitoring of internal structure vibrations.

. Incore neutron detector fluctuations can give important information on the vibratory behaviour of the fuel assemblies.

Recomendation for R&DOrsanizations Some complementary investigations for concluding on:

. Final identification of (normaland abnormal) driving sources

. Contacts between fuel assemblies

. Incore detector/fuelasSembly relative vibratory displacement ~.

. Neutronics effects of fuel assemblies vibrations

wouldbe useful in order to useincore noise for a systematic monitoring.

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019310023

Control rods and fuel assembly vibrations seem to be the main applica- tion of neutron noise monitoring. There are not enough industrial LMFBRs, of identical design, for more precise remarks. An increase of the efficiency of the neutron detector wouldbenefit the monitoring accuracy.

4.3.3 Monitoring svstems

It seems clear that the trend iS to develop on line (quasi COntinUOUS) monitoring systems. 1 Such systems would include refinedclassification rules and data in order to give a valuable.detection and diagnosis.

1 Concerning incore monitoring, PWRs with moveable incore detectors would allow only periodic incore monitoring.

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5 SDRVEILIJhNCE SYSTEMS AND EVALUATION METNODS

5.1 INTRODUCTION

The subject of this chapter is inherently related to all other chapters because surveillance systems for reactor performance monitoring cover one or more of the areas described in other chapters. As a consequence some overlap is unavoidable. The bulk of the chapter is divided into three parts. First attention is given to a general subject which iS common to all surveillance systems and more or less independent of reactor type, i.e. the basic methods for surveillance. In the actual application there is aclear dis- tinction between reactor types with regard to the physical phenomena being monitored. Therefore the remaining two paragraphs pertain to PWRs/LMPBRs and BWRs respectively. As an addendum to this chapter a summary is given in the form of tables of surveillance objects and items in PWRs (Table A), in LMPBRs (Table B) andin BWRs (Table C) as well as a table on sensor SUrVeillaIEe (Table D).

5.2 EVALUATION MEWJDS DEVELOPMENT

Surveillance of a system is based on the measurement of process signals and the conversion of these signals to a form in which the relevant signal properties can be distinguished. After this conversion the remaining task is a recognition problem. First a learning period is needed during which the surveillance system learns, as accurately as possible, the characteristics of process signals in case of 'normal' process behaviour. The term 'sur- veillance system' should be taken here in a broad sense; incase of an on-line system it consists of a combination of hardware and software, in case of off-line surveillance, human brains are mostly part of the system. The exis- tence of normal process behaviour during the learning period is in fact a hypothesis on which the subsequentmonitoringis based. ~.

In most cases the process signals are converted into power spectral densities andassociated functions of frequency. For automated surveillance it iS Often desirable to condense these spectra into a rather limited number of quantities, which are characteristic for the spectral distributions. These quantities can then be used as discriminants for the actual monitoring. During the learning phase the 'normal values of tne discriminants are determinedas accurately as possible. During the monitoring phase, the discriminant values, as measured during certain sampling periods, are continuously comparedtothe normal values. A decision for action is taken on the basis of alert and alarm limits, respectively. During the learning period the behaviour of the discri- minants, in particular their fluctuations from sampling interval to sampling interval, can be used to adjust limiting criteria in order to avoidatoo high frequency of spurious alarms. Presently there are nonoise-based surveillance Systems that automatically interveneinthe process (e.g. via power setback or scram) in the case of an alarm level being exceeded. The criteria for setting alert and alarm limits are often difficult to fix because the actual safe operation limits for the process parameters and variables are not known. In addition to this, these values can of course not be determined experimentally by intentional introduction of unsafe operating conditions. Noise surveillan- ce should therefore be based on good engineering judgement, both with respect to definition of normal operation andtothe setting of alertandalarmlimits.

A further Step in the surveillance process is automated diagnosis of the cause of an alert or alarm limit crossing. For this purpose artificial intelligence is under development, which is based on indicating causes of

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abnormal process behaviour on the basis of the behaviour of a combination of discriminants. It is perhaps superfluous to state that the actual intelligence resides in the designers of the software; the term 'expert system' seems to be a better one, because it emphasizes that the software is in fact a collection of knowledge and experience of agroup of experts.

For the conversion of process signals into frequency dependent quantities, the well-established technique of Fast Fourier Transform is in Use as a general tool for noise analysis. There is a considerable development in the use of methods based on Auto Regression, which are particularly powerful for analysis of complicated multivariable systems via the technique of Noise Contribution Ratios. A recent development is Signal Transmission Path analysis. Whereas NCR analysis evaluates the contribution of a particular noise source to a variable of interest through all possible transmission paths together, it is claimed by the advocates that STP analysis reveals through which STPs fluctuations are transmitted from one variable to the other and which STPs play the most significantrolein characterising the measured power Spectral density of avariable. It is expectedthatautomated STP analysis Will

be developed that avoids the tedious visual examination of STP networks for all combinations of variables and may be a pOWerfU1 tool for diagnosis.

In the applications of AR methods, problems are often encountered in the non-perfect diagonalization of the noise source matrix when a particular STP is considerably faster than other ones. Another problem is the determination of Optimal model orders. The research that is presently done concerning the fundamentals of AR-analysis and the consequences of imposing an AR-model on an actual physical system, iS of high relevance for the practical applications.

Another point of interest is the rise of the so-called Least Squares AR method as a rival of the Yale Walker method. It is claimed that the LSAR method has, for equal sample size, a higher statistical accuracy than the YWARmethod which makes it especially suited as a 'small sample analysis method' for analyzing time-varying characteristics of noise. Application to resonance parameter and velocity determination has shown that the LSAR technique is a promising one for early detection of process anomalies.

A special form for time domain technique has recently bs!en introduced and is based on Hilbert transform. It breaks away from the traditional analysis methods which are all based on some type of averaging to reduce the effects of short-term variations. In this approach the short-term fluctuations are utilised in an attempt to extract information which is lost in the 'traditional' methods and thus it could be powerful for incipient failure detection.

An example of 'condensation' of spectral information into a limited number of discriminants is the set of eight discriminants developed by Piety. This set iS designed to detect specific features in power spectral density estimates and has been implemented in some surveillance system!;. It has been shown that the sensitivity of each discriminant to process changes depends on the physical phenomena causing the change (e.g. only a few discriminants seem to be useful for boiling detection).

Another important subject is the analysis of resonances in PSD's, e.g. vibration peaks in PWR spectra and the rather broad peak in BWR spectra which

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is the basis for assessment of reactor stability. Efficient methods for extracting the relevant resonance parameters (central frequency, total power, damping coefficient) are available.

Detection and diagnosis of process anomalies canbebasedonalert and alarm limits for individualdiscriminants but also on more complicated pattern recognition methods. Advanced methods, developed in the general field of signal analysis, are being implemented in the nuclear engineering field. Examples are diagnostics with incomplete learning sets, decision procedures using fuzzy classification concepts, etc.

5.3 PWR and LMFBR

Surveillance of PWR systems has reached a rather advanced state in recent years. Bany physical variables can be monitoredvia appropriate sensors and the insight into the meaning of Signal characteristics has increased considerably; in addition there is an increased application of surveillance to the sensors themselves. Sensor surveillance basedonnoiseanalysis offers the possibility to monitor relevant sensor properties without disturbing or interrupting its operation. Such relevant properties concern the static and dynamic behaviour that can deteriorate by changes in sensor materials (like gas filling of ion chambers), isolation reSistaWe, Cable capacities, connector qualities and properties of electronic devices.

Mechanical surveillance of pressure vessel internals is performed with accelerometers, excore and incore neutron detectors. In this way fuel element vibrations, core barreland thermal shield vibrations are monitored. By analysing the cross correlations between several detectors, the different vibration modes can be distinguished (beam mode and shell mode, direction of vibrations). In order to ease the interpretation it has become usual to start vibration analysis already in the construction phase of the plant. The knowledge of the influence of process conditions (e.g. temperatures, boron concentration) on spectral characteristics has increased considerably. In several other parts of the primary and secondary systems vibration measurements are done routinely (pumps, steam generators, turbine).

Loose parts monitoring as well as leak monitoring is based on the use of acoustic sensors in strategic positions (bottom of core pressure vessel and steam generators, pipes). A specific application in LMFBR's is monitoring of the pumps for cavitation. Many other process signals are used for surveillance of totalsystemperformance, suchas:

. system pressures

. water levels (pressurizer, steam generators)

. system flows (primary flow, steam generator feedwater flow and steam flow)

. temperatures (inlet, outlet)

Monitoring of sensor performance is mostly based on surveillance of the dynamic characteristics as well as mutual comparisons of noise levels. A special feature in LBFBR surveillance is the thermal hydraulic surveillance of the core. For this aspectreferenceis madetothe relevantpartof chapter 2.

A complete surveillance system is capable of handling some tens of process signals which implies that a large number of signals and signalcombi- nations must be analyzed. The system architecture can haves either the

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07310927

character of a distributed system or of a single computer system. In the former case the signals of groups of sensors (e.g. for vibration, loose parts and leakage monitoring respectively) are treated in separate dedicated processors, whereas system management, pattern recognition and expert decisions are performedby a central computer.

The present developments aim at more or less continuous monitoring in the sense of determination of relevant discriminants once or a few times per day. An important issue is the filing of baseline signaturr?s for normal operation and signatures in case of (developing) anomalies. This should form the basis for the statement of criteria for alert and alarm levels. Further development of surveillance systems is a matter of concerted effort by research groups, vendors and utilities. Particular attention should however be paid to an important conclusion drawn during the SMORN-IV meeting in 1984 by Saxe : 'The application of advanced computer methods to diagnoses etc. is entirely dependent on the initial reduction of the fluctuation signals to a usable form (e.g. frequency spectrum) and the possibilities of (surveillance and) diagnosis will be limited by the information inherently contained within this usable form. In every method of reduction, some information will be rejected or de-emphasised. Therefore, the more methodsthatare available, the more the choice of method may be made to fit in with the diagnostic goals of the whole system'.

In view of present developments it seems probable that future advances in surveillance techniques Will be concentrated in the field of signal analysis with time domain methods.

BWR surveillance is focussed on some particular diagnosis items which are related to the core and to the control systems. Incore (andin some plants excore) neutron detectors are Used for monitoring core reactivity stability (see also Chapter 6). Incore detectors also provide information about channel flow stability, flow distributions and possible instrument tube vibrations. Core stability is a typical BWR item connected to the two-phase flow. The interest in stability monitoring has increased recently since incentives exist for operating BWR's at reduced coolant flow in a spectral shift regime, by

which the operational flexibility is improved. Such operation mode however reduces core stability and thus asks for a proper determination of actual stability margins. This can be done by measuring the resonance parameters of the power spectral density of the neutron noise or the decay ratio in the associated correlation function. It has been shownthatone shouldbe careful with the latter method because in case of approximate pole-zero cancellation in the transfer function, the apparent decay ratio leads to over-estimation of stability margin. Another method for assessing stability is the analysis of the CoUpling between pressure noise and neutron noise, which requires multivariate autoregression analysis.

Controlsystemsurveillance is mostly based on monitoring of feedwater flow, recirculation flow, steam flow, system pressure and associatedactuators like control valves. Up to now most BWR surveillance is performed off-line. Multi-purpose on-line systems are under development, dedicated single-purpose monitors are in use for items like core stability and instrument tube vibrations.

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Historically the BWR has been the object for introduction and further development of tne application of AR methods in the reactor field, although since then useful applications to PWR's have also been demonstrated. This may be due to the fact that in a two-phase primary system the different subsystems are strongly connected which calls for amultivariate analysis and clear iden- tification of signal transmission paths. As a consequence, in the development of multi-purpose surveillance systems for BWR's, the effort should be concentrated in two directions: on the one hand further investigations of what physical information could be extracted by what types of sensors; on the other hand the implementation of advancedand efficient signal analysis methods.

:. .~

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07310029

---~-..-- ..- +--.~~--,----..---,------.

0 CA P3

Table D. Suuucary of 6831801 surveillance

i Survcillsnce ckject j Physical phencmena rlonitorcd i

f --- I I Thermccoupl~s Response time

-- I I !

Resistaxe thermometers i Response time I

1 Pressure transducers ic, remname bFi:sviour <in case j ; Response t;rv of connectl3n by lony; tubesj 1

/

Ionisation chambers / Statical and dynemical behaviour (filling! j gas, isolation resistance, cable 2nd con-! I nectars condition;

I

sdf-FOVErt?d detfCtOrS j Isclation resistance I

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Q731Cj034

6 SYSTEM DYNAMIC ANALYSIS

This section deals with the use of noise analysis for dynamic perfor- mancemonitoringof nuclear plants.

PRYSICAL OUARTITIES CONSIDERED

The major application of noise analysis for dynamic analysis has been in BWRs, with particular attention given to the measurement of trS.IISfer functions between such variables as steam dome pressure, neutron flux, and coolant flow. Measurement of stability margin and controlsysteminfluence on overall dynamics aretwomajorthrusts.

POSSIBLE ANOMALIES INVOLVED

Low overall core stability margin during low-flow operation as well as individual channel instabilities, have been addressed. By comparing measured transfer functions with model predictions, deficiencies in the dynamic models used for reactor licensing can be identified. Identification and subsequent reduction of noise on feedwater flow instrumentation signals have improved the precision of reactor power measurement.

SMSORS USED FOR DRTRCTIOR

Normal plant sensors have been used for noise measurements at BWRs. Neutron noise is obtained on acore average basis using the Average Power Range MOnitorS (APRM?.) and on a lOCal basis using the Local Power Range Monitors (LPRXS). Other Signals that have proven valuable for transfer function measurements are Steam dome pressure: steam, core coolant and feedwater flow-rates and reactor vessel water level,

CONDITIONS OF APPLICATION

As with all noise analyses, the measurements should be made while the reactor is in steady-state operation. Sufficient data must be acquired to obtain an unbiased estimate of stability margin (-30 min. for decay ratios less than 0.5; two or three min. for decay ratios near unity). Real time compu- tation and good accuracy are important when using noise analysis to help operators achieve conditions of increased stability.

FVTURE TRENDS

The use of noise analysis in BWRs can be expectedtoincrease, with the implementation of on-line stability monitors to guide operations at low flow. Noise measurements of stability marginwillbe used to address licensingques- tions, such as operation with higher performance fuel (which tends to decrease stabilitymargin)andextension ofallowedoperatingrange.

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RECOt%GFNDATIONS

Utilities

BWR owners should become familiar with the benefits of noise analysis by installing on-line stability monitors, thereby providing a stsbility margin baseline for all operating conditions encountered. A more ambitious program would include acquiring a complete baseline of noise signatures and so establish a basis for relaxation of licensing requirements that presently restrict plants' operational envelopes.

Manufacturers

Manufacturers can greatly aid the implementation of noi!;e analysis in BWRs by providing high-quality signals (isolated from control and protection systems) at patch panels, thereby permitting ready access to such signals as average and local flux, steam dome pressure , reactor vessel water level, and flow rates for steam, feedwater, and core coolant. Integration of reliable, accurate and real-time stability margin monitors in BWR control rooms will be valued by utility customers.

R&D Orsanizations

The noise analysis research community should continuetoidentifythe sources of noiseinBWRs and further improve the accuracy of BWRdynamic models through comparison of measured transfer functions withmodelpredictions. R&D organizations should develop real-time algorithms for measurement of stability margin.

Increased emphasis should be placed on the application of dynamic analysis for parameter inference in both fast reactors and PWRs, especially in the area of reactivity feedback.

Committee on Reactor Phvsics

NBACRP sho&d compile examples where the application of dynamic analy- ses has improved plant operation, and continue to aid utilities and licensing bodies in their assessment of noise analysis. The Committee should also distribute non-proprietary dynamic models and stability measurement algorithms to utilities and manufacturers, along with guidf?lines on the procedures to be employedinthe acquisition and interpretation of noise data.

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