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Fatigue monitoring in German nuclear power plants
Nuclear Engineering and Design 144 (1993) 409-421 North-Holland
409
Fatigue monitoring in German nuclear power plants H.-J. G o l e m b i e w s k i a n d M. Miksch Siemens A G Power Generation Group (KWU), Hammerbacherstr. 12 + 14, D-91050 Erlangen, Germany
Received 25 September 1992, revised version 20 May 1993
The paper presents the strategy followed for monitoring fatigue in German nuclear power plants. It discusses the essential loadings contributing to component fatigue. It describes an in-service fatigue monitoring approach with reference to the fatigue monitoring system FAMOS developed by Siemens-KWU.
I. Introduction
German nuclear power plants have by now run up service lives of between 4 and 23 years. As the mechanical components age, in Germany as well as worldwide [1-9] thought is being given to how the high availability we have come to expect from these plants can be preserved in the long term. From both economic and political aspects it appears expedient to install in good time, that is to say years or even decades in advance, the information sources that will one day be needed to provide the data base on which decisions can be taken as to the continuing serviceability of individual components or even of whole plants. This is all the more essential when the parameter most crucial to such a decision is a "variable of state", specifically cumulative material fatigue, which can be derived only from the component's loading history over long years of service. No other material property, not even radiation embrittlement, exhibits such a complex cumulative characteristic, one which, to this day, defies direct quantification by measurements performed on the material itself (despite tentative approaches by Seibold, Scheibe, ABmann [10]). The following is a description of the basic features of the strategy used in German nuclear power plants to achieve a realistic quantification of the material fatigue parameter. It discusses various aspects of that strategy, such as the loadings currently known to
* Extended and updated version of the presentation given at the SMiRT-11 Post-Conference Seminar No. 2, Assuring Structural Integrity of Steel Reactor Pressure Boundary Components, Taipei, Taiwan, August 26-28, 1991.
contribute to fatigue, the monitoring system used, and the procedure used to concentrate the large volumes of information gathered down to the target "variable of state".
2. Loads As part of the stress analysis carried out in the design process for each component, a fatigue analysis was performed on the basis of an assumed operating history. This assumed operating history was defined as a certain mode of plant operation, i.e. as a sequence of known transients of known frequencies of occurrence, and was laid down first in specifications and later in the operating manual. Definition of the transients included component-specific and transient-specific pressure and temperature histories intended to make enveloping allowance for the stress and fatigue implications of all transients potentially occurring in service. The analyses show that in normal operation the components are subject mainly to thermal loading. In piping of diameter greater than 100 mm, besides internal pressure other mechanical loadings, for example dynamic loadings such as vibration, are of only minor importance. Consider for instance the much discussed water hammer in the feedwater lines of steam generators. Our own experiments and theoretical analyses (Bouecke, Schwarz [11]) have shown pressure peaks not exceeding 23 bar in Siemens-KWU steam generators. Water hammer is also conceivable in other systems, depending on their design and mode of operation (Kim, Safwat, Van Duyne [12]).
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
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Closely related to material fatigue, the phenomenon of deterioration due to various corrosion mechanisms can not yet be monitored on-line because of a lack of suitable measurement data and damage correlations. The analysis makes allowance for corrosion indirectly via W6hler curves. Work is, however, going on at present to find suitable deterioration models that would make it possible to include the dominant corrosion parameters (electrochemical potentials, O 2 / H 2 concentrations etc., Lenz, Wieling [13]) in fatigue monitoring. The loadings making a major contribution to fatigue can be described with the aid of Fig. 1. The plot shows the pressure and temperature histories at an instrumentation plane in the horizontal region of the surge line of a pressurized water reactor during start-up. Two types of thermal loading over the pipe cross-section can be distinguished: - "slug f l o w " , with a rotationally symmetrical temperature field (see Magnification 1 on p. 411) and - "stratified f l o w " , with a vertically symmetrical temperature field (see Magnification 2 on p. 412).
The latter occurs under specific geometrical and thermohydraulic conditions which it would be beyond the scope of this paper to discuss (see Miksch, Lenz, L6hberg [14]). What is important in our present context is that an instrumentation plane in a vertical section of the same pipe only, say, one metre away would exhibit a completely different measured data profile, as stratified flow is not possible in vertical piping. It is thus evident that in-service loadings may be highly localized. For the sake of comparison, Fig, 1 also shows the pressure and temperature profiles in the surge line as specified for the "start-up" transient. Pronounced differences due to the specific operating mode of the plant and to the aforesaid local effects are apparent. The loading specifications drawn up for normal operation of the plant assume that all components of the plant are functioning perfectly; for instance that a valve that is closed is actually flow-tight. Figure 2 shows a plot from an instrumentation plane in the feedwater line at the nozzle of a steam generator in "hot standby" condition, i.e. with the feedwater valve
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closed. But since the valve is not flow-tight, complex, thermally driven secondary flows can be seen in the horizontal piping section downstream of the valve. The nearby steam generator acts as a heat source on the more or less pronounced feedwater leakage flow, which acts as a heat sink. Here, too, a highly localized temperature field deriving from a moderate stratified flow can be discerned. These thermal loads are examples of those monitored by the F A M O S fatigue monitoring system developed at Siemens-KWU. Typical of many others, they indicate that - the magnitude and frequency of occurrence of the loads are dependent on the specific mode of operation of the plant, - further loads may occur if components do not function properly, - loads may be highly localized. This makes it very difficult to gain an accurate picture of the momentary fatigue status of a component simply by extrapolating the fatigue analysis performed in the design phase. On the contrary, the examples show that
permanent in-service recording of relevant load data is essential if knowledge of the fatigue status of a component is to be kept up to date. It was with this in mind that we at Siemens-KWU developed the monitoring strategy described in the following and the associated fatigue monitoring system.
3. Strategy The fatigue monitoring strategy followed in German nuclear power plants is divided into a preparatory phase and three implementation stages. The preparatory phase, known as Stage 0, consists of drawing up a fatigue manual for the power plant in question. The fatigue manual identifies those components which, on the basis of the design calculations but also in the light of the local loadings known from operating experience, are expected to undergo fatigue more quickly than other components. The selection may be restricted to the components of the primary coolant pressure retaining boundary. But in the interests of overall plant
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H.-Z Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
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availability, it is now common practice to include some secondary-side systems, too. The fatigue-enhancing transients are identified separately for each component, and the parameters to be examined for fatigue monitoring are defined. These include parameters which are used to analyze the plant status. The instrumentation already in place for monitoring operation of the plant is used as far as possible. But in order to gain a realistic picture of localized loads, additional thermocouples have to be installed. The final step in the preparatory phase is the compilation of an instrumentation map. Thus, the fatigue manual gives information as to where, why and how. In implementation Stage 1, the data acquisition system is installed during a scheduled plant outage, generally during shutdown for inspection. As of this time, it delivers on-line load and system data. For reasons that will be explained in the following, however, these data are not evaluated on-line but go into long-term storage. Evaluation is performed at a later point in time, in Stage 2 at the load evaluation level and in Stage 3 at the stress and fatigue analysis level.
Figure 3 plots the cumulative usage factor U over the service life of a component to illustrate the procedure used in evaluation. It shows a typical case in which fatigue monitoring does not commence until after the component has been in operation for some time. At the time of commencement of fatigue monitoring, the fatigue status is known, i.e. U = 0, only if that point in time coincides with commissioning of the component. For this reason, it will in most cases be possible initially to determine only a usage factor increment, the fatigue rate a. The desired momentary material condition will be known only when the previous operating history, the area shaded gray in Fig. 3, has been analyzed. The fatigue fraction U0 then serves as an integration constant, as the starting point for continuous updating of the fatigue status, which is now being monitored on-line. Determining U0 involves analyzing control room logs, plotter charts, transient count lists and commissioning programs. Component-specific transients have to be correlated with individual usage factors and frequencies of occurrence. The differences in operating mode between the commissioning phase
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
(time period A) and the first years of on-line operation (time period B) have to be taken into account. Finally, on the basis of U0 and the fatigue rate a, a prognosis can be given as to the future progress of fatigue. The current margin to the acceptability limit U = 1 can be identified as a function of time. It is important to note that both U0 and a are significantly influenced not only by the actual time history of loading but also by the computation methods used. In this respect, a fatigue monitoring system such as that described in the following will have a normalizing effect, supplying comparable results thanks to implementation of standardized computation methods for all components and power plants. At first, however, on-line data acquisition generates a flood of information which can be meaningfully handled only by computerized analysis as an integral part of the fatigue monitoring system. If on-line fatigue monitoring is conceived as an information source, the
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copious original flow of data from which must be reduced in stages and as required to, ultimately, a single value, any economically viable strategy must exhibit a breakdown such as that illustrated in Fig. 4. Stage 1 collects all desired data on-line. Stage 2 is performed at intervals, when significant quantities of data have accumulated in Stage 1. The data are correlated by component and analyzed at the load level (temperatures, pressures). As the final step, in Stage 3, the fatigue history and ultimately the cumulative usage factor can be calculated for each component from the measured load profiles. This approach makes it possible to do only what is necessary, when it is necessary. The acquired data base remains intact in long-term storage. Significant information can be gained even at the load level in Stage 2 (as the examples given earlier show) and may prompt the plant operator to consider improving his plant operating practices and possibly even enable him to reduce the fatigue rate a in Fig. 3.
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Thus beneficial influence can be brought to bear on the plant's fatigue status even without that status having been explicitly identified.
4. The FAMOS fatigue monitoring system Siemens-KWU has implemented the requirements for a fatigue monitoring system deriving from such a strategy in FAMES. A separate functional unit consisting of hardware and software has been developed for each of the three stages (Fig. 5). The three functional units work independent of each other in time and space. The data acquisition unit runs on-line in the power plant. The data measured by the special FAMES instrumentation, at present temperatures only, are pro-
cessed together with the other plant operating data obtained from the plant computer (temperatures, pressures, water levels in vessels, flow rates, valve positions etc.) in a microprocessor system (Intel 320). The typical FAMES "data telegram", generated from a scan performed every ten seconds, contains about 300 items of measured data. These are checked for plausibility (self-monitoring feature) and are then stored in a loop memory on the hard disc, but only if at least one value has changed so much that it lies beyond a defined scatter band. The data acquisition station has a graphics screen and printer to display and print out measured data profiles for the previous 24 hours. The data are automatically transferred from loop memory to magnetic tape/optical disc every 12 hours. The magnetic tape/optical disc serves as the link to the "data evaluation" and "fatigue analysis" functional units.
H.oJ. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
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Data evaluation and later fatigue analysis are performed on personal computers (AT, 80386/387, 8 MB RAM, 150 MB HD, MS-DOS). Figure 6 shows the master menu for user guidance. Submenu 2 transfers the measured data from the magnetic tape/optical disc to the hard disc of the PC. Submenu 6 allows them to be displayed in color on screen (compare Figs. 1 and 2) according to certain selection criteria (instrumentation plane, physical unit). An expanded-scale function is provided for the time and parameter value axes. Plant statuses and operating modes can be analyzed and documented in this submenu. Submenu 3 permits visual comparison of the measured transients with the load-case-specific design transients stored for this purpose in the PC. In submenu 4, the load cases recognized in submenu 3 are stored by component and in
chronological order in a file known as the load case history list. In this way, regular evaluation of the measured data makes it possible to trace and record the loading history of certain components. In submenu 5, the list of transients can be printed out in accordance with various sort criteria. Even at this stage, it may already be possible to conclude that normal in-service loading of a certain component causes only negligible material fatigue. Since the visual analysis of measured data profiles is relatively time-consuming, a tool has been provided in submenu 7 to permit quick evaluation of the fatigue-related parameters in the period of observation for all components. The temperature and pressure profiles associated with the components arc examined for fluctuations by means of a rainflow algorithm (Matsuishi, Endo [15]) (Fig. 7). The result con-
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sists essentially of a list which identifies, for each component, the frequencies of occurrence of certain defined classes of temperature and pressure fluctuations (Fig. 8) The counts from sub-periods can be accumulated. Thus, these lists reveal very quickly periods in which individual components experienced no or only slight fatigue-related loads. Even if the time history of the temperature profiles, which is a major factor influencing the strain on the component, is not evident from the count output from quick evaluation, the frequency of occurrence and magnitude of AT and Ap nevertheless give some indication that unusual events have occurred. After quick evaluation of a sub-
period of, say, the length of one magnetic tape, a session of about 10 minutes, it is sufficient to follow up these clues with a graphic display of the corresponding measured data profiles. This facilitates economic data reduction as early as at the load level. Stage 3, the fatigue analysis proper, is necessary only if Stage 2 has identified significant loadings. The fatigue analysis converts the pressure and temperature profiles measured for pre-defined locations at the component into stress profiles. The procedures used to calculate the stresses from the thermal loading effects described earlier are matched to the capacity of the PC. The stress fractions resulting from slug flow, tem-
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
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perature stratification, internal pressure and any section forces and moments possibly present are added as shown in Figure 9 to give the total stress. The time histories of the stress intensities are evaluated by means of the rainflow algorithm (Matsuishi, Endo [15]), otherwise, however, in accordance with the applicable codes and standards (KTA [16], ASME [17]). The fatigue fractions resulting from the stress cycles recognized are taken from the design fatigue curves (KTA [16], ASME [17]) and accumulated by Miner's linear method [18]. The output of the calculation is the partial usage factors AU in the period of observation At for various locations at the component. If the cumulative usage factor U0 at the time of commencement of monitoring is known (refer to Fig. 3), the momentary fatigue status U can be obtained as the sum of U0 and all the partial usage factors AU/ hitherto calculated, i.e. U = U0 +
FAMOS functional units
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
52AUi. T h e n the fatigue rate a = A U / A t can be applied to extrapolate the cumulative usage factor at any time in the future ( c o m p a r e Fig. 3). T h e F A M O S fatigue analysis software can be configurated for various c o m p o n e n t geometries (nozzles, vessels, tube sheets, p u m p and valve bodies). T h e effort involved consists of the pre-calculation of stress responses to s t a n d a r d transients. T h e s e are stored on the PC as baseline p a r a m e t e r s in the configuration data file, known as the c o m p o n e n t file. T h e c o m p o n e n t file also contains geometry and material data, comp u t e r run control data, and user guidance data. This makes it possible to a d a p t the system to m a n y different c o m p o n e n t geometries. It also makes it possible to reduce the conservatisms c o n t a i n e d in conventional fatigue analyses such as - use of global specified load transients, - use of n o n - c o n t i n u o u s calculation m e t h o d s (calculation t r a n s i e n t by transient), - estimated frequencies of occurrence for transients, - c o m b i n a t i o n of transients to maximize d a m a g e effects, as described in K T A [16] a n d A S M E [17]. It also m a k e s it very simple to calculate individual usage factors for specific transients taking into account the m e a s u r e d loading history. T h e initial cumulative usage factor U 0 described earlier (Fig. 3) can be determ i n e d by addition of the partial usage factors from the transients t h a t have o c c u r r e d in the past. It is also possible to input simulated t e m p e r a t u r e and pressure histories to investigate how a c h a n g e in o p e r a t i n g mode, o t h e r transient time histories, or a design c h a n g e would affect the fatigue p e r f o r m a n c e of the c o m p o n e n t . T h u s the system can be of a d v a n t a g e as early ase in the c o m p o n e n t design stage.
5. S u m m a r y
T h e strategy followed for fatigue m o n i t o r i n g in German nuclear power plants comprises a p r e p a r a t o r y phase a n d the t h r e e i m p l e m e n t a t i o n stages data acquisition, data evaluation, a n d fatigue analysis. T h e measured data flow is r e d u c e d in t h r e e steps down to the cumulative usage factor of the individual c o m p o n e n t . T h e t h r e e steps are i m p l e m e n t e d in t h r e e mutually i n d e p e n d e n t functional units within the F A M O S fatigue m o n i t o r i n g system. T h e system h a r d w a r e and software can be a d a p t e d to various in-plant configurations. Fatigue m o n i t o r i n g provides useful information even before the cumulative usage factor has actually b e e n calculated. T h e possible applications for fatigue analysis by m e a n s of the F A M O S system go far beyond
just the analysis of m e a s u r e d data. F A M O S is already in use in o n e or o t h e r stage of i m p l e m e n t a t i o n in most G e r m a n nuclear power plants (Fig. 10).
References
[1] M. Miksch, Betriebsbegleitende Ermiidungsflberwachung yon Kraftwerkskomponenten, Atomenergie-Kerntechnik, 47 Nr. 1 (1985) 20-22, in German. [2] M. Miksch et al., FAMOS - a tool for transient recording and fatigue monitoring, in: Life Extension and Assessment: Nuclear and Fossil Power Plant Components, ed. C.E. Jaske et al., American Society of Mechanical Engineers. PVP-Vol. 138/NDE-Vol. 4 (1988). [3] A.Y. Kuo et al., An on-line fatigue monitoring system for power plants: Part 1 - Direct calculation of transient peak stress through transfer matrices and Green's functions, in: Design and Analysis Methods for Plant Life Assessment, ed. T.V. Narayanan and S. Palusamy, American Society of Mechanical Engineers, PVP-Vol. 112 (1986). [4] S.S. Tang et al., An on-line fatigue monitoring system for power plants: Part 2 - Development of a personal computer based system for fatigue monitoring, in: Design and Analysis Methods for Plant Life Assessment, ed. T.V. Narayanan and S. Palusamy, American Society of Mechanical Engineers. PVP-Vol. 112 (1986). [5] G. Bimont and G. Cordier, Developments in EDF policy with regard to monitoring of the aging factor in PWR NSSS, in: International Nuclear Power Plant Aging Symposium, Bethesda, Maryland, Aug. 30 to Sept. I, 1988. [6] G. Bimont and G. Cordier, A new approach for NSSS fatigue life assessment, in: Performance and Life Extension of Operating Reactors, ed. A.H. Hadjian, Transactions of the 10th International Conference on Structural Mechanics in Reactor Technology, Vol. D, 1989. [7] L. Lazzeri et al., SAUL program for on-line analysis of stresses and fatigue on structures, in: Performance and Life Extension of Operating Reactors, ed. A.H. Hadjian, Transactions of the 10th International Conference on Structural Mechanics in Reactor Technology, Vol. D, 1989. [8] S. Masamori et al., R&D status on continuous monitoring of plant components, in: Nuclear Power Life Extension, Proceedings of Topical Meeting Sponsored by American Nuclear Society, Evergreen Nuclear Society and Atomic Energy Society of Japan, Snowbird, Utah, July 31 to Aug. 3, 1988. [9] Y. Takahashi et al., Application of plant data acquisition system to Kashiwazaki-Kariwa NPS Units 3 and 4, in: Transactions of the l l t h International Conference on Structural Mechanics in Reactor Technology, Tokyo, Japan. Aug. 1991, Vol. D. pp. 359-364. [10] A. Seibold, A. Scheibe, H.-D. ABmann, Determination of the usage factor of components after cyclic k)ading using
H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs high-resolution microstructural investigations, 15th MPA-Seminar, 5-6, Oktober 1989, Staatliche Materialpriifungsanstalt Stuttgart, Vol. 1. Paper No. 8, in German. [11] R. Bouecke, T. Schwarz, Probability and effects of anticipated water hammer events in the feedwater line inside the KWU-steam generator, First Int. Symposium on Power Plant Transients 1987, The Winter Annual Meeting of the ASME, Chicago, III., Nov. 27-Dec. 2, 1988, FED-Vol. 67, pp. 49-51. [12] J.H. Kim, H.H. Safwat, D.A. Van Duyne, Water hammer program and progress in the nuclear industry, First Int. Symposium on Power Plant Transients 1987, The Winter Annual Meeting of the ASME, Chicago, III., Nov. 27Dec. 2, 1988, FED-Vol. 67, pp. 65-69. [13] E. Lenz, N. Wieling, RiBkorrosion in Kraftwerksystemen Ihre Abhilfemal3nahmen und M6glichkeiten der OnLine-15berwachung, 17. Metallfachtagung, Dresden, 1990, in German. -
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[14] M. Miksch. E. Lenz, R. L6hberg, Loading conditions in horizontal feedwater pipes of LWR's influenced by thermal shock and thermal stratification, 9th MPA Seminar. Staatliche Materialpriifungsanstalt Stuttgart, 1983, in German. [15] M. Matsuishi and T. Endo, Fatigue of metals subjected to varying stresses, Kyushu District Meeting of the Japanese Society of Mechanical Engineers, March 1968, also: T. Endo et al., Damage evaluation of metals for random or varying loading, Proceedings of the 1974 Symposium on Mechanical Behavior of Materials, Vol. 1, The Society of Material Science. Japan, 1974, pp, 371-380. [16] Sicherheitstechnische Regeln des Kerntechnischen Ausschusses, KTA 3201.2, Fassung 3/84. [17] American Society of Mechanical Engineers, ASME Section III, Division 1, Subsection NB, NB 3000 (Edition 1989). [18] M.A. Miner, Cumulative damage in fatigue, ASME Journal of Applied Mechanics (Sept. 1945) pp. A159-A164.
409
Fatigue monitoring in German nuclear power plants H.-J. G o l e m b i e w s k i a n d M. Miksch Siemens A G Power Generation Group (KWU), Hammerbacherstr. 12 + 14, D-91050 Erlangen, Germany
Received 25 September 1992, revised version 20 May 1993
The paper presents the strategy followed for monitoring fatigue in German nuclear power plants. It discusses the essential loadings contributing to component fatigue. It describes an in-service fatigue monitoring approach with reference to the fatigue monitoring system FAMOS developed by Siemens-KWU.
I. Introduction
German nuclear power plants have by now run up service lives of between 4 and 23 years. As the mechanical components age, in Germany as well as worldwide [1-9] thought is being given to how the high availability we have come to expect from these plants can be preserved in the long term. From both economic and political aspects it appears expedient to install in good time, that is to say years or even decades in advance, the information sources that will one day be needed to provide the data base on which decisions can be taken as to the continuing serviceability of individual components or even of whole plants. This is all the more essential when the parameter most crucial to such a decision is a "variable of state", specifically cumulative material fatigue, which can be derived only from the component's loading history over long years of service. No other material property, not even radiation embrittlement, exhibits such a complex cumulative characteristic, one which, to this day, defies direct quantification by measurements performed on the material itself (despite tentative approaches by Seibold, Scheibe, ABmann [10]). The following is a description of the basic features of the strategy used in German nuclear power plants to achieve a realistic quantification of the material fatigue parameter. It discusses various aspects of that strategy, such as the loadings currently known to
* Extended and updated version of the presentation given at the SMiRT-11 Post-Conference Seminar No. 2, Assuring Structural Integrity of Steel Reactor Pressure Boundary Components, Taipei, Taiwan, August 26-28, 1991.
contribute to fatigue, the monitoring system used, and the procedure used to concentrate the large volumes of information gathered down to the target "variable of state".
2. Loads As part of the stress analysis carried out in the design process for each component, a fatigue analysis was performed on the basis of an assumed operating history. This assumed operating history was defined as a certain mode of plant operation, i.e. as a sequence of known transients of known frequencies of occurrence, and was laid down first in specifications and later in the operating manual. Definition of the transients included component-specific and transient-specific pressure and temperature histories intended to make enveloping allowance for the stress and fatigue implications of all transients potentially occurring in service. The analyses show that in normal operation the components are subject mainly to thermal loading. In piping of diameter greater than 100 mm, besides internal pressure other mechanical loadings, for example dynamic loadings such as vibration, are of only minor importance. Consider for instance the much discussed water hammer in the feedwater lines of steam generators. Our own experiments and theoretical analyses (Bouecke, Schwarz [11]) have shown pressure peaks not exceeding 23 bar in Siemens-KWU steam generators. Water hammer is also conceivable in other systems, depending on their design and mode of operation (Kim, Safwat, Van Duyne [12]).
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
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Closely related to material fatigue, the phenomenon of deterioration due to various corrosion mechanisms can not yet be monitored on-line because of a lack of suitable measurement data and damage correlations. The analysis makes allowance for corrosion indirectly via W6hler curves. Work is, however, going on at present to find suitable deterioration models that would make it possible to include the dominant corrosion parameters (electrochemical potentials, O 2 / H 2 concentrations etc., Lenz, Wieling [13]) in fatigue monitoring. The loadings making a major contribution to fatigue can be described with the aid of Fig. 1. The plot shows the pressure and temperature histories at an instrumentation plane in the horizontal region of the surge line of a pressurized water reactor during start-up. Two types of thermal loading over the pipe cross-section can be distinguished: - "slug f l o w " , with a rotationally symmetrical temperature field (see Magnification 1 on p. 411) and - "stratified f l o w " , with a vertically symmetrical temperature field (see Magnification 2 on p. 412).
The latter occurs under specific geometrical and thermohydraulic conditions which it would be beyond the scope of this paper to discuss (see Miksch, Lenz, L6hberg [14]). What is important in our present context is that an instrumentation plane in a vertical section of the same pipe only, say, one metre away would exhibit a completely different measured data profile, as stratified flow is not possible in vertical piping. It is thus evident that in-service loadings may be highly localized. For the sake of comparison, Fig, 1 also shows the pressure and temperature profiles in the surge line as specified for the "start-up" transient. Pronounced differences due to the specific operating mode of the plant and to the aforesaid local effects are apparent. The loading specifications drawn up for normal operation of the plant assume that all components of the plant are functioning perfectly; for instance that a valve that is closed is actually flow-tight. Figure 2 shows a plot from an instrumentation plane in the feedwater line at the nozzle of a steam generator in "hot standby" condition, i.e. with the feedwater valve
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closed. But since the valve is not flow-tight, complex, thermally driven secondary flows can be seen in the horizontal piping section downstream of the valve. The nearby steam generator acts as a heat source on the more or less pronounced feedwater leakage flow, which acts as a heat sink. Here, too, a highly localized temperature field deriving from a moderate stratified flow can be discerned. These thermal loads are examples of those monitored by the F A M O S fatigue monitoring system developed at Siemens-KWU. Typical of many others, they indicate that - the magnitude and frequency of occurrence of the loads are dependent on the specific mode of operation of the plant, - further loads may occur if components do not function properly, - loads may be highly localized. This makes it very difficult to gain an accurate picture of the momentary fatigue status of a component simply by extrapolating the fatigue analysis performed in the design phase. On the contrary, the examples show that
permanent in-service recording of relevant load data is essential if knowledge of the fatigue status of a component is to be kept up to date. It was with this in mind that we at Siemens-KWU developed the monitoring strategy described in the following and the associated fatigue monitoring system.
3. Strategy The fatigue monitoring strategy followed in German nuclear power plants is divided into a preparatory phase and three implementation stages. The preparatory phase, known as Stage 0, consists of drawing up a fatigue manual for the power plant in question. The fatigue manual identifies those components which, on the basis of the design calculations but also in the light of the local loadings known from operating experience, are expected to undergo fatigue more quickly than other components. The selection may be restricted to the components of the primary coolant pressure retaining boundary. But in the interests of overall plant
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H.-Z Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
412
availability, it is now common practice to include some secondary-side systems, too. The fatigue-enhancing transients are identified separately for each component, and the parameters to be examined for fatigue monitoring are defined. These include parameters which are used to analyze the plant status. The instrumentation already in place for monitoring operation of the plant is used as far as possible. But in order to gain a realistic picture of localized loads, additional thermocouples have to be installed. The final step in the preparatory phase is the compilation of an instrumentation map. Thus, the fatigue manual gives information as to where, why and how. In implementation Stage 1, the data acquisition system is installed during a scheduled plant outage, generally during shutdown for inspection. As of this time, it delivers on-line load and system data. For reasons that will be explained in the following, however, these data are not evaluated on-line but go into long-term storage. Evaluation is performed at a later point in time, in Stage 2 at the load evaluation level and in Stage 3 at the stress and fatigue analysis level.
Figure 3 plots the cumulative usage factor U over the service life of a component to illustrate the procedure used in evaluation. It shows a typical case in which fatigue monitoring does not commence until after the component has been in operation for some time. At the time of commencement of fatigue monitoring, the fatigue status is known, i.e. U = 0, only if that point in time coincides with commissioning of the component. For this reason, it will in most cases be possible initially to determine only a usage factor increment, the fatigue rate a. The desired momentary material condition will be known only when the previous operating history, the area shaded gray in Fig. 3, has been analyzed. The fatigue fraction U0 then serves as an integration constant, as the starting point for continuous updating of the fatigue status, which is now being monitored on-line. Determining U0 involves analyzing control room logs, plotter charts, transient count lists and commissioning programs. Component-specific transients have to be correlated with individual usage factors and frequencies of occurrence. The differences in operating mode between the commissioning phase
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
(time period A) and the first years of on-line operation (time period B) have to be taken into account. Finally, on the basis of U0 and the fatigue rate a, a prognosis can be given as to the future progress of fatigue. The current margin to the acceptability limit U = 1 can be identified as a function of time. It is important to note that both U0 and a are significantly influenced not only by the actual time history of loading but also by the computation methods used. In this respect, a fatigue monitoring system such as that described in the following will have a normalizing effect, supplying comparable results thanks to implementation of standardized computation methods for all components and power plants. At first, however, on-line data acquisition generates a flood of information which can be meaningfully handled only by computerized analysis as an integral part of the fatigue monitoring system. If on-line fatigue monitoring is conceived as an information source, the
413
copious original flow of data from which must be reduced in stages and as required to, ultimately, a single value, any economically viable strategy must exhibit a breakdown such as that illustrated in Fig. 4. Stage 1 collects all desired data on-line. Stage 2 is performed at intervals, when significant quantities of data have accumulated in Stage 1. The data are correlated by component and analyzed at the load level (temperatures, pressures). As the final step, in Stage 3, the fatigue history and ultimately the cumulative usage factor can be calculated for each component from the measured load profiles. This approach makes it possible to do only what is necessary, when it is necessary. The acquired data base remains intact in long-term storage. Significant information can be gained even at the load level in Stage 2 (as the examples given earlier show) and may prompt the plant operator to consider improving his plant operating practices and possibly even enable him to reduce the fatigue rate a in Fig. 3.
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Thus beneficial influence can be brought to bear on the plant's fatigue status even without that status having been explicitly identified.
4. The FAMOS fatigue monitoring system Siemens-KWU has implemented the requirements for a fatigue monitoring system deriving from such a strategy in FAMES. A separate functional unit consisting of hardware and software has been developed for each of the three stages (Fig. 5). The three functional units work independent of each other in time and space. The data acquisition unit runs on-line in the power plant. The data measured by the special FAMES instrumentation, at present temperatures only, are pro-
cessed together with the other plant operating data obtained from the plant computer (temperatures, pressures, water levels in vessels, flow rates, valve positions etc.) in a microprocessor system (Intel 320). The typical FAMES "data telegram", generated from a scan performed every ten seconds, contains about 300 items of measured data. These are checked for plausibility (self-monitoring feature) and are then stored in a loop memory on the hard disc, but only if at least one value has changed so much that it lies beyond a defined scatter band. The data acquisition station has a graphics screen and printer to display and print out measured data profiles for the previous 24 hours. The data are automatically transferred from loop memory to magnetic tape/optical disc every 12 hours. The magnetic tape/optical disc serves as the link to the "data evaluation" and "fatigue analysis" functional units.
H.oJ. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
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H.-Z Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
Data evaluation and later fatigue analysis are performed on personal computers (AT, 80386/387, 8 MB RAM, 150 MB HD, MS-DOS). Figure 6 shows the master menu for user guidance. Submenu 2 transfers the measured data from the magnetic tape/optical disc to the hard disc of the PC. Submenu 6 allows them to be displayed in color on screen (compare Figs. 1 and 2) according to certain selection criteria (instrumentation plane, physical unit). An expanded-scale function is provided for the time and parameter value axes. Plant statuses and operating modes can be analyzed and documented in this submenu. Submenu 3 permits visual comparison of the measured transients with the load-case-specific design transients stored for this purpose in the PC. In submenu 4, the load cases recognized in submenu 3 are stored by component and in
chronological order in a file known as the load case history list. In this way, regular evaluation of the measured data makes it possible to trace and record the loading history of certain components. In submenu 5, the list of transients can be printed out in accordance with various sort criteria. Even at this stage, it may already be possible to conclude that normal in-service loading of a certain component causes only negligible material fatigue. Since the visual analysis of measured data profiles is relatively time-consuming, a tool has been provided in submenu 7 to permit quick evaluation of the fatigue-related parameters in the period of observation for all components. The temperature and pressure profiles associated with the components arc examined for fluctuations by means of a rainflow algorithm (Matsuishi, Endo [15]) (Fig. 7). The result con-
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H.-J. GolembiewskL M. Miksch / Fatigue monitoring in German NPPs
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
sists essentially of a list which identifies, for each component, the frequencies of occurrence of certain defined classes of temperature and pressure fluctuations (Fig. 8) The counts from sub-periods can be accumulated. Thus, these lists reveal very quickly periods in which individual components experienced no or only slight fatigue-related loads. Even if the time history of the temperature profiles, which is a major factor influencing the strain on the component, is not evident from the count output from quick evaluation, the frequency of occurrence and magnitude of AT and Ap nevertheless give some indication that unusual events have occurred. After quick evaluation of a sub-
period of, say, the length of one magnetic tape, a session of about 10 minutes, it is sufficient to follow up these clues with a graphic display of the corresponding measured data profiles. This facilitates economic data reduction as early as at the load level. Stage 3, the fatigue analysis proper, is necessary only if Stage 2 has identified significant loadings. The fatigue analysis converts the pressure and temperature profiles measured for pre-defined locations at the component into stress profiles. The procedures used to calculate the stresses from the thermal loading effects described earlier are matched to the capacity of the PC. The stress fractions resulting from slug flow, tem-
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
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perature stratification, internal pressure and any section forces and moments possibly present are added as shown in Figure 9 to give the total stress. The time histories of the stress intensities are evaluated by means of the rainflow algorithm (Matsuishi, Endo [15]), otherwise, however, in accordance with the applicable codes and standards (KTA [16], ASME [17]). The fatigue fractions resulting from the stress cycles recognized are taken from the design fatigue curves (KTA [16], ASME [17]) and accumulated by Miner's linear method [18]. The output of the calculation is the partial usage factors AU in the period of observation At for various locations at the component. If the cumulative usage factor U0 at the time of commencement of monitoring is known (refer to Fig. 3), the momentary fatigue status U can be obtained as the sum of U0 and all the partial usage factors AU/ hitherto calculated, i.e. U = U0 +
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H.-J. Golembiewski, M. Miksch / Fatigue monitoring in German NPPs
52AUi. T h e n the fatigue rate a = A U / A t can be applied to extrapolate the cumulative usage factor at any time in the future ( c o m p a r e Fig. 3). T h e F A M O S fatigue analysis software can be configurated for various c o m p o n e n t geometries (nozzles, vessels, tube sheets, p u m p and valve bodies). T h e effort involved consists of the pre-calculation of stress responses to s t a n d a r d transients. T h e s e are stored on the PC as baseline p a r a m e t e r s in the configuration data file, known as the c o m p o n e n t file. T h e c o m p o n e n t file also contains geometry and material data, comp u t e r run control data, and user guidance data. This makes it possible to a d a p t the system to m a n y different c o m p o n e n t geometries. It also makes it possible to reduce the conservatisms c o n t a i n e d in conventional fatigue analyses such as - use of global specified load transients, - use of n o n - c o n t i n u o u s calculation m e t h o d s (calculation t r a n s i e n t by transient), - estimated frequencies of occurrence for transients, - c o m b i n a t i o n of transients to maximize d a m a g e effects, as described in K T A [16] a n d A S M E [17]. It also m a k e s it very simple to calculate individual usage factors for specific transients taking into account the m e a s u r e d loading history. T h e initial cumulative usage factor U 0 described earlier (Fig. 3) can be determ i n e d by addition of the partial usage factors from the transients t h a t have o c c u r r e d in the past. It is also possible to input simulated t e m p e r a t u r e and pressure histories to investigate how a c h a n g e in o p e r a t i n g mode, o t h e r transient time histories, or a design c h a n g e would affect the fatigue p e r f o r m a n c e of the c o m p o n e n t . T h u s the system can be of a d v a n t a g e as early ase in the c o m p o n e n t design stage.
5. S u m m a r y
T h e strategy followed for fatigue m o n i t o r i n g in German nuclear power plants comprises a p r e p a r a t o r y phase a n d the t h r e e i m p l e m e n t a t i o n stages data acquisition, data evaluation, a n d fatigue analysis. T h e measured data flow is r e d u c e d in t h r e e steps down to the cumulative usage factor of the individual c o m p o n e n t . T h e t h r e e steps are i m p l e m e n t e d in t h r e e mutually i n d e p e n d e n t functional units within the F A M O S fatigue m o n i t o r i n g system. T h e system h a r d w a r e and software can be a d a p t e d to various in-plant configurations. Fatigue m o n i t o r i n g provides useful information even before the cumulative usage factor has actually b e e n calculated. T h e possible applications for fatigue analysis by m e a n s of the F A M O S system go far beyond
just the analysis of m e a s u r e d data. F A M O S is already in use in o n e or o t h e r stage of i m p l e m e n t a t i o n in most G e r m a n nuclear power plants (Fig. 10).
References
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