Determination of High-Risk Zones for Local Wall Thinning due to Flow-Accelerated Corrosion

Transcription

1 E-Journal of Advanced Maintenance Vol.5- () - Japan Society of Maintenology Determination of High-Risk Zones for Local Wall Thinning due to Flow-Accelerated Corrosion Shunsuke UCHIDA,*, Masanori NAITOH, Hidetoshi OKADA, Hiroaki SUZUKI, Yoshiyuki TSUJI, Seiichi KOSHIDUKA and Derek H. LISTER Institute of Applied Energy, -- Nishi-Shimbashi, Minato-ku, Tokyo 5-, Japan Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 6-86, Japan University of Tokyo7--, Hongo, Bunkyo-ku, Tokyo, -8656, Japan University of New Brunswick, PO Box, Fredericton, NB, Canada, EB 5A ABSTRACT Thousands of flow-accelerated corrosion (FAC)-possible zones cause long and costly inspection procedures for nuclear power plants as well as fossil power plants. In order to narrow down the number of inspection zones, a speedy and easy-to-handle tool for determination of FAC risk zones, a D FAC code, was developed. FAC risk was defined as the mathematical product of the possibility of wall thinning occurrence and its hazard scale. The local maximum thinning rate could be predicted with accuracy within a factor of with the D FAC code. High FAC risk zones and high priority locations for thinning monitoring along entire cooling systems and the effects of countermeasures on mitigating the risks could be evaluated within a small amount of computer time. The fusion of prediction and monitoring might go well to improve plant performance. KEYWORDS FAC, wall thinning, monitoring, mass transfer coefficient, temperature, ph, O, risk analysis ARTICLE INFORMATION Article history: Received 5 November Accepted June. Introduction (Arial, pt) Flow-accelerated corrosion (FAC) of condensate and feed water piping is still one of the key issues in determining the reliability of aged nuclear power plants (NPPs) as well as fossil fuelled power plants (FPPs) [-]. Early detection and prediction of FAC along major piping systems and application of suitable countermeasures such as water chemistry improvements are essential for preventing pipe rupture in aged plants []. There are generally two approaches to evaluating further wall thinning in FAC-affected zones; one is based on inspection and the other on prediction or estimation. Thousands of FAC-possible zones cause long and costly inspection procedures for plants, even if the number of zones is minimized on the basis of temperature and flow velocity. In order to narrow down the number of inspection zones, suitable prediction or estimation procedures for FAC occurrence should be applied and the resulting computer programs tuned with as many inspection data as possible. Such coupling of the estimation and inspection procedures should lead to effective and reliable preparation against FAC occurrence and propagation. Indeed, following the pipe rupture in the condensate water line at Mihama-, the Nuclear and Industrial Safety Agency (NISA) of Japan has promoted parallel inspection and estimation approaches to FAC and has just started a project on advanced management of pipe wall thinning based on a combined technology of estimation and inspection [5]. Many basic equations related to FAC have already been reported [6-8]. A computer simulation code for FAC has been prepared for both evaluations of FAC occurrence zones and FAC rates based on the previously reported numerical equations [9-]. Computer program packages for FAC evaluation, e.g., CHECWORKS, WATHEC and BRT-CICERO, have been available for many years and their accuracy and applicability have been confirmed [-7]. Unfortunately, details of their theoretical basis and of the data bases of the program packages are classified due to intellectual property rights. Both traceability of the computer program package and its validation are required for making policy on plant reliability when applying the package calculations. The authors are developing computer simulation codes based on 6-step evaluation procedures for FAC * Corresponding author, suchida@iae.or.jp ISSN / JSM and the authors. All rights reserved.

2 occurrence and wall thinning rate of NPPs and trying to publish their basic equations, major constants for calculation and the results for their validation [9-]. A six-step procedure to estimate local wall thinning due to FAC is proposed as one part of the coupled approach [-]. As a result of a V&V (verification and validation method) evaluation based on a comparison of calculated and measured wall thinning, it was confirmed that zones of high FAC risk could be identified with satisfactory safety margins via first three steps, and then, wall thinning rates could be predicted with an accuracy within a factor of. It was also confirmed that residual wall thicknesses after one year operation could be estimated with an error less than % [8-]. Based on previous estimates of residual pipe wall thicknesses and evaluations of the effects of water chemistry on major materials in PWR secondary systems, O injection into the condensate water was planned and successfully carried out at a PWR plant in Japan [, ], One of the disadvantages of the D FAC code was in D computational fluid dynamics (CFD) analysis, which required a lot of computational time and memory. In order to avoid individual variation for determination of FAC occurrence, the computer program packages for FAC occurrence evaluation from Step through were reassembled. The other purpose for developing the code reassembling step through Step was to prepare a speedy and easy-to-handle FAC code based on D CFD analysis and to apply it to the whole plant system in a restricted computer time in order to point out the locations where future problems might occur, pipe inspections should be required and early implementation countermeasures should be done []. For this purpose, not only the probability of serious wall thinning occurrence in the future but also a hazard scale of pipe rupture due to the serious wall thinning should be analyzed. FAC risk was defined as the mathematical product of the possibility of serious wall thinning occurrence and its hazard scale. In this paper, computer code packages of determination procedures for high FAC risk zones based on the D FAC code are introduced and determination processes for high FAC risk zones are demonstrated.. WALL THINNING DUE TO FAC.. Major Problems Related to Structural Materials Major subjects related to materials in cooling systems and material atlases of pressurized water reactors (PWRs) and boiling water reactors (BWRs) are shown in Fig. []. Stress corrosion cracking (SCC), e.g., intergranular SCC (IGSCC) for BWRs and primary water SCC (PWSCC) for PWRs, is one of the most frequently reported material problems for nuclear power plants but no serious accidents related to it have ever been reported. Defects of steam generator tubing often interrupt PWR plant operation but they have never caused a serious accident. Copper alloy heater tubes are applied for some PWRs, while stainless tubes are applied for most BWRs to mitigate corrosion product input into the reactors. In each system, uniformly controlled cooling water is in contact with different materials, which complicates corrosion problems. Corrosion behaviors are much affected by water qualities and differ according to the values of water qualities and the materials themselves. primary cooling system secondary cooling system Major materials moisture separator stainless steel steam generator HP turbine carbon steel reactor LP turbine nickel base alloy pressure vessel moisture separator pressurizer HP turbine zirconium alloy 5 copper alloy/ titanium fuel LP turbine reactor assemblies 5 pressure condenser vessel 6 condenser heater drain Problems related to corrosion heater drain 6 fuel 6 pre-filter : zirconium corrosion assembly demineralizer : SG tube defects : IGSCC/PWSCC HP LP : FAC HP LP heater heater 5 heater heater : LDI (erosion) a) PWR 6 : LDI (corrosion) b) BWR Fig. Major subjects related to materials in cooling systems of nuclear power plants FAC in single-phase flow has caused two serious accidents with PWRs [, ]. It has not led to serious damage in BWR feed water piping due to continuous oxygen addition []. FAC in two-phase flow used to be a serious problem in heater drain lines in BWRs but it was mitigated by replacing carbon steel with chromium containing low alloy steel, and it was not so serious a problem in PWR heater drain lines due to the higher ph in them. But FAC in two-phase flow in heater drain lines under increasing steam quality is much

3 E-Journal of Advanced Maintenance Vol.5- () - Japan Society of Maintenology affected by droplet impingement on the pipe inner surface. The phenomenon is designated as liquid droplet impingement (LDI). LDI is divided into two types; one is determined by a mechanical process (designated as LDI (erosion) and the other is determined by a corrosion process (designated as LDI (corrosion)). LDI on the turbine blades is a typical pattern of LDI (erosion), which is often mitigated by improving surface hardness, e.g., application of stellite alloy coating. The final stage of heater drain lines with rather low steam velocity is subject to LDI (corrosion), while the stage with rather high steam velocity is subject to LDI (erosion). In the case of LDI, even if there are small holes, lower pressure in the piping than the ambient one results in in-leakage but not out-leakage, which does not cause serious environmental damage. From the viewpoint of plant risk, FAC is much more important than LDI, though any LDI problem should be reported to the government with detailing its roof cause and countermeasures for avoiding the same kind of problems in the future [5]... Major Parameters to Determine FAC FAC is determined by six parameters [-]. The thickness of the boundary layer is much affected by flow dynamics. Chromium content in the steel is another important parameter to determine FAC. Solubility of ferrous ion, which is also an important parameter to determine FAC rate, is expressed as a function of temperature and ph. Oxygen concentration ([O ]) in the boundary layer also plays an important role for oxidizing magnetite to hematite, which contributes to achieving much higher corrosion resistance. Ferrous ion concentration in the water, [Fe + ], is calculated with a chemical reaction model based on the obtained flow pattern, and then calculated [Fe + ] is fed back to the environmental parameters for the wall thinning calculation [6]. Generally speaking, FAC rate decreases inversely with two parameters, [O ] and [Fe + ] [6]. Power plants are usually operated under low [O ] and low [Fe + ]. For evaluation of the high FAC risk zone (() in Fig. ), those parameters were taken off and considered as safety margins, and the others determined by D analysis were applied for the high FAC risk zone evaluation, where D mass transfer coefficient was multiplied by geometrical factors []. Wall thinning should be evaluated at least for the high FAC risk zones pointed out by the first steps of the evaluation. For determination of the precise wall thinning rate (() in Fig. ), D mass transfer coefficient based on the D CFD code calculation as well as the effects of the other parameters, temperature, ph, [Cr], [O ] and [Fe].. DETERMINATION OF WALL THINNING RATE.. Wall Thinning Rate due to FAC... Evaluation process. Six calculation steps were prepared for predicting FAC occurrence and evaluating wall thinning rate (Fig. ). Flow pattern and temperature in each elemental volume along the flow path are obtained with a D CFD code and then corrosive conditions, e.g., [O ] and electrochemical corrosion potential (ECP), along the flow path are calculated with the O -N H reaction code [7-8]. Precise flow patterns around the structure surface are calculated with a D CFD code and then distributions of mass transfer coefficients at the surface are obtained [9]. The high FAC risk zone is evaluated by coupling major FAC parameters obtained by Steps through. At the indicated high FAC risk zone, wall thinning rates are calculated with the coupled model of static electrochemical analysis and dynamic double oxide layer analysis. As a final evaluation, residual lifetime of the pipes and applicability of countermeasures against FAC are evaluated in Step 6. The details of calculation procedures for Steps and 5 were shown previously [,]. Step D CFD code Selection of measuring point Step D O -hydrazine reaction code Selection of measurement location for wall thinning based on JASE code Step D wall thinning calculation Periodic wall thinning measurement Step Step 5 D CFD code Improvement of FAC codes Improvement of D FAC code Wall thinning calculation code Continuous wall thinning measurement Evaluation of residual wall thickness Step 6 Total evaluation [planning for preventive maintenance, analysis of plant system safety] Flow dynamics analysis Corrosion (chemical) analysis System analysis Measurement and inspection

4 Fig. Evaluation inspection steps for wall thinning due to FAC In order to narrow down the number of inspection zones, evaluated prediction results are applied. Precise measurements at the restricted area are expected to obtain reliable data sets. And evaluated measured wall thickness data can be feedback for improvement of the prediction code. Such coupling of the estimation and inspection procedures should lead to effective and reliable preparation against FAC occurrence and propagation.... Wall thinning evaluation based on D FAC code. From comparison of the calculated wall thinning rates due to FAC with hundreds of measured results for secondary piping of an actual PWR plant, it was confirmed that the calculated wall thinning rates agreed with the measured ones within a factor of []. Most of the calculated/measured ratios were in the factor of two region, while those for the very low thinning rate were still outside the region and had values larger than a factor of two. One of the causes of the discrepancies between the measured and calculated results was the very low thinning rate with large errors by UT measurements. Certainly, calculation procedures should be improved, and measurement accuracies should also be improved. Mitigating the discrepancy between the calculated and measured values at low measured regions is a future subject for consideration, and the root reasons for underestimation should be carefully investigated to establish the proposed six-step process as a standard code for FAC evaluation. The reliability of piping is determined by residual thickness. So it is important to evaluate residual thickness with high accuracy. The accuracy of the evaluation model for pipe wall thickness both for piping and T junctions was confirmed to be less than %, as shown in Fig. []. 5 (drum: 9 ºC) measured (mm) (pipe: 9 ºC) +% -% feed water line (ºC) condensate water (6ºC) 5 calculated (mm) Fig. Calculated results based on D FAC code: residual thickness.. Wall Thinning Rate Obtained from D FAC Code Calculation procedures for Steps through in Fig. are shown in Fig.. Five of 6 parameters for FAC calculation are determined with sub-codes, while one of the parameters, ferrous ion concentration, is omitted for determination because of its conservative effects on FAC. The details for determination of the major parameters were shown previously []. Select the systems for FAC calculation Piping and component configurations D CFD code Materials of piping and components ([Cr]) Temperature and flow velocity distributions Plant operational history Hydrazine concentration D O -hydrazine reaction code D wall thinning calculation Regional maximum wall thinning rate ph Oxygen concentration Geometry factors Input data for wall thinning calculation

5 E-Journal of Advanced Maintenance Vol.5- () - Japan Society of Maintenology Fig. Calculation procedures and major input data of D FAC code (DREAM-FAC).. Mass transfer coefficient In order to determine the approximate mass transfer coefficient, the mass transfer coefficient for D straight pipe geometry calculated by applying D flow velocity data was multiplied by the geometrical factor for a, orifice and other complex geometries [-5]. The mass transfer coefficient is a function of temperature as well as flow velocity. So, first dimensionless quantities, e.g. Reynolds number and Schmidt number, for a given flow velocity were obtained and then mass transfer coefficient and thickness of the surface boundary layer for mass transfer were calculated based on the dimensionless quantities, which were expressed as empirical formulae for easy calculation []. Properties of cooling water: =8/T () =5exp(-.T) () x -6 =.67 x -5 /T/(exp(-.T) () D=6. x -8 x (exp(-/(rt)) () Sc= /D (5) Flow dynamics data: Re=du/ (6) / =./d Re.8 Sc (7) Mass transfer coefficient: h m =D/ (8) h * m =h m K c (9) Major geometrical factors, K c, are listed in Table [-5]. From the latest experimental data, the geometrical factors for an orifice was expressed as a function of the orifice factor, designated as the ratio, d o /d I. stagnation points of primary flow Table Geometrical factors for FAC type of exposure reference velocity at distributor and behind orifices impact velocity K C *.75.6 stagnation points of secondary flow r/d * I =.5 in s r/d I =.5 and outlet. r/d I =.5 diffusers flow velocity.5 behind junctions.5 stagnation points after separation vortices at and behind obstructions.6 d O /d * I =. d O /d I =.5 d O /d I =.6 behind orifices flow velocity.9 *.8 *.6 * without stagnant point in straight pipes flow velocity. * * d I : pipe inner diameter (m), r: radius of curvature (m) * Geometrical factor for orifice was redefined as a function of orifice geometry d I : pipe inner diameter (m), d O : orifice diameter (m) * Geometrical factor for straight pipe:. * Latest data for orifice measured at Nagoya University... Complex geometrical factor. Complicated geometry consisting of connections of s and orifices and so on requires a complex geometrical factor, which is defined as follows [5]. Point A Point B just downstream of point A A K c B K c 5

6 Distance between A and B: x (m) Complex geometrical factor: K AB c =K B A c +ΔK c () ΔK A A c =K c exp(-c G Δx/d I ) ()... Wall thinning evaluation due to D FAC code Calculated results obtained with the D FAC code were compared with those obtained with the D FAC code, for which accuracy had been confirmed as within a factor of []. The accuracy of the evaluation from the D FAC code was confirmed to be less than a factor of as shown in Fig. 5. Thinning rate calculated with D code (arbitrary unit) +% -5% Thinning rate ( D code) (arbitrary unit) for PWR secondary system (ph>9.) for orifice experiment (ph: 7.)....5 Thinning rate calculated with D code Thinning rate (D code) (arbitrary unit) (arbitrary unit) Fig. 5 Comparison of wall thinning rates calculated with D and D FAC codes %.. Application of D FAC code for evaluation of FAC risks at plants. -5% As a result of the Steps and calculation, five of six parameters could be determined with D CFD and O -N H reaction calculations. Evaluation procedures for FAC occurrence are shown in Fig.. Temperature along the flow path was calculated with the D CFD code and ph was determined from plant experience with chemical injection. Mass transfer coefficient for straight piping could be calculated by applying a flow velocity distribution along the flow path obtained from the D CFD calculation into Eqs. () through (9) and then they could be multiplied by the appropriate geometrical factor to obtain the mass transfer coefficient for complex geometries, e.g.,, orifice and others ()...5. Target system for D FAC code evaluation Distributions of flow velocity and temperature along the flow in the cooling system shown in Fig. 6 were calculated with the D system simulation code, RELAP5 []. Condensate water from the main condensers is polished by the demineralizers, heated by multi stages of condensate and feed water heaters and then fed into the steam generators (SGs). condensate water feed water heater heater demineralizer * 5 main condenser deaerator steam generator Fig. 6 Schematic diagram of PWR secondary cooling system *The numbers correspond to the location numbers in Table 6

7 E-Journal of Advanced Maintenance Vol.5- () - Japan Society of Maintenology Flow patterns throughout the whole system were calculated with RELAP5 in Step. Calculation conditions and results are shown in Table. And then, precise flow patterns were calculated with -D CFD codes based on D calculation results in Step. Table Major input data for D FAC code location [Cr] (%) inner diameter d I (m) wall thickness T w (mm) flow velocity v ( m/s) pressure P (MPa) temperature T ( ) enthalpy H (kj/kg) hazard scale enthalpy x d I (a.u) geometry +orifice geometrical factor K c Plant chemistry parameters Chemistry parameters can be controlled daily. Major chemical parameters at Plant A are shown in Fig. 7. Even when hardware parameters and flow parameters are fixed for long term operation, chemical parameters are controlled due to plant needs. The data of ph and hydrazine concentration were from the plant operational recorder, while oxygen concentration was calculated with the O -hydrazine reaction code. ph (-) RESULTS AND DISCUSSIONS.. Evaluation of FAC Occurrence cycle number 5 6 [O ]* [N H ] ph operating hours (k EFPH) [O ] (ppb) [N H ] (ppm) * [O ]:calculated with O -hydrazine reaction analysis code Fig. 7 History of water chemistry control at Plant A As a result of the Step and calculations, five of six parameters can be determined with the D system simulation code and O -N H reaction calculations. Evaluation procedures for FAC occurrence are shown in Table. Temperature along the flow path is calculated with the D system simulation code and ph is determined from plant experience with chemical injection. The mass transfer coefficient for straight piping can be calculated by applying the flow velocity distribution along the flow path obtained from the D system simulation to Eqs. () through (9) and then it can be multiplied by the geometrical factor to obtain mass transfer coefficient for complex geometries, e.g., and orifice. 7

8 Temperature and ph factors are integrated into the ferrous ion solubility with the function. Temperature also affects the mass transfer coefficient. The effect of chromium and oxygen on FAC was shown previously []. The effect of ferrous ion concentration is omitted in the evaluation procedures, at least for the present stage. Five sets of factors to determine wall thinning rate are multiplied to determine the thinning rate. location inner diameter d I (m) flow velocity (m/s) Table Wall thinning rate calculated with the D FAC code temperature mass transfer coefficient T ( ) h m (m/s)..5e-..5e- 7..8E- 7..6E E E E E E- 86..E- 86..E- 88..E- 88..E-..66E-..7E-..66E- geometry +orifice GF K c T&pH- Cr maximum factors h m (m/s).6 6.E-. 8.6E-..8E-..5E-..5E-.5.87E-.5.E E-.6.78E-.5.E- 8.E- 9.7E- 9.7E-.E-.6.E-.5E- H O- Fe- da/dt (a.u) ph (-): 9., [O ] (ppb):, [Fe + ] (ppb): The detectable change in wall thickness (detectable wall thickness) is around. mm in the laboratory and around mm in plants. Even if pipe wall thickness is measured every year, detectable wall thinning rate will be around mm/y. The FAC occurrence threshold,.5 mm/y, might be acceptable for the present stage of discussion, while further discussion should be carried out by changing the value... Discussions.. Time margin evaluation FAC risk was defined as the mathematical product of the possibility of serious wall thinning occurrence and its hazard scale. For this, not only probability of serious wall thinning occurrence in the future but also the hazard scale of pipe rupture due to the serious wall thinning should be analyzed (Table ). It was defined that the pipe suddenly ruptured when its thickness reached the minimum permissible thickness. For determining the probability of pipe rupture due to FAC, the time margin for pipe rupture was evaluated. Basic approaches toward probability evaluation of pipe rupture due to FAC are shown in Fig. 8. pipe thickness (arbitrary unit) original thickness (measured) * calculation based on design data original thickness (designed) * calculation based on measured original thickness * measured thickness * calculation based on measured thickness * * prediction of the effects of water chemistry improvement * time for * minimum permissible thickness evaluation (in a severe earthquake) minimum permissible thickness time margin for (normal operation) maintenance operating time (arbitrary unit) Fig. 8 Conceptual drawing for predicting pipe wall thickness and their uncertainty... Probability analysis Prediction accuracy for wall thinning rate was within a factor of, which resulted in wall thinning rate as a Gaussian probability profile (Fig. 9 a)). At the same time evaluation errors for original pipe wall thickness and 8

9 E-Journal of Advanced Maintenance Vol.5- () - Japan Society of Maintenology minimum possible thickness required for the pipe also should be considered as Gaussian probability (Fig. 9 b)). Combining both uncertainties for evaluation of thinning rate and the margin for thinning resulted in probability of the time for pipe rupture (Fig. 9 c)). The time margin for pipe rupture was designated as the time reaching 5 % of the peak value. probability density (-) predicted thinning rate (within a factor of ) - thinning rate (mm/y) a) Predicted thinning rate probability density (-). deviation s:.5 mm (for original and permissible thickness) thickness (mm) b) Evaluated margin thickness probability density (-) margin in minimum permissible thickness:mm time margin thinning rate: mm/y.5 mm/y 5 operating time (y) c) Rupture time Fig. 9 Probability densities of thinning rate, margin in thickness and rupture time There have been many discussions on the definition of hazard scale of pipe rupture. Simply put, the hazard was defined as the volume of effluent steam and water from the ruptured mouth, which was enthalpy of water in the pipe multiplied by the square of the pipe inner diameter. Both are shown in Table.... Relationship of time margin for rupture and relative effects of rupture Calculated time margin for time rupture and hazard scale are shown in Fig. a). In order to understand the risk, the relationship of time margin and hazard scale is shown in Fig. b)... time margin primary location for.8.8 inspection and maintenance relative effects location time margin for rupture (y) a) Time margin and hazard scale according to location b) Relationship of time margin and hazard scale time margin for rupture (y) relative hazard scale (-) relative hazard scale (-) Fig. Probability distributions of time margin and hazard scale of pipe rupture By considering the time margin and hazard scale, the number of inspection zones can be narrowed down and continuous wall thick monitoring can be applied at high priority locations. At the same time precise data from continuous measurement of wall thickness can be applied for tuning the prediction tool and improving prediction accuracy...5. Major countermeasures for FAC FAC can be mitigated by controlling one or two parameters shown in Fig. out of the FAC occurrence region. Major countermeasures to mitigate FAC occurrence and wall thinning rate are listed in Table. By applying the D FAC code, the effects of countermeasures on FAC mitigation can be evaluated. One of the most effective countermeasures to avoid the high FAC risk zone is application of chromium containing materials. Chromium application is among the best countermeasures when applied at the plant design stage, but in already constructed plants, replacement of structural materials is a costly procedure with high material, fabrication and labor costs. The easiest why to mitigate FAC is water chemistry control, e.g., increasing ph of oxygen injection. Not only the target effects but also adverse effects should be evaluated for final decision, what countermeasure to apply. Applicable water chemistry improvements are different in PWRs, BWRs and FPPs. Increasing ph is 9

10 widely applied in FPPs but its use is restricted for some PWRs with copper heater tubes due to serious copper corrosion when ph is higher than 9.. Oxygen injection is another effective candidate to mitigate FAC and it is commonly applied for BWRs. In FPPs, all-volatile treatment with oxidizing conditions (AVT(O)) and oxygenated treatment (OT) are applied to mitigate FAC, but in PWRs oxygen injected into the feed water should be removed at the SG inlet to avoid SG tube corrosion. There is a tradeoff of oxygen in the feed water and being oxygen-free at the SG inlet. Optimal water chemistry control to satisfy both the corrosive conditions at the feed water piping and those at SG tubing can be evaluated and established by quantitative evaluation of wall thinning rate under water chemistry improvement []. Table Major countermeasures for FAC in PWR, BWR and fossil power plants Plants equipment material water chemistry improvement remarks where the feed improvement ph [O ] water flows in PWR steam generator increasing [Cr] increasing ph AVT(H&O) minimizing [O ] at SG inlet BWR reactor core increasing [Cr] - (neutral) oxygen [O ] generated injection due to radiolysis Fossil boiler increasing [Cr] increasing ph AVT(O) OT AVT: all volatile treatment OT: oxygenated treatment AVT(H&O): oxygen addition to AVT(R) AVT(O): AVT (oxidizing conditions (residual oxygen present)) AVT(R): AVT (reducing conditions (added reducing agent)) 5. CONCLUSIONS The conclusions are summarized as follows.. TheD FAC code has been developed based on the D FAC code. It was confirmed that estimation accuracy of wall thinning rate obtained with the D FAC code was within a factor of. This speedy and easy-to-handle tool for FAC occurrence can be applied for evaluation of FAC occurrence probability for entire plant systems.. FAC risk designated as the mathematical product of the probability serious wall thinning determined from the time margin for pipe rupture and the hazard scale of pipe rupture could be applied for selection of thinning detection location and suitable FAC mitigation application.. Computer code packages of determination procedures for high FAC risk zones were introduced and determination processes were demonstrated.. The D FAC code could be improved by applying precise wall thinning data obtained by continuous monitoring at the prior locations suggested by prediction. The fusion of prediction and monitoring might go well to improve plant performance. ACKNOWLEDGMENTS Development of the analysis models has been supported by the Innovative and Viable Nuclear Energy Technology Development Project of the Ministry of Economy, Trade and Industry, as Development of Evaluation Method on Flow-induced Vibration and Corrosion of Components in Two-phase Flow by Coupled Analysis (5-7). The authors express their sincere thanks to the sponsor who gave them the chance to develop the model and to draw attention to many related research achievements. The evaluation of the model by comparing the calculated results with the measured has been carried out as a part of the project studies sponsored by the Nuclear and Industrial Safety Agency (NISA). The authors express their sincere thanks to NISA for its sponsorship and acceptance of publication of the results. NOMENCLATURE C G : constant(c G =.)[] C s solubility (mol/m ) [Cr]: chromium content (%) d: equivalent diameter (m) d I : pipe inner diameter (m) D: diffusion constant (m /s)

11 F Cr : chromium factor (-) F ox : oxygen factor (-) h m : mass transfer coefficient (m/s) h m * : geometry calibrated mass transfer coefficient (m/s) K c : geometrical factor (-) [superscripts: A, at point A; B, at point B; AB, synthesizing A and B] R: gas constant, 8. (J/mol/K) Re: Reynolds number (-) Sc: Schmidt number (-) t: exposure time (s) T: temperature (K) T w : wall thickness (m) u: average velocity (m/s) x: distance (m) : thickness of boundary layer (m) : ph (-) : viscosity ( Pa s) : kinematic viscosity (m /s) : density (kg/m ) ABBREVIATIONS -D: one- to three-dimensional BWR: boiling water reactor CFD: computational flow dynamics ECP: electrochemical corrosion potential FAC: flow accelerated corrosion FPP: fossil fuel power plant NPP: nuclear power plant PWR: pressurized water reactor SG : steam generators V&V: verification and validation REFERENCES []. R. B. Dooley, Flow Accelerated Corrosion in Fissile and Combined Cycle/HRSG Plants, Power Plant Chemistry, Power Plant Chemistry, (), 68 (8). [] Secondary Piping Rupture Accident at Mihama Power Station, Unit, of the Kansai Electric Power Co., Inc. (Final Report), Rev., Nuclear and Industrial Safety Agency, Tokyo, Japan (Translated by the Japan Nuclear Energy Safety Organization) (5). [] C. Z. Czajkowski, Metallurgical Evaluation of an 8 Inch Feedwater Line Failure at the Surry Unit Power Station, NUREG/CR-868 BNL-NUREG-557 (987). [] S. Uchida, M. Naitoh, H. Okada, T. Ohira, S. Koshizuka and D. H. Lister, Application of Coupled Electrochemistry and Oxide Layer Growth Models to Water Chemistry Improvement against Flow Accelerated Corrosion in the PWR Secondary System, Corrosion, Paper No. 98, Mar. -7, Houston, TX, USA, National Association of Corrosion Engineers () [5] N. Sekimura, Securing the Stability of Aging NPP Considering Fukushima Daichi Lessons Learning-Improving Inspection System and Aging Management and Planning, Proc. rd Int. Conf. on Nuclear Power Plant Life Management, Saly Lake City, UT, USA, May -8,, International Atomic Energy Agency (). [6] L. E. Sanchez-Caldera, The Mechanism of Corrosion-Erosion in Steam Extraction Lines of Power Stations, Ph. D. Thesis, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts (98). [7] G. J. Bignold, K. Garbett, R. Garnsey and I. S. Woolsey, Erosion-corrosion in nuclear steam generators, Proc. Second Meeting on Water Chemistry of Nuclear Reactors, British Nuclear Engineering Society, London, 5 (98). [8] D. H. Lister and L. C. Lang, A Mechanistic Model for Predicting Flow-assisted and General Corrosion of Carbon Steel in Reactor Primary Coolants, Proceedings of the International Conference on Water Chemistry of Nuclear Reactor Systems,, Avignon, France, April -6,, French Nuclear Energy Society (). [9] M. Naitoh, S. Uchida, K. Koshizuka, S. Ninokata, N. Hiranuma, K. Dozaki, K. Nishida, M. Akiyama and H. Saitoh, Evaluation Methods for Corrosion Damage of Components in Cooling Systems of Nuclear Power Plants by Coupling Analysis of Corrosion and Flow Dynamics (I), Major targets and development strategies of the evaluation methods, J. Nucl. Sci. Technol., 5 [], 6 (8). [] S. Uchida, M. Naitoh, Y. Uehara, H. Okada, N. Hiranuma, W. Sugino and S. Koshizuka, Evaluation methods for corrosion damage of components in cooling systems of nuclear power plans by coupling analysis of corrosion and flow dynamics (II) Evaluation of corrosive conditions in PWR secondary cooling system, J. Nucl. Sci. Technol., 5[], 75 (8). [] S. Uchida, M. Naitoh, Y. Uehara, H. Okada, N. Hiranuma, W. Sugino, S. Koshizuka and D. H. Lister, Evaluation methods for corrosion damage of components in cooling systems of nuclear power plans by coupling analysis of corrosion and flow dynamics (III) Analysis and dynamic double oxide layer analysis, J. Nucl. Sci. Technol., 6[], (9).

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