Ut Testing for Screening of Dmws

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A Methodology for Screening Candidate

Dissimilar Metal Welds for Repair or Replacement

Thomas SherlockLaney Bisbee

Structural Integrity Associates, Inc.

Alex Bonnington

Potomac Electric Power Company

Abstract

Dissimilar Metal Welds are required in high temperature sections of boiler reheater andsuperheater tubing to join low alloy steel tubing to the finishing stainless tubing. The

intrinsic difference in the coefficients of expansion cause high stresses to develop at therelatively weak ferritic/weld interface. The power generation industry began to

experience failures of type 309 stainless steel welds in the early 1980s and has recentlybegun to experience nickel-based weld failures on tubes with 150,000 or greater

operating hours.

For utilities who have or wish to institute a program of periodic inspection and a DMWrepair/replacement maintenance strategy, one of the difficulties has been reliable NDE.

Radiographic techniques have shown to be of some benefit, but the cost and lostmaintenance time due to safety concerns makes it less than ideal. Replication and

electrical resistance techniques also have drawbacks from the standpoint of accuracy. In1996, SI developed an ultrasonic scanning technique for DMWs. In 1998, the DMWs at

the Morgantown Station of PEPCO were examined using this technique and reasonablygood correlation was found between UT and destructive metallographic techniques.

This paper outlines the application of the focused scanning technique used to quantify the

damage in DMWs, the means for selecting damaged DMWs for correlation with thetechnique and the manner in which this information is incorporated into a reliability-

centered maintenance strategy for improving boiler availability.

Introduction

In the early 1980s, EPRI sponsored workshops to deal with the problem of excessiveDMW failures in power boilers (1). The main culprit was the use of a 309 type filler

material, which has the greater difference in coefficient of thermal expansion vis--vislow alloy steel when compared to nickel-based filler materials. Utilities embarked on

programs of inspecting and repairing/replacing damaged welds before they would fail


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and cause excessive consequential damage to the boiler tubing and significant losses in

unit availability. A computer code, PODIS, was developed by EPRI for the purpose ofpredicting the rate of damage accumulation in DMWs as a function of tube operating

temperature, type of weld, degree of bending stress and number of unit cycles. Somedouble wall radiographic techniques were developed which were useful in detecting

DMW damage, but the main drawback was the cost per radiograph and the exclusion ofpersonnel from the boiler in the vicinity of the radiographic tests. Replication and

electrical resistance techniques were also employed, but their accuracy was questionable,as they are primarily surface, as opposed to volumetric, techniques.

In the early 1990s, ESEERCO (Empire State Electric Energy Research Corporation)

requested that a review of the PODIS technology be conducted. A utility survey wasconducted and it was found that the code was very conservative for nickel-based welds.

From this program, a new code (DMW LIFE) was developed for ESEERCO. In the mid-1990s, SI used the probabilistic DMW LIFE on a project for PEPCO, wherein failure

projections were made for DMWs , based on a few tube samples per boiler. In general,

the predictions were reasonable and showed that weld failures could begin and increaseover the next 5 10 years of operation. None did occur before this inspection.

Focused Ultrasonic Techniques

SI had developed TestPro, a PC-based digital UT system, in the early 1980s. One of thefirst utility applications was for determining the wall and internal oxide thickness of

SH/RH tubes. Using the principle of focused sound waves, a similar technique wasdeveloped for interrogating the weld metal/ferritic interface using a scanning transducer

as shown in Figure 1 (2).

Figure 1. DMW Scanning Transducer Assembly.


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Based on laboratory and early in-boiler tests, SI felt that an accuracy of +/- 10% onthrough-wall damage was feasible.

Inspection Results

During April 1998, the Morgantown Station Unit #1 boiler SH DMWs were examined by

SI. The DMWs were located in the penthouse, consisting of 171 platen assemblies withDMWs in tube rows 19 through 24, exclusively. Due to access limitations and the small

size of the tubing (1.5-inch diameter), only one scan could be performed on tubes 19, 20,23 and 24. Two (2) scans were performed on tubes 21 and 22. The inspections were

carried out from the space under the header between rows 21 and 22, which limited theavailable access and speed of the inspection.

A total of 870 DMWs were specified for examination, resulting in a total number of scans

of 1160 scans, when 2 per tube 21 and 22 are included. Of the specified 1160 scans, 23

(or about 2%) were not performed due to tube surface conditions or access limitations.336 scans (or about 30%) exhibited no recordable indications. After all data was collected(four twelve hour shifts with two crews of two each), the permanently stored scans of

those tubes exhibiting recordable indications were reviewed and sized in approximate10% increments of tube wall thickness. In addition, a best effort characterization was

performed on the indications to differentiate fabrication flaws from service-induceddamage. Representative B-Scan images from the DMW inspection were saved to disk,

and an example is shown in Figure 2.

Of the tubes examined, two (2) were found to have damage levels of about 80%, four (4)were found to have damage levels of about 70%, seven (7) were found with 60% and

fourteen (14) were found with levels of 50%. It should be noted that in some instances, agood inspection of the ID of the DMW (left side of Figure 2) could not be performed due

to the presence of a wide weld crown or accessibility considerations. This meant that thedamage level in the weld could be higher, especially since the ID is a primary initiation

spot when bending stresses are high. Thus a damage level of 70% (of the UT visibleweld could be somewhat larger when the entire cross section of the weld is examined.

Based on the analysis, five welds were recommended for removal and rapid turn-around

analysis by PEPCOs Metallurgical Laboratory.


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Figure 2. Example of a B-Scan Image from a DMW.

Metallurgical Analysis

The five samples were sent to the laboratory where each weld was cross-sectioned at

approximately 90o

intervals. A summary of the correlations is found in Table 1.

Table 1. Summary of Metallurgical and UT Results

Wall

Thickness

Extent of OD Damage UT Results Metallurgical Comments

0.345 0.233 68% 50% Large OD Notch + Midwall

Microcracking

0.412 0.339 82% 50%

0.375 0.315 84% 50%

0.413 0.320 77% 80% OD Creep Microcracking

0.411 0.118 29% 70% Isolated Slag Inclusion at31% Through-Wall

0.411 0.118 37% 70% Isolated Slag Inclusion at

71% Through-Wall

0.400 0.154 39% 50% OD Creep Microcracking


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0.398 0.320 80% 60% Fine Mid-Wall

Microcracking

0.373 0.285 69% 60% Large OD Notch and FineMid-Wall Cracking

0.372 .320 86% 60% Large OD Notch + Midwall

Microcracking

Typical photomicrographs of the damage are shown in Figure 3.


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Figure 3. Typical Photomicrographs of Damage Found in Three of the Welds.

OD Notches are on the Right Side of the Photomicrograph.


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The metallurgical results, in general, correlated well with the UT results and the large

differences in the third row of the summary table can be explained by the mid-wallinclusions, which returned a UT signal, resulting in an overly conservative estimate of the

amount of damage. The lack of UT signals from the ID of the DMWs was the cause ofthe non-conservative UT estimates. It was concluded in PEPCOs final report that the

UT technique was a good screening tool for identifying the most severely damagedDMWs. Following a review of all of the data, it was recommended that an additional 32

DMWs be removed from service to ensure the long-term reliability of the superheater.

Discussion of Results

The overall evaluation of the data showed that the vast majority of tubes (97%) containedless than 50% damage, which is good performance for a unit with 200,000+ operating

hours. A plot of damage levels is shown in Figure 4.

Figure 4. Distribution of Damage in the UT Results.

The one factor that could easily explain the good performance of these welds is a rather

uniform temperature distribution across the boiler. Using DMW LIFE, an estimate of thedamage expected can be made versus temperature and the results are shown in Figure 5.

Distribution of Damage

0

10

20

30

40

50

60

70

80

90

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

% With Damage

Damage%


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Figure 5. Damage Fraction Versus Temperature for 200,000 Hours Operation.

The small percentage of tubes that exhibited a damage fraction of 50% or greateroperated at temperatures of 1060F or higher (or possibly had very high bending stresses).

This is fairly normal for a boiler to have a +/- 50F spread around a main steam outlet

temperature of 1000F. Thus it appears that about 3% of the tubes were operating in thetemperature range 1060 1090F.

In order to assess the value of the inspection and DMW replacement strategy, futurefailure projections are required to develop a cost/risk benefit analysis. Traditional theory

relies on a linear rate of DMW damage accumulation and that is the method forextrapolating damage projections. Also, since a +/- 10% standard deviation in the ability

to measure damage with UT seems reasonable, then using the Monte Carlo technique, theuncertainty in the UT DMW damage can easily be expressed as follows:

Damage = Damage * (1 +/- 0.1),

With the 0.1 randomly picked from a normal distribution with a mean of 1 and a SD of

0.1. If the time of operation is assigned a normalized value of 1, then the probability oftube failures versus operating time can easily be generated as shown in Figure 6.

Damage Index Versus Temperature

0

0.2

0.4

0.6

0.8

1

1.2

980 1000 1020 1040 1060 1080 1100 1120

Temperature, F

DamageFraction


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Figure 6. Percentage of Population Expected to Fail Versus Operating Time.(Time Value of 1 is the Time of Inspection)

A future failure is defined as the randomly generated damage index exceeding 0.95. The

population of damage used for this case was the 26 tubes with damage greater than 50%

(the population has a mean of 57.7 % damage, with a standard deviation of 9.7%). All ofthis assumes that the basic mode of boiler operation remains constant for future operatingintervals. Firing harder or changing to cyclic operation can drastically change the tube

temperature distribution across a boiler and could result in higher than expected failurerates.

Since all welds exceeding 50% were removed from service, the new population has a

much lower mean damage (15.6%) and higher standard deviation (13.3%). When thismodel was run for a time increase of 1.5, the projected failure rate was 0.03% for the time

interval.

What this exercise shows is that the decision to replace the 37 worst welds has reducedthe expected number of tube failures over the next (todays operating hours * 1.5) time

interval from 9 11 (35 - 40% of 26) to zero for all practical purposes.

One very important result of this inspection is that PEPCO now has a map of theDMWs in their boiler. Should it become necessary to retest the DMWs in the future in

order to determine that damage accumulation is linear, or that boiler operation haschanged, UT testing can be concentrated in the most critical areas, thus reducing

Percentage of Tubes Failured

y = 0.2684x12.317

R2

= 0.9849

0

5

10

15

20

25

30

35

40

45

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Time Increase

PercentageFailed


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inspection and preparation costs. Such inspections could be staged during very short 2

4 day outages, minimizing boiler downtime. If, after 1.5x hours of additional operation,PEPCO elects to perform a full or limited DMW inspection, similar results should be

obtained and selected DMW replacement could be used to extend the failure free periodof operation to 2x current operating hours.

Conclusions

1. UT testing of DMWs can be rapidly implemented during an outage and has anaccuracy of about +/- 10% on damage detection. As with the progress made inthe oxide thickness technique, better accuracies can be obtained with more

experienced NDE technicians and perhaps some weld crown grinding.

2. Having a DMW damage map enables utilities to make selective DMWreplacements during a scheduled outage, which can drastically reduce future

failures and maximize boiler availability. It also serves as a tool to avoid

wholesale replacement of sections, which is becoming less justifiable in todayscompetitive generation market.

3. The statistical approach used in this example can readily be extended to risk-based inspection scheduling and economic risk/benefit analysis, which are

expected to become more well recognized as maintenance tools of the future.

References

1. Dissimilar Metal Weld Failure Analysis and Development Program, EPRI CS-4252, Final Report, November 1985.

2. Dissimilar Metal Welds for Defect Detection, Characterization and Sizing EPRIInternational Conference on Boiler Tube Failures in Fossil Plants November 11 - 13,1997, Nashville, TN.

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Ut Testing for Screening of Dmws