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A Risk-Based Inspection Method for Flow Accelerated Corrosion Detection

by Thomas Godby

With limited resources and a mixed fleet of both legacy and new build power plants, it can be a challenge to keep up with the many inspection locations and data produced by a fleet flow accelerated corrosion (FAC) program. In addition, for those new to this realm of inspections, it can be intimidating to determine where to begin an inspection program, considering the thousands of possible locations from which to choose. To remedy this, a risk-based inspection approach that focuses on the highest impact areas first should be used. This approach leverages the risk grid, or risk matrix, where a composite score can be generated by using the formula: Risk = Probability x Consequence (R=PxC). This score subsequently can be used to determine where resources are to be focused on areas of highest probability of FAC and whose consequences could result in personnel injury, severe equipment damage and lost generation.

To begin, one must first understand the mechanisms that influence FAC in power plants. For the purpose of this article, the focus will be on lessons learned from elevating an internal FAC program for a lignite coal burning fleet on low energy piping. The piping systems included the boiler feedwater, condensate, heater drain, extraction steam, boiler water separator and boiler blowdown systems. As you can see, even with immediate elimination of other power plant piping systems, there are still many components to screen across an entire fleet of assets. To continue to drill down further, certain documentation can be useful in understanding where FAC is most likely present. Piping line lists that contain information on the line size, material composition, design and operating temperatures, pressures and flows are a valuable asset. This information can help you understand your plant's risk and susceptibility to FAC.

Industry experience has shown that FAC occurs predominately in water or water steam mixed media systems with carbon steel piping that operate in the range of 150 to 500 degrees Fahrenheit. If you obtain this temperature information, along with pressure information, you can better understand what degree of superheat exists and determine if you have single or two-phase flow in the piping. Industry information indicates that FAC wear rates accelerate in a certain range of temperatures. Using this information, you can assign a scoring system based on where you are on the curve. For example, you could divide the FAC temperature range into five distinct bands and assign a score to each based on an assessment of severity as it applies to wear rate. This same principle holds true for understanding where your plant operates in the pH band and which flows are present in the piping. These points of reference, along with their scores, will ultimately tally up to a probability score for susceptibility.

It is understandable that not everyone has great documentation. In this case, obtaining a heat balance is your next greatest ally. You can then look at the FAC susceptible systems and get a basic understanding of temperatures, pressures and flows to do your assessment. A visit to your control room can also help by taking a look at your control system and seeing what is displayed while your plant is operating. By taking the same probability approach, you can ask additional questions as they pertain to plant chemistry and operating context. For example, an older site may have been exposed to reducing chemistry, like all-volatile treatment reducing AVT(R) or the addition of hydrazine. In this case, plants running reducing chemistries are very susceptible to FAC, so a detailed search is in order. A meeting with the local chemistry team will allow you to understand where in the FAC pH band the plant has historically operated. If you are operating newer plants, it is likely running oxygenated chemistries, such as all-volatile treatment oxidizing AVT(O) or oxygenated treatment (OT) with a higher pH. This profile has been shown to almost completely eliminate single phase FAC. If this is the case, your search becomes even more focused since you essentially will be looking at two-phased flow in systems where you can have flashing, such as heater drains piping sections, after control valves. As you discover more information about your susceptible lines, add it to your probability scoring algorithm. The more information you have, the more robust your calculation will be. If you find you are limited in the information you can uncover, do not be discouraged; little information and taking a logical engineering approach to probability is better than none at all.

The next part of the equation is the consequence side of the calculation. The first consequence to think about is personnel safety. Once you have the lines selected based on susceptibility, walk them down and take pictures of each inspection location. Develop a communication package and schedule times to meet with the operators in the control room, the folks doing operator rounds and any seasoned veterans at your plant that have a good feel for what areas would be considered high traffic. Score these assessments accordingly using a numeric value. For example, you can assign a five for a high traffic area and a one for a low traffic area. Other locations to consider are those that are near workshops, restrooms, or any area where personnel may have a tendency to congregate. For those sites that are older and have asbestos insulation, an additional scoring category should be added to account for the increased risk to personnel.

The consequences of equipment damage should be considered next. While performing your walk down, think about what would happen if there was a steam leak or rupture in the area. Is there switchgear or other electronic equipment in the area? Give consideration to any equipment that, if damaged, would result in a unit trip or require a major maintenance outage to repair. Lastly, while discussing locations with the operators, ask what would happen to unit operations if a pipe rupture or leak occurred. Score the responses accordingly, for example, a one would be no effect to plant operation, whereas a three could be a unit derate and a five would be a unit trip.

Now you are ready to begin developing your risk grid and inspection scope list. An example of the risk grid can be viewed in Figure 1. In this example scoring has been applied to the various categories on the X and Y axis such that a composite risk score can be displayed. The grid is then broken down into areas based on low, medium, high and extreme risk. This information can be applied to the inspection scope list and risk ranking spreadsheet, an example of which can be viewed in Figure 2. As the scores are added to each proposed piping line, you can begin to see which lines pose the highest threat to safety and generation. This information is also great to have in the case of reductions in budget or outage scope. If either of these situations occurs, you will be armed with information to make a very good risk-based decision on where to draw your cut line. Be sure to add any inspection location that has been removed to your next year's plan.

In summary, this methodology can be used to focus resources and budgets while reducing risk to safety and generation for your generating fleet. It provides a framework by which piping lines can be evaluated using various sources of data and institutional knowledge. It also offers an organized approach to collating and displaying data for discussion meetings where budgets will be allocated towards future inspections. Lastly, it offers a visual method to display the information graphically so that program managers and inspection leads can quickly show high risk and high impact areas to managers, facilitating data driven decision making and reducing risk exposure to flow accelerated corrosion related piping failures.

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