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FAC-Compass®: Flow-Accelerated Corrosion Modeling, Life Prediction and Materials Selection in Water-Steam Systems  


Version 9.20


    Performance        Functionality        Usability

Anytime       Anywhere      Any Device      Any OS

No USB dongles     No installation       No Browser Plug-ins

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Why WebCorr | Performance Guarantee | Unparalleled Functionality | Unmatched Usability | Any Device Any OS | Free Training & Support | CorrCompass

Features and Functions of FAC-Compass

FAC-Compass is the only device-and-OS independent software tool on the market for Erosion Corrosion and Flow-Accelerated Corrosion (FAC) modeling, life prediction, and materials selection in water-steam systems. Designers, engineers, consultants, maintenance and inspection personnel can quickly assess and quantify the impact of erosion corrosion and FAC on the remaining life of their components in the water-steam systems anytime, anywhere, on any device running any OS without the need to install or download anything.

FAC-Compass models the effects of the following parameters on the rate of metal wastage and wall thinning due to erosion corrosion (EC) and flow-accelerated corrosion (FAC):

  • Fluid chemistry including pH, temperature, and oxygen content.

  • Fluid velocity, Flow pattern and geometry of the component in the water-steam system.

  • Metallurgy of the components used in the water-steam system

The outputs from FAC-Compass include:

  • Quantitative evaluation of the metallurgy's resistance to FAC: the FAC resistance index, R, and the Chromium equivalent. The metallurgy's resistance to FAC is classified into 3 categories as (1) not resistant to FAC; (2) generally resistant to FAC, and (3) highly resistant to FAC.

  • The predicted FAC rate (wall thinning) in mm/y

  • The predicted remaining life of the component

  • The predicted FAC rate as a function of temperature

  • The predicted FAC rate as a function of oxygen content

  • The predicted FAC rate as a function of (Cr+Mo)% content in the steel or alloy

  • The predicted FAC rate as a function of velocity

  • The predicted FAC rate as a function of pH

Overview and Application Examples of FAC-Compass


Figures below show the screen shots of FAC-Compass.


Figure 1 Overview of FAC-Compass


Users of FAC-Compass start by selecting the phase of flow (2-phase wet steam or single phase of water) from the dropdown list (Figure 2).


Figure 2 Phase of Flow: Single Phase (Water) and 2-Phase (Wet Steam)


After entering the metallurgy of the component, FAC-Compass computes the chromium equivalent and the FAC resistance index with comment on the FAC resistance of the selected metallurgy. The FAC rate in mm/y can be plotted as a function of (Cr+Mo)% under the prevailing operating conditions of the water-steam system (Figure 3). This function is particularly useful for FAC-resistant materials evaluation, assessment and selection. Users of FAC-Compass can also plot the FAC rate in mm/y as a function of temperature, velocity, pH, oxygen, as shown in Figure 3 below.


Figure 3 Plot Options in FAC-Compass


Service Life Prediction for a 1 1/4" Steam Pipe Elbow 

A pipe elbow (SA105) in a wet steam line perforated after 6 years in service. The metallurgy of the elbow is: C% (0.030), Cu%(0.020), Cr%(0.050), Mo%(0.010). FAC-Compass determines that this metallurgy is not resistant to FAC based on the evaluation of the chemical composition of the elbow. The chemistry of the fluid is as shown in Figure 4. The FAC rate predicted by FAC-Compass under the prevailing operating condition is 1.018 mm/y. The nominal wall thickness is 6 mm, the elbow is predicted by FAC-Compass to perforate in 6 years.


Figure 4 Service life prediction for a pipe elbow in wet steam service


The powerful applications of FAC-Compass in water-steam services are truly unlimited in engineering design, FAC resistant materials evaluation and selection, remaining life prediction, process optimization (such as temperature, pH, O2, velocity), trouble-shooting and failure analysis. 


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FAC-Compass, giving you the right directions in FAC Prediction and Assessment

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