Estimating corrosion growth rate is a non-linear, multi-dimensional (space and time) challenge. Above-ground outdoor assets are affected by natural atmospheric factors such as climate, salinity and human contributions such as pollution. International Standard ISO9223( ) provides guidance, including response functions and a classification schema (C1 thru C5) for estimating corrosion risk as a function of three variables: weather (temperature and humidity), dry deposition of sulfides, and dry deposition of chlorides. Climate data is widely available but dry deposition data is either not available or very expensive to collect, requiring collection and laboratory testing to determine. Fortunately, wet deposition data for chlorides and sulfides are available and accurately reported. In this paper, a method for estimating ISO9223 compliant dry deposition data using wet deposition data and other climate-based factors is presented.
An approach to extrapolate all ISO9223 inputs for any location in North America using Geographic Information System (GIS) algorithms is also demonstrated. This method uses inverse distance weighted (IDW) technique to build parameter estimates based on geospatial interpolation, and linear models for estimation of atmospheric conditions. This provides the ability to estimate ISO9223 classification schema for any latitude and longitude pairs in North America, leveraging the ISO9223 methodology using more widely available data. The potential benefits are significant, from optimization of coating selections and maintenance schedules to construction considerations. As a case study, the model was applied for a North American pipeline operator to develop an atmospheric corrosivity map of their assets. Future work includes direct collection of on-site growth rate data and improved ISO9223 response functions incorporating additional variables such as electromagnetic interference and NO-based pollution sources.
The inability to accurately classify corrosivity of environmental conditions onsite, without the need for lengthy inspection processes has resulted in an industry environment where coating manufacturers and/or owners tend to overbuild coating systems to assure maximum asset life-expectancy. A solution reviewed in this paper includes a method for collecting public data on atmospheric chemistry. Then to geographically translate this data within the confines of ISO9223 (C1-CX) environments as a cost-effective and sustainable method of analysis and suggesting coating systems based on desired life-expectancy within the confines of ISO12944-2.
This paper further hopes to explain the hurdles faced in overcoming somewhat dated methods for data collection, observations, and analysis. The projected benefits are: improved capacity to manage assets, maximizing the life-time value of the asset, cost to manage, and an overall reduction in risk.