Corrosion is the biggest enemy of transmission pipelines. According to PHSMA, about 40% of pipeline damage and leakage is the direct result of corrosion, and other types of pipeline damage, such as excavation and natural force damage, are also highly associated with pipeline corrosion and can be easily triggered. Overall, soil corrosivity is the key and influences the degree of corrosion that happens on a pipeline.
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In this section, the objective is to determine the soil corrosivity and assess the corrosion risks of pipelines by developing a continuous soil corrosivity index surface by using ArcMap and ArcGIS Pro in Harris County. Given the fact that soil corrosivity is influenced by a number of different soil properties at different levels, multi-criteria evaluation (MCE) was used as the technique to determine soil corrosivity in Harris County.
Corrosion is the biggest enemy of transmission pipelines. According to PHSMA, about 40% of pipeline damage and leakage is the direct result of corrosion, and other types of pipeline damage, such as excavation and natural force damage, are also highly associated with pipeline corrosion and can be easily triggered. Overall, soil corrosivity is the key and influences the degree of corrosion that happens on a pipeline.
​
In this section, the objective is to determine the soil corrosivity and assess the corrosion risks of pipelines by developing a continuous soil corrosivity index surface by using ArcMap and ArcGIS Pro in Harris County. Given the fact that soil corrosivity is influenced by a number of different soil properties at different levels, multi-criteria evaluation (MCE) was used as the technique to determine soil corrosivity in Harris County.
The lack of preparedness of local governments and energy companies led to this serious state-wide power outage and energy crisis. Therefore, to prevent similar series of disasters from happening, it is crucial to ensure and assess the resiliency and integrity of current transmission pipelines in the State of Texas.
In this project, the main objective is to investigate the driving factors of pipeline incidents (failures, accidents) of currently existing pipelines.
The lack of preparedness of local governments and energy companies led to this serious state-wide power outage and energy crisis. Therefore, to prevent similar series of disasters from happening, it is crucial to ensure and assess the resiliency and integrity of current transmission pipelines in the State of Texas.
In this project, the main objective is to investigate the driving factors of pipeline incidents (failures, accidents) of currently existing pipelines.
Section I: Physical Risk Assessment -
Multi-criteria Evaluation of Soil Properties in Harris County
Corrosion is the biggest enemy of transmission pipelines. According to PHSMA, about 40% of pipeline damage and leakage is the direct result of corrosion, and other types of pipeline damage, such as excavation and natural force damage, are also highly associated with pipeline corrosion and can easily trigger failures on corroded pipelines. Overall, soil corrosivity is a key factor that can influence the overall resiliency of pipelines.
​
In this section, the objective is to determine the soil corrosivity and assess the corrosion risks of pipelines by developing a continuous soil corrosivity index surface by using ArcMap and ArcGIS Pro in Harris County. Given the fact that soil corrosivity is influenced by a number of different soil properties at different levels, multi-criteria evaluation (MCE) was used as the method to determine soil corrosivity in Harris County.
Soil properties, such as pH level, are crucial factors to local soil corrosivity. However, these properties vary dramatically in different regions with different climates, altitudes or geologic histories. In this study, to determine the input soil properties and their importance, an interview with a professional corrosion engineer and his crew from an international steel structure corrosion inspection company was carried out. Important soil properties and their qualitative importance were recorded from the interview. Then the qualitative importance was then converted into quantitative numbers by using the analytic hierarchy process (AHP) calculator. Quantified importance was generalized and then used as weights in the weighted map.
Input parameters and their relative importance in the MCE
Map 4.1 shown below contains all six input soil property raster layers retrieved from USDA's Soil Data Viewer extension. Each layer was classified into three groups representing different levels of risk.
Map 4.1: Input soil properties for the MCE analysis. Data retrieved from Soil Data Viewer, USDA NRCS