The application of macro modeling concept for the soil/coating External corrosion for ECDA process by using statistical tools
Conference Paper
Overview
Overview
abstract
2014 by NACE International. External corrosion direct assessment includes four steps in the SP ECDA standard practice as a recommended methodology. The first step in the process is the pre-evaluation and the fourth step is the post assessment; we propose the first step to include the integration of macro-parameters, such as rainfall, water accumulation, chemistry of the soil, and soil corrosiveness. These parameters are associated with indirect measurement influencing corrosion (as time-dependent threats) for underground pipelines. Real time macro-modeling was used to enhance the pre-assessment and indirect assessment and clustering analysis was performed to aid in the pre-evaluation and post assessment steps. This work aims to provide a case study for pre-evaluation assessment based on dynamic macro-modeling previously introduced for external corrosion direct assessment of a buried pipeline that is 110 km (68.35 miles) in length and 457.2 mm (18in) in diameter. The macro-modeling concept was previously presented and was based on the parameters affecting the soil properties in different regions during four seasons due to the climate, rainfall, soil properties and environmental parameters. The noise of the field data obtained from indirect surveys and direct assessments can be reduced based on a statistical approach (principal component analysis), and the soil and environmental properties are then grouped into similar clusters via clustering models in order to increase accuracy of the estimation of the corrosion rate in an underground pipeline. The statistical analysis helped to develop the pre-evaluation and post assessment step for the ECDA process. parameters. The noise of the field data obtained from indirect surveys and direct assessments can be reduced based on a statistical approach (principal component analysis), and the soil and environmental properties are then grouped into similar clusters via clustering models in order to increase accuracy of the estimation of the corrosion rate in an underground pipeline. The statistical analysis helped to develop the pre-evaluation and post assessment step for the ECDA process. parameters. The noise of the field data obtained from indirect surveys and direct assessments can be reduced based on a statistical approach (principal component analysis), and the soil and environmental properties are then grouped into similar clusters via clustering models in order to increase accuracy of the estimation of the corrosion rate in an underground pipeline. The statistical analysis helped to develop the pre-evaluation and post assessment step for the ECDA process. parameters. The noise of the field data obtained from indirect surveys and direct assessments can be reduced based on a statistical approach (principal component analysis), and the soil and environmental properties are then grouped into similar clusters via clustering models in order to increase accuracy of the estimation of the corrosion rate in an underground pipeline. The statistical analysis helped to develop the pre-evaluation and post assessment step for the ECDA process.
