Work

Enhanced prediction of corrosion rates of pipeline steels using simulated annealing-optimized ANFIS models

Year: 2024

Type: article

Abstract: Accurate prediction of corrosion rates is crucial for preventing infrastructure failures, reducing maintenance costs, and ensuring operational safety. Traditional models often struggle to account for the complex, non-linear interactions between environmental factors and material properties. This study presents a novel approach integrating Simulated Annealing (SA) with an Adaptive Network-based Fuzzy Inference System (ANFIS) to improve corrosion rate predictions for pipeline steels. The SA-ANFIS model features six input neurons representing temperature, H₂S pressure, CO₂ pressure, salinity, moisture content, and material type. These factors influence corrosion rates, represented by a single output neuron. The SA algorithm optimizes the ANFIS model's parameters, enhancing its ability to handle non-linear relationships. Historical corrosion data for P110SS, L80, and 2205 Duplex steel were used, incorporating environmental variables such as temperature, pH, and gas pressures. The SA-ANFIS model achieved superior accuracy, with a maximum error of 2.8424 % and an average error of 1.2536 %, outperforming the GA-ANFIS model and conventional ANFIS and SVR models. The SA-ANFIS model offers a robust, optimized tool for predicting corrosion in petroleum pipelines, significantly improving prediction accuracy under harsh conditions. • Integration of Simulated Annealing with ANFIS significantly reduces maximum error and improves R-squared values, enhancing predictive precision. • The model targets crucial petroleum industry alloys—L80, P110, and 2205 stainless steel. • The model adeptly manages non-linear relationships among variables like temperature, pH, and pressures, improving corrosion rate predictions.

Source: Results in Engineering

DOI: 10.1016/j.rineng.2024.102853

Authors: Ali Hussein Khalaf, Bing Lin, Ahmed N. Abdalla, Zhongzhi Han, Ying Xiao, Junlei Tang

Institutions: Southwest Petroleum University, Huai'an University, Beijing University of Chemical Technology, China National Petroleum Corporation (China)

Language: English

Topic: Structural Integrity and Reliability Analysis

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,490