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Analysis of machine learning models and data sources to forecast burst pressure of petroleum corroded pipelines: A comprehensive review
A comprehensive evaluation of the integrity of oil and gas pipelines subjected to corrosion
defect is required for forecasting health & safety actions. If corrosion is ignored, it may have …
defect is required for forecasting health & safety actions. If corrosion is ignored, it may have …
An automated machine-learning-assisted stochastic-fuzzy multi-criteria decision making tool: Addressing record-to-record variability in seismic design
While uncertainty quantification (UQ) has served a prominent role in ensuring the safety of
dynamical engineering systems, the lack of an integrated approach to handle the aleatory …
dynamical engineering systems, the lack of an integrated approach to handle the aleatory …
Reliability assessment for pipelines corroded by longitudinally aligned defects
Internal corrosion poses a significant threat to offshore pipeline services. Toward offshore
pipeline integrity management, this paper aims to use Finite Element Method (FEM) to …
pipeline integrity management, this paper aims to use Finite Element Method (FEM) to …
A data-driven methodology for predicting residual strength of subsea pipeline with double corrosion defects
X Li, R Jia, R Zhang - Ocean Engineering, 2023 - Elsevier
The accurate residual strength prediction can support the maintenance planning of
damaged subsea pipeline. Recently, machine learning techniques become a remarkable …
damaged subsea pipeline. Recently, machine learning techniques become a remarkable …
Assessment of the Implications and Challenges of Using Artificial Intelligence for Urban Water Networks in the Context of Climate Change When Building Future …
MT Bui, H Yáñez-Godoy… - Journal of Pipeline …, 2025 - ascelibrary.org
Urban water networks are more than obligatory infrastructures that help to develop and
sustain cities; they are integral to urban resilience. Water networks have undergone an …
sustain cities; they are integral to urban resilience. Water networks have undergone an …
Collapse pressure prediction of mechanically lined pipes using FEM and machine learning techniques
Mechanically lined pipe, which proves to be an economical and reliable way to transport
corrosive hydrocarbons, has been used in many offshore projects. The presence of liner and …
corrosive hydrocarbons, has been used in many offshore projects. The presence of liner and …
Prediction and deployment of compressive strength of high-performance concrete using ensemble learning techniques
Concrete is widely utilized in construction; however, accurately predicting its compressive
strength is difficult due to the complex relationships within its mixture. Although previous …
strength is difficult due to the complex relationships within its mixture. Although previous …
Corroded pipeline assessment using neural networks, the Finite Element Method and discrete wavelet transforms
An essential task in the oil and gas industry is establishing an efficient way to assess
corroded pipeline integrity. The literature shows that integrity analysis with Finite Elements …
corroded pipeline integrity. The literature shows that integrity analysis with Finite Elements …
Integrated finite element analysis and machine learning approach for propagation pressure prediction in hybrid Steel-CFRP subsea pipelines
Accurate prediction of the propagation pressure (PP) in hybrid steel-CFRP pipe systems
presents a substantial challenge due to intricate interactions and complex collapse failure …
presents a substantial challenge due to intricate interactions and complex collapse failure …
[HTML][HTML] Explainable ensemble models for predicting wall thickness loss of water pipes
Abstract Water Distribution Networks (WDNs) are susceptible to pipe failures with significant
consequences. Predicting wall-thickness loss in pipes is vital for proactive maintenance and …
consequences. Predicting wall-thickness loss in pipes is vital for proactive maintenance and …