Predicting Seismic-Induced Settlement of Pipelines Buried in Sandy Soil Reinforced with Concrete and FRP Micropiles: A Genetic Programming Approach

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@Article{al-jeznawi:2025:JoCS,

• author = "Duaa Al-Jeznawi and Musab Aied Qissab Al-Janabi and Laith Sadik and Luis Filipe Almeida Bernardo and Jorge Miguel de Almeida Andrade",
• title = "Predicting Seismic-Induced Settlement of Pipelines Buried in Sandy Soil Reinforced with Concrete and {FRP} Micropiles: A Genetic Programming Approach",
• journal = "Journal of Composites Science",
• year = "2025",
• volume = "9",
• number = "5",
• pages = "Article No. 207",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2504-477X",
• URL = "https://www.mdpi.com/2504-477X/9/5/207",
• DOI = "10.3390/jcs9050207",
• abstract = "Unstable sandy soils pose significant challenges for buried pipelines due to soil-infrastructure interaction, leading to settlement that increases the risk of displacement and stress-induced fractures. In earthquake-prone regions, seismic-induced ground deformation further threatens underground infrastructure. Fiber-reinforced polymer (FRP) composites have emerged as a sustainable alternative to conventional piling materials, addressing durability issues in deep foundations. This paper introduces novel explicit models for predicting the maximum settlement of oil pipelines supported by concrete or polymer micropiles under seismic loading. Using genetic programming (GP), this study develops closed-form expressions based on simplified input parameters--micropile dimensions, pile spacing, soil properties, and peak ground acceleration--improving the models' practicality for engineering applications. The models were evaluated using a dataset of 610 data points and demonstrated good accuracy across different conditions, achieving coefficients of determination (R2) as high as 0.92, among good values for other evaluation metrics. These findings contribute to a robust, practical tool for mitigating seismic risks in pipeline design, highlighting the potential of FRP micropiles for enhancing infrastructure resilience under challenging geotechnical scenarios.",
• notes = "also known as \cite{jcs9050207}",

}

Genetic Programming entries for Duaa Al-Jeznawi Musab Aied Qissab Laith Sadik Luis Filipe Almeida Bernardo Jorge Miguel de Almeida Andrade

Citations