Advanced Pile Foundation Design for Disaster Resilience Using Best Worst Method and Computational Modeling

Gitartha Kalita; Palash Jyoti Hazarika

doi:10.54060/a2zjournals.jmce.84

Authors

Gitartha Kalita Assam Engineering College, Jalukbari, Guwahati, Assam, India
Palash Jyoti Hazarika Assam Engineering College, Jalukbari, Guwahati, Assam, India

DOI:

https://doi.org/10.54060/a2zjournals.jmce.84

Keywords:

Load transfer behavior, Best Worst Method, Pile-soil interface, Octave software, Decision tree model

Abstract

The load transfer behavior at the pile-soil interface is essential for ensuring the stability and resilience of pile foundations, particularly in disaster-prone regions. The allowable load a pile can bear depends on factors such as soil type, pile dimensions, and the in-teraction between the pile and surrounding soil, all of which are critical in maintaining structural integrity during seismic events, floods, and other natural disasters. This study investigates these complexities, proposing innovative approaches to accurately calculate load transfer and optimize disaster resilience strategies. An extensive review of three decades of literature identified six foundational studies on load transfer equations. Load-settlement curves were generated using Octave software, accommodating various soil types and pile dimensions commonly encountered in disaster scenarios. To refine calculations, codes were developed to compute allowable bearing loads using formulas from the Indian Standard code. A decision tree model implemented in Python further predicted the optimal calculation methods for specific conditions under disaster stress scenarios.
Additionally, the research explored six distinct methods for evaluating allowable loads: Point by Point Curve, Cubic Root, Hiramaya Curve, Hyperbolic Curve, Krasinski Curve, and Root Curve. Among these, the Hiramaya Curve emerged as the most con-servative and reliable, offering a higher factor of safety due to its lower allowable load estimates. To enhance accuracy, weightages for each method were evaluated using the Best Worst Method, offering a systematic framework for prioritizing the methods based on their reliability and effectiveness. The findings revealed significant variations in load-bearing capacities across soil types and pile dimensions, emphasizing the necessity of site-specific designs. A novel code was also developed to streamline optimal load calculation methods, improving the efficiency, reliability, and disaster resilience of pile foundation designs. This comprehensive framework equips geotechnical engineers with adaptable tools and robust methodologies to design safer, more resilient structures across diverse geotechnical conditions.

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