Vol. 1 No. 1 (2026)

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Implementing Random-Field Reliability Analysis in MATLAB for Soil-Nailed Slope Stability: A Reproducible Workflow

Aduot Madit Anhiem, Department of Civil Engineering · Univers iti Teknologi PETRONAS
Published: February 11, 2026

Abstract

This paper presents a complete, reproducible MATLAB workflow for random-field (RF) reliability analysis of soil-nailed slopes. The implementation integrates four main software modules: a data-structure builder (inputData), a Karhunen–Loève random field generator (randomfield), a slice-based slope stability solver (soilCalc), and interchangeable reliability engines (FORM via slopeBeta; Monte Carlo Simulation via a custom MCS driver; Adaptive Radial Based Importance Sampling via ARBIS). The allData structure serves as the central data carrier, passing geometric, soil, nail, and probabilistic parameters between modules without global variables. Worked code excerpts from each module are presented alongside annotated pseudocode. Results demonstrate that spatially variable cohesion and friction angle, discretised over a 10-slice mesh, yield probability of failure estimates between 7% and 46%—values that conventional scalar-parameter FORM analysis cannot reproduce. The workflow is designed for transparency and replication; each function is self-contained with well-defined inputs and outputs.

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How to Cite

Aduot Madit Anhiem (2026). Implementing Random-Field Reliability Analysis in MATLAB for Soil-Nailed Slope Stability: A Reproducible Workflow. African Journal of Women in Leadership and Governance, Vol. 1 No. 1 (2026).

Keywords

MATLAB · random field · Karhunen–Loève expansion · slope stability · soil nailing · Monte Carlo simulation · ARBIS · allData structure · reliability workflow

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Vol. 1 No. 1 (2026)
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