PROBABILISTIC DESIGN OF FOUNDATIONS AND STRUCTURES: ADDRESSING UNCERTAINTY IN GEOTECHNICAL PARAMETERS

Abstract

This study examined the role of probabilistic design methods in addressing uncertainty in geotechnical parameters related to foundations and structures. The research focused on evaluating how probabilistic frameworks improved structural safety, reliability, and foundation performance under uncertain subsurface conditions. A quantitative research design was adopted, and data were collected from a sample of 300 geotechnical engineers, structural engineers, researchers, and construction professionals using a structured questionnaire based on a five-point Likert scale. Statistical analysis was performed using descriptive statistics, correlation analysis, and regression analysis to evaluate the relationships among probabilistic design methods, geotechnical parameter uncertainty, reliability-based design, and structural safety. The findings indicated high mean values for Structural Safety and Stability (M = 4.21), Probabilistic Design Methods (M = 4.18), Reliability-Based Design (M = 4.12), and Foundation Performance Optimization (M = 4.09). Correlation analysis revealed strong positive relationships among all variables, while regression analysis showed that Reliability-Based Design produced the strongest influence on structural safety with a beta coefficient of 0.42 and a significance value of 0.000. The coefficient of determination (R² = 0.73) demonstrated that probabilistic design variables explained 73% of the variation in structural safety and stability. The study concluded that probabilistic geotechnical engineering approaches improved uncertainty management, minimized structural risks, optimized foundation performance, and supported sustainable infrastructure development in modern engineering projects.

Keywords : Foundation Optimization, Geotechnical Engineering, Probabilistic Design, Reliability Analysis, Soil Variability, Structural Safety.