An Integrated Methodology for Novel Algorithmic Modeling of Non-Spherical Particle Terminal Settling Velocities and Comprehensive Digital Image Analysis

Abstract

Accurate prediction of settling velocities for irregular particles offers significant advantages in various fields, including more efficient water/wastewater treatment, environmental pollution control, industrial productivity, and sustainable resource utilization. These predictions are essential for advancing sustainable hydraulic engineering and environmental management. In this study, a new algorithmic modeling framework was proposed to estimate the terminal settling velocity of irregularly shaped particles/materials. The framework integrates advanced non-linear regression techniques with robust optimization methods. The model successfully incorporated seven key input parameters to construct a comprehensive mathematical representation of the settling process. The proposed explicit model demonstrates superior prediction accuracy compared to existing empirical and drag correlation models. The model's validity was confirmed using a large and morphologically diverse dataset of 86 irregular materials and rigorously evaluated using an extensive battery of statistical goodness-of-fit parameters. The developed model is a robust and highly accurate tool for predicting the settling behavior of non-spherical particles in the transition flow regime. Beyond its technical merits, the model could offer significant sustainability benefits by enhancing the design and optimization of wastewater treatment systems. More precise predictions of non-spherical particle settling behavior could improve sedimentation or particle removal efficiency, potentially reducing energy consumption and mitigating adverse environmental impacts on industrial waste management and aquatic ecosystem preservation.