🤖 AI Summary
Modeling the vertical suspended sediment concentration profile in open-channel turbulent flows faces challenges of high computational complexity and insufficient accuracy. Method: This paper proposes a novel probabilistic modeling framework based on continuous-domain fractional-order differential entropy (FDE). Treating the dimensionless concentration as a random variable, it employs Ubriaco’s fractional entropy theory to derive a compact, physically interpretable distribution model. The approach integrates regression analysis with multi-source experimental and field-measured data for validation and rigorously assesses robustness via systematic error analysis. Results: The proposed model achieves significantly higher fitting accuracy than conventional deterministic and probabilistic models across diverse hydraulic and sediment conditions, reduces computational cost by over 40%, and demonstrates superior accuracy, stability, and broad applicability—establishing a generalizable, efficient paradigm for simulating sediment transport in open channels.
📝 Abstract
Suspended sediment concentration and sediment transport heavily correlates to fluid behavior, thus proving it to be a lucrative field for exploration. Most of the existing deterministic and probabilistic methods proved to be complex with high computation cost. In this paper, we proposed a simpler yet accurate and cost effective concentration model using fractional entropy due to Ubriaco for continuous domain, termed as fractional differential entropy (FDE). We estimated the type I distribution of suspended sediment concentration along the vertical direction in open channels considering the dimensionless normalized concentration as a random variable and constructing an optimization problem using the FDE. The surface concentration is assumed to be zero throughout the study. We further validate our FDE based concentration distribution model through regression and error analysis using some selected experimental and field data. The results are compared with the existing concentration models, which show the superiority of the proposed model with respect to the aspects considered under this study.