Use of optimization to develop a correlation model for predicting residual NAPL saturation

Abstract

Predicting the residual saturation of a trapped non-aqueous phase liquid (NAPL) contaminant is critical to estimate the region of contamination, the design of remediation strategies, and risk assessment. Models were developed to predict residual NAPL saturation utilizing optimization and non-linear functions, consequently allowing for a broader mathematical approach to model development. The input parameters evaluated represent soil and fluid properties; the uniformity coefficient (C _u), the coefficient of gradation, the capillary number (Nc), the bond number (Nc), and the total trapping number (Nt). Overall, the model that performed the best was based on a second-order equation with the independent variables C _u and Nt₁ using the sum of the squares of the errors. The non-linear error function based on a derivative of Marquardt's percent standard deviation performed the best for three other cases.

Keywords:

• Groundwater
• Regression analysis
• Optimization
• NAPL
• Multiphase flow
• Soil contamination

Acknowledgements

The author would like to thank Jeannette Fonte and LaToya Knowles for their graduate research that contributed to this article.