PNNL

Abstract

Pulse jet mixing tests were conducted to support the design of mixing systems for the Hanford Waste Treatment and Immobilization Plant. A physical approach (based on hydro-dynamic behavior) and two semi-empirical (SE) approaches were applied to the data to develop models for predicting two response variables (critical-suspension velocity and cloud height). Tests were conducted at three geometric scales using multiple noncohesive simulants and levels of possibly influential factors. The physical modeling approach based on hydro- dynamic behavior was first attempted, but this approach can yield models with spurious correlation. To overcome this dilemma, two semi-empirical (SE) models were developed by generalizing the form of the physical model using dimensional and/or nondimensional (ND) variables. The results of applying statistical intelligence (STI) tools to resolve the spurious correlation problem via fitting the physical and SE models are presented and compared. Considering goodness-of-fit, prediction performance, spurious correlation, and the need to extrapolate, the SE models based on ND variables are recommended.