Geometrically Calibrated Network Models for Progressive Cavity Pump Design

Abstract

Linear network models are promisingly simple progressive cavity pump design tools. Current linear network models are difficult to use in the design process because they require calibration against experimental data or computationally intensive simulation. In this paper we present new approaches for implementing linear network progressive cavity pump models and provide new methods to accurately and quickly estimate the values of each resistor in the model from pump geometry for both laminar and turbulent flows. This paper also argues that sealing-line flow transitions from laminar to turbulent at orders of magnitude smaller Reynolds numbers than described in the literature thus far. We propose a new hypothesis for the point of transition to turbulent performance.