An adaptive approach for prediction of propellant feedline dynamics in fluid network

Abstract

PurposeThis paper aims to propose an adaptive unstructured finite volume procedure for efficient prediction of propellant feedline dynamics in fluid network.Design/methodology/approachThe adaptive strategy is based on feedback control of errors defined by changes in key variables in two subsequent time steps.FindingsAs an evaluation of the proposed approach, two feedline dynamics problems are formulated and solved. First problem involves prediction of pressure surges in a pipeline that has entrapped air and the second is a conjugate heat transfer problem involving prediction of chill down of cryogenic transfer line. Numerical predictions with the adaptive strategy are compared with available experimental data and are found to be in good agreement. The adaptive strategy is found to be efficient and robust for predicting feedline dynamics in flow network at reduced CPU time.Originality/valueThis study uses an adaptive reduced-order network modeling approach for fluid network.