Numerical modeling of pressurization of a propellant tank

Majumdar, Alok; Steadman, Todd

doi:10.2514/6.1999-879

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…The GFSSP was originally formulated to model heat transfer and fluid flow in the shuttle turbomachinery [13,14] and has been applied to cryogenic feed systems [15], tank pressurization [16], shuttle propellant loading [17], and no vent fill operation [18]. The code has since been updated to include modeling of chemical reactions [19] and conjugate heat transfer [20].…”

Section: Numerical Modelmentioning

confidence: 99%

Numerical Modeling of the Transient Chilldown of a Cryogenic Propellant Transfer Line

Hartwig

Vera

2016

Journal of Thermophysics and Heat Transfer

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Before cryogenic fuel depots can be fully realized, efficient methods with which to chill down the spacecraft transfer line and receiver tank are required. This paper presents numerical modeling of the chilldown of a liquid hydrogen tankto-tank propellant transfer line using the Generalized Fluid System Simulation Program. To compare with data from recently concluded turbulent liquid hydrogen chilldown experiments, seven different cases were run across a range of inlet liquid temperatures and mass flow rates. Both trickle and pulse chilldown methods were simulated. The Generalized Fluid System Simulation Program model qualitatively matches external skin-mounted temperature readings, but large differences are shown between measured and predicted internal stream temperatures. Discrepancies are attributed to the simplified model correlation used to compute two-phase flow, boiling heat transfer. Flow visualization from testing shows that the initial bottoming out of skin-mounted sensors corresponds to annular flow but that considerable time is required for the stream sensor to achieve steady state as the system moves through annular, churn, and bubbly flows. The Generalized Fluid System Simulation Program model does adequately well in tracking trends in the data, but further work is needed to refine the two-phase flow modeling to better match observed test data. Nomenclature C p = specific heat, J∕kg · K k = thermal conductivity, W∕m · K Nu = Nusselt number Pr = Prandtl number Re = Reynolds number t closed = valve-off time, s t open = valve-on time, s u = fluid velocity, m∕s x = quality Y = mass fraction μ = viscosity, Pa · s ρ = density, kg∕m 3

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Section: Numerical Modelmentioning

confidence: 99%

Numerical Modeling of the Transient Chilldown of a Cryogenic Propellant Transfer Line

Hartwig

Vera

2016

Journal of Thermophysics and Heat Transfer

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“…The conservation of energy for solid nodes is solved at the solid nodes for solid node temperature simultaneously with all the other fluid flow conservation equations. This way the reduced-order fluid network modeling provides a feasible approach to aerospace system modeling and analysis (Cross et al , 2002; Majumdar and Ravindran, 2011; Majumdar and Steadman, 2001; Majumdar and Ravindran, 2010). Yet there are practical aerospace configurations for which large versions of flow circuit are needed resulting in higher dimensional reduced-order network models.…”

Section: Introductionmentioning

confidence: 99%

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

Ravindran

Majumdar

2018

HFF

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Purpose This paper aims to propose an adaptive unstructured finite volume procedure for efficient prediction of propellant feedline dynamics in fluid network. Design/methodology/approach The adaptive strategy is based on feedback control of errors defined by changes in key variables in two subsequent time steps. Findings As 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/value This study uses an adaptive reduced-order network modeling approach for fluid network.

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“…The computation of fluid flow in network consisting of both systems and components is of significant importance in engineering and industry such as design and operation of rocket propulsion systems(Majumdar and Steadman, 2001), design of natural gas and water distribution (Osiadacz, 1988), and design of air flow through a gas turbine combustor (Stuttaford and Rubini, 1996). Most of the existing network flow analysis methods deal mainly with specific flows such as flow in pipelines, incompressible flows, slightly compressible flows, or isothermal flows.…”

Section: Introductionmentioning

confidence: 99%

Fast, nonlinear network flow solvers for fluid and thermal transient analysis

Majumdar

Ravindran

2010

Int Jnl of Num Meth for HFF

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Purpose -The purpose of this paper is to present a fast nonlinear solver for the prediction of transients in network flows. Design/methodology/approach -Broyden method-based nonlinear solvers are developed to solve the system of conservation equation for fluids by judiciously exploiting physical coupling among the equations. Findings -To demonstrate the feasibility and robustness of the solvers, two test cases of practical engineering interest were solved. The results obtained by the solvers were verified against analytical results for a simplified case. The performance of the solvers was found to be comparable or better than existing solvers. Originality/value -The proposed solver enables predictions of fluid and thermal transients in complex flow networks feasible in reduced computational time.

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Numerical modeling of pressurization of a propellant tank

Abstract: ABSTRACT

Cited by 7 publications

References 2 publications

Numerical Modeling of the Transient Chilldown of a Cryogenic Propellant Transfer Line

Numerical Modeling of the Transient Chilldown of a Cryogenic Propellant Transfer Line

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

Fast, nonlinear network flow solvers for fluid and thermal transient analysis

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