Transient Convective Heat Transfer During and After Gas Injection Into Containers

Means, J. D.; Ulrich, Richard D

doi:10.1115/1.3450356

Cited by 13 publications

(8 citation statements)

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“…The leading coefficients in the laminar and turbulent free convection heat transfer correlations used in NETFLOW are approximately 20% greater than those previously reported by others ( see e.g. [2,3]). …”

Section: Modeling Summarymentioning

confidence: 37%

“…Means [3] and Means and Ulrich [4] conducted a series of experiments to develop heat transfer correlations for tank filling and evacuation. Their correlations depend on the location of the gas entrance and exit with respect to gravity, the shape of the tank, and whether or not the flow is choked at the inlet.…”

Section: Heat Transfer Correlationsmentioning

confidence: 99%

“…This work was followed by other experimental work not well documented leading to the development of a simple compressible flow computational model, TRIC, developed by Clark in the early 1980s [2]. In TRIC, heat transfer correlations derived by Means [3,4] and later modified by Meyer [5] are implemented (see Clark [2] for documentation). The origin of these adjustments to the Means expressions or the data from which these adjustments are derived appears undocumented.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of high pressure transient PVT measurements and model predictions. Part I.

Felver¹,

Paradiso²,

Evans³

et al. 2010

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A series of experiments consisting of vessel-to-vessel transfers of pressurized gas using Transient PVT methodology have been conducted to provide a data set for optimizing heat transfer correlations in high pressure flow systems. In rapid expansions such as these, the heat transfer conditions are neither adiabatic nor isothermal. Compressible flow tools exist, such as NETFLOW that can accurately calculate the pressure and other dynamical mechanical properties of such a system as a function of time. However to properly evaluate the mass that has transferred as a function of time these computational tools rely on heat transfer correlations that must be confirmed experimentally. In this work new data sets using helium gas are used to evaluate the accuracy of these correlations for receiver vessel sizes ranging from 0.090 L to 13 L and initial supply pressures ranging from 2 MPa to 40 MPa. The comparisons show that the correlations developed in the1980s from sparse data sets perform well for the supply vessels but are not accurate for the receivers, particularly at early time during the transfers. This report focuses on the experiments used to obtain high quality data sets that can be used to validate computational models. Part II of this report discusses how these data were used to gain insight into the physics of gas transfer and to improve vessel heat transfer correlations. Network flow modeling and CFD modeling is also discussed. 4

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Section: Modeling Summarymentioning

confidence: 37%

Section: Heat Transfer Correlationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of high pressure transient PVT measurements and model predictions. Part I.

Felver¹,

Paradiso²,

Evans³

et al. 2010

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“…For the most part, steady flow correlations such as the Moody friction factor correlation [10] and numerous heat transfer correlations (e.g. references [11,12]) are used. Steady correlations are used for two reasons.…”

Section: Topaz Coding and Modeling Philosophymentioning

confidence: 99%

TOPAZ - the transient one-dimensional pipe flow analyzer: equations and numerics

Winters¹

1985

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“…Perhaps the most extensive work to date on vessel heat transfer was conducted by Means and Ulrich [23]. They performed experiments and analyzed the transient convective heat transfer during and after the sonic filling of a receiving vessel with gas from a high pressure source.…”

Section: Survey Of the Vessel Heat Transfer Literaturementioning

confidence: 99%

Transient PVT measurements and model predictions for vessel heat transfer. Part II.

Report¹,

Rice²,

Paradiso³

et al. 2010

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Part I of this report focused on the acquisition and presentation of transient PVT data sets that can be used to validate gas transfer models. Here in Part II we focus primarily on describing models and validating these models using the data sets. Our models are intended to describe the high speed transport of compressible gases in arbitrary arrangements of vessels, tubing, valving and flow branches. Our models fall into three categories: (1) network flow models in which flow paths are modeled as one-dimensional flow and vessels are modeled as single control volumes, (2) CFD (Computational Fluid Dynamics) models in which flow in and between vessels is modeled in three dimensions and (3) coupled network/CFD models in which vessels are modeled using CFD and flows between vessels are modeled using a network flow code. In our work we utilized NETFLOW as our network flow code and FUEGO for our CFD code. Since network flow models lack three-dimensional resolution, correlations for heat transfer and tube frictional pressure drop are required to resolve important physics not being captured by the model. Here we describe how vessel heat transfer correlations were improved using the data and present direct model-data comparisons for all tests documented in Part I. Our results show that our network flow models have been substantially improved. The CFD modeling presented here describes the complex nature of vessel heat transfer and for the first time demonstrates that flow and heat transfer in vessels can be modeled directly without the need for correlations. 4 ACKNOWLEDGMENTS

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Transient Convective Heat Transfer During and After Gas Injection Into Containers

Cited by 13 publications

References 0 publications

Comparison of high pressure transient PVT measurements and model predictions. Part I.

Comparison of high pressure transient PVT measurements and model predictions. Part I.

TOPAZ - the transient one-dimensional pipe flow analyzer: equations and numerics

Transient PVT measurements and model predictions for vessel heat transfer. Part II.

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