A thermodynamic property formulation for air

Jacobsen, R. T.; Penoncello, Steven G.; Beyerlein, Steven; Clarke, W. P.; Lemmon, Eric W.

doi:10.1016/0378-3812(92)85124-q

Cited by 22 publications

(14 citation statements)

References 7 publications

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“…A project on the thermophysical properties of standard air and related mixtures of nitrogen, oxygen, and argon is nearing completion. This research, sponsored mainly by the National Aero-Space Plane project within NASA [16], included experimental measurements primarily at NIST and modeling work performed primarily at the Center for Applied Thermodynamic Studies at the University of Idaho [17]. The work pointed to problems in the previous standards for air, especially at low temperatures, and has already proven to be of great use in more traditional aspects of the aerospace industry.…”

Section: Standards Under Developmentmentioning

confidence: 99%

Thermophysical property standard reference data from NIST

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Huber

1994

Int J Thermophys

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and Technology (NIST) has a primary function to develop and disseminate standard reference data for the thermophysical properties of fluids and fluid mixtures of interest to the industrial and scientific communities, in this paper we discuss five computerized databases distributed by the Standard Reference Data (SRDI Program of NIST. The databases provide national standards for the properties of pure fluids, an accurate evaluated mixture program focusing on the properties of natural gas mixtures, a predictive package emphasizing hydrocarbon systems up to C_~., a database for refrigerant and prospective alternative refrigerant fluids, and the current scientific thermophysical property surfaces for pure water and steam. The databases include both thermodynamic surfaces and representations for transport properties over broad ranges of temperature, pressure, and composition. We also discuss our current research to improve the standards for air and for aqueous systems including the binary mixture of ammonia and water.

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Section: Standards Under Developmentmentioning

confidence: 99%

Thermophysical property standard reference data from NIST

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Huber

1994

Int J Thermophys

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“…This finding is not surprising considering that 99 % of the molecules in air are simple diatomic oscillators with similar modes of energy storage. The calculated C, values in Table I were derived from the equation of state of Jacobson et al [17] as…”

Section: Resultsmentioning

confidence: 99%

Molar heat capacity at constant volume for air from 67 to 300 K at pressures to 35 MPa

Magee

1994

Int J Thermophys

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Measurements of the molar heat capacity at constant volume C, for air were conducted with an adiabatic calorimeter. Temperatures ranged from 67 to 300 K, and pressures ranged up to 35 MPa. Measurements were conducted at 17 densities which ranged from gas to highly compressed liquid states. In total, 227 C, values were obtained. The air sample was prepared gravimetrically from research purity gases resulting in a mole fraction composition of 0.78112 N 2 + 0.20966 0 2 + 0.00922 Ar. The primary sources of uncertainty are the estimated temperature rise and the estimated quantity of substance in the calorimeter. Overall, the uncertainty 1+2o-) of the C, values is estimated to be less than +2% for tile gas and +0.5% for the liquid.

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“…The values of Z and (∂ Z /∂ T ) p at the next temperature are predicted using (∂ 2 Z /∂ T 2 j ) p along with equations (6) and (7). The procedure given in the previous paragraph is then used to calculate values for…”

Section: And (∂ Z /∂ T ) ρ With Taylor Series Expansionsmentioning

confidence: 99%

“…These approaches, which will be discussed below, are: (1) correlating equations of state using multi-property regression; (7,8) (2) converting acoustic virial coefficients to second and third virial coefficients, including both empirical and intermolecular potential based approaches; (9)(10)(11)(12) and (3) numerical techniques for manipulating fundamental thermodynamic relationships. (12)(13)(14)(15)(16)(17)(18)(19)(20) Kamei et al (8) and Jacobsen et al (7) used multi-property regression algorithms involving speed of sound data (u, T, p) along with other data forms to determine a Helmholtz function equation of state. However, in each of these cases, speed of sound data (u, T, p) had to be linearized before beginning the linear regression process.…”

Section: Property Measurement Technique Uncertaintymentioning

confidence: 99%