Compressed Liquid Densities and Saturated Liquid Densities of Dimethyl Ether (RE170)

Abstract

Dimethyl ether (RE170) is a very important chemical compound, largely employed in the chemical industry, but the available literature data for this fluid, especially in terms of liquid density, are scarce. In this paper, compressed liquid density data were measured along eight isotherms between (283.15 and 353.15) K up to 35 MPa with a vibrating tube densimeter (Anton Paar DMA 512) and, on the basis of these data, the saturated liquid densities were estimated. The overall estimated uncertainty for the density data is within ± 0.1 %. The experimental compressed liquid density data and the estimated saturated density data were correlated by means of fitting equations that are also presented in this paper.

Experimental densities, vapor pressures, and critical point, and a fundamental equation of state for dimethyl ether

“…5 as 100 × (ρ exp − ρ calc )/ρ exp . All of the densities measured in this work and those of Bobbo et al [16] are represented with an average absolute deviation of 0.08%. The data presented here at temperatures below 390 K have an average absolute deviation of 0.02%.…”

“…Until now, only limited literature density data for dimethyl ether are available. Compressed liquid densities have recently been published by Bobbo et al [16] for the range between 283 and 353 K and up to 35 MPa. These data are in good agreement with the correlation, with an average absolute deviation of 0.07% in density.…”

“…In the compressed liquid (subcritical and supercritical), densities of dimethyl ether have previously been measured from 283 to 353 K with pressures up to 36 MPa by Bobbo et al [16]. They also reported saturated densities in the liquid phase.…”

“…From this preliminary equation, the exponents of the equation were allowed to float, similar to the method used in the work of Lemmon et al [25]. The PρT data used in the fit comprise the data measured in this work and some of the data of Bobbo et al [16]. In addition, the vapor pressure data reported here, and some of the data of Bobbo et al [26][27][28][29][30] and Kennedy et al [43] were used in the fitting process.…”

Estimation of thermophysical properties of dimethyl ether as a commercial refrigerant based on artificial neural networks

“…Percent deviations of predicted densities by using ANN in comparison with the training and testing data measured by Ihmels and Lemmon (2007), and finally other experimental data set reported by Bobbo, Scattolini, Fedele, and Camporese (2005) are presented. Results are shown in Fig.…”