Analysis of Ultrasonic Velocities in Hydrocarbon Mixtures
نویسندگان
چکیده
Ultrasonic velocity data on hydrocarbon mixtures was shown by Wang and Nur [JASA 89, 2725 (1991)] to agree quite well with the predictions of a simple mixing rule (volume average of velocity). The same data is reanalyzed using Wood's formula and the time average approximation. Wood's formula for acoustic velocity is shown to be always less than the time average formula, which is itself always less than the simple mixing rule result. Although the volume average rule agrees best with the data on binary mixtures of 1-decene and 1-octadecene, all these formulas agree with the data to within 1% and, therefore, it is not possible to distinguish among the formulas using this data set. Similar results are also found for six multicomponent hydrocarbon mixtures. PACS numbers: 43.35.Bf, 43.20.Bi, 43.20.Hq
منابع مشابه
Analysis of ultrasonic velocities in hydrocarbonmixturesJames
Ultrasonic velocity data on hydrocarbon mixtures was shown by Wang and Nur JASA 89, 2725 (1991)] to agree quite well with the predictions of a simple mixing rule (volume average of velocity). The same data is reanalyzed using Wood's formula and the time average approximation. Wood's formula for acoustic velocity is shown to be always less than the time average formula, which is itself always le...
متن کاملPrediction of true critical temperature and pressure of binary hydrocarbon mixtures: A Comparison between the artificial neural networks and the support vector machine
Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. In order to have a fair comparison and to achieve the highest efficiency, a comprehen...
متن کاملSurface Tension Prediction of Hydrocarbon Mixtures Using Artificial Neural Network
In this study, artificial neural network was used to predict the surface tension of 20 hydrocarbon mixtures. Experimental data was divided into two parts (70% for training and 30% for testing). Optimal configuration of the network was obtained with minimization of prediction error on testing data. The accuracy of our proposed model was compared with four well-known empirical equations. The arti...
متن کاملA New Correlation for Prediction of Wax Disappearance Temperature of Hydrocarbon Mixtures at Various Pressures
Wax precipitate is one of the most serious issues the oil industry is currently facing, since it can cause some troubles such as increasing of the pressure losses in pipe which subsequently increases the required power for pumpage. To remove this problem, prediction of wax disappearance temperature (WDT) seems necessary. In this study, the pressure influence on the wax disappearance temperatu...
متن کاملElastic characterization of porous bone by ultrasonic method through Lamb waves
The object of this research is to characterize the porous bones by an ultrasonic method using Lamb waves. In recent years, the characterization of such materials has attracted many authors and takes a perfect place in the field of medicine. It requires the development of more efficient technology for getting the necessary quality and security. This paper aims to exploits the dispersion curves o...
متن کامل