Models for the prediction of the thermophysical properties of halogenated substances
datasetposted on 08.01.2019 by Maria E. Mondejar Montagud, Fredrik Haglind, Jens Abildskov, Stefano Cignitti, Jerome Frutiger, John M. Woodley, Gürkan Sin
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
This entry contains, first, the Matlab functions code for the calculation of the critical temperature, critical pressure, acentric factor, normal boiling temperature, and ideal gas heat capacity by using a classical group contribution approach (GCM functions.p) or a neural-network-based approach (ANN functions.p). The input for their use is an
array containing the number of groups for the definition of the fluid, except for the case of the ideal gas capacity, where the first element of the array will be the temperature in K. An example of use can be found in the related publications.
Second, function for the estimation of the uncertainty of the predicted values are also included:
uncertainty model.m: obtains the estimated uncertainty for a specified model and property. The input for its use is the array containing the number of groups for the fluid, except
for the case of the ideal gas capacity, where the first element of the array will be the temperature in Kelvin. An example of use of this function can be found in the related publication.
Tc model.mat: is a structure that contains the array of experimental values of Tc (Tcexp), the fluid groups (groups), the models' parameters (param GCM, param ANN), the predictions of the GCM and the ANN (Tc GCM, Tc ANN), their uncertainties (u GCM, u ANN), and the PDF of both model parameters (pdf GCM, pdf ANN).
Pc model.mat, w model.mat, and cp0 model.mat are analogous to Tc model.mat.
Tc model.csv, Pc model.csv, w model.csv, and cp0 model.csv: contain the data of the .mat files in csv format.