(3d) Molecular Weight and Its by-Boiling-Point Distribution of Middle Distillates for Hydroprocessing Modeling and Simulation | AIChE

(3d) Molecular Weight and Its by-Boiling-Point Distribution of Middle Distillates for Hydroprocessing Modeling and Simulation

Authors 

Chen, J. - Presenter, CanmetENERGY
Briker, Y. - Presenter, National Centre for Upgrading Technology
Hager, D. - Presenter, Natural Resources Canada
Ring, Z. - Presenter, British petroleum


Molecular weight (MW) and its by-boiling-point distribution are important physical properties of petroleum feedstocks. Such information is much required in process and reactor modeling, kinetics studies, vapor-liquid equilibrium analysis, and in many other chemistry- and engineering-related analyses and computations. Even for distillates, there are no universally applicable methods or correlations to estimate the average MW. An efficient method to determine the MW distribution by boiling point is simply unavailable in the open literature. Direct measurement is not easy for a sample with a wide boiling range. Established ASTM methods are either for samples with low boiling points (Freezing Point Depression, FBP<300°C) or for samples with high boiling points (Vapor Pressure Method, IBP>220°C) to provide an averaged MW. There is no suitable method that can be used for samples in the diesel boiling range without pre-separation. Measurement of MW distribution by-boiling-point requires distillation of the sample into a number of fractions, which is time and effort consuming. This paper presents a quick and convenient method to determine the MW and its by-boiling-point distribution using off-the-shelf GC-FIMS (Gas Chromatography-Field Ionization Mass Spectrometry) data. This method has several advantages: 1) simple (once the method is established); 2) requires a very small amount of sample; and 3) no need for distillation. To establish and validate the method, a total of 12 different middle distillate samples were chosen to undergo distillation to obtain 8 fractions for each sample. MW was measured for each of the fractions to obtain by-boiling-point distribution, which was further used to validate and calibrate the GC-FIMS predicting method. The density by-boiling-point distribution was also correlated by using the experimental data. Details on the method development and experiments will be given in the full paper and in the presentation.