A novel experimental unit has been designed, allowing the examination of the fouling tendency in all relevant sections of a steam cracking furnace, that is, dry feed preheater (DFP), dilute feed preheater I & II (DFPH I & II), radiant section, and transfer line exchanger in a single experiment, using among others an electrobalance. Large differences in coke deposition have been observed in each of these sections when cracking a wide range gas oil (WRGO) and a naphtha fraction (NF). WRGO results in fouling rates which are 20, 86, 253, and 10 times higher in the DFP, DFPH I, DFPH II, and transfer line heat exchanger sections compared to the NF, whereas the fouling rate in the radiant section is 56% lower. The standard deviations are 13, 18, and 7% for DFP, DFPH I, and DFPH II, respectively. Online effluent analysis reveals that significantly less valuable olefins and more Pygas and pyrolysis fuel oil (PFO) are formed during WRGO cracking compared to NF cracking, that is, 16.2 wt % versus 21.9 wt % ethylene, 12.1 wt % versus 14.1 wt % propylene, 24.8 wt % versus 19.6 wt % Pygas, and 14.1 wt % versus 11.3 wt % PFO. This unit can thus provide vital information to develop single step crude to olefin process by examining possible heavy feedstocks.
Fuel microchannels for regenerative
cooling are receiving increasing
attention in advanced aviation technologies. Those microchannels allow
heat integration between the endothermic cracking of the jet fuels
and their subsequent combustion. In this work, a detailed elementary-step
kinetic model is developed to gain insights into the cracking chemistry
of a Jet A surrogate (n-dodecane, isooctane, n-propyl benzene, and 1,3,5-trimethylbenzene), which allows
for further optimization of those aviation technologies. A dedicated
procedure is described for the automated generation of kinetic models
for multi-component mixtures with the open-source Reaction Mechanism
Generator (RMG) software. The full kinetic model is validated against
experimental measurements in multiple reactor geometries, under various
experimental conditions, including both a surrogate mixture and a
commercial Jet A. The experimental data include new experimental measurements
for the pyrolysis of a Jet A surrogate in a tubular reactor with a
detailed product analysis using comprehensive 2D GC. The good performance
of the kinetic model for data from a broad range of experimental conditions
demonstrates the advantage of a kinetic model with detailed chemistry
against empirical kinetic models that are limited in their applicability
range. Further analysis of the important chemistry in the kinetic
model shows that it is essential to account for cross-reactions between
the different surrogate components.
Automatically generated kinetic networks are ideally validated against a large set of accurate, reproducible, and easy‐to‐model experimental data. However, although this might seem simple, it proves to be quite challenging. QUANTIS, a publicly available Python package, is specifically developed to evaluate both the precision and accuracy of experimental data and to ensure a uniform, quick processing, and storage strategy that enables automated comparison of developed kinetic models. The precision is investigated with two clustering techniques, PCA and t‐SNE, whereas the accuracy is probed with checks for the conservation laws. First, the developed tool processes, evaluates, and stores experimental yield data automatically. All data belonging to a given experiment, both unprocessed and processed, are stored in the form of an HDF5 container. The demonstration of QUANTIS on three different pyrolysis cases showed that it can help in identifying and overcoming instabilities in experimental datasets, reduce mass and molar balance closure discrepancies, and, by evaluating the visualized correlation matrices, increase understanding in the underlying reaction pathways. Inclusion of all experimental data in the HDF5 file makes it possible to automate simulating the experiment with CHEMKIN. Because of the employed InChI string identifiers for molecules, it is possible to automate the comparison experiment/simulation. QUANTIS and the concepts demonstrated therein is a potentially useful tool for data quality assessment, kinetic model validation, and refinement.
Renewable cracking feedstocks from plastic waste and the need for novel reactor designs related to electrification of steam crackers drives the development of accurate and fundamental kinetic models for this...
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