Crude to olefins : effect of feedstock composition on coke formation in a bench-scale steam cracking furnace

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 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

The merit of pressure dependent kinetic modelling in steam cracking

Modelling case study on the role of pressure dependence in single event kinetic modelling for steam cracking of both ethane and propane. Results are validated with in-house generated experimental data.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 process, despite its large scale implementation for more than half a century. Pressure dependent kinetics have mostly been omitted in fundamental steam cracking models, while they are crucial in combustion models. Therefore, we have assessed the importance of pressure dependent kinetics for steam cracking via in-depth modelling and experimental studies. In particular we have studied the influence of considering fall-off on the product yields for ethane and propane steam cracking. A high-pressure limit fundamental kinetic model is generated, based on quantum chemical data and group additive values, and supplemented with literature values for pressure dependent kinetic parameters for beta-scission reactions and homolytic bond scissions of C-2 and C-3 species. Model simulations with high-pressure limit rate coefficients and pressure dependent kinetics are compared to new experimental measurements. Steam cracking experiments for pure ethane and propane feeds are performed on a tubular bench-scale reactor at 0.17 MPa and temperatures ranging from 1058 to 1178 K. All important product species are identified using a comprehensive GC x GC-FID/q-MS. For homolytic bond scissions, the inclusion of pressure dependent kinetics has a significant effect on the conversion profile for ethane steam cracking. On the other hand, pressure dependence of C-2 beta-scissions significantly influences conversion and product species profiles for both ethane and propane steam cracking. The C-3 beta-scissions pressure dependence has a negligible effect in ethane steam cracking, while for propane steam cracking the effect is non-negligible on the product species profiles

QUANTIS : data quality assessment tool by clustering analysis

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

Detailed kinetic modeling for the pyrolysis of a jet a surrogate

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