Computer aided kinetic modeling with KMT and KME

Wei, Wei; Bennett, Craig A.; Tanaka, Ryuzo; Hou, Gang; Klein, Michael T.

doi:10.1016/j.fuproc.2007.11.015

Cited by 59 publications

(68 citation statements)

References 18 publications

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“…Therefore, only one reaction was written for aromatic ring condensation to represent the possible condensation of any two aromatic cores in the system. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 With these reaction families and reaction rules, the reaction network was generated, automatically, using an in-house software, the Interactive Network Generator, INGen 12,13 . INGen takes a starting set of reactant molecules as network building seeds, and exhaustively searches the molecules for the reaction sites.…”

Section: Decarboxylationmentioning

confidence: 99%

Molecular-Level Kinetic Modeling of Resid Pyrolysis

Horton

Zhang

Hou

et al. 2014

Ind. Eng. Chem. Res.

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A molecular-level kinetic model of heavy oil pyrolysis was developed for a Venezuelan vacuum residue. Model development proceeded in three major steps: creation of a molecular description of the feedstock, generation of a reaction network, and model solution and parameter tuning. The feedstock composition, as described in previous work [Zhang et al. Energy Fuels 2014, 28, 1736−1749, was modeled in terms of probability density functions (PDFs) of three finite attribute groups (385 cores, 2 intercore linkages, and 194 side chains) and a PDF for each of a cluster-size and binding site distribution. These attributes, or molecule building blocks, represent more than 0.4 M molecules. An attribute reaction network was developed using the fundamental reaction chemistry for resid pyrolysis including 6274 reactions that fall into one of 11 reaction families. To make solution time tractable, we used attribute reaction modeling (ARM) which constrained the number of material balances to the number of attributes and irreducible molecules in the system or 2841 total equations. Therefore, reactor output was a set of reaction-altered attribute PDFs and molar amounts of irreducible molecules. The quantitative molecular composition of the reactor outlet was obtained through the juxtaposition of the final attribute PDFs. The properties of both the sampled molecules and the char fraction were obtained using quantitative structure−property relationships (QSPRs). The kinetic model was tuned using a least-squares objective function comparing the model predictions to measurements from the molecular to bulk-property level for all relevant boiling point fractions. The tuned model showed reasonably good agreement with the experimental measurements.

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Section: Decarboxylationmentioning

confidence: 99%

Molecular-Level Kinetic Modeling of Resid Pyrolysis

Horton

Zhang

Hou

et al. 2014

Ind. Eng. Chem. Res.

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“…Automatic kinetic model generation tools have been utilized in various chemical processes including combustion , pyrolysis , and catalytic conversion processes . In this context, Genesys was developed to aim at providing a generic framework of algorithms for the automated construction of kinetic models.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Stereochemistry in Automatic Kinetic Model Generation

Vandewiele

Vijver

Carstensen

et al. 2016

Int. J. Chem. Kinet.

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The kinetic model generation code Genesys is extended by the addition of algorithms for the detection of stereocenters and for the detection of stereoisomers. To make this possible, a so‐called 2.5D representation of molecules that accounts for the presence of stereocenters and that keeps track of the associated stereoconfiguration of the stereocenters is introduced. A novel algorithm for the detection of steric relations between substituents allows the automated assignment of rate coefficients to stereoselective reactions. The functionality of the algorithms is illustrated for the thermal rearrangement of the monoterpenoid 2‐pinanol, an intermediate in the fragrance industry. Accounting for stereochemistry proves to be essential in explaining the reactive behavior of 2‐pinanol and the selectivity to its products. Good agreement with experimental data from the literature was obtained. CBS‐QB3 calculations for (R)‐cis‐ and (R)‐trans‐2‐pinanol support the experimentally observed differences for the suggested stereoselective and stereospecific reactions.

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“…U literaturi [27][28][29][30][31] su date procedure za uspostavljanje matematičkih kriterijuma za grupisanje komponenata u kompleksnim sistemima. Kriterijum za grupisanje koji su predložili Kuo i Wei [29] je primenjen za modelovanje velikog broja sistema, uključujući i katalitički reforming benzina.…”

Section: Definisanje Pseudo-komponenataunclassified

“…Coxson i Bischoff [31] su modifikovali tehniku koju su razvili Kuo i Wei, a njihova metoda je uspešno primenjena na proces katalitičkog krekovanja. Klein i saradnici [27,28] su razvili tehniku za grupisanje komponenata upotrebom grafičke teorije.…”

Computer aided kinetic modeling with KMT and KME

Cited by 59 publications

References 18 publications

Molecular-Level Kinetic Modeling of Resid Pyrolysis

Molecular-Level Kinetic Modeling of Resid Pyrolysis

Implementation of Stereochemistry in Automatic Kinetic Model Generation

Modeling and energy optimization of the catalytic naphtha reforming process

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