J. G. Speight, . Hydrocracking, J. G. Speight, and . Ed, The Refinery of the Future, pp.275-313, 2011.

M. Bricker, V. Thakkar, and J. Petri, Hydrocracking in Petroleum Processing, Handbook of Petroleum Processing

S. A. Treese, P. R. Pujadó, and D. S. Jones, , pp.317-359, 2015.

, Stratas Advisors. 13 Countries Move Up in Top 100 Ranking on Diesel Sulfur Limits | Stratas Advisors, p.15, 2020.

. Imo, Sulphur 2020-Cutting Sulphur Oxide Emissions, p.15, 2020.

J. Ancheyta, S. Sánchez, and M. A. Rodríguez, Kinetic modeling of hydrocracking of heavy oil fractions: A review, Catal. Today, vol.109, pp.76-92, 2005.

A. T. Jarullah, I. M. Mujtaba, and A. S. Wood, Kinetic model development and simulation of simultaneous hydrodenitrogenation and hydrodemetallization of crude oil in trickle bed reactor, Fuel, vol.90, pp.2165-2181, 2011.

P. J. Becker, B. Celse, D. Guillaume, H. Dulot, and V. Costa, Hydrotreatment modeling for a variety of VGO feedstocks: A continuous lumping approach, Fuel, vol.139, pp.133-143, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01138513

S. A. Esmaeel, S. A. Gheni, and A. T. Jarullah, 5-Lumps kinetic modeling, simulation and optimization for hydrotreating of atmospheric crude oil residue, Appl. Petrochem. Res, vol.6, pp.117-133, 2016.

H. M. Lababidi and F. S. Alhumaidan, Modeling the hydrocracking kinetics of atmospheric residue in hydrotreating processes by the continuous lumping approach, Energy Fuels, vol.25, 1939.

X. Tang, S. Li, C. Yue, J. He, and J. Hou, Lumping kinetics of hydrodesulfurization and hydrodenitrogenation of the middle distillate from chinese shale oil, Oil Shale, vol.30, 2013.

J. Bonnardot, Kinetic Modelling of Hydro-Treatment Reactions by Study of Different Chemical Groups, 1998.

C. López-garcía, D. Hudebine, J. Schweitzer, J. J. Verstraete, and D. Ferré, In-depth modeling of gas oil hydrotreating: From feedstock reconstruction to reactor stability analysis, Catal. Today, vol.150, pp.279-299, 2010.

L. O. Oyekunle and O. A. Edafe, Kinetic modeling of hydrodenitrogenation of pyridine, Pet. Sci. Technol, vol.27, pp.557-567, 2009.

C. S. Raghuveer, J. W. Thybaut, and G. B. Marin, Pyridine hydrodenitrogenation kinetics over a sulphided NiMo/?-Al 2 O 3 catalyst, Fuel, vol.171, pp.253-262, 2016.

M. Nguyen, M. Tayakout-fayolle, G. D. Pirngruber, F. Chainet, and C. Geantet, Kinetic modeling of quinoline hydrodenitrogenation over a NiMo(P)/Al 2 O 3 catalyst in a batch reactor, Ind. Eng. Chem. Res, vol.54, pp.9278-9288, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01229992

M. Nguyen, G. D. Pirngruber, F. Chainet, M. Tayakout-fayolle, and C. Geantet, Indole hydrodenitrogenation over alumina and silica-Alumina-supported sulfide catalysts-Comparison with quinoline, Ind. Eng. Chem. Res, vol.56, pp.11088-11099, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01625635

R. Doukeh, M. Bombos, A. Trifoi, O. Mihai, D. Popovici et al., Kinetics of thiophene hydrodesulfurization over a supported Mo-Co-Ni catalyst, Comptes Rendus Chimie, vol.21, pp.277-287, 2018.

N. Charon-revellin, H. Dulot, C. López-garcía, and J. Jose, Kinetic modeling of vacuum gas oil hydrotreatment using a molecular reconstruction approach, Oil Gas Sci. Technol. Rev. IFP Energies Nouv, vol.66, pp.479-490, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00877849

J. Schweitzer, P. Galtier, and D. Schweich, A single events kinetic model for the hydrocracking of paraffins in a three-phase reactor, Chem. Eng. Sci, vol.54, pp.2441-2452, 1999.

A. Elkamel, A. Al-ajmi, and M. Fahim, Modeling the hydrocracking process using artificial neural networks, Pet. Sci. Technol, vol.17, pp.931-954, 1999.

M. Bahmani, K. Sharifi, and M. Shirvani, Product Yields Prediction of Tehran Refinery Hydrocracking Unit Using Artificial Neural Networks, Iran. J. Chem. Eng, vol.7, pp.50-63, 2010.

S. Sadighi and G. Reza-zahedi, Comparison of kinetic-based and artificial neural network modeling methods for a pilot scale vacuum gas oil hydrocracking reactor, Bull. Chem. React. Eng. Catal, issue.8, 2013.

S. Sadighi and S. R. Mohaddecy, Evaluating the ability of R for modeling a commercial scale VGO hydrocracking plant using Artificial Neural Network (ANN), Pet. Coal, vol.60, pp.358-364, 2018.

L. P. De-oliveira, D. Hudebine, D. Guillaume, J. J. Verstraete, and J. F. Joly, A Review of Kinetic Modeling Methodologies for Complex Processes, Oil Gas Sci. Technol. Rev. IFP Energ. Nouv, vol.71, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01395195

S. H. Yang and C. N. Satterfield, Some effects of sulfiding of a NiMoAl 2 O 3 catalyst on its activity for hydrodenitrogenation of quinoline, J. Catal, vol.81, pp.168-178, 1983.

M. Sau, K. Basak, U. Manna, M. Santra, and R. P. Verma, Effects of organic nitrogen compounds on hydrotreating and hydrocracking reactions, Catal. Today, vol.109, pp.112-119, 2005.

N. Cao, B. Celse, D. Guillaume, I. Guibard, and J. W. Thybaut, Stabilization time modeling for hydroprocessing: Identification of the dominant factors, Chem. Eng. Sci, vol.2020
URL : https://hal.archives-ouvertes.fr/hal-02447484

C. Waldron, A. Pankajakshan, M. Quaglio, E. Cao, F. Galvanin et al., An autonomous microreactor platform for the rapid identification of kinetic models, React. Chem. Eng, 2019.

D. W. Marquardt, An algorithm for least-squares estimation of nonlinear parameters, J. Soc. Indust. Appl. Math, vol.11, pp.431-441, 1963.

J. J. More, The Levenberg-Marquardt Algorithm: Implementation and Theory, 1978.

R. W. Kennard and L. A. Stone, Computer aided design of experiments, vol.11, pp.137-148, 1969.

A. C. Atkinson, Beyond response surfaces: Recent developments in optimum experimental design, Chemom. Intell. Lab. Syst, vol.28, pp.35-47, 1995.

P. F. Aguiar, B. Bourguignon, M. S. Khots, D. L. Massart, and R. Phan-than-luu, D-optimal designs, Chemom. Intell. Lab. Syst, vol.30, pp.199-210, 1995.

L. Pronzato and A. Pázman, Design of Experiments in Nonlinear Models, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00879984

A. Saptoro, M. O. Tadé, and H. Vuthaluru, A modified Kennard-Stone algorithm for optimal division of data for developing artificial neural Network Models, Chem. Prod. Process Modeling, vol.7, 2012.

B. Celse, J. J. Da-costa, and V. Costa, Experimental design in nonlinear case applied to hydrocracking model: How many points do we need and which ones?, Int. J. Chem. Kinet, vol.48, pp.660-670, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01408735

V. V. Fedorov, Theory of Optimal Experiments, 1972.

W. H. Vandevender and K. H. Haskell, The SLATEC Mathematical Subroutine Library. Signum Newsl, vol.17, pp.16-21, 1982.

P. A. Fox, A. P. Hall, and N. L. Schryer, The PORT Mathematical Subroutine Library, ACM Trans. Math. Softw, vol.4, pp.104-126, 1978.

A. Fontijn, A. J. Sabadell, and R. J. Ronco, Homogeneous chemiluminescent measurement of nitric oxide with ozone. Implications for continuous selective monitoring of gaseous air pollutants, Anal. Chem, vol.42, pp.575-579, 1970.

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