Numerical Investigations of the Oxidative Dehydrogenation of Propane in a Spouted Bed Reactor

Li, Rongzhao; Wang, Yanxiao; Du, Yiqing; Liu, Haitao; Yang, Chaohe

doi:10.1021/acs.energyfuels.0c02029

Cited by 5 publications

(4 citation statements)

References 61 publications

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“…176 Oxidative PDH in a spouted-bed reactor is simulated using the multiphase particle-in-cell model. 177 The changes in propylene selectivity and propane conversion are observed with changes in parameters, such as catalyst particle size, static bed height, oxygen concentration, and temperature. Changes in the reaction environment due to physical factors such as a change in the direction of the injection pattern from upward to downward can create a significant difference in the outcome.…”

Section: Computer Simulations and Theoretical Observationsmentioning

confidence: 99%

“…Ignition limit maps (i.e., combustion behavior of the reactants inside the reactor) are also drawn using suitable modeling techniques with the help of ANSYS Fluent software . Oxidative PDH in a spouted-bed reactor is simulated using the multiphase particle-in-cell model . The changes in propylene selectivity and propane conversion are observed with changes in parameters, such as catalyst particle size, static bed height, oxygen concentration, and temperature.…”

Section: Computer Simulations and Theoretical Observationsmentioning

confidence: 99%

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Elucidation of Catalytic Propane Dehydrogenation Using Theoretical and Experimental Approaches: Advances and Outlook

Kumar,

Srivastava

2023

Energy Fuels

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Propylene is an important chemical used in the production of polypropylene, propylene oxide, propylene carbonate, and many more useful chemical compounds. High propylene demand and low industrial production motivate propane dehydrogenation (PDH) technology for propylene production. CrO x and Pt–Sn catalysts are employed for industrial PDH, occurring via the nonoxidative route. Cr-based catalysts face serious health and environmental issues. Moreover, the nonoxidative route used industrially faces thermodynamic limitations and catalyst deactivation occurring, because of recrystallization, sintering, agglomeration, and coking. The nonoxidative routes favor homolytic dissociation of the bonds (because of positive values of ΔG and ΔH of reaction), while both homolytic and heterolytic dissociation are observed in the oxidative route. Nonoxidative PDH follows the Langmuir–Hinshelwood mechanism, whereas oxidative PDH can occur via the Langmuir–Hinshelwood mechanism (with soft oxidants such as CO2, S2, SO2, and NO x ) or the Mars–van Krevelen mechanism (with O2). First-order kinetics of nonoxidative PDH and cracking is observed at low partial pressures of propane, whereas, at high partial pressures, it becomes zero-order, along with standard Gibbs free energy of the reaction (ΔG R 0) and enthalpy change of the reaction (ΔH R 0) equal to 86.2 kJ mol–1 and 124.3 kJ mol–1, respectively, at 25 °C. ΔG R 0 values for all the steps of oxidative PDH are negative, showing the thermodynamic feasibility of the oxidative route for PDH. Using H2 as a cofeed for nonoxidative PDH removes the precursor of coke, which increases catalyst stability and decreases the coke formation rate. Water addition results in an increase in the COx selectivity with an increment in the amount of water. The effect of promoters, reaction conditions, and support on Pt and Pt-based catalysts in terms of selectivity and yield of propylene, conversion of propane, changes in binding and bond dissociation energies, and activation energy is discussed with the help of DFT calculations and characterization techniques, such as X-ray photoelectron spectroscopy (XPS), extended X-ray absorption fine structure (EXAFS), etc. Limitations of coking and regeneration cycles and possible theoretical improvements through mathematical calculations and simulations are discussed for further research in PDH.

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Section: Computer Simulations and Theoretical Observationsmentioning

confidence: 99%

Section: Computer Simulations and Theoretical Observationsmentioning

confidence: 99%

Elucidation of Catalytic Propane Dehydrogenation Using Theoretical and Experimental Approaches: Advances and Outlook

Kumar,

Srivastava

2023

Energy Fuels

View full text Add to dashboard Cite

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“…With the rise in interest in biomass pyrolysis, numerical modeling studies have been conducted to investigate the process at different scales. These scales range from the molecular level and reaction kinetics to the reactor level for estimating product compositions [81][82][83]. Although multi-scale investigations are crucial, the input parameters from the molecular and particle scales are elementary and require integration with reactor levels for designing, scaling up, and optimizing industrial applications.…”

Section: Analysis Of Cfd Studiesmentioning

confidence: 99%

Advances in Computational Fluid Dynamics Modeling for Biomass Pyrolysis: A Review

Kulkarni,

Mishra,

Palla

et al. 2023

Energies

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Pyrolysis, a process for extracting valuable chemicals from waste materials, leverages computational fluid dynamics (CFD) to optimize reactor parameters, thereby enhancing product quality and process efficiency. This review aims to understand the application of CFD in pyrolysis. Initially, the need for pyrolysis and its role in biomass valorization are discussed, and this is followed by an elaboration of the fundamentals of CFD studies in terms of their application to the pyrolysis process. The various CFD simulations and models used to understand product formation are also explained. Pyrolysis is conducted using both conventional and microwave-assisted pyrolysis platforms. Hence, the reaction kinetics, governing model equations, and laws are discussed in the conventional pyrolysis section. In the microwave-assisted pyrolysis section, the importance of wavelength, penetration depth, and microwave conversion efficiencies on the CFD are discussed. This review provides valuable insights to academic researchers on the application of CFD in pyrolysis systems. The modeling of pyrolysis by computational fluid dynamics (CFD) is a complex process due to the implementation of multiple reaction kinetics and physics, high computational cost, and reactor design. These challenges in the modeling of the pyrolysis process are discussed in this paper. Significant solutions that have been used to overcome the challenges are also provided with potential areas of research and development in the future of CFD in pyrolysis.

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“…These drawbacks can be naturally overcome by a Euler−Lagrange approach, such as the MP-PIC method and CFD-DEM. Based on the MP-PIC approach, Li et al 19 assessed the performance of oxidative dehydrogenation of propane in a spouted-bed reactor with or without an internal draft tube. Similarly, Dwivedi et al 20 used the MP-PIC method to explore the impact of different-shaped risers on wall erosion and gas− solid hydrodynamics in a circulating fluidized-bed reactor.…”

Section: Introductionmentioning

confidence: 99%

Impact of the Reactor Structure on Biomass Pyrolysis in Fluidized-Bed Reactors: A Coarse-Grained CFD-DEM Study

Wang

Lin

et al. 2021

Energy Fuels

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A coarse-grained computational fluid dynamics coupled with the discrete element method (CFD-DEM) model, combined with a smoothed voidage algorithm and a multicomponent and multistep pyrolysis scheme, has been developed, validated, and used to study biomass pyrolysis in different-shaped fluidized-bed reactors. Correspondingly, fluidized-bed reactors with three different section shapes (i.e., circular, square, and rectangular sections) and gas inlet areas (i.e., 25, 50, and 100% of the bottom section) were devised to explore the effect of the reactor structure on pyrolysis behavior. The simulation results have been extensively analyzed and discussed by various indicators, such as the gas–solid flow patterns, bubble behaviors, pyrolysis product species, biomass reaction rates, and reactor wall erosion depths. It is found that the circular reactor has the largest mean bed height but the lowest fluctuation frequency. Moreover, the circular reactor generally has the largest bubble equivalent diameter at the same height, followed by the square reactor, and the rectangular reactor provides the smallest bubbles. Regarding the effect of the gas inlet area, the fluctuation frequency monotonically increases with reducing the gas inlet area. The largest gas inlet gives the lowest biomass mass loss rate and the smallest bubble equivalent diameter, whereas the other two smaller gas inlets provide quite similar results. Moreover, decreasing the gas inlet area also generates large bubbles more frequently. Finally, the circular reactor suffers the severest wear, followed by the square and the rectangular reactors. These findings are helpful in optimizing the design and operation of biomass fluidized-bed pyrolysis processes.

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Numerical Investigations of the Oxidative Dehydrogenation of Propane in a Spouted Bed Reactor

Cited by 5 publications

References 61 publications

Elucidation of Catalytic Propane Dehydrogenation Using Theoretical and Experimental Approaches: Advances and Outlook

Elucidation of Catalytic Propane Dehydrogenation Using Theoretical and Experimental Approaches: Advances and Outlook

Advances in Computational Fluid Dynamics Modeling for Biomass Pyrolysis: A Review

Impact of the Reactor Structure on Biomass Pyrolysis in Fluidized-Bed Reactors: A Coarse-Grained CFD-DEM Study

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