A comparison of lumped and distributed models of monolith catalytic combustors

Groppi, Gianpiero; Belloli, Alberto; Tronconi, Enrico; Forzatti, Pio

doi:10.1016/0009-2509(95)00099-q

Cited by 153 publications

(100 citation statements)

References 35 publications

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“…Given the measured rates, the pore resistance effect was estimated using Wagner-Weisz-Wheeler modulus M W [44]. With the value of 1.7228 × 10 −2 at 550 • C, which is the highest value of M W , the pore resistance is negligible in this study.…”

Section: Experimental Datamentioning

confidence: 99%

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Water–Gas Shift Reaction over Ni/CeO2 Catalysts

et al. 2017

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This paper reports the results of a study of a water-gas shift reaction over nickel-ceria catalysts with different metal loading. Within this study, the overall CO conversion and observed kinetic behavior were investigated over the temperature range of 250-550 • C in different reactor configurations (fixed-bed and microchannel reactors). The quasi-steady state kinetics of the CO water-gas shift reaction was studied for fractions of Ni-containing cerium oxide catalysts in fixed-bed experiments at lab-scale level using a very dilute gas (1% CO + 1.8% H 2 O in He). A set of experiments with a microchannel reactor was performed using the feed composition (CO:H 2 O:H 2 :N 2 = 1:2:2:2), representing a product gas from methane partial oxidation. The results were interpreted using computational models. The kinetic parameters were determined by regression analysis, while mechanistic aspects were considered only briefly. Simulation of the WGS reaction in the microreactor was also carried out by using the COMSOL Multiphysics program.

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Section: Experimental Datamentioning

confidence: 99%

“…The mass transfer and heat transfer coefficients were evaluated from the correlations (15) for Nu and Sh numbers [44]. The reaction rate constants for the WGS Reaction (1) ( Table 3) and methanation Reaction (2) ( Table 8) were adapted to be suitable the computational domain (Table 9).…”

Section: Cell Dimensionsmentioning

confidence: 99%

Water–Gas Shift Reaction over Ni/CeO2 Catalysts

et al. 2017

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“…Due to the dimensions of the system, the concentration and speed radial profiles are developed in a small distance and thus, only the axial direction variations are considered in the model [7], [8]. Moreover, all the honeycomb subchannels operate in the same way [9], [10], [11], and therefore, the reactor will be treated as a single channel. It is also assumed that pressure remains constant throughout the reactor [12], [13].…”

Section: Mathematical Modelingmentioning

confidence: 99%

“…Moreover, all the honeycomb subchannels operate in the same way [9], [10], [11], and therefore, the reactor will be treated as a single channel. It is also assumed that pressure remains constant throughout the reactor [12], [13]. With respect to the thermal model, the next assumptions are considered: the temperature of the solid phase is equal to the gas phase [14], and only axial heat convection is modeled as heat transfer mechanism.…”

Section: Mathematical Modelingmentioning

confidence: 99%

Nonlinear Model Predictive Control for hydrogen production in an Ethanol Steam Reformer with membrane separation

Contreras

Prat

Ocampo‐Martínez

et al. 2016

2016 IEEE Conference on Control Applications (CCA)

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Abstract-This paper presents a new Nonlinear Model Predictive Control (NMPC) design for an Ethanol Steam Reformer with Pd-Ag membrane separation stage. The reformer is used to produce pure hydrogen able to feed a Proton Exchange Membrane Fuel Cell. Mass and energy balances are used to obtain the nonlinear dynamic model of both the reforming and the separation stages. Constraints, system nonlinearities and flexible cost function are the main reasons to select an NMPC controller, which is tested against the ordinary differential equations as simulation model, and has an internal model based on the sample data technique.

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“…On the other hand, numerical simulations of catalytic micro-combustors encompass investigations of combustion stability and performance using 1-D models with lumped heat and mass transport coefficients (Kaisare et al, 2008;Ronney, 2003), 2-D models with detailed chemistry kinetics but without heat conduction in the solid wall (Maruta et al, 2002), 2-D models with simplified chemistry kinetics accounting for heat conduction in the solid (Deshmukh et al, 2004;Stefanidis and Vlachos, 2009), and finally full 2-D CFD models where all relevant heat transfer mechanisms in the solid (including heat conduction and surface radiation heat transfer) along with detailed homogeneous and heterogeneous chemistry kinetics are accounted (Karagiannidis et al, 2007). It is emphasized that although Sherwood and Nusselt number empirical correlations have been proposed for laminar channel flows with surface catalytic reactions (Groppi et al, 1995), their universal applicability under different reacting conditions is not warranted. Moreover, 1-D models fail to describe homogeneous combustion due to the strong dependence of homogeneous reactions on the boundary layer profiles of temperature and species (Mantzaras and Benz, 1999).…”

Section: Introductionmentioning

confidence: 99%

Effect of Wall Thermal Conductivity on Hydrogen-Assisted Catalytic Ignition Characteristics of Propane-Air at Micro-Scales in Different Feeding Modes

Chen¹,

Gao²,

Xu³

2015

Frontiers in Heat and Mass Transfer

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Effect of wall thermal conductivity on hydrogen self-ignition and hydrogen-assisted ignition of propane-air mixtures in different feeding modes from ambient cold-start conditions were investigated numerically with chemical kinetic model in Pt/γ-Al2O3 catalytic micro-combustors. For the steady and transient state, effect of wall thermal conductivity on self-ignition characteristics of lean hydrogen-air mixtures was presented, and hydrogenassisted combustion of propane-air mixtures was investigated numerically in the co-feed mode and the sequential feed mode. The computational results indicate the large thermal inertia of the micro-combustor solid structure leads to slow temperature dynamics, and transient response is dominated by the thermal inertia. The heat localization in poorly conducting walls leads to fast ignition and shorter steady state time. In general, the concentration of hydrogen required for propane ignition increased with increasing wall thermal conductivity, decreasing inlet velocity, and decreasing inlet equivalence ratio of propane-air mixtures. In the co-feed mode, the combustion characteristics of hydrogen-assisted propane qualitatively resemble the selectively preheating initial portion of the combustion chamber wall. In the sequential feed mode, the time taken to reach steady state, the hydrogen cut-off time, the propane ignition time and the cumulative propane emissions increased with increasing wall thermal conductivity; the ignition characteristics are similar to partially preheating the initial segment for low and moderate wall thermal conductivity values (0.5 and 20 W/m· K); however, the ignition characteristics are close to completely heating the micro-combustor wall for high wall thermal conductivity values (200 W/m· K).

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A comparison of lumped and distributed models of monolith catalytic combustors

Cited by 153 publications

References 35 publications

Water–Gas Shift Reaction over Ni/CeO2 Catalysts

Water–Gas Shift Reaction over Ni/CeO2 Catalysts

Nonlinear Model Predictive Control for hydrogen production in an Ethanol Steam Reformer with membrane separation

Effect of Wall Thermal Conductivity on Hydrogen-Assisted Catalytic Ignition Characteristics of Propane-Air at Micro-Scales in Different Feeding Modes

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