Numerical simulations of the industrial circulating fluidized bed boiler under air- and oxy-fuel combustion

Adamczyk, Wojciech; Kozołub, Paweł; Klimanek, Adam; Białecki, Ryszard A.; Andrzejczyk, M.; Klajny, Marcin

doi:10.1016/j.applthermaleng.2015.04.056

Cited by 48 publications

(20 citation statements)

References 33 publications

(43 reference statements)

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“…Particle number in a parcel,

N_{normalp}

, which affects the accuracy of results, is an important parameter for coarse‐grained modelling approaches . Usually in the DDPM modelling approach, the standard treatment for particle number in a parcel is calculated by the ratio of parcel mass to the particle mass:

N_{normalp} = \frac{m_{parcel}}{m_{particle}} = \frac{N_{normalp} \cdot ρ_{normalp} \cdot \frac{1}{6} π d_{normalp}^{3}}{ρ_{normalp} \cdot \frac{1}{6} π d_{normalp}^{3}} = \frac{ρ_{normalp} \cdot \frac{1}{6} π d_{parcel}^{3}}{ρ_{normalp} \cdot \frac{1}{6} π d_{normalp}^{3}} = {(\frac{d_{parcel}}{d_{p}})}^{3}

…”

Section: Resultsmentioning

confidence: 99%

Numerical simulation of a semi‐industrial scale CFB riser using coarse‐grained DDPM‐EMMS modelling

et al. 2017

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In this work, a coarse‐grained Dense Discrete Phase Model (DDPM) coupled with the Energy‐Minimization Multi‐Scale (EMMS) drag, was used to simulate the hydrodynamics of a 3D semi‐industrial scale Circulating Fluidized Bed (CFB) with Geldart A particles. The effect of particle numbers in a parcel, an important parameter in a coarse‐grained approach, was investigated. It was found that when parcel diameter falls into the size range of clusters, simulation results are insensitive to particle number in a parcel and generally agree with the experimental data. Further, a comparison between DDPM and Eulerian Two‐Fluid Modelling (TFM) approaches was investigated, both coupled with EMMS and conventional homogenous drag. The simulation results suggested that the effect of meso‐scale structures on drag force needs to be considered in both modelling approaches.

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“…Particle number in a parcel,

N_{normalp}

N_{normalp} = \frac{m_{parcel}}{m_{particle}} = \frac{N_{normalp} \cdot ρ_{normalp} \cdot \frac{1}{6} π d_{normalp}^{3}}{ρ_{normalp} \cdot \frac{1}{6} π d_{normalp}^{3}} = \frac{ρ_{normalp} \cdot \frac{1}{6} π d_{parcel}^{3}}{ρ_{normalp} \cdot \frac{1}{6} π d_{normalp}^{3}} = {(\frac{d_{parcel}}{d_{p}})}^{3}

…”

Section: Resultsmentioning

confidence: 99%

Numerical simulation of a semi‐industrial scale CFB riser using coarse‐grained DDPM‐EMMS modelling

et al. 2017

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“…For the radiation heat transfer calculation of oxy‐fuel combustion, the weighted‐sum‐of‐gray‐gases (WSGG) model can quickly and accurately calculate the radiation characteristics of oxy‐fuel gases; and it has been widely used in oxy‐fuel furnace computational fluid dynamics (CFD) simulation research . In recent years, scholars have developed different WSGG models for oxy‐fuel conditions based on different benchmark models.…”

Section: Introductionmentioning

confidence: 99%

“…For the radiation heat transfer calculation of oxy-fuel combustion, the weighted-sum-of-gray-gases (WSGG) model can quickly and accurately calculate the radiation characteristics of oxy-fuel gases; 15,16 and it has been widely used in oxy-fuel furnace computational fluid dynamics (CFD) simulation research. 17,18 In recent years, scholars have developed different WSGG models for oxyfuel conditions based on different benchmark models. Yin 19 and Rehfeldt 20 developed new WSGG models using the exponential wide band model (EWBM) as benchmark; after that, Johansson developed new WSGG model correlations based on the SNB model of the EM2C database.…”

Section: Introductionmentioning

confidence: 99%

New weighted-sum-of-gray-gases model for typical pressurized oxy-fuel conditions

et al. 2017

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Summary Pressurized oxy‐fuel combustion technology has received considerable attention due to its ability to improve the overall system efficiency and to control CO2 emissions. The characteristics of radiation heat transfer are significant for pressurized oxy‐fuel gas mixture and different from those under atmospheric conditions. Therefore, to calculate the radiation characteristics of pressurized oxy‐fuel gas mixture quickly and accurately, new weighted‐sum‐of‐gray‐gases (WSGG) model for pressurized oxy‐fuel conditions was first presented in this paper, which was applied in 3 typical high pressure conditions: 5, 10, and 15 bar. The new WSGG model correlations were suitable for pressurized conditions with a molar ratio range of 0.125‐2, temperature range of 400‐2500 K, and path length range of 0.1‐20 m. Calculations for a variety of typical pressurized oxy‐fuel combustion cases showed that the new WSGG model can accurately predict the radiation characteristics and heat transfer characteristics of the gas mixtures compared with the SNB model benchmark. In addition, the application of the previous atmospheric WSGG models yielded non‐ideal results under pressurized conditions. Consequently, the new model can provide efficient and accurate radiation heat transfer results for pressurized oxy‐fuel conditions and can be used to design pressurized oxy‐fuel combustion furnaces or boilers.

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“…This suggests that the furnace temperature has a greater influence on the heat transfer coefficient than the suspension density. A similar trend in heat transfer coefficient variation is observed both for laboratory/pilot units [20,58] and CFB boilers operating with low suspension densities (less than 20 kg/m 3 ) [7,8,[60][61][62][63]. The heat transfer data for both fuzzy logic and cluster renewal approach are close to each other.…”

Section: Bed-to-wall Heat Transfer Coefficient Distributionsmentioning

confidence: 49%

A comparison of fuzzy logic and cluster renewal approaches for heat transfer modeling in a 1296 t/h CFB boiler with low level of flue gas recirculation

Błaszczuk¹,

Krzywański²

2017

Archives of Thermodynamics

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The interrelation between fuzzy logic and cluster renewal approaches for heat transfer modeling in a circulating fluidized bed (CFB) has been established based on a local furnace data. The furnace data have been measured in a 1296 t/h CFB boiler with low level of flue gas recirculation. In the present study, the bed temperature and suspension density were treated as experimental variables along the furnace height. The measured bed temperature and suspension density were varied in the range of 1131-1156 K and 1.93-6.32 kg/m 3 , respectively. Using the heat transfer coefficient for commercial CFB combustor, two empirical heat transfer correlation were developed in terms of important operating parameters including bed temperature and also suspension density. The fuzzy logic results were found to be in good agreement with the corresponding experimental heat transfer data obtained based on cluster renewal approach. The predicted bed-to-wall heat transfer coefficient covered a range of 109-241 W/(m 2 K) and 111-240 W/(m 2 K), for fuzzy logic and cluster renewal approach respectively. The divergence in calculated heat flux recovery along the furnace height between fuzzy logic and cluster renewal approach did not exceeded ±2%.

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Numerical simulations of the industrial circulating fluidized bed boiler under air- and oxy-fuel combustion

Cited by 48 publications

References 33 publications

Numerical simulation of a semi‐industrial scale CFB riser using coarse‐grained DDPM‐EMMS modelling

Numerical simulation of a semi‐industrial scale CFB riser using coarse‐grained DDPM‐EMMS modelling

New weighted-sum-of-gray-gases model for typical pressurized oxy-fuel conditions

A comparison of fuzzy logic and cluster renewal approaches for heat transfer modeling in a 1296 t/h CFB boiler with low level of flue gas recirculation

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