CPFD simulation of a dual fluidized bed cold flow model

Lunzer, A.; Kraft, Stephan; Müller, Stefan; Hofbauer, Hermann

doi:10.1007/s13399-020-01229-4

Cited by 6 publications

(4 citation statements)

References 26 publications

(24 reference statements)

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“…The particle normal stress is affected only by the modification near or above the close pack. Increasing the P s value will increase the particle normal stress at lower particle volume fractions τ ( θ normalp ) = P s θ p β max [ θ c p − θ normalp , ε false( 1 − θ p false) ] θ p = ∫ ∫ ∫ f m normalp ρ normalp normald m p .25em normald u p .25em normald T p …”

Section: Mathematical Modelmentioning

confidence: 99%

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Numerical Study on the Steam Gasification of Biomass in a 100 kW Dual Fluidized Bed Gasifier

Yang,

Hu,

Chen

et al. 2024

Energy Fuels

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The dual fluidized bed (DFB) shows great potential for the steam gasification of biomass to produce hydrogen. Understanding the hydrodynamics and thermochemical characteristics in a pilot-scale DFB system is crucial for optimizing the operating conditions and devising the reactor design. In this study, a three-dimensional model, based on the multiphase particle-in-cell (MP-PIC) method, is developed for a 100 kW biomass DFB system featuring a staged gasification reactor. The entire DFB system is simulated, with a focus on the gasification reaction in the gasifier reactor and ignoring the reactions in the combustion reactor. The basic simulation settings are optimized based on the pressure distribution observed in the cold experiment results. The optimized model correctly predicts the reactor temperature, pressure distribution, and gas production characteristics of the gasification process. Then, the effects of temperature, steam-to-biomass ratio (S/B), and gasification atmosphere on gasification performance are explored based on the verified model. It shows that the H 2 production and CO 2 production are increased together with an increasing H 2 /CO ratio with the increase of gasification temperature. With the increase of S/B, the yields of H 2 and CO 2 and the ratio of H 2 /CO first increase and then decrease. The optimal S/B for this DFB is 0.5, as excessive steam can lower the reaction temperature, which is unfavorable for gasification conversion. Changing the gasification agent from pure steam to a CO 2 /H 2 O mixture results in increased CO yield and a lower H 2 content because of the competition of CO/H 2 O gasification and water gas shift reactions. This study provides meaningful insights on biomass gasification with steam in a large-scale fluidized bed gasifier, and the findings are beneficial for designing and optimizing DFB, particularly in the context of staged gasification processes.

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Mathematical Modelmentioning

confidence: 99%

Numerical Study on the Steam Gasification of Biomass in a 100 kW Dual Fluidized Bed Gasifier

Yang,

Hu,

Chen

et al. 2024

Energy Fuels

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“…The simulation and monitoring applications observe the process performance and support the design and commissioning. Several examples for simulation and monitoring applications can be found in [67][68][69][70][71][72]. The evaluation and verification stand for the information analysis, which helps to optimize the process from the design to the decommissioning phase by implementing sustainability indicators.…”

Section: Applications Challenges and Properties Of Virtual Representa...mentioning

confidence: 99%

Methodology for the Development of Virtual Representations within the Process Development Framework of Energy Plants: From Digital Model to Digital Predictive Twin—A Review

et al. 2023

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Digital reflections of physical energy plants can help support and optimize energy technologies within their lifecycle. So far, no framework for the evolution of virtual representations throughout the process development lifecycle exists. Based on various concepts of virtual representations in different industries, this review paper focuses on developing a novel virtual representation framework for the process development environment within the energy sector. The proposed methodology enables the continuous evolution of virtual representations along the process development lifecycle. A novel definition for virtual representations in the process development environment is developed. Additionally, the most important virtual representation challenges, properties, and applications for developing a widely applicable framework are summarized. The essential sustainability indicators for the energy sector are listed to standardize the process evaluation throughout the process development lifecycle. The virtual representation and physical facility development can be synchronized by introducing a novel model readiness level. All these thoughts are covered through the novel virtual representation framework. Finally, the digital twin of a Bio-SNG production route is presented, to show the benefits of the methodology through a use case. This methodology helps to accelerate and monitor energy technology developments through the early implementation of virtual representations.

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“…T. Basmoen et al [9] conducted an experimental and computational study on the gasification of biomass in fluidized beds. This study aimed to investigate the effect of the air-to-biomass ratio on the composition of the gas produced by the high-energy components H2, CH4, and CO.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of the Effect of Particle Size Distribution on Fluidized Bed Gasifier

Aklis,

Wijianto,

Asmindra

2024

E3S Web of Conf.

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The rapid development of technology and industrialization has confronted humanity with two important problems: the depletion of fossil energy resources and environmental damage. This study aims to determine the effect of the particle size distribution of the bed on the composition of the produced syngas which has the potential to replace fossil fuels. The particle bed used is silica sand with 4 variations of particle size distribution with a diameter of 600-1000 µm. The results of this study indicate that the larger the particle size distribution of the bed can reduce the temperature distribution and composition of the syngas produced. The highest temperature distribution was found in the 1st particle size distribution variation of 1060.23 K. The highest syngas composition was found in the 3rd particle size distribution variation of 2.21% CH4, 19.68% CO, 6.21% CO2, and 18.51% H2The highest syngas composition was found in the 3rd particle size distribution variation of 2.21% CH4, 19.68% CO, 6.21% CO2, and 18.51% H2. The lowest temperature distribution was obtained in the 3rd particle size distribution variation of 1057.77 K. The lowest syngas composition was found in the 4th particle size distribution 1.99% CH4, 17.71% CO, 5.63% CO2, and 16.66% H2.

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CPFD simulation of a dual fluidized bed cold flow model

Cited by 6 publications

References 26 publications

Numerical Study on the Steam Gasification of Biomass in a 100 kW Dual Fluidized Bed Gasifier

Numerical Study on the Steam Gasification of Biomass in a 100 kW Dual Fluidized Bed Gasifier

Methodology for the Development of Virtual Representations within the Process Development Framework of Energy Plants: From Digital Model to Digital Predictive Twin—A Review

Numerical Simulation of the Effect of Particle Size Distribution on Fluidized Bed Gasifier

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