José I. Bielma, Mengmeng Cui, Juan M. Colom, Isa Al Aslani, Diego Zapater, Rubén Medina Flores, Lujain Alfilfil, Isidoro Morales Osorio, Mohammed Hakami, Khalid Almajnouni, Jorge Gascon, Pedro Castaño
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引用次数: 0
Abstract
Scaling and optimizing dense fluidized bed reactors remain
challenging
because gas–solid interactions are complex and highly heterogeneous,
most experimental observations are limited to pseudo-2D systems, and
validating the numerical models used for design is difficult. This
challenge is particularly pronounced for geometries with diameter-transformed
structures (i.e., the bottom section of transported risers and two-
and multizone fluidized bed reactors) and for Geldart A solids, whose
fine particle size and cohesive behavior produce complex, chaotic
flow patterns. In this work, we developed an approach that integrates
cold-flow testing with CPFD simulations to regulate gas–solid
fluidization in a 3D diameter-transformed dense fluidized bed reactor.
We modified the Ergun-based drag model using pressure-drop measurements
and implemented it in CPFD simulations. The model accurately reproduces
experimental pressure drop and local solids holdup in a dense bed
reactor containing 1.2 kg of Geldart A particles, demonstrating its
predictive capability. We employed the validated model to evaluate
hydrodynamics (i.e., void fraction, solid flux, and residence time
distribution) under various operating conditions, enabling flexible
application across different reactions.
缩放和优化致密流化床反应器仍然具有挑战性,因为气固相互作用复杂且高度不均匀,大多数实验观察仅限于伪二维系统,并且验证用于设计的数值模型是困难的。这一挑战对于具有直径转换结构的几何形状(即,输送立管和两区和多区流化床反应器的底部)和Geldart A固体来说尤其明显,这些固体的细粒度和内聚行为产生了复杂、混乱的流动模式。在这项工作中,我们开发了一种方法,将冷流测试与CPFD模拟相结合,以调节三维直径转换致密流化床反应器中的气固流化。我们使用压降测量对基于ergun的阻力模型进行了改进,并在CPFD仿真中实现了该模型。该模型在含有1.2 kg Geldart a颗粒的密集床反应器中准确地再现了实验压降和局部固体含率,证明了其预测能力。我们使用验证过的模型来评估各种操作条件下的流体动力学(即空隙率、固体通量和停留时间分布),从而能够灵活地应用于不同的反应。
期刊介绍:
)ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)