Dynamic characterizations of gas–solid flow in a novel multistage fluidized bed via nonlinear analyses

Comparison of hydrodynamics and operational characteristics of a multistage fluidized bed with high-density and low-density powders

Simulations can reduce the time and cost to develop and deploy advanced technologies and enable their rapid scale-up for fossil fuel-based energy systems. However, to ensure their usefulness in practice, the credibility of the simulations needs to be established with uncertainty quantification (UQ) methods. The National Energy Technology Laboratory (NETL) has been applying non-intrusive UQ methodologies to categorize and quantify uncertainties in computational fluid dynamics (CFD) simulations of gas-solid multiphase flows. To reduce the computational cost associated with gas-solid flow simulations required for UQ analysis, techniques commonly used in the area of artificial intelligence (AI) and data mining are used to construct smart proxy models, which can reduce the computational cost of conducting large numbers of multiphase CFD simulations. The feasibility of using AI and machine learning to construct a smart proxy for a gas-solid multiphase flow has been investigated by looking at the flow and particle behavior in a non-reacting rectangular fluidized bed. The NETL’s in house multiphase solver, Multiphase Flow with Interphase eXchanges (MFiX), was used to generate simulation data for the rectangular fluidized bed. The artificial neural network (ANN) was used to construct a CFD smart proxy, which is able to reproduce the CFD results with reasonable error (about 10%). Several blind cases were used to validate this technology. The results show a good agreement with CFD runs while the approach is less computationally expensive. The developed model can be used to generate the time averaged results of any given fluidized bed with the same geometry with different inlet velocity in couple of minutes.

The paper presents a study of the flow in a fluidized bed. The analysis is based on measurements made on an experimental stand and computer simulations. Free software packages have been used for simulations. Simulation is done used the most common model for this kind of problem. The first type of model is the Eulerian-Eulerian type and have as their first approximation, the assimilation of the solid phase with a continuous environment. The second category of models is Eulerian-Lagrangean type, they treat the fluid phase as continuous and the solid phase as individual particles or groups of particles “parcels” with similar characteristics. The results of the simulations were compared with the measurements performed on an experimental stand. The experimental stand is composed of a glass column with a diameter of 75mm and a height of 500mm and allows the study of flow in a fluidized bed containing spherical glass beads of 250–500μm in diameter. The results of the simulation were in good agreement whit measured data and in accordance whit the result presented in other specialized studies.

Gas and solids mixing characteristics in the bubbling and turbulent regimes of a gas‐solid fluidized bed are examined using helium and phosphor tracer techniques to obtain the gas and solids dispersion coefficients, respectively. The real time, quasi‐3‐D flow behavior is qualified and quantified by the electrical capacitance tomography (ECT) technique. The mixing behavior varies significantly with the flow regimes. As the gas velocity increases, axial and radial gas dispersion coefficients increase in the bubbling regime, reach a peak at Uc, the transition velocity from the bubbling to turbulent regimes, and then decrease. In contrast, as the gas velocity increases, axial and radial solids dispersion coefficients increase in the bubbling regime and continuously increase through Uc to the turbulent regime. Temperature and pressure have little effect on the gas and solids mixing behavior. A small quantity of fine particles is noted to drastically affect the gas and solids mixing behavior in the turbulent fluidized bed. The axial and radial dispersion coefficients of gas and solids reach their maximum when the fines content is about 15%. The ECT measurements illustrate the effect of adding fines on the flow behavior in the bed. A small quantity of fine particles disintegrate the bubble/void phase, significantly modifying bubble/void‐ and emulsion‐phase mixing behavior.

Parallel LES-DEM simulation of dense flows in fluidized beds

Multi-scale numerical simulation of fluidized beds: Model applicability assessment

Currently there are significant amounts of natural gas that cannot be produced and treated to meet pipeline specifications, because that would not be economically viable. This work investigates a bench scale multistage fluidized bed (MSFB) with shallow beds for sour gas removal from natural gas using a commercially available supported amine sorbent. A MSFB is regarded as a promising adsorber type for deep sour gas removal to parts per million concentrations. A series of experiments was conducted using carbon dioxide as sour gas and nitrogen to mimic natural gas. Removal below 3 mol ppm was successfully demonstrated. This indicates that gas bypassing is minor (that is, good gas–solid contacting) and that apparent adsorption kinetics are fast for the amine sorbent applied. Tray efficiencies for a chemisorption/adsorption system were reported for one of the first times. Current experiments performed at atmospheric pressure strongly indicate that deep removal is possible at higher pressures in a multistage fluidized bed.

Process simulation of an efficient temperature swing adsorption concept for biogas upgrading

The experiments discussed here have been carried out to investigate the mechanism of gas flow and mixing in fluidized beds. Two tracing techniques have been employed in this study. One is referred to as the fine-powder tracing technique, which was developed in the present investigation to observe characteristics of gas flow in a two-dimensional fluidized bed. In the other technique hydrogen was applied as tracer gas to obtain the residence time distribution (RTD) and values of dispersion efficiency of gas. A Dirac delta-function input signal of hydrogen was injected in the beds when the beds were stationary.

In Victoria, Australia, brown coal is utilised as a major source of energy for the power generation industry. Victorian and South Australian brown coals have a very high moisture content and therefore, the efficiencies of power generation in traditional pulverised fuel fired furnaces are low. Fluidised beds offer a number of advantages over conventional furnaces, leading to improvements in efficiency and environmental impact. A disadvantage with implementing fluidised bed technology is the issue of scale-up. Fluidised bed behaviour can alter significantly with changes in scale, because of their strong dependence on the bed hydrodynamics. Hence, there is a need to accurately model bed behaviour to ensure that the effect of changes in scale are well understood and will not become costly and time consuming. Computational Fluid Dynamics (CFD) techniques can be applied to fluidised bed systems to gain a better understanding of the hydrodynamic behaviour involved. In the past, numerical models have considered only single particle sizes due to the added complexity of interaction between particles of differing sizes and densities. Industrial fluidised beds typically contain more than one particle size and density, therefore there is a need to develop a numerical model which takes this into account. The aim of this thesis is to develop and validate CFD techniques for modelling the behaviour of a gas-solid fluidised bed containing more than one particle size and density. To provide validation data for the numerical model, physical experiments are undertaken on a small two-dimensional bubbling gas-solid fluidised bed. Mixing and segregation behaviour of different materials are investigated. The experiments demonstrate that whilst only a small proportion of the bed consists of different size/density particles, significant changes in bed behaviour are apparent. Changes in bubble rise velocity, bubble size and bubble shape are observed. A number of constitutive equations must be included in the numerical model, including relationships for the momentum transfer between various phases and solids pressure. Different combinations of these constitutive equations are investigated. A new equation for particle-particle interactions is derived and included in a CFD model. The CFD model is validated against both data in the literature and physical experiments. From the validation studies, an optimum equation set is identified. This optimum equation set produces numerical results that closely resemble experimental bed behaviour, thus bringing the goal of solving scale-up problems one step closer. The use of this type of CFD model will ultimately result in timely and cost effective solutions for both the power generation and chemical processing industries.

Pneumatically controlled downcomers which are free from bridging and spouting of solids have been developed and tested. The principle has been applied successfully to the development of new types of multi-stage fluidized beds, which have been tested up to the pilot-plant scale.

CFD-DEM (computational fluid dynamic-discrete element method) is a promising approach for simulating fluid–solid flows in fluidized beds. This approach generally under-predicts the granular temperature due to the use of drag models for the average drag force. This work develops a simple model to improve the granular temperature through increasing the drag force fluctuations on the particles. The increased drag force fluctuations are designed to match those obtained from PR-DNSs (particle-resolved direct numerical simulations). The impacts of the present model on the granular temperatures are demonstrated by posteriori tests. The posteriori tests of tri-periodic gas–solid flows show that simulations with the present model can obtain transient as well as steady-state granular temperature correctly. Moreover, the posteriori tests of fluidized beds indicated that the present model could significantly improve the granular temperature for the homogenous or slightly inhomogeneous systems, while it showed negligible improvement on the granular temperature for the significantly inhomogeneous systems.

This report summarizes the objectives, tasks and accomplishments made during the three year duration of this research project. The report presents the results obtained by applying advanced computational techniques to develop reduced-order models (ROMs) in the case of reacting multiphase flows based on high fidelity numerical simulation of gas-solids flow structures in risers and vertical columns obtained by the Multiphase Flow with Interphase eXchanges (MFIX) software. The research includes a numerical investigation of reacting and non-reacting gas-solids flow systems and computational analysis that will involve model development to accelerate the scale-up process for the design of fluidization systems by providing accurate solutions that match the full-scale models. The computational work contributes to the development of a methodology for obtaining ROMs that is applicable to the system of gas-solid flows. Finally, the validity of the developed ROMs is evaluated by comparing the results against those obtained using the MFIX code. Additionally, the robustness of existing POD-based ROMs for multiphase flows is improved by avoiding non-physical solutions of the gas void fraction and ensuring that the reduced kinetics models used for reactive flows in fluidized beds are thermodynamically consistent.

Acceleration techniques for reduced-order models based on proper orthogonal decomposition

Visualization and void fraction distribution of downward gas–liquid two-phase flow in a plate heat exchanger by neutron radiography