Engineering topics

Huckaby, E. D.

Publications and source records attributed to Huckaby, E. D..

4 records

DOE OSTI2017

Kinetic theory-based numerical modeling and analysis of bi-disperse segregated mixture fluidized bed

We discuss a series of continuum Euler-Euler simulations of an initially mixed bi-disperse fluidized bed which segregates under certain operating conditions. The simulations use the multi-phase kinetic theory-based description of the momentum and energy exchanges between the phases by Simonin’s Group [see e.g. Gourdel, Simonin and Brunier (1999). Proceedings of 6th International Conference on Circulating Fluidized Beds, Germany, pp. 205-210]. The discussion and analysis of the results focus on the fluid-particle momentum exchange (i.e. drag). Simulations using mono- and poly-disperse fluid-particle drag correlations are analyzed for the Geldart D-type size bi-disperse gas-solid experiments performed by Goldschmidt et al. [Powder Tech., pp. 135-159 (2003)]. The poly-disperse gas-particle drag correlations account for the local particle size distribution by using an effective mixture diameter when calculating the Reynolds number and then correcting the resulting force coefficient. Simulation results show very good predictions of the segregation index for bidisperse beds with the mono-disperse drag correlations contrary to the poly-disperse drag correlations for which the segregation rate is systematically under-predicted. The statistical analysis of the results shows a clear separation in the distribution of the gas-particle mean relaxation times of the small and large particles with simulations using the mono-disperse drag. In contrast, the poly-disperse drag simulations have a significant overlap and also a smaller difference in the mean particle relaxation times. This results in the small and large particles in the bed to respond to the gas similarly without enough relative time lag. The results suggest that the difference in the particle response time induce flow dynamics favorable to a force imbalance which results in the segregation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Multiphase flow simulations of a moving fluidized bed regenerator in a carbon capture unit

To accelerate the commercialization and deployment of carbon capture technologies, computational fluid dynamics (CFD)-based tools may be used to model and analyze the performance of carbon capture devices. This work presents multiphase CFD-based flow simulations for the regeneration device responsible for extracting CO 2 from CO 2 -loaded sorbent particles before the particles are recycled. The use of solid particle sorbents in this design is a departure from previously reported systems, where aqueous sorbents are employed. Another new feature is the inclusion of a series of perforated plates along the regenerator height. The influence of these plates on sorbent distribution is examined for varying sorbent holdup, fluidizing gas velocity, and particle size. The residence time distribution of sorbents is also measured to classify the low regime as plug flow or well-mixed flow. The purpose of this work is to better understand the sorbent flow characteristics before reaction kinetics of CO 2 desorption can be implemented.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2013

Multi-Phase CFD Modeling of Solid Sorbent Carbon Capture System

Computational fluid dynamics (CFD) simulations are used to investigate a low temperature post-combustion carbon capture reactor. The CFD models are based on a small scale solid sorbent carbon capture reactor design from ADA-ES and Southern Company. The reactor is a fluidized bed design based on a silica-supported amine sorbent. CFD models using both Eulerian-Eulerian and Eulerian-Lagrangian multi-phase modeling methods are developed to investigate the hydrodynamics and adsorption of carbon dioxide in the reactor. Models developed in both FLUENT® and BARRACUDA are presented to explore the strengths and weaknesses of state of the art CFD codes for modeling multi-phase carbon capture reactors. The results of the simulations show that the FLUENT® Eulerian-Lagrangian simulations (DDPM) are unstable for the given reactor design; while the BARRACUDA Eulerian-Lagrangian model is able to simulate the system given appropriate simplifying assumptions. FLUENT® Eulerian-Eulerian simulations also provide a stable solution for the carbon capture reactor given the appropriate simplifying assumptions.

Ryan, Emily M.↗

DOE OSTI2012

MULTI-PHASE CFD MODELING OF A SOLID SORBENT CARBON CAPTURE SYSTEM

Post-combustion solid sorbent carbon capture systems are being studied via computational modeling as part of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI). The work focuses on computational modeling of device-scale multi-phase computational fluid dynamics (CFD) simulations for given carbon capture reactor configurations to predict flow properties, outlet compositions, temperature and pressure. The detailed outputs of the device-scale models provide valuable insight into the operation of new carbon capture devices and will help in the design and optimization of carbon capture systems. As a first step in this project we have focused on modeling a 1 kWe solid sorbent carbon capture system using the commercial CFD software ANSYS FLUENT®. Using the multi-phase models available in ANSYS FLUENT®, we are investigating the use of Eulerian-Eulerian and Eulerian-Lagrangian methods for modeling a fluidized bed carbon capture design. The applicability of the dense discrete phase method (DDPM) is being considered along with the more traditional Eulerian-Eulerian multi-phase model. In this paper we will discuss the design of the 1 kWe solid sorbent system and the setup of the DDPM and Eulerian-Eulerian models used to simulate the system. The results of the hydrodynamics in the system will be discussed and the predictions of the DDPM and Eulerian-Eulerian simulations will be compared. A discussion of the sensitivity of the model to boundary and initial conditions, computational meshing, granular pressure, and drag sub-models will also be presented.

Ryan, Emily M.↗