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Xu, Yupeng

Publications and source records attributed to Xu, Yupeng.

16 records
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DOE OSTI2024

Air Classification of Forestry Residues for Fast Pyrolysis

Understanding critical biomass attributes through efficient fractionation is crucial for advancing sustainable pyrolysis for renewable energy and chemical production. This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency.

09 - BIOMASS FUELS↗
DOE OSTI2024

Numerical Simulation of Biogenic Fluid Catalytic Cracking (BFCC) Regenerators at Different Scales with MFIX-Exa

Catalytic Fast Pyrolysis (CFP) is a process that converts biomass into liquid intermediates suitable for transportation fuels by rapidly heating it in the presence of a catalyst, aiming to produce stable oils with reduced oxygen content. During CFP, the catalyst can become deactivated by the accumulation of coke, a carbon-rich deposit formed from the decomposition of biomass components. Unlike in petroleum refining, regenerating coked catalysts from biomass pyrolysis requires specific approaches due to the different chemical nature of the coke formed. An experimental technique, Temperature Programmed Oxidation (TPO), was used to study the de-coking process by gradually increasing temperature while monitoring the production of CO and CO2, which provides data for kinetic modeling. Utilizing data from TPO experiments, coke combustion kinetic model was developed to describe the rate of coke removal at different temperatures, allowing for simulation of regeneration processes. Then kinetic model is integrated into MFIX-Exa for the simulation of Biogenic Fluid Catalytic Cracker (BFCC) regenerator at different scales, enabling analysis of catalyst flow, temperature distribution, and regeneration efficiency under various operating conditions.

biogenic fluid catalytic cracking↗
DOE OSTI2024

The Effect of Air Separations on Fast Pyrolysis Products for Forest Residue Feedstocks

This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency. In summary, a detailed understanding and strategic manipulation of critical material attributes in biomass through efficient fractionation techniques are imperative for advancing fast pyrolysis as a sustainable avenue for renewable energy and chemical production.

09 BIOMASS FUELS↗
DOE OSTI2022

CFD Simulation of Biomass Pyrolysis Vapor Upgrading over a Pt/TiO 2 Catalyst in Fixed and Moving Beds

This report presents a comprehensive computational fluid dynamics (CFD) study of the biomass pyrolysis vapor phase upgrading and the catalyst regeneration in different reactors under various operational conditions. This study used the open-source software Multiphase Flow with Interphase eXchanges (MFiX), developed at National Energy Technology Laboratory (NETL) for simulating hydrodynamics, heat transfer, and chemical reactions in multiphase systems. This simulation solved the conservation of mass, momentum, energy, species for gas and solid phases with chemical reactions.

09 BIOMASS FUELS↗
DOE OSTI2021

Multiscale CFD simulation of biomass fast pyrolysis with a machine learning derived intra-particle model and detailed pyrolysis kinetics

Coupling particle and reactor scale models is as essential as reactor fluid dynamics and particle motion for accurate Computational Fluid Dynamic (CFD) simulations of biomass fast pyrolysis reactors due to intraparticle heat transfer and chemical reactions controlling conversion time and product distributions. Direct online coupling of a particle model with a reactor model is computationally expensive, while offline coupling is case-dependent. In this research, solutions from a series of particle pyrolysis simulations were regressed with Artificial Neural Network (ANN). Furthermoer, this machine learning-derived model predicted the same temperature and conversion profiles compared with particle resolved simulation while the isothermal approach overpredicted the temperature by 130 K and underpredicted the conversion time by 30 s. The ANN model was then integrated into CFD simulations of fluidized bed biomass fast pyrolysis with varied feedstocks via coupling PyTorch and MFiX. The averaged error of simulation predicted bio-oil yields with four feedstocks is 6.4%. This multi-scale approach provides an efficient tool for the coupled particle and reactor scale simulations of biomass pyrolysis.

09 BIOMASS FUELS↗
DOE OSTI2020

Coupling reduced‐order modeling and coarse‐grained CFD‐DEM to accelerate coal gasifier simulation and optimization

Abstract High fidelity three‐dimensional (3‐D) numerical simulations of commercial‐scale coal gasifiers are very time consuming and expensive. This article proposes a reduced‐order modeling approach that uses quasi one‐dimensional (1‐D) CFD–DEM simulation results to serve as an accurate initial condition for the 3‐D simulation, which significantly shortens the physical time from several hours to minutes to achieve steady states. The 3‐D simulation employs a previously validated coarse‐grained CFD‐DEM approach, which further accelerates the simulation. Both 1‐D and 3‐D simulations adopt a particle shrinkage scheme to correctly account for the particle volume change due to chemical reaction and thus provides an accurate bed height. Comparison with available experimental measurements of the bed temperature and synthesis gas composition is used to validate the simulation. The final syngas composition and flowrates are strongly affected by the fuel or gasification agent rate and process operating conditions as expected. This approach is then used to optimize two important operating conditions (air and steam flows) to achieve specific gasifier performance goals for the production of Fischer–Tropsch synthesis gas and production of fuel gas for gas turbines.

Yu, Jia↗
DOE OSTI2020

Experimental and numerical investigation of sands and Geldart A biomass co-fluidization

This study investigated the fluidization of sands and small Geldart A biomass mixtures. The mixture fluidized like Geldart A type particles with a uniform bed expansion regime before bubbling. The video recorded color distance between pure sands and sands–biomass mixtures was used to estimate the sands–biomass mixing. The coarse-grained computational fluid dynamics–discrete element method with a hybrid drag model which couples the Syamlal–O'Brien drag and a filtered drag can capture the mixing while the simulation with Gidaspow drag predicted a segregated bed. The simulations were further validated with experimental measured pressure drops. The time averaged pressure drop equals the weight of the bed material, however, its fluctuation is about three times of the bed material fluctuation.

42 ENGINEERING↗
DOE OSTI2019

Comprehensive experimental investigation on biomass-glass beads binary fluidization: A data set for CFD model validation

Fluidization behavior of biomass and glass beads binary mixtures in a bubbling fluidized bed was experimentally investigated. Mixtures containing different mass fraction of Loblolly Pine white wood and glass beads were fluidized at different fluidization velocities. The particle properties were characterized in a QICPIC that uses a dynamic image processing method to measure both particle size and sphericity. The minimum fluidization velocity was determined using the pressure drop method. An image processing method was developed to capture the dynamic expanded bed height at a very high frequency. The effect of biomass mass fraction and inlet gas velocity on mixing and segregation behavior was studied and analyzed through pressure drop measurements. Pressure drop fluctuations and expanded bed height fluctuations via fast Fourier transform were analyzed and compared. Here, the complete and accurate experimental data reported in this study could provide a benchmark data set for various computational fluid dynamics models validation, calibration, and identification.

42 ENGINEERING↗
DOE OSTI2018

Numerical and experimental comparison of tracer particle and averaging techniques for particle velocities in a fluidized bed

Particle tracking methods using emitted radiation show potential for following motion in opaque systems such as granular materials. Leading examples are Positron Emission Particle Tracking (PEPT) and Radioactive Particle Tracking (RPT). The application of such techniques sometimes requires the use of tracer particles which differ in size, density and/or shape from the particles of interest. This study investigates the extent to which such differences affect the result of the study by using the open source MFIX-DEM software to model particle motion in the travelling fluidized bed experiments. The results are compared with previously reported experimental studies using both PEPT and RPT. Consistent numerical results were obtained for both PEPT and RPT tracer particles. In determining averaged velocities using such techniques, there is a choice to be made between averaging velocities of particles crossing a virtual plane over a period of time (the “face-average” approach) or those passing through a defined volume over time (the “volume-average” approach). The differences between results obtained with these two methods are shown to be significant in this case, for both computation and experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Assessment of different coarse graining strategies to simulate polydisperse gas-solids flow

Continuum methods require the additional development of solids stress closures for polydisperse powders based on complex kinetic theories that are non-trivial to develop, code, and numerically converge for the wide range of fluidization regimes from very dilute to dense/frictional flow limit. On the other hand, it is straightforward to model the flow of polydisperse granular materials by treating particles as discrete rigid bodies that are tracked following simple physical laws of motion. The coarsening of these discrete methods by lumping several particles in a parcel alleviates the significant computational cost associated with these discrete methods while introducing some inaccuracies in the numerical results. In this research, we explore two different coarse graining methods that can be applied to polydisperse powders, namely the same statistic weight method (SSW) and the same size parcel method (SSP), and assess their accuracy by comparison with the finest simulation results obtained with a discrete element method (DEM). For Geldart group B powders fluidized at a relative low superficial velocity, the numerical results indicate that the SSW is more accurate than the SSP method. For type A powders fluidized at relatively high velocity, these two methods predict similar results. Interestingly, up to four times increase in the speed of simulation of the SSP method was obtained because the original polydisperse powder is scaled to a mono-disperse system in terms of particle-particle collision. Lastly, these results suggest that the SSP method is more favorable for the simulation of fluidized beds due to its accuracy and efficiency while the SSW method may be used for granular flow and dense fluidized bed systems where capturing the size segregation of particles due to collision is important.

42 ENGINEERING↗