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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

An approach for drag correction based on the local heterogeneity for gas-solid flows

The drag models typically used for gas-solids interaction are mainly developed based on homogeneous systems of flow passing fixed particle assembly. It has been shown that the heterogeneous structures, i.e., clusters and bubbles in fluidized beds, need to be resolved to account for their effect in the numerical simulations. Since the heterogeneity is essentially captured through the local concentration gradient in the computational cells, this study proposes a simple approach to account for the non-uniformity of solids spatial distribution inside a computational cell and its effect on the interaction between gas and solid phases. Finally, to validate this approach, the predicted drag coefficient has been compared to the results from direct numerical simulations. In addition, the need to account for this type of heterogeneity is discussed for a periodic riser flow simulation with highly resolved numerical grids and the impact of the proposed correction for drag is demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions

The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not work for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Verification of Eulerian-Eulerian and Eulerian-Lagrangian simulations for turbulent fluid-particle flows

Here, we present a verification study of three simulation techniques for fluid–particle flows, including an Euler–Lagrange approach (EL) inspired by Jackson's seminal work on fluidized particles, a quadrature–based moment method based on the anisotropic Gaussian closure (AG), and the traditional two-fluid model. We perform simulations of two problems: particles in frozen homogeneous isotropic turbulence (HIT) and cluster-induced turbulence (CIT). For verification, we evaluate various techniques for extracting statistics from EL and study the convergence properties of the three methods under grid refinement. The convergence is found to depend on the simulation method and on the problem, with CIT simulations posing fewer difficulties than HIT. Specifically, EL converges under refinement for both HIT and CIT, but statistics exhibit dependence on the postprocessing parameters. For CIT, AG produces similar results to EL. For HIT, converging both TFM and AG poses challenges. Overall, extracting converged, parameter-independent Eulerian statistics remains a challenge for all methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Dynamic real‐time optimization for a CO 2 capture process

Growing awareness of climate change has led to increased focus on new energy processes that mitigate generation of CO 2 , or provide for its efficient capture. To enable the development of these processes, advanced modeling and optimization platforms have been created. New capabilities among platforms include efficient solution strategies for online optimization problems. For real time, dynamic optimization of CO 2 capture processes, we demonstrate the application of the Python‐based Pyomo platform to facilitate realization of Moving Horizon Estimation and Nonlinear Model Predictive Control, through novel nonlinear optimization and sensitivity strategies. This capability allows large scale, first principle models to be applied for online optimization. Here, we introduce the Control and Adaptation with Predictive Sensitivity Enhancements (CAPRESE) framework to demonstrate this framework for advanced energy processes. Moreover, we present two case studies: profile tracking with detailed tray‐by‐tray distillation models and Bubbling Fluidized Bed reactors for CO 2 capture. © 2018 American Institute of Chemical Engineers AIChE J , 65: e16511 2019

Thierry, David↗
DOE OSTI2016

Influence of the Feedstock on Catalytic Fast Pyrolysis with a Solid Acid Catalyst

Abstract At RTI, we are developing a catalytic fast pyrolysis process with a new solid acid catalyst, the performance of which has been evaluated in a pilot‐scale reactor using loblolly pine. More robust technology development requires a deeper understanding of the influence of the feedstock properties of process performance defined by the organic liquid yield and composition. Seven types of woody and herbaceous biomass were tested in a 2.54 cm diameter fluidized‐bed reactor. This study shows that the product distribution and biocrude composition vary widely with different feedstocks. The yield of organic biocrude is in the range of 14.0–20.8 wt % for the tested feedstocks. The yields of incondensable gases and carbonaceous solids vary significantly from feedstock to feedstock, which may be because of the variation of the ash content in the feedstock. A feedstock with a higher ash content generates more gases; specifically more CO 2 but not necessarily more CO. The chemical composition, which includes lignin, hemicellulose, and cellulose, also affects the biocrude composition and the yield of gases. We also demonstrated a positive correlation between the cellulose content and CO yield and a negative correlation between the hemicellulose content and CO yield.

Wang, Kaige↗
DOE OSTI2015

Modeling biomass gasification system using multistep kinetics under various oxygen–steam conditions

Biomass gasification is an effective method to convert low‐value lingocellulosic biomass into useful gas products. The ability to predict the gas composition is important to process design. In this study, simulations of biomass gasification were carried out for various feedstocks at different operating conditions, and the model results were validated using experimental data. A multistep kinetics model was developed to predict the syngas composition using different biomass feedstocks under various oxygen‐enriched air and steam conditions. The oxygen level in the gasifying agent ranged from 21% (air) to 45% (pure oxygen). Five different biomass materials were used, including pine, maple–oak mixture, seed corn, corn stover, and switchgrass. The fluidized bed gasifier was maintained at 800°C. The present kinetics model was able to predict the concentrations of H 2 , CO, CO 2 , H 2 O, CH 4 , and N 2 in the syngas, and the predicted compositions were in good agreement with the experimental data. The results show that the model was sensitive to the variation in the oxygen level, steam flow rate, and the composition of the biomass material. As the oxygen level increased, the model also predicted the increase in H 2 , CO, CH 4 , and the H 2 /CO ratio. The mechanism on improving the syngas quality was also explained by analyzing the reaction equations. The increase in hydrogen is believed to be due to the use of steam for gasification. The present model can further be integrated into the process simulation model for predicting the performance of a biorefinery to help utilize biomass energy. © 2015 American Institute of Chemical Engineers Environ Prog, 34: 1148–1155, 2015

Banerjee, Sudhanya↗
DOE OSTI2018

A novel chemical looping partial oxidation process for thermochemical conversion of biomass to syngas

The Biomass-to-Syngas (BTS) chemical looping process is an advanced thermochemical biomass conversion process for the production of sustainable fuels and chemicals. The BTS process is novel in that it converts biomass feedstock to high purity syngas with adjustable H 2 :CO molar ratio without needing an air separation unit (ASU), a tar reformer, a steam reformer, or a water-gas-shift (WGS) reactor. In the BTS process, biomass feedstock is partially oxidized to produce syngas by oxygen carriers in a reducer that is operated in a co-current gas-solid moving bed contact mode. The reduced oxygen carriers are regenerated in a fluidized bed combustor via the oxidation reaction with air. The BTS process uses the iron-titanium composite metal oxide (ITCMO) material as the oxygen carrier, which is capable of cracking the volatiles produced in biomass pyrolysis as well as regulating the syngas composition. The co-current moving bed reducer eliminates back-mixing, channeling, or bypassing of solid and gas reactants, resulting in a syngas composition that is close to the thermodynamic equilibrium. In this paper, the rationale of a successful BTS process is discussed along with the thermodynamic characteristics of the ITCMO oxygen carrier, that can effectively react with a woody biomass feedstock, analyzed based on an ASPEN Plus model. Bench scale moving bed reducer experiments are presented, indicating the conversion of wood pellets to syngas with a H 2 :CO ratio of 2, which is suitable for methanol or liquid fuel synthesis. The gas and solid composition produced in the bench scale reducer matches the prediction from the ASPEN Plus thermodynamic model. Furthermore, this model is further used to analyze the performance of the BTS process under autothermal conditions for methanol production, with a comparison with a baseline indirectly heated gasification process.

09 BIOMASS FUELS↗
DOE OSTI2025

Advancing Pumped Thermal Energy Storage Performance and Cost Using Silica Storage Media

Pumped Thermal Energy Storage (PTES) is an electricity storage system that is suitable for long-duration energy storage (10-1000 h) due to its low marginal cost of energy capacity. We present a techno-economic model of a PTES system that uses particle thermal energy storage. Particles have low costs and can be operated over a wide temperature range leading to increased efficiency and reduced costs compared to other PTES designs. We show how the round-trip efficiency, specific power output, capital cost, and levelized cost of storage (LCOS) depend on parameters such as the pressure ratio, heat exchanger approach temperature and pressure loss, and maximum temperature. We compare particle-PTES (P-PTES) performance to PTES which uses liquid thermal energy storage - i.e. molten salt hot storage and methanol cold storage (MS-PTES). We find that using silica particles for storage advances PTES technology: P-PTES can be operated at higher maximum temperatures than MS-PTES. Furthermore, P-PTES can achieve lower approach temperatures in the heat exchangers than MS-PTES without increasing capital costs, because P-PTES uses direct-contact heat transfer in fluidized bed heat exchangers. As a result, we find that P-PTES systems achieve higher round-trip efficiency than MS-PTES (66 % versus 57 %) and lower LCOS (e.g. 0.115 +- 0.03 $/kWhe versus 0.171 +- 0.04 $/kWhe for 10 h discharge). The low cost of particles and containment means that P-PTES can provide long-duration energy storage at low capital cost per unit energy capacity. For example, the total capital cost per unit energy reduces from 245 $/kWhe at 10 h to 38 $/kWhe at 100 h. These costs are considerably lower than MS-PTES (72 $/kWhe at 100 h) and also outcompete current and future Li-ion battery system projections (100-265 $/kWhe).

25 ENERGY STORAGE↗
DOE OSTI2024

Design and evaluation of a dilute flow particle-to-air heat exchanger for energy storage applications

The use of inert and redox-active particles for high-temperature energy storage requires the development of components that can efficiently transfer energy to high-pressure working fluids like supercritical carbon dioxide (sCO 2 ). Dilute flow reactors can enable high working fluid outlet temperatures and minimal parasitic losses compared to moving packed bed and fluidized bed reactors. This research uses both computational and experimental methods to explore the design trade-offs and practical challenges of a novel component for transferring energy from dilute flows of hot, reduced metal oxide (MO x ) particles to sCO 2 in tubes. A discretized thermal resistance network model, which accounts for particle hydrodynamics, multi-mode heat transfer, and reaction equilibrium, guides the design of a prototype device. This device is experimentally tested with a surrogate heat transfer fluids and inert particle temperatures up to 400°C and a heat duty exceeding 1 kW. The data are used to validate the thermal hydraulic sub-models, allowing for the simulation of reacting particle scenarios. Under nominal design conditions, the flow rate of reactive particles is predicted to be 30% lower than that of inert particles for the same energy recovered, with over 70% of the stored particle energy transferred to the sCO 2 . Furthermore, these findings can inform the design of more efficient energy recovery reactors for particle-based systems and can be integrated into system-level concentrated solar power models with thermal storage to optimize operating conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗
DOE OSTI2015

Few layer graphene synthesis on transition metal ferrite catalysts

Development of cheap, green and up scalable production methods for graphene is one of the most challenging problems in its manufacture on an industrial scale. We report here a large scale substrate-free fluidized bed catalytic chemical vapour deposition (FB-CCVD) process for few layer graphene (FLG) powder production that uses a crystalline oxide catalyst of the general formula A(x)B(3-x)O(4), wherein the FLG layer thickness and domain sizes can be varied. A and B can be chosen from a list of transition elements including Co, Fe, Ni, Mn, Cu and Zn. The best results in terms of activity and selectivity are obtained for the CoxFe3-xO4 system. We also investigated the reaction mechanism using in situ EXAFS and Raman spectroscopy, and electron tomography. Since FB-CCVD processes are already used for industrial scale production of carbon nanotubes, this process should enable the large scale production of free standing FLG in the near future.

Bacsa, Revathi R.↗
DOE OSTI2018

Restoring ZSM-5 performance for catalytic fast pyrolysis of biomass: Effect of regeneration temperature

Zeolite catalysts used for biomass catalytic fast pyrolysis (CFP) deactivate rapidly, similar to a fluidized catalytic cracking (FCC) catalyst used in refining. To operate effectively when there is rapid deactivation, biomass CFP can take place in a riser FCC-style reactor in which the catalyst has a short contact time (seconds) with reactants before it is regenerated. The regeneration, therefore, has two major needs for effective operation: 1) heat balance, since the heat required for the CFP reactions is brought into the reactor by the hot catalyst and 2) relatively short (minutes) regeneration to restore the catalyst activity to be near its initial state. In order to understand effective conditions to regenerate zeolites used for CFP, a series of experiments were performed to determine the effect of regeneration temperature on the activity of ZSM-5 (SiO 2 /Al 2 O 3 = 30). After use for pine pyrolysis vapor upgrading, the catalyst was oxidized in 4% O 2 at temperatures between 500-700 °C and reevaluated for the upgrading of pine pyrolysis vapors to assess the extent of regeneration. Additional testing was performed using ethylene aromatization as a surrogate reaction to probe regeneration efficiency. Regeneration experiments were performed for either a fixed length of time (20 min) or until there was no further CO 2 measured in the effluent gas. Results from the ethylene aromatization reactions were shown to serve as an excellent surrogate for CFP reactivity and indicated that the use of model compound studies can effectively be used to understand reaction and regeneration processes from biomass CFP. Both sets of results indicate that a spent ZSM-5 used for biomass CFP could be fully regenerated at 650 degrees C and 700 °C within 20 min, whereas regeneration temperatures of 550 °C and 600 °C required longer regeneration temperatures and in the case of regeneration at 500 °C, there may be coke species that are not removed and the catalyst activity may never be fully restored. Characterization by pyridine diffuse reflectance infrared spectroscopy, thermogravimetric analysis coupled with infrared spectroscopy, and N 2 physisorption showed that higher regeneration temperatures are more effective for restoring Bronsted acid sites and catalyst mesoporosity by rapidly removing aromatic coke deposits. In conclusion, regeneration at 650 °C and 700 °C led to a slightly higher total porosity as compared to the pristine catalyst, which was attributed to the formation of additional mesoporosity from catalyst steaming.

09 BIOMASS FUELS↗
DOE OSTI2020

Validation and application of a multiphase CFD model for hydrodynamics, temperature field and RTD simulation in a pilot-scale biomass pyrolysis vapor phase upgrading reactor

Accurate prediction of transport phenomena is critical for VPU reactor design, optimization, and scale-up. The current study focused on the validation and application of a multiphase CFD model within an open-source code MFiX for hydrodynamics, temperature field, and residence time distribution (RTD) simulation in a non-reacting circulating fluidized bed riser for biomass pyrolysis vapor phase upgrading (VPU). First, an Eulerian-Eulerian approach three-dimensional CFD model was employed to simulate the pilot-scale VPU riser on the supercomputer Joule. Excellent quantitative agreement between experimental and simulated results was achieved for pressure drops and temperature field in a range of operating conditions. Then the validated multiphase CFD model was applied to predict gas and solid residence time distributions (RTDs) since prediction and analysis of RTD is an important tool to study the complex multiphase flow behavior and mixing inside chemical reactors. The predictions show that solid mean residence time is 3.5 times the gas residence time; the solid RTD is more sensitive to the process gas flow rate than the solids circulation rate.

09 BIOMASS FUELS↗
DOE OSTI2021

Critical analysis of velocimetry methods for particulate flows from synthetic data

Particle tracking methods that extract high-fidelity particle velocity data from high speed video of particle laden flows is a common experimental technique applied to chemical processes. These measurements are used to better understand the motion of particles and fluids in complex systems and create data against which computational models are validated. However, the methods, codes, and experimental setups all have limitations. It is imperative that practitioners verify the methods and their implementation as well as understand the limitations of experimental setups. This work focuses on quantifying the visible depth of field in a high particle concentration fluidized bed. Following a precedent set by the particle imaging velocimetry community, a particle velocity field is manufactured using a computational fluid dynamics and discrete element method simulation. Photo realistic high-speed videos are rendered based on the simulated data using the three-dimensional creation software Blender. Particle velocities are extracted from the synthetic high-speed videos using three variants of Particle Tracking Velocimetry and Optical Flow Velocimetry methodologies. Here, the tracked results are then compared to the known solution, quantifying the error associated with the assumed visible depth. The results indicate that at depth of one particle diameter, all three particle tracking codes give accurate measurements, largely within 5%. However, the error increases when the full bed video measurements are compared to the known solution at one particle diameter, i.e., mimicking a validation study. Finally, for some statistics the constant depth assumption only increases the error slightly, for others significantly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Assessment of a Detailed Biomass Pyrolysis Kinetic Scheme in Multiscale Simulations of a Single-Particle Pyrolyzer and a Pilot-Scale Entrained Flow Pyrolyzer

A detailed biomass pyrolysis kinetic scheme was assessed in the multiscale simulations of a single-particle pyrolyzer with slow pyrolysis and a pilot-scale entrained flow pyrolyzer with fast pyrolysis. The detailed kinetic scheme of biomass pyrolysis developed by the CRECK group consists of 32 reactions and 58 species. A multiscale simulation model was developed, where the CRECK kinetics was employed to simulate biomass pyrolysis reactions, a one-dimensional particle model was utilized to simulate the intraparticle transport phenomena, and the particle-in-cell (PIC) model was employed to simulate the hydrodynamics. The multiscale model was first applied to simulate a single-particle pyrolysis experiment. The simulation with nonisothermal particles matched the experimental data better than the simulation with isothermal particles. Then the multiscale model was applied to simulate the pilot-scale entrained flow pyrolyzer. In this case, the simulation with isothermal particles matched the experimental data better than the simulation with nonisothermal particles. The reason for this difference might be that the kinetics itself already partially included the intraparticle transport effect as it was fitted using both TGA data (slow pyrolysis of small size biomass) and fluidized bed data (fast pyrolysis of relatively large size biomass). This study provides some insights into biomass pyrolysis kinetics development and pyrolyzer multiscale simulation for a future study.

09 BIOMASS FUELS↗
DOE OSTI2017

A framework for modeling and optimizing dynamic systems under uncertainty

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming. We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Comparison of Surface Tension Generation Methods in Smoothed Particle Hydrodynamics for Dynamic Systems

Developing robust numerical models of dynamic surface tension dominated multiphase systems is an ongoing challenge, especially in scenarios with large density and viscosity ratios. This is critical to the design and understanding of various physical and engineering systems, such as fluidized beds, fuel injectors, and drug delivery schemes. Much of the computational work in surface tension dominated multiphase flows has employed the continuum surface force method (CSF) of Brackbill et al. [1], which recasts surface tension from a surface force to a volumetric force that can be imposed in the vicinity of an interface. The CSF method produces accurate results across a variety of systems, however it relies on the identication of surface normals, which can be unreliable under certain conditions. Alternative methods of simulating surface tension have been proposed. Here the advantages and disadvantages of the CSF method in comparison to a pairwise forces (PF) method proposed by Tartakovsky and Panchenko [2] are explored. The CSF and PF methods are used in a smoothed particle hydrodynamics (SPH) framework to model dynamic systems. Results are compared to existing test cases from the literature and to analytic solutions derived from fundamental normal mode behavior of bubbles and droplets. A physical system for which the PF method is more stable and physically appropriate than the CSF method is identied.

smoothed particle hydrodynamics, multiphase flow↗