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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Machine Learning-Enhanced Multiphase CFD for Carbon Capture Modeling Run Data

Repository for the data generated as part of the 2023-2024 ALCC project "Machine Learning-Enhanced Multiphase CFD for Carbon Capture Modeling." The data was generated with MFIX-Exa's CFD-DEM model. The problem of interest is gravity driven, particle-laden, gas-solid flow in a triply-periodic domain of length 2048 particle diameters with an aspect ratio of 4. The mean particle concentration ranges from 1% to 40% and the Archimedes number ranges from 18 to 90. The particle-to-fluid density ratio, particle-particle restitution and friction coefficients and domain aspect ratio are held constant at values of 1000, 0.9, 0.25 and 4, respectively. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award ALCC-ERCAP0025948.

AMReX↗
DOE OSTI2022

Fast estimation of reaction rates in spherical and non-spherical porous catalysts

Here we present a methodology for modeling multi-step reaction rates in porous catalyst particles for use in CFD-DEM and two fluid models. Single-step effectiveness factors based on a Thiele modulus, while useful, cannot accurately capture the cascading reaction systems common in high temperature vapor-phase chemical reactors like fluidized catalytic cracking units and catalytic biomass fast pyrolysis systems. Instead, multi-step effectiveness vectors derived from steady-state solutions to the governing reaction-diffusion equations are needed. Solutions for various catalyst shapes are presented, including spheres, cylinders, and prisms. Computational challenges inherent in repeated evaluation of reaction rates with diffusion limitations are discussed, and an efficient implementation based on pre-computed lookup tables is proposed and demonstrated on a simulation of a fluidized bed reactor. Open-source code is provided for the compilation of reaction rate tables for use in ODE, DEM, and two-fluid models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Numerical Investigation of the Ability of Salt Tracers to Represent the Residence Time Distribution of Fluidized Catalytic Cracking Particles

For a long time, salt tracers have been used to measure the residence time distribution (RTD) of fluidized catalytic cracking (FCC) particles. However, due to limitations in experimental measurements and simulation methods, the ability of salt tracers to faithfully represent RTDs has never been directly investigated. Our current simulation results using coarse-grained computational fluid dynamic coupled with discrete element method (CFD-DEM) with filtered drag models show that the residence time of salt tracers with the same terminal velocity as FCC particles is slightly larger than that of FCC particles. This research also demonstrates the ability of filtered drag models to predict the correct RTD curve for FCC particles while the homogeneous drag model may only be used in the dilute riser flow of Geldart type B particles. The RTD of large-scale reactors can then be efficiently investigated with our proposed numerical method as well as by using the old-fashioned salt tracer technology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Numerical Simulation and Experimental Study of the Gas–Solid Flow Behavior Inside a Full-Loop Circulating Fluidized Bed: Evaluation of Different Drag Models

Both experimental and computational studies of the fluidization of high-density polyethylene (HDPE) particles in a small-scale full-loop circulating fluidized bed (CFB) are conducted. Experimental measurements of pressure drop are taken at various locations along the bed. The solids circulation rate is measured with an advanced particle image velocimetry (PIV) technique. Bed height of the quasi-static region in the standpipe is also measured. Comparative numerical simulations are performed with a computational fluid dynamics solver utilizing a discrete element method (CFD-DEM). Here, this paper examines the effect of different drag laws used in the CFD simulations through a detailed and direct comparison with experimental data from a small-scale, full-loop circulating fluidized bed. The Hill–Koch–Ladd drag correlation was shown to have good agreement with respect to system component pressure drop and inventory height in the standpipe.

42 ENGINEERING↗
DOE OSTI2022

Assessment of Lost Circulation Material Particle-Size Distribution on Fracture Sealing: A Numerical Study

Summary Lost circulation materials (LCMs) are essential to combat fluid loss while drilling and may put the whole operation at risk if a proper LCM design is not used. The focus of this research is understanding the function of LCMs in sealing fractures to reduce fluid loss. One important consideration in the success of fracture sealing is the particle-size distribution (PSD) of LCMs. Various studies have suggested different guidelines for obtaining the best size distribution of LCMs for effective fracture sealing based on limited laboratory experiments or field observations. Hence, there is a need for sophisticated numerical methods to improve the LCM design by providing some predictive capabilities. In this study, computational fluid dynamics (CFD) and discrete element methods (DEM) numerical simulations are coupled to investigate the influence of PSD of granular LCMs on fracture sealing. Dimensionless variables were introduced to compare cases with different PSDs. We validated the CFD-DEM model in reproducing specific laboratory observations of fracture-sealing experiments within the model boundary parameters. Our simulations suggested that a bimodally distributed blend would be the most effective design in comparison to other PSDs tested here.

Engineering↗
DOE OSTI2021

MFIX DEM Enhancement for Industry-Relevant Flows (Final Report)

The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Modeling Dense Particle Flow in Multistage and Obstructed Flow Receivers Using High Fidelity Simulations

Particles are a leading contender for next-generation, concentrating solar power technologies, and the design of the particle receiver is critical to minimize the levelized cost of electricity. Falling particle receivers (FPRs) are a viable receiver concept, but many new designs feature complex particle obstructions that include dense discrete phase flows. This creates additional challenges for modeling as particle-to-particle interactions (i.e., collisions) and particle drag become more complex. To improve upon existing modeling strategies, a CFD-DEM simulation capability was created by coupling two independent codes: Sierra/Fuego and LAMMPS. A suitable receiver model was then defined using a traditional continuum-based model for the air and a granular model for the particle curtain. A sensitivity study was executed using this model to determine the relevance of different granular model inputs on important quantities of interest in obstructed flow FPRs: the particle velocity and curtain opacity. The study showed that the granular model inputs had little effect on the particle velocity magnitude and curtain opacity after an obstruction.

Mills, Brantley↗
NASA NTRSDate not supplied

Agent-based modeling of microbes in space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal microgravity; however, much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER results agree with experimental data indicating that indirect effects of radiation (reactive oxygen species generation, metabolic impairment) have a greater impact on microorganisms than direct effects (DNA damage).

Jessica A Lee↗
NASA NTRS2022

Agent-Based Modeling of Microbes in Space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal gravity, and much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER growth curves recapitulate experimental results, and allow comparison between direct effects (DNA damage) and indirect effects (reactive oxygen species generation, metabolic impairment) of radiation.

microbiology↗
NASA NTRSDate not supplied

Microbial Communities in Microgravity: Simulation in Lab and on the Computer

Microorganisms grow differently in spaceflight than they do on Earth. While much remains unexplained about how microgravity affects microbial growth, one dominant hypothesis is that the lack of density-driven convection in the liquid growth environment makes mixing diffusion-limited, and therefore slower. This is supported by evidence that individual microbial strains experience starvation and acid stress in microgravity. However, if it is true, then microgravity would also have measurable effects on microbes in mixed communities, because many interspecies interactions involve the exchange of soluble metabolites through the medium (cross-feeding). Specifically, cooperative cross-feeding communities would grow more slowly in microgravity, and cooperation would be less stable on evolutionary timescales. Here we describe our efforts to test this hypothesis by simulating microgravity in silico and in the lab, using a model system of Eschericia coli and Salmonella enterica that grow only when they can exchange methionine and acetate. We created CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) as an extension of CFDEM®coupling software, to carry out computational modeling of biological flows, growth, and mass transfer in microgravity and also in laboratory artificial microgravity devices (rotating wall vessels, RWV). Using CAMDLES, we found distinct differences in growth rates between RWV and true microgravity, and we were able to identify several features, such as spatial distribution, biofilm formation, and product yield parameters, that influence the degree to which RWV growth recapitulates microgravity growth. In addition, we report on the development of a laboratory system for monitoring growth rates and species ratios of the community in RWVs, using fluorescent strains. Pairing CAMDLES with the laboratory model system allows us to generate quantitative predictions about the effects of spaceflight on organisms that will be essential to sustaining human space exploration in the long term.

microbiology↗
DOE OSTI2022

MFIX-Exa: Performance prediction of multiphase energy conversion devices

MFIX-Exa targets the high-fidelity CFD-DEM model in which particles are unresolved by the fluid grid (typically using a fluid mesh approximately twice the particle diameter) but discrete particle dynamics including collisions are resolved with a simple linear-spring dashpot model. The fluid field is solved with a modern low Mach number formation of a cell-centered, nodal-pressure approximate projection method using a Godunov scheme . Physics capabilities include: complex geometries via embedded boundaries (EBs), open and closed system ideal gas equations of state, species transport and heterogeneous chemi- cal reactions. MFIX-Exa is built on the AMReX software framework, the ECP Block-Structured Adaptive Mesh Refinement (AMR) Co-Design Center, which allows the code to be portable and performant.Further integration into the ECP ecosystem includes HYPRE linear solvers and Ascent for in situ visualization. Current project efforts focus on scaling up realistic simulations to the KPP of the challenge problem: NETs 50kW chemical looping reactor, shakedown and scaling on JSLE and OLCF TDS systems and reaching for any remaining performance improvements.

Musser, Jordan↗
DOE OSTI2021

Coupling particle scale model and SuperDEM–CFD for multiscale simulation of biomass pyrolysis in a packed bed pyrolyzer

An efficient biomass pyrolysis process requires a comprehensive understanding of the chemical and physical phenomena that occur at multi-length and time scales. In this study, a multiscale computational approach was developed and validated for biomass pyrolysis in a packed-bed reactor by integrating pyrolysis kinetics, a particle scale model, and SuperDEM-CFD in open-source code MFiX. A one-dimensional particle-scale model that discretizes the characteristic length of biomass particle into layers was developed to predict the intraparticle phenomena inside a single particle. The 1D model was validated by comparing it with a single biomass particle pyrolysis experiment. Here, a recently developed SuperDEM-CFD model was employed to simulate the non-spherical particle-particle contact and fluid-particle interaction. The coupled model was applied to simulate the pyrolysis of cubic biomass particles in a packed bed and validated by comparing with experimental data. Simulation with and without particle-scale model was compared, and the effect of the gas-solid heat transfer models was also investigated.

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 OSTI2022

Detailed biomass fast pyrolysis kinetics integrated to computational fluid dynamic (CFD) and discrete element modeling framework: Predicting product yields at the bench-scale

Fast pyrolysis is an intricate process due to the variability and anisotropy of lignocellulosic biomass and the complicated chemistry and physics during conversion in a bubbling fluidized bed reactor (BFBR). The complexity of biomass fast pyrolysis lends itself well to computational fluid dynamics (CFD) and discrete element (DEM) analysis, which promises to reduce experimental time and its associated cost. This work investigated switchgrass fast pyrolysis simulated by computational fluid dynamics coupled with a discrete element method to track individual reacting biomass particles throughout a bench-scale BFBR reactor. We accounted for the fast pyrolysis chemistry through a comprehensive reaction scheme with secondary cracking reactions. We performed a three-step reduction for secondary cracking reactions to convert the full cracking scheme into a reduced scheme easily incorporated into our model. We assessed the impact of operational conditions on the steady-state yields of liquid bio-oil, non-condensable gases (NCG), at 550 °C over a range of fluidization numbers (2 – 6 Umf), reported as a ratio to the minimum fluidization velocity (Umf). At steady-state, the volatile bio-oil yield had a range of 49.3–50.4 wt%. Levoglucosan was the primary volatile component present with 21 wt% of the bio-oil while water was the second largest with 20 wt%. The reduction of the secondary reaction schemes did not appreciably affect the overall yields of switchgrass pyrolysis compared to the full secondary scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Memory access optimization for particle operations in computational fluid dynamics-discrete element method simulations

Computational Fluid Dynamics - Discrete Element Method is used to model gas-solid systems in several applications in energy, pharmaceutical and petrochemical industries. Computational performance bottlenecks often limit the problem sizes that can be simulated at industrial scale. The data structures used to store several millions of particles in such large-scale simulations have a large memory footprint that does not fit into the processor cache hierarchies on current high-performance-computing platforms, leading to reduced computational performance. This paper specifically addresses this aspect of memory access bottlenecks in industrial scale simulations. The use of space-filling curves to improve memory access patterns is described and their impact on computational performance is quantified in both shared and distributed memory parallelization paradigms. The Morton space filling curve applied to uniform grids and k-dimensional tree partitions are used to reorder the particle data-structure thus improving spatial and temporal locality in memory. The performance impact of these techniques when applied to two benchmark problems, namely the homogeneous-cooling-system and a fluidized-bed, are presented. We report these optimization techniques lead to approximately two-fold performance improvement in particle focused operations such as neighbor-list creation and data-exchange, with ~ 1.5 times overall improvement in a fluidization simulation with 1.27 million particles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Toward reducing uncertainty quantification costs in DEM models of particulate flow: Testing simple, sensitivity-based, forward uncertainty propagation techniques

The performance of two conceptually-simple uncertainty quantification techniques are tested against the rigorous nested-loop sampling technique of Roy and Oberkampf (Comput Methods Appl Mech Eng, 200: 2131–2144, 2011) (herein called full-sampling) using two very small-scale DEM-based models of particulate flow (one gas-solid flow and one granular flow). The first simplified forward uncertainty propagation technique, reduced-sampling, uses a sensitivity analysis to eliminate uncertain inputs that have little impact on the model output prior to nested-loop sampling. The second technique, boundary-sampling, uses a sensitivity analysis to inform the selection of two bounding cases for each key model output. In conclusion, the uncertainties in the model outputs obtained via the reduced- and boundary-sampling methods agree well with those from full-sampling for both the gas-solid and granular flow models while yielding computational savings of 65–75% (reduced sampling) and 94–97% (boundary sampling).

42 ENGINEERING↗
DOE OSTI2024

Asynchronous GPU-based DEM solver embedded in commercial CFD software with polyhedral mesh support

A novel graphical processing unit-based discrete element method solver is introduced to improve stability, performance, and provide seamless integration into commercial or open-source computational fluid dynamics software. A key innovation is eliminating a need for network communication between solvers, which was previously required for cross-platform coupling. This is accomplished by a direct coupling method that employs dynamic-linked libraries. Furthermore, the solver optimizes memory usage by streamlining the particle-cell search algorithm by eliminating the cells' searching grid. This ensures the solver is compatible with a wide range of mesh types, providing high geometric flexibility. The approach simplifies the simulation process by directly incorporating computational fluid dynamics mesh information into the discrete element method solver. The performance analysis indicates about sixteen times boost in computational speed compared to benchmark central processing unit-based solvers. Finally, the solver's compatibility with polyhedral meshes, a vital advantage for complex geometries, is tested against a referenced study regarding the simulation of an immersed-tube fluidized bed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗