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At least 541 records · Page 30

Coupling DAEM and CFD for simulating biomass fast pyrolysis in fluidized beds

We report results from computational simulations of an experimental, lab-scale bubbling bed biomass pyrolysis reactor that include a distributed activation energy model (DAEM) for the kinetics. In this study, we utilized multiphase computational fluid dynamics (CFD) to account for the turbulent hydrodynamics, and this was combined with the DAEM kinetics in a multi-component, multi-step reaction network. Our results indicate that it is possible to numerically integrate the coupled CFD–DAEM system without significantly increasing computational overhead. It is also clear, however, that reactor operating conditions, reaction kinetics, and multiphase flow dynamics all have major impacts on the pyrolysis products exiting the reactor. We find that, with the same pre-exponential factors and mean activation energies, inclusion of distributed activation energies in the kinetics can shift the predicted average value of the exit vapor-phase tar flux and its statistical distribution, compared to single-valued activation-energy kinetics. Perhaps the most interesting observed trend is that increasing the diversity of the DAEM activation energies appears to increase the mean tar yield, all else being equal. As a result, these findings imply that accurate resolution of the reaction activation energy distributions will be important for optimizing biomass pyrolysis processes.

09 BIOMASS FUELS↗

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗

An experimental system and procedure of unsteady-state relative permeability test for gas hydrate-bearing sediments

Reliable estimations of the relative permeability of gas and water in hydrate-bearing sediments (HBS) and the dependency of the relative permeability on hydrate saturation are critical to predict the productivity of a hydrate reservoir. Yet, this remains poorly estimated owing to lack of experimental data associated with difficulties in conducting multiphase flow experiments in HBS. Recognizing the experimental challenges, this study intends to develop and validate a new experimental system and procedure of unsteady-state relative permeability test that can generate reliable and reproducible flow measurements in HBS. Furthermore, gas hydrate is considered as a part of solid matrix in the sediment, so one of the challenges is to maintain a constant hydrate saturation, which is achieved in this experimental study using tight pressure-temperature (P-T) control near the hydrate stability boundary. The measured differential pressure across the specimen, methane injection flow rate, and volume of displaced brine are used to calculate the relative permeability by adopting a conventional Buckley-Leverett theory-based interpretation method. Residual brine saturation calculated for the hydrate-bearing specimen is higher than that of hydrate-free specimen, presumably due to decrease in pore size, increase in heterogeneity of solid matrix, and increase in size distribution of solid matrix and pore in the presence of hydrates. Further studies are necessary to represent the results of the unsteady-state flow experiment in HBS with a gas hydrate-dependent relative permeability model.

03 NATURAL GAS↗

Anode-Design Strategies for Improved Performance of Polymer-Electrolyte Fuel Cells with Ultra-Thin Electrodes

Here, we report results of systematic, holistic, diagnostic, and cell studies to elucidate the mechanistic role of the experimentally determined influence of the anode gas-diffusion layer (GDL) on the performance of ultra-thin electrode polymer-electrolyte fuel cells, which can further enable fuel-cell market penetration. Measurements of product water balance and in situ neutron imaging of operational membrane-electrode-assembly water profiles demonstrate how improved performance is due to a novel anode GDL fiber-density modulated structure at the micrometer scale that removes water preferentially out of the anode, a key strategy to manage water in these cells. The banded structure results in low transport-resistance pathways, which affect water-droplet removal from the GDL surface. This interfacial effect is unexpectedly shown to be critical for decreasing overall water holdup throughout the cell. Finally, these studies demonstrate a new material paradigm for understanding and controlling fuel-cell water management and related high-power technologies or electrodes where multiphase flow occurs.

25 ENERGY STORAGE↗

CFD-DEM modeling the effect of column size and bed height on minimum fluidization velocity in micro fluidized beds with Geldart B particles

The fluidization behavior of Geldart B particles in micro fluidized beds is investigated numerically using Computational Fluid Dynamics coupled with Discrete Element Method (CFD-DEM) available in the open-source Multiphase Flow with Interphase eXchanges (MFIX) code. The effects of different bed inner diameters (D) of 8 mm, 12 mm, 16 mm and various initial static bed heights (H) were examined. It is found that both decreasing the column diameter and increasing the bed height in a micro fluidized bed increases the minimum fluidization velocity (Umf). The observed overshoot in pressure drop that occurs before the onset of fluidization decreases in magnitude with increasing column diameter, however there is less sensitivity to bed height. Overall, the numerical results agree qualitatively with existing theoretical correlations and experimental studies. The simulations show that both column diameter and particle-wall friction contribute to the variation in minimum fluidization velocity. Finally, these two factors are coupled and hard to separate. The detailed influences of wall friction on minimum fluidization velocity are then investigated for a prescribed column diameter of 8 mm by varying the wall friction from 0 to 0.4.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Particles climbing along a vertically vibrating tube: numerical simulation using the Discrete Element Method (DEM)

It has been reported experimentally that granular particles can climb along a vertically vibrating tube partially inserted inside a granular silo. Here, we use the Discrete Element Method (DEM) available in the Multiphase Flow with Interphase eXchanges (MFIX) code to investigate this phenomenon. By tracking the movement of individual particles, the climbing mechanism was illustrated and analyzed. The numerical results show that a sufficiently high vibration strength is needed to form a low solids volume fraction region inside the lower end of the vibrating tube, a dense region in the middle of the tube, and to bring the particles outside from the top layers down to fill in the void. The results also show that particle compaction in the middle section of the tube is the main cause of the climbing. Consequently, varying parameters which influence the compacted region, such as the restitution coefficient, change the climbing height.

42 ENGINEERING↗

SiOC coatings on yttria stabilized zirconia microspheres using a fluidized bed coating process

In this study, defect-free SiOC coatings were prepared on yttria stabilized zirconia (YSZ) microspheres by a fluidized bed coating process. Effects of the rheological properties of the coating solution on the coating process were elucidated. An impact regime diagram was constructed, which demonstrated that the coating mechanisms were collision/impact. During the fluidized bed coating, longer spouted time resulted in wider dispersion, longer residence time, and more circulatory motion of particles; the fluid distributed more uniformly throughout the column, as demonstrated in our Multiphase Flow with Interface eXchange (MFiX) simulations. Two-step pyrolysis in Ar achieved complete coating layers, which were comprised of SiOC, SiO 2 , SiC, and graphite. The two stage mass loss during the pyrolysis corresponded to simultaneous reactions due to depolymerization and hydrocarbon loss from 400 to 600°C. Carbon cluster size in the pyrolyzed samples was calculated to be 25 ± 2 Å. In conclusion, this work provides a new method for producing SiOC coatings on micron spheres, with nuclear TRISO fuel particles as the application.

42 ENGINEERING↗

Clustering of inertial particles in turbulent flow through a porous unit cell

We report direct numerical simulation is used to investigate effects of turbulent flow in the confined geometry of a face-centred cubic porous unit cell on the transport, clustering and deposition of fine particles at different Stokes numbers (St = 0.01, 0.1, 0.5, 1, 2) and at a pore Reynolds number of 500. Particles are advanced using one-way coupling and the collision of particles with pore walls is modelled as perfectly elastic with specular reflection. Tools for studying inertial particle dynamics and clustering developed for homogeneous flows are adapted to take into account the embedded, curved geometry of the pore walls. The pattern and dynamics of clustering are investigated using the volume change of Voronoi tesselation in time to analyse the divergence and convergence of the particles. Similar to the case of homogeneous, isotropic turbulence, the cluster formation is present at large volumes, while cluster destruction is prominent at small volumes and these effects are amplified with the Stokes number. However, unlike homogeneous, isotropic turbulence, the formation of a large number of very small volumes was observed at all Stokes numbers and attributed to the collision of particles with the pore wall. Multiscale wavelet analysis of the particle number density indicates that the peak of the energy density spectrum, representative of enhanced particle clustering, shifts towards larger scales with an increase in the Stokes number. Scale-dependent skewness and flatness quantify the intermittent void and cluster distribution, with cluster formation observed at small scales for all Stokes numbers, and void regions at large scales for large Stokes numbers.

42 ENGINEERING↗

Reactive Transport Modeling of Hydrogen Production from Serpentinization of Olivine

Hydrogen production from serpentinization of ultramafic rocks represents a promising natural pathway for generating carbon-free energy, yet its kinetics and controlling factors remain incompletely understood. A key challenge in advancing serpentinization research lies in the heterogeneity of porosity and permeability in rocks, which leads to nonuniform fluid velocity fields, as well as uncertainties in estimating reactive surface area and identifying appropriate mineral reaction equilibria. Additional complexities arise from the role of dissolved SiO 2 , Fe 2+ /Fe 3+ partitioning, and the limited effect of pH variations within the strongly alkaline regime on hydrogen yields. These challenges hinder straightforward extrapolation from laboratory tests to practical applications of hydrogen production from natural rocks. Here, in this work, we address these questions using a simulation-based reactive transport modeling framework calibrated against controlled laboratory experiments reported elsewhere. The model couples geochemical kinetics, multiphase flow, and mineralogical feedbacks, enabling systematic evaluation of how surface area, dissolved silica concentration, Fe redox state, temperature, and pressure govern serpentinization and H2 generation. We find that surface area exerts the strongest control on reaction rates and hydrogen yields, while Fe 2+ /Fe 3+ ratios act as secondary modulators. Elevated dissolved silica concentrations suppress hydrogen production but accelerate serpentine precipitation, whereas increasing pH beyond 12 within the strongly alkaline regime produces only marginal gains. Finally, we demonstrate that integrating targeted experiments with calibrated simulations offers a powerful and efficient approach for predicting hydrogen yields and assessing parameter trade-offs in industrial-scale applications. This integration can substantially reduce the experimental burden while improving predictive capability, thereby enhancing both the mechanistic understanding and the practical feasibility of hydrogen production from serpentinization.

08 HYDROGEN↗

Methane Hydrate Formation and Evolution During Sedimentation

We explored methane hydrate formation with sedimentation with a newly developed one-dimensional, multiphase flow, multicomponent transport numerical model. Our model couples methane hydrate formation from in situ microbial methane generation within the hydrate stability zone (HSZ), methane recycling, and microbial methane generation below the base of the hydrate stability zone (BHSZ). Both recycled methane and deeply generated methane are transported into the HSZ by buoyancy-driven free gas flow. Free gas flows through the HSZ by both the processes of capillary-dependent pore fillings and by salt exclusion during hydrate formation, with the former being the dominant mechanism. We quantitively illustrated the formation of enriched hydrate in muddy sediments above, and interconnected free gas below, the BHSZ, which are common features along the world's continental margin. In addition, we showed two ways to form concentrated methane hydrate above the BHSZ. The first mechanism is local free gas flow during methane recycling. This happens at sites with sufficient methane generation above the BHSZ. The second mechanism is deep microbial methane generation which is transported into the HSZ by free gas flow. This mechanism plays a more important role at sites with high sedimentation rates. This study provides new insights into methane hydrate formation and distribution below the seafloor. It is important for understanding the carbon cycle and carbon storage below the seafloor and for resource evaluation and exploitation.

58 GEOSCIENCES↗

Quantifying the Effect of Pore‐Size Dependent Wettability on Relative Permeability Using Capillary Bundle Model

Abstract Relative permeability is a key parameter for characterizing the multiphase flow dynamics in porous media at macroscopic scale while it can be significantly impacted by wettability. Recently, it has been reported in microfluidic experiments that wettability is dependent on the pore size (Van Rooijen et al., 2022). To investigate the effect of pore‐size‐dependent wettability on relative permeability, we propose a theoretical framework informed by digital core samples to quantify the deviation of relative permeability curves due to wettability change. We find that the significance of impact is highly dependent on two factors: (i) the function between contact angle and pore size (ii) overall pore size distribution. Under linear function, this impact can be significant for tight porous media with a maximum deviation of 1,000%.

Yu, Siqin↗

Pore geometry control of apparent wetting in porous media

Abstract Wettability, or preferential affinity of a fluid to a solid substrate in the presence of another fluid, plays a critical role in the statics and dynamics of fluid-fluid displacement in porous media. The complex confined geometry of porous media, however, makes upscaling of microscopic wettability to the macroscale a nontrivial task. Here, we elucidate the contribution of pore geometry in controlling the apparent wettability characteristics of a porous medium. Using direct numerical simulations of fluid-fluid displacement, we study the reversal of interface curvature in a single converging-diverging capillary, and demonstrate the co-existence of concave and convex interfaces in a porous medium—a phenomenon that we also observe in laboratory micromodel experiments. We show that under intermediate contact angles the sign of interface curvature is strongly influenced by the pore geometry. We capture the interplay between surface chemical properties and pore geometry in the form of a dimensionless quantity, the apparent wettability number, which predicts the conditions under which concave and convex interfaces co-exist. Our findings advance the fundamental understanding of wettability in confined geometries, with implications to macroscopic multiphase-flow processes in porous media, from fuel cells to enhanced oil recovery.

42 ENGINEERING↗

Are continuum predictions of clustering chaotic?

Gas-solid multiphase flows are prone to develop an instability known as clustering. Two-fluid models, which treat the particulate phase as a continuum, are known to reproduce the qualitative features of this instability, producing highly-dynamic, spatiotemporal patterns. However, it is unknown whether such simulations are truly aperiodic or a type of complex periodic behavior. By showing that the system possesses a sensitive dependence on initial conditions and a positive largest Lyapunov exponent, λ 1 ≈1/τ, we provide a tentative answer: continuum predictions of clustering are chaotic. We further demonstrate that the chaotic behavior is dimensionally dependent, a conclusion which unifies previous results and strongly suggests that the chaotic behavior is not a direct consequence of the fundamental kinematic instability, but requires a secondary (inherently multidimensional) instability. Granular matter is a collection of discrete, interacting solid particles which, like classic (molecular) matter, can be generally classified into one of three states:1 (i) under static conditions granular heaps or piles can sustain gravity-induced stress and behave like a solid; (ii) dense granular flows characterized by enduring and multi-particle contacts behave similarly to a fluid; and (iii) rapid granular flows characterized by instantaneous contacts described as a granular gas. However, it is worth noting that all three granular states are only superficially similar to their molecular counterparts due to the dissipative nature of particle-particle contacts (inelasticity, friction, etc.). In industrial operations, rapid (collision-dominated) granular flows are often encountered in devices in which the particles are fluidized by a gas; such gas-solid flows are the focus of this work. Rapid gas-solid flows are prone to an instability termed clustering in which particles tend to form spatially inhomogeneous patterns of high and low concentrations. Continuum or two-fluid models (TFM) have long been known to be able to predict the qualitative nature of the clustering instability and more recent quantitative assessments have also shown promising results. However, it is yet unknown whether or not such predictions are chaotic. We take a first step in answering this question by simulating fluidization in an unbounded domain and calculating a positive largest Lyapunov exponent (LLE), thereby indicating that continuum predictions of clustering are in fact chaotic. Further, we show that chaotic behavior may be reduced to periodic behavior by constraining the dimensionality of the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the effect of mixing-driven vaporization in a homogeneous relaxation modeling framework

The homogeneous relaxation model (HRM) is one of the most widely used models to describe the liquid–gas phase transition in multiphase flows due to the occurrence of cavitation. However, in its original formulation, the HRM does not account for the presence of ambient gas species, which generally limits its applicability to the injector's internal flow where ambient gases are negligible. In this work, a mixing-driven vaporization (MDV) model was developed to extend the capability of the HRM in handling the mixing effect in the regions external to the nozzle, where vapor–liquid equilibrium for multi-species mixtures of fuel and ambient gas is considered. Herein, to assess the model performance, simulations of the Engine Combustion Network's Spray G injector were performed with the HRM and the MDV model under both flash-boiling and evaporating conditions. It was found that the MDV model led to a better match against x-ray measurements of fuel density in the near-nozzle region. In contrast to the HRM, the MDV model was able to reproduce the vaporization process in the mixing zone at the edge of the fuel jet, which aligns with the expected physics. This resulted in substantial differences in the prediction of other flow characteristics such as mixture temperature and pressure. Furthermore, this work demonstrates that evaporation timescales have a considerable effect on the MDV model's predictions, as shown by a parametric study in which a time factor was introduced to mimic the effect of different timescales due to different phase change mechanisms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Development of a Validation Approach for an Integrated Waste Glass Melter Model

Integrated models are being developed to represent the physics occurring within the high-level and low-activity waste melters that will be used to vitrify legacy tank waste at the Hanford site. These models couple the melt pool, cold cap, and plenum region within a single computational domain. Validation of the models is essential to ensure the reliability of the numerical predictions of the operational melters. Experimental data from laboratory- and pilot-scale tests are thus being used to inform and validate various aspects of the melter model. This study presents a tiered approach to model validation consisting of a series of progressively more complex test cases designed to model the physics occurring in the full-scale system. A hierarchical methodology has been developed to segregate and simplify the physical phenomena affecting the multiphase flow and heat transfer within a waste glass melter. Finally, four hierarchical levels are defined in a validation pyramid and built up in levels of increasing complexity from unit problems to subsystem cases, to pilot-scale systems, and then to the full-scale system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗