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At least 433 records · Page 24

Mechanistic Insights for Plasma-Catalytic CO 2 Reduction over TiO 2 in a Dielectric Barrier Discharge Reactor

Reaction kinetics experiments coupled with phenomenological kinetic modeling and parameter estimation are used to elicit insights into the mechanism and active sites for the plasma-catalytic dissociation of CO 2 on TiO 2 . Experimental and model insights showed that gas-phase reactions contribute at least two-thirds of the overall product formation at explored conditions; weak temperature dependence, strong sensitivity to specific energy input (SEI), apparent first order in CO 2 , and positive influence of cofed argon (Ar) and oxygen (O 2 ) for the gas-phase contributions all suggest that expected plasma reaction steps such as electron-impact and high-energy collisions are the dominant modes for CO 2 dissociation. The Arrhenius-like expression for gas contributions resulted in a preexponential of 4.40 × 10 –3 s –1 , an E SEI,g of 7.90 × 10 –4 mol/kJ, and an E a,g of 1.00 × 10 –3 J/mol. For surface contributions, the small apparent barrier of 16.3 kJ/mol, relatively weaker dependence on SEI, first-order dependence on CO 2 , and insensitivity to cofed Ar and O 2 all point to CO 2 dissociation on TiO 2 surface facets without vacancies and aided by plasma (leading to vibrationally excited CO 2 and/or a reactive surface with significant surface charge accumulation). The Arrhenius-like expression resulted in a preexponential of 7.81 × 10 –2 s –1 , an E SEI,s of 1.90 × 10 –3 mol/kJ, and an E a,s of 1.63 × 10 4 J/mol. The derived kinetic model further enabled a systematic evaluation of the effect of inputs (plasma power, flow rate, CO 2 inlet concentration, and temperature) to identify process trends and optimal operating conditions.

catalyst↗

An In Situ , Automated High-Explosives Aging Method Utilizing Two-Dimensional Gas Chromatography–Mass Spectrometry

Understanding chemical changes that occur in high explosives as they age is of great importance to the safe employment and storage of these compounds. Traditional methods of aging high explosives even under accelerated aging conditions are time intensive with durations on the order of months to years. The nature of traditional aging analyses reduces each sample to a snapshot data point often separated widely in time, requiring many assumptions as to how the degradation products develop. Further complicating matters, several analytical techniques are typically employed for each sample analysis in order to ascertain an entire picture of the decomposition pathways. To address these shortcomings with existing methods, a new method of accelerated aging of high explosives utilizing comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry (GC × GC-HRMS) was developed using 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20) as a model compound for method development. This in situ automated method reduces the time scale of aging to a matter of hours using the inlet of the GC × GC as the aging vessel. GC × GC in combination with HRMS allowed for the collection of both evolved gases and other decomposition products produced during the entire aging process in real time with HRMS providing far greater certainty in identification of explosives aging products. Additionally, this method allowed for a higher throughput of samples with greatly simplified sample preparation. Chemometric analysis of the GC × GC-HRMS data set via the alteration analysis (ALA) enabled discovery of statistically significant chemical changes providing insight into the variation of decomposition pathways with varying aging temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ambient ion focusing from a field-free region to a detector: enhanced signal for explosives and drug detection with mass spectrometry

This study demonstrates ion focusing at ambient pressure and increased ion signal by creating a voltage gradient from a field-free region to a detector, thereby improving the detection of chemicals, such as explosives and drugs. At ambient pressure, ion loss and resulting signal reduction pose challenges that limit detection sensitivity in analytical instruments. Techniques to increase sensitivity, such as atmospheric flow tube-mass spectrometry (AFT-MS), extend ion-molecule reaction times but result in significant overall ion loss due to diffusion. Ion manipulation techniques, though challenging at ambient pressure, can mitigate these losses by concentrating ions toward the detector inlet. Using SIMION, ion trajectories were modeled with a voltage gradient applied between a flow tube and a detector, revealing ion focusing at ambient pressure. Experimental verification with an atmospheric flow tube employed both mass spectrometry and Faraday plate detectors to measure ion beam profiles across varying flow rates, tube diameters, and voltage gradients. Application of a voltage gradient effectively directed ions to the axial center of the flow tube, narrowed ion beam width, and increased signal intensity by 5 to 10 times compared to conditions without a voltage gradient. This ion focusing approach shows promise for improving sensitivity in ambient-pressure instruments. This technique has the potential to enhance detection levels in security and forensic applications, with particular benefits for field-portable devices used at checkpoints to identify explosives and drugs.

ambient pressure↗

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗

Characterizing the Effect of Capillary Heterogeneity on Multiphase Flow Pulsation in an Intermediate–Scale Beadpack Experiment using Time Series Clustering and Frequency Analysis

An intermediate-scale beadpack drainage experiment was conducted to investigate how simple layered lamination heterogeneity affects CO 2 flow. Two simple layers of capillary barriers are manually packed in the tank and slow drainage was carried out using analog fluids to mimic the capillary- and gravity-dominated CO 2 upward migration process in deep saline aquifers. Nonwetting phase saturation time series clustering analysis and frequency analysis have been conducted on the experimental data. Additionally, modified invasion percolation numerical simulations were done on a digital model of the beadpack to compare to experimental results. Results show that capillary barriers can lead to strong pulsation behavior, which in turn can cause unexpected early breaching through other barriers. The inlet pressure is found to be able to respond to saturation changes in far regions of the domain, indicating that the wetting phase can transmit pressure changes from the other phase. Although static simulations were not able to capture all the dynamic behavior observed in the experiment, Monte Carlo composite simulation results combining many different realizations can better illustrate how the nonwetting phase will behave in the heterogeneous domain. Furthermore, our results suggest the need for CO 2 storage site selection with preference given to aquifers with more capillary barriers with finer grain sizes to avoid flow pulsation and to retard plume upward migration.

58 GEOSCIENCES↗

Emergence of Unstable Focused Flow Induced by Variable‐Density Flows in Vertical Fractures

Abstract Fluids with different densities often coexist in subsurface fractures and lead to variable‐density flows that control subsurface processes such as seawater intrusion, contaminant transport, and geologic carbon sequestration. In nature, fractures have dip angles relative to gravity, and density effects are maximized in vertical fractures. However, most studies on flow and transport through fractures are often limited to horizontal fractures. Here, we study the mixing and transport of variable‐density fluids in vertical fractures by combining three‐dimensional (3D) pore‐scale numerical simulations and visual laboratory experiments. Two miscible fluids with different densities are injected through two inlets at the bottom of a fracture and exit from an outlet at the top of the fracture. Laboratory experiments show the emergence of an unstable focused flow path, which we term a “runlet.” We successfully reproduce the unstable runlet using 3D numerical simulations and elucidate the underlying mechanisms triggering the runlet. Dimensionless number analysis shows that the runlet instability arises due to the Rayleigh‐Taylor instability (RTI), and flow topology analysis is applied to identify 3D vortices that are caused by the RTI. Even under laminar flow regimes, fluid inertia is shown to control the runlet instability by affecting the size and movement of vortices. Finally, we confirm the emergence of a runlet in rough‐walled fractures. Since a runlet dramatically affects fluid distribution, residence time, and mixing, the findings in this study have direct implications for the management of groundwater resources and subsurface applications.

Environmental Sciences & Ecology↗

Pore‐Scale Modeling of Reactive Transport with Coupled Mineral Dissolution and Precipitation

Abstract We present a new pore‐scale model for multicomponent advective‐diffusive transport with coupled mineral dissolution and precipitation. Both dissolution and precipitation are captured simultaneously by introducing a phase transformation vector field representing the direction and magnitude of the overall phase change. An effective viscosity model is adopted in simulating fluid flow during mineral dissolution‐precipitation that can accurately capture the velocity field without introducing any empirical parameters. The proposed approach is validated against analytical solutions and interface tracking simulations in simplified structures. After validation, the proposed approach is employed in modeling realistic rocks where mineral dissolution and precipitation are dominant at different locations. We have identified three regimes for mineral dissolution‐precipitation coupling: (a) compact dissolution‐precipitation where dissolution is dominant near the inlet and precipitation is dominant near the outlet, (b) wormhole dissolution with clustered precipitation where dissolution generates wormholes in the main flow paths and precipitation clogs the secondary flow paths, and (c) dissolution dominant where all solid grains are gradually dissolved. In the three regimes, the proposed approach provides reliable porosity‐permeability relationships that cannot be described well by traditional macroscale models. We find that the permeability can increase while the overall porosity decreases when the main flow paths are expanded by dissolution and adjacent pore spaces are clogged by precipitation.

58 GEOSCIENCES↗

Mercury methylation by metabolically versatile and cosmopolitan marine bacteria

Microbes transform aqueous mercury (Hg) into methylmercury (MeHg), a potent neurotoxin that accumulates in terrestrial and marine food webs, with potential impacts on human health. This process requires the gene pair hgcAB, which encodes for proteins that actuate Hg methylation, and has been well described for anoxic environments. However, recent studies report potential MeHg formation in suboxic seawater, although the microorganisms involved remain poorly understood. In this study, we conducted large-scale multi-omic analyses to search for putative microbial Hg methylators along defined redox gradients in Saanich Inlet, British Columbia, a model natural ecosystem with previously measured Hg and MeHg concentration profiles. Analysis of gene expression profiles along the redoxcline identified several putative Hg methylating microbial groups, including Calditrichaeota, SAR324 and Marinimicrobia, with the last the most active based on hgc transcription levels. Marinimicrobia hgc genes were identified from multiple publicly available marine metagenomes, consistent with a potential key role in marine Hg methylation. Computational homology modelling predicts that Marinimicrobia HgcAB proteins contain the highly conserved amino acid sites and folding structures required for functional Hg methylation. Furthermore, a number of terminal oxidases from aerobic respiratory chains were associated with several putative novel Hg methylators. Our findings thus reveal potential novel marine Hg-methylating microorganisms with a greater oxygen tolerance and broader habitat range than previously recognized.

59 BASIC BIOLOGICAL SCIENCES↗

Time-resolved 3D imaging of two-phase fluid flow inside a steel fuel injector using synchrotron X-ray tomography

The multiphase flow inside a diesel injection nozzle is imaged using synchrotron X-rays from the Advanced Photon Source at Argonne National Laboratory. Through acquisitions performed at several viewing angles and subsequent tomographic reconstruction, in-situ 3D visualization is achieved for the first time inside a steel injector at engine-like operating conditions. The morphology of the internal flow reveals strong flow separation and vapor-filled cavities (cavitation), the degree of which correlates with the nozzle's asymmetric inlet corner profile. Micron-scale surface features, which are artifacts of manufacturing, are shown to influence the morphology of the resulting liquid-gas interface. The data obtained at 0.1 ms time resolution exposes transient flow features and the flow development timescales are shown to be correlated with in-situ imaging of the fuel injector's hydraulically-actuated valve (needle). As more than 98.5% of the X-ray photon flux is attenuated within the steel injector body itself, we are posed with a unique challenge for imaging the flow within. Time-resolved imaging under these low-light conditions is achieved by exploiting both the refractive and absorptive properties of X-ray photons. The data-processing strategy converted these images with a signal-to-noise ratio of similar to 10 into a meaningful dataset for understanding internal flow and cavitation in a nozzle of diameter 200 mu m enclosed within 1-2 millimeters of steel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Microbial community dynamics and cycling of plutonium and iron in a seasonally stratified and radiologically contaminated pond

Plutonium (Pu) cycling and mobility in the environment can be impacted by the iron cycle and microbial community dynamics. We investigated the spatial and temporal changes of the microbiome in an iron (Fe)-rich, plutonium-contaminated, monomictic reservoir (Pond B, Savannah River Site, South Carolina, USA). The microbial community composition varied with depth during seasonal thermal stratification and was strongly correlated with redox. During stratification, Fe(II) oxidizers (e.g., Ferrovum, Rhodoferax, Chlorobium) were most abundant in the hypoxic/anoxic zones, while Fe(III) reducers (e.g., Geothrix, Geobacter) dominated the deep, anoxic zone. Sulfate reducers and methanogens were present in the anoxic layer, likely contributing to iron and plutonium cycling. Multinomial regression of predicted functions/pathways identified metabolisms highly associated with stratification (within the top 5%), including iron reduction, methanogenesis, C1 compound utilization, fermentation, and aromatic compound degradation. Two sediment cores collected at the Inlet and Outlet of the pond were dominated by putative fermenters and organic matter (OM) degraders. Overall, microbiome analyses revealed the potential for three microbial impacts on the plutonium and iron biogeochemical cycles: (1) plutonium bioaccumulation throughout the water column, (2) Pu–Fe-OM-aggregate formation by Fe(II) oxidizers under microaerophilic/aerobic conditions, and (3) Pu–Fe-OM-aggregate or sediment reductive dissolution and organic matter degradation in the deep, anoxic waters.

54 ENVIRONMENTAL SCIENCES↗

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗

Highly selective and productive reduction of carbon dioxide to multicarbon products via in situ CO management using segmented tandem electrodes

Electrochemical CO 2 reduction provides a promising route to the sustainable generation of valuable chemicals and fuels. Tandem catalysts enable sequential CO 2 -to-CO and CO-to-multicarbon (C 2+ ) product conversions on complementary active sites, to produce high C 2+ Faradaic efficiency (FE). Unfortunately, previous tandem catalysts exhibit poor management of CO intermediates, which diminishes C 2+ FE. Here, we design segmented gas-diffusion electrodes (s-GDEs) in which a CO-selective catalyst layer (CL) segment at the inlet prolongs CO residence time in the subsequent C 2+ -selective segment, enhancing conversion. This phenomenon enables increases in both the CO utilization and C 2+ current density for a Cu/Ag s-GDE compared to pure Cu, by increasing the *CO coverage within the Cu CL. Lastly, we develop a Cu/Fe-N-C s-GDE with 90% C 2+ FE at C 2+ partial current density (j C2+ ) exceeding 1 A cm -2 . These results prove the importance of transport and establish design principles to improve C 2+ FE and j C2+ in tandem CO 2 reduction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advanced manufacturing for electrosynthesis of fuels and chemicals from CO 2

Advanced manufacturing (AM) represents an appealing approach for creating novel electrochemical systems for chemicals synthesis. In this work, we demonstrate AM for rapid development and testing for improved performance for the carbon dioxide reduction reaction across an evolution of vapor-fed reactor designs. In our final design, we observe activation- and mixed-control regimes for a variety of operating conditions via inlet CO 2 flow rate and electrochemical potential. Furthermore, we define a dimensionless number (Da) to identify mass transport regimes by exploring the impact of hypothesized underlying mass transport mechanisms, including consumption of CO 2 via OH - , increased local temperatures, and partial penetration of electrolyte into gas diffusion layer. The accelerated pace of reactor design and development led to high geometric current densities (500 mA cm -2 ), heightened selectivity (85.5% FE C 2+ products), and increased carbon dioxide conversion (16.6%) and cathodic energy efficiency (49.6% CO 2 R). Using AM vapor-fed reactors, we attain high ethylene (3.67%) and record ethanol (3.66%) yields compared to the literature. Finally, this work underscores the promise of AM for accelerating reactor design, understanding of governing phenomena, and improving the performance of catalytic systems.

36 MATERIALS SCIENCE↗

Designing optimal core–shell MOFs for direct air capture

Metal–organic frameworks (MOFs), along with other novel adsorbents, are frequently proposed as candidate materials to selectively adsorb CO 2 for carbon capture processes. However, adsorbents designed to strongly bind CO 2 nearly always bind H 2 O strongly (sometimes even more so). Given that water is present in significant quantities in the inlet streams of most carbon capture processes, a method that avoids H 2 O competition for the CO 2 binding sites would be technologically valuable. Here, in this paper, we consider a novel core–shell MOF design strategy, where a high-CO 2 -capacity MOF “core” is protected from competitive H 2 O-binding via a MOF “shell” that has very slow water diffusion. We consider a high-frequency adsorption/desorption cycle that regenerates the adsorbents before water can pass through the shell and enter the core. To identify optimal core–shell MOF pairs, we use a combination of experimental measurements, computational modeling, and multiphysics modeling. Our library of MOFs is created from two starting MOFs-UiO-66 and UiO-67-augmented with 30 possible functional group variations, yielding 1740 possible core–shell MOF pairs. After defining a performance score to rank these pairs, we identified 10 core–shell MOF candidates that significantly outperform any of the MOFs functioning alone.

42 ENGINEERING↗

Direct high-altitude observations of 2-methyltetrols in the gas- and particle phase in air masses from Amazonia

We present direct observations of 2-methyltetrol (C 5 H 12 O 4 ) in the gas- and particle phase from the deployment of a Filter Inlet for Gases and Aerosols coupled to a Time-of-Flight Chemical Ionization Mass Spectrometer (FIGAERO-CIMS) during the Southern Hemisphere High Altitude Experiment on Particle Nucleation and Growth (SALTENA), which took place between December 2017 and June 2018 at the high-altitude Global Atmosphere Watch station Chacaltaya (CHC) located at 5240 m a s l in the Bolivian Andes. 2-Methyltetrol signals were dominant in a factor resulting from Positive Matrix Factorization (PMF) identified as influenced by Amazon emissions. We combine these observations with investigations of isoprene oxidation chemistry and uptake in an isolated deep convective cloud in the Amazon using a photochemical box model with coupled cloud microphysics and show that, likely, 2-methyltetrol is taken up by hydrometeors or formed in situ in the convective cloud, and then transported in the particle phase in the cold environment of the Amazon outflow and to the station, where it partially evaporates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sneezing and asymptomatic virus transmission

The novel coronavirus disease (COVID-19) spread pattern continues to show that geographical barriers alone cannot contain a virus. Asymptomatic carriers play a critical role in the nature of this virus quickly escalating into a global pandemic. Asymptomatic carriers may transmit the virus unintentionally through sporadic sneezing. A novel Computational Fluid Dynamics (CFD) approach has been proposed with a realistic modeling of a human sneeze achieved by the combination of state-of-the-art experimental and numerical methods. This modeling approach may be suitable for future engineering analyses aimed at reshaping public spaces and common areas, with the main objective to accurately predict the spread of aerosol and droplets that may contain pathogens. This study shows that the biomechanics of a human sneeze, including complex muscle contractions and relaxations, can be accurately modeled by the angular head motion and the dynamic pressure response during sneezing. These have been considered as the human factors and were implemented in the CFD simulation by imposing a momentum source term to the coupled Eulerian–Lagrangian momentum equations. The momentum source was modeled by the measured dynamic pressure response in conjunction with the angular head motion. This approach eliminated the need to create an ad hoc set of inlet boundary conditions. With this proposed technique, it is easier to add multiple fixed and/or moving sources of sneezes in complex computational domains. Additionally, extensive sensitivity analyses based on different environmental conditions were performed, and their impact was described in terms of potential virus spread.

42 ENGINEERING↗

Investigation of turbulent inflow specification in Euler–Lagrange simulations of mid-field spray

The process of atomization of a liquid jet by a parallel high-speed gas stream results in a spray, whose downstream development is of considerable interest to several applications. The round jet spray can be spatially divided into (i) a near-field (near-nozzle) region of liquid atomization and (ii) a downstream mid-field region of fully-dispersed droplets. In order to accurately model mid-field droplet dispersion, this work aims at developing a rigorous and robust injection model for Euler–Lagrange spray simulations. Results from experiments are used to obtain the relevant droplet number density, size distribution, and mean and standard deviation velocity distributions of the injection model, systematically in a step-by-step process. Two-phase large eddy simulations are performed by stochastically generating the Lagrangian droplets at the inlet of the mid-field region. Number flux, diameter distribution, mean velocity, and other time-averaged statistics at several downstream locations are shown to agree well with the corresponding experimental data.

42 ENGINEERING↗

Impact of particle loading and phase coupling on gas–solid flow dynamics: A case study of a two-phase, gas–solid flow in an annular pipe

The present study is devoted to a two-phase, gas–solid flow in an annular pipe (hollow cylinder) at an elevated pressure of 15 bars and moderate Reynolds number of circa 6000. The influence of the particle loading, the interaction between the phases, and turbulence dispersion on the flow dynamics is systematically studied by means of computational fluid dynamics simulations, employing the Ansys FLUENT commercial package. The cases with a particle volumetric fraction of 1.2% are referred to as “high particle loading,” and those with 0.13% are denoted as “low particle loading.” The following cases are investigated: (1) pure gas flow; (2) low particle loading two-phase flow with one-way coupling and with turbulence dispersion; (3) low particle loading two-phase flow with two-way coupling but without turbulence dispersion; (4) low particle loading two-phase flow with two-way coupling and with turbulence dispersion; (5) high particle loading two-phase flow with one-way coupling and with turbulence dispersion; (6) high particle loading two-phase flow with two-way coupling but without turbulence dispersion; and (7) high particle loading two-phase flow with two-way coupling and with turbulence dispersion. Additionally, the boundary layer is found to grow without fluctuations of the turbulent kinetic energy (TKE) for cases 1, 2, and 5. For case 4, the TKE fluctuations have been identified, although they appear to be less substantial than those in cases 6 and 7. The authors attribute the semi-chaotic nature of the TKE fluctuations to the particle loading and two-way coupling. In addition, the onset and development of the flow instability have been observed at a random axial distance in cases 4, 6, and 7. Such instability is also attributed to the two-way coupling with turbulence dispersion in the flow. It is concluded that the particle loading, one-way, or two-way coupling between the phases, and the turbulence dispersion models significantly influence the development of the flow dynamics with the same inlet and boundary conditions. Consequently, it is not a trivial question, which result a user should trust. The present computational results inspire to perform verification as well as experimental validation of the simulations, so the simulation results can subsequently be used with confidence for design analysis.

42 ENGINEERING↗