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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A numerical solver for investigating the space charge effect on the electric field in liquid argon time projection chambers

This paper reports the development of a numerical solver aimed to simulate the interaction between the space charge (i.e. ions) distribution and the electric field in liquid argon time projection chamber (LArTPC) detectors. The ion transport equation is solved by a time-accurate, cell-centered finite volume method and the electric potential equation by a continuous finite element method. The electric potential equation updates the electric field which provides the drift velocity to the ion transport equation. The ion transport equation updates the space charge density distribution which appears as the source term in the electric potential equation. The interaction between the space charge distribution and the electric field is numerically simulated within each physical time step. The convective velocity in the ion transport equation can include the background flow velocity in addition to the electric drift velocity. The numerical solver has been parallelized using the Message Passing Interface (MPI) library. Numerical tests show and verify the capability and accuracy of the current numerical solver. It is planned that the developed numerical solver, together with a Computational Fluid Dynamics (CFD) package which provides the flow velocity field, can be used to investigate the space charge effect on the electric field in large-scale particle detectors.

42 ENGINEERING↗
DOE OSTI2023

A New Proposal Generalized Predictive Control Algorithm With Polynomial Reference Tracking Applied for Sodium Fast Reactors

This paper proposes a generalized predictive control (GPC) with constraints and orthonormal Laguerre functions using the simplified model of the primary system (reactor core and intermediate heat exchanger (IHX)) of a prototypical sodium fast reactor (SFR). This paper develops a multiple-input multiple-output (MIMO) GPC with input constraints able to track polynomial references of any degree applied in coolant temperature difference across the core and fractional power. The manipulated variables of the GPC-SFR are the reactivity and the sodium flow rate of the primary and secondary pipes. Moreover, orthonormal Laguerre functions and step down condition number techniques were also applied to avoid the numerical ill-conditioning issue in quadratic programming of large systems. Thus, a GPC type-2 was designed to control fractional power, coolant temperature difference across the core and sodium tank temperature of the SFR primary system when temperature references change according to a linear ramp after reaching their steady-state operation, sustaining 100% power operation on the reactor. In order to analyze the load tracking capability of the GPC-SFR type-2, the load following from 100% fractional power (FP) to 60% FP at 0.8% FP/min rate is simulated. Constraints on the rate of coolant temperature difference across the core and reactivity were applied for the design safety. For comparison criteria, this paper compares the GPC-SFR type-2 with the GPC-SFR type-1, i.e., standard model predictive control (MPC), to verify the viability and superior performance of the proposal regarding: (a) ramp-tracking capability of temperature and load; (b) the rejections of a reactivity disturbance of -1 cent and a secondary sodium inlet temperature disturbance of +10°F; and (c) a simulation with uncertainty in reactor design. The simulations show that the GPC-SFR type-2 overcome the GPC-SFR type-1 robustness and performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Quasi-Steady Simulation of Glaze Ice Accretion and Heat Transfer in the Supercooled Large Droplet Regime in Atmospheric Turbulent Air Flow

Abstract To avoid the use of a computationally intensive full unsteady simulation while providing an accurate solution, a quasi-steady simulation has been performed to study glaze and mixed ice accretion in the supercooled large droplet (SLD) regime in turbulent flow of atmospheric air. We have attempted to find the minimum time-step necessary to adequately simulate the icing process on an airfoil surface. Based on node displacement, a mesh morphing scheme has been adopted in the computations to account for the moving boundaries that are caused by the continuous ice buildup. We have modeled ice accretion on an airfoil surface for a time period of 232 s using several time steps. At each time-step we solved the steady-state conservation equations for the air and droplet phases and then used the results as initial conditions for the next time position. The magnitude of the time-step ranged from a least accurate two-shot simulation (where the time-step is 116 s) to a most accurate 2320-shot simulation (where the time-step is 0.1 s). In-between these two extreme time steps, we have performed a three-shot simulation (where the time-step is 77.33 s), a four-shot simulation (where the time-step is 58 s), a six-shot simulation (where the time-step is 38.67 s), a 46-shot simulation (where the time-step is 5 s), and a 232-shot simulation (where the time-step is 1 s). We have done so to find out the degree of accuracy (or inaccuracy) of the multishot simulation approach and to find out the appropriate time-step needed for a successful and valid quasi-steady simulation. A valid quasi-steady simulation needs to use a time-step that is small enough to reproduce the full time-dependent solution within a very small error band. We have found that both the 1 s and the 0.1 s time steps produce virtually identical results. This is the primary litmus test that proves the validity of the quasi-steady-state assumption. The results adopted in this paper are thus all based on the more conservative 0.1 s time-step. In the process of performing the simulations, remeshing was required in order to maintain the grid density in zones of high curvature to be able to capture the full physics in those zones. After successfully modeling glaze ice accretion over the airfoil surface using the 0.1 s quasi-steady simulation approach, the effects of supercooled large droplets (SLDs) impacting the surface have been examined and presented in terms of the variation of the local collection efficiency, the water film thickness, and the heat transfer rate. Examination of the variation of the angle that the ice horn makes with the airfoil chord line demonstrated a 20% improvement in angle prediction when the time-step is reduced from 116 s to 0.1 s. The analysis also reveals a 12% or 8.5% increase in the maximum collection efficiency, βmax, depending on whether the value of the liquid water content (LWC) has been doubled from 0.5 g/m3 to 1 g/m3, or the value of the freestream velocity has been doubled from 75 m/s to 150 m/s, respectively. Because of the need to monitor the local collection efficiency and convective heat fluxes at each shot (regardless of the number of shots employed), the approach adopted here was found to be effective in successively and successfully reproducing the curvature of the glaze ice horn.

Engineering↗
DOE OSTI2025

Rotary Inertia Friction Welding of Dissimilar High-Strength 422 Martensitic Stainless Steel and 4140 Low Alloy Steel for Heavy-Duty Engine Piston Fabrication

AISI 422 martensitic stainless steel with superior high temperature performance (oxidation resistance and strength) is under evaluation for replacing current heavy-duty piston crown materials, AISI 4140 martensitic steel and micro alloyed steel (MAS) 38MnSiVS5, to fabricate a multimaterial piston. This multimaterial piston concept further improved power density and fuel economy by allowing heavyduty diesel engines to operate at higher temperatures and pressures. Joining AISI 422 steel piston crowns with AISI 4140 steel piston skirts is a key manufacturing step for this multimaterial piston. However, the significant differences in strength, elevated temperature flow stress, alloy chemistry, and temper resistance between these two martensitic steels cause some weldability issues (cracking) and metallurgical challenges (alloying element migration/segregation) when using conventional fusion-based welding processes. Rotary inertia friction welding (RIFW), a solid-state welding process, has been the preferred method to join 4140 crowns to 4140 skirts (and MAS crowns to MAS skirts) in high-volume production of current heavy-duty diesel engine pistons. It has been used to join these two materials with relatively comparable alloy chemistry to fabricate pistons with MAS skirts and 4140 crowns. Meanwhile, RIFW has also been a preferred method of dissimilar metal welding. However, RIFW of dissimilar high-strength martensitic steels has yet to be widely pursued. The interfacial microstructure complexities created by the thermomechanical process and highly nonequilibrium phase transformations during RIFW are a significant challenge for understanding and predicting their joining behavior and have not been reported in detail. Here, in this work, defect-free AISI 422 steel-AISI 4140 multimaterial pistons were successfully fabricated using the RIFW process. The interfacial microstructure and mechanical properties of dissimilar 422/4140 steel RIFW in the as-welded condition were experimentally studied in detail. The results provide critical baseline information for understanding RIFW mechanisms and guiding subsequent postweld heat treatment (PWHT) practice.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Rapid detection of mexX in Pseudomonas aeruginosa based on CRISPR-Cas13a coupled with recombinase polymerase amplification

The principal pathogen responsible for chronic urinary tract infections, immunocompromised hosts, and cystic fibrosis patients is Pseudomonas aeruginosa , which is difficult to eradicate. Due to the extensive use of antibiotics, multidrug-resistant P. aeruginosa has evolved, complicating clinical therapy. Therefore, a rapid and efficient approach for detecting P. aeruginosa strains and their resistance genes is necessary for early clinical diagnosis and appropriate treatment. This study combines recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats-association protein 13a (CRISPR-Cas13a) to establish a one-tube and two-step reaction systems for detecting the mexX gene in P. aeruginosa . The test times for one-tube and two-step RPA-Cas13a methods were 5 and 40 min (including a 30 min RPA amplification reaction), respectively. Both methods outperform Quantitative Real-time Polymerase Chain Reactions (qRT-PCR) and traditional PCR. The limit of detection (LoD) of P. aeruginosa genome in one-tube and two-step RPA-Cas13a is 10 aM and 1 aM, respectively. Meanwhile, the designed primers have a high specificity for P. aeruginosa mexX gene. These two methods were also verified with actual samples isolated from industrial settings and demonstrated great accuracy. Furthermore, the results of the two-step RPA-Cas13a assay could also be visualized using a commercial lateral flow dipstick with a LoD of 10 fM, which is a useful adjunt to the gold-standard qRT-PCR assay in field detection. Taken together, the procedure developed in this study using RPA and CRISPR-Cas13a provides a simple and fast way for detecting resistance genes.

Zhu, Xiao-Xuan↗
DOE OSTI2020

Method and system for preparing polycrystalline group III metal nitride

A process of preparing polycrystalline group III nitride chunks comprising the steps of (a) placing a group III metal inside a source chamber; (b) flowing a halogen-containing gas over the group III metal to form a group III metal halide; (c) contacting the group III metal halide with a nitrogen-containing gas in a deposition chamber containing a foil, the foil comprising at least one of Mo, W, Ta, Pd, Pt, Ir, or Re; (d) forming a polycrystalline group III nitride layer on the foil within the deposition chamber; (e) removing the polycrystalline group III nitride layer from the foil; and (f) comminuting the polycrystalline group III nitride layer to form the polycrystalline group III nitride chunks, wherein the removing and the comminuting are performed in any order or simultaneously.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High Fidelity Simulations of Air-Cooled Reactor Cavity Cooling System

Nuclear energy is increasingly acknowledged as pivotal in the global shift towards cleaner energy solutions. Advanced nuclear technologies, including High Temperature Gas-cooled Reactors (HTGRs), stand out as appealing options among Generation IV reactors due to their high temperature heat output and potential for cogeneration. HTGR designs incorporate passive safety systems, such as the Reactor Cavity Cooling System (RCCS), which utilize natural principles to manage heat dissipation from the reactor pressure vessel (RPV) during accidents or routine shutdowns. Regulatory bodies require thorough validation of safety systems like the RCCS to ensure they meet specified standards. Consequently, there is a pressing need within the industry for advanced simulation tools capable of assessing these systems’ performance accurately. There is a knowladge gap in the literature concerning high-fidelity data for the RCCS, which motivates the focus of this study. This research focuses on a specific RCCS designed for the Modular High-Temperature Gas Reactor developed by General Atomics (GA- MHTGR). Experimental studies on a scaled version of the air-cooled RCCS of GA-MHTGR were conducted by the University of Wisconsin-Madison. This work contributes to a broader initiative aimed at establishing a numerical benchmark based on the UW-Madison experiments. As first step we performed high fidelity simulations of the experimental facility setup, to analyze flow physics in such systems and validate NekRS and the MOOSE heat transfer and radiation modules.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

One-Step Ahead Prediction of Thermal Mixing Tee Sensors with Long Short Term Memory (LSTM) Neural Networks

High-temperature advanced reactors under development, such as sodium fast reactors (SFR) and molten salt cooled reactors (MSCR), are expected to offer lower levelized cost of energy (LCOE) compared to existing light water reactor (LWR’s). In the existing light water reactors (LWR’s), operation and maintenance (O&M) expenses constitute the largest fraction of the total operating cost. Some of the O&M costs are related maintenance of sensors which can fail due to exposure to harsh environment in a reactor. The O&M costs of Advanced Reactor (AR)’s are expected to constitute a significant fraction of the total cost as well, because of high temperature and radiation level in AR are likely to cause material fatigue and premature failure of sensors and components. The O&M costs in AR’s could be reduced through integration of advanced informatics of performance-related sensors into a digital twin designed for reactor monitoring. For example, machine learning (ML) could be employed for real-time validation and correction of performance-related sensors, and reducing the number of performance-related physical sensor units through virtual sensing. As part of the effort, we investigate real-time validation of thermal hydraulic sensors through one-step ahead forecasting of sensor values using long short-term memory (LSTM) recurrent neural networks (RNN). The sensors are installed in a flow loop containing a thermal mixing tee, which is a common experimental model to study thermal fatigue in a thermal hydraulic loop. In addition, nonlinear transients generated in a thermal mixing tee constitute a good challenge data set for training and validation of ML algorithms. Sensors in this study include thermocouples, flow meters, and optical fibers for distributed temperature sensing. In one experiment, measurement data sets were obtained for a loop was filled with water, and in another experiment, measurements were performed on a loop filled with liquid metal Galinstan. We have also conducted preliminary investigation of one-step ahead prediction of fiber optics-based distributed temperature sensing with LSTM networks. In predicting fiber-based temperature measurements, we treated each gauge pitch of the fiber as an independent sensor. Accuracy of one-step ahead forecasting was estimated by calculating root mean square error (RMSE) for the test segment of time series of each sensor. RMSE’s for temperature sensors in water loop were, for the most part, lower than for the same sensors in Galinstan loop. The RMSE’s for flow meters were similar for both loops. The RMSE’s for distributed temperature measured with the fiber optic sensor were similar to those of the point sensors. Results of this study demonstrated the capability of LSTM one-step ahead forecasting with RMSE comparable to uncertainty in sensor measurements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Growth of organized flow coherent motions within a single-stream shear layer: 4D-PTV measurements

Abstract This study investigates the evolution of a single-stream shear layer (SSSL) originating from a wall boundary layer past a backward-facing step. Utilizing a time-resolved 3D-Particle Tracking Velocimetry (4D-PTV) technique, we track the trajectories of fluorescent particles to gain insight into the flow characteristics of the SSSL. A compact water tunnel facility ( $$\textrm{Re}_\tau =1\,240$$ Re τ = 1 240 ) is fabricated to obtain an SSSL with a perpendicular slow entrainment stream past the separation edge. A hybrid interpolation approach that combines ensemble binning and Gaussian weighting is implemented to derive minimally filtered mean and instantaneous lower- and higher-order flow field parameters. Spanwise-dominant coherent motion accompanied by finer flow scales is observed to grow due to flow entrainment through “nibbling” actions of small-scale vortices, “engulfing” by large-scale vortices, and vortex pairing events. Furthermore, the non-zero-speed stream edge grows relatively faster than the zero-speed stream edge, showing a strong asymmetry in mixing composition across a mixing layer. The SSSL reaches self-similarity at a streamwise distance of $$\approx 55\,\theta _{0}$$ ≈ 55 θ 0 , where $$\theta _0$$ θ 0 is the initial momentum thickness from the separation edge, i.e., considerably shorter than reported in previous studies. A literature comparison of growth rate parameters raises intriguing questions regarding a potential inclusive growth scaling unifying the free shear layers. A turbulent kinetic energy (TKE) budget analysis reveals a negative production region immediately downstream of the separation edge attributed to a large positive streamwise gradient of streamwise velocity. In the self-similar region, the phase-averaged flow mapping demonstrates a larger concentration of turbulence production rate around the outer edges of spanwise vortices, specifically at the intersection of braids and vortices. Furthermore, a spatial separation exists in the regions of peak production and dissipation rates within the vortex core region favoring dissipation. The braids exhibit a larger concentration of turbulence diffusion rates, indicating their function as a conduit for exchanging turbulence between neighboring coherent motions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Impact of particle size and particle-flow-wall coupling on pressurized oxy-combustion in the down-fired burner

Concerns over climate change have led to numerous efforts in developing low-carbon energy technologies. Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Designing an effective burner plays a vital role in developing new coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the burner of a pressurized oxy-combustor is close or even higher than the maximum limit that commercial CFD codes (e.g., ANSYS FLUENT) can handle. At this high particle volume fraction, the interactions among particles, fluid flow, and wall need to be re-evaluated. The present computational work is the first step of a systematic analysis of the particle influence, like releasing method, releasing locating, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In a POC process, pulverized coal is burned under elevated pressure and O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing ANSYS FLUENT, using Reynolds-averaged Navier-Stokes (RANS) modeling. It is revealed that for this pilot-scale, pressurized burner, velocity profiles of the near-wall region in this POC facility exhibit some discrepancy against the near-wall turbulent flow velocity profile. In order to investigate the particle influence in the near-wall region, particle releasing location will be investigated. Numerical simulation results exhibit the coupling effect of turbulence flow and particles in this case. The particle size also demonstrates a great effect on particle trajectory, then further has an impact on flame stability and temperature.

Li, Lei↗
DOE OSTI2022

Visualization and validation of twin nucleation and early-stage growth in magnesium

The abrupt occurrence of twinning when Mg is deformed leads to a highly anisotropic response, making it too unreliable for structural use and too unpredictable for observation. Here, we describe an in-situ transmission electron microscopy experiment on Mg crystals with strategically designed geometries for visualization of a long-proposed but unverified twinning mechanism. Combining with atomistic simulations and topological analysis, we conclude that twin nucleation occurs through a pure-shuffle mechanism that requires prismatic-basal transformations. Also, we verified a crystal geometry dependent twin growth mechanism, that is the early-stage growth associated with instability of plasticity flow, which can be dominated either by slower movement of prismatic-basal boundary steps, or by faster glide-shuffle along the twinning plane. The fundamental understanding of twinning provides a pathway to understand deformation from a scientific standpoint and the microstructure design principles to engineer metals with enhanced behavior from a technological standpoint.

36 MATERIALS SCIENCE↗
DOE OSTI2020

From Interstellar Cloud to Star to Laboratory: Frontier HEDP Studies of Magnetized Colliding Plasma Flows with Strong Radiative Cooling (Final Report)

High-speed flows of gas are the norm in astrophysics where exploding stars, winds from the regions around black holes and streams of galactic material create “supersonic flows”. As the flows collide, strong shock waves are formed where gas is compressed and heated. The regions behind these shock waves are of great interest to scientists. New stars can form in these shock regions in the context of galaxies. In the context of planets like our Earth, the shocks waves come from the interaction of the solar wind with our planets’ magnetic field causing Aurora and placing astronauts and satellites in jeopardy. Thus, understanding supersonic flows of magnetized plasmas is essential for progress in many fields of astronomy and space physics (relevant to planets and the Earth). Remarkably, we can also create these kinds of flows in the laboratory using Z-pinches and laser driven experiments that include magnetic fields. The exploration of these forms of “High Energy Density Physics” (HEDP) flows is also critical in order to achieve Inertial Confinement Fusion, which is a step towards developing a sustainable source of Fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Initial development of a high temperature life prediction method directly accounting for variability in material properties

This report presents the initial development of a life prediction method that accounts for the variability of the material properties in Grade 91 steel. We account for material variability by both fitting a variable 3-parameter Weibull distribution to the rupture data of the material and by quantifying the effect that the creep deformation properties have on stresses via a Monte Carlo approach. To ensure a reasonable time frame when applying Monte Carlo to the creep stress, we propose a methodology that models the material as an extremely viscous Stokes flow with a non-Newtonian viscosity, therefore solving the problem in a single step. We use the final probabilistic model for structural failure developed in this document to evaluate a Flat Head Vessel designed with the Section III, Division 5 ASME Boiler Pressure and Vessel Code rules with a 100,000h design life and assess its probability of premature failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization

Traditional trial-and-error methods for materials discovery are inefficient to meet the urgent demands posed by the rapid progression of climate change. This urgency has driven the increasing interest in integrating robotics and machine learning into materials research to accelerate experimental learning. However, idealized decision-making frameworks to achieve maximum sampling efficiency are not always compatible with high-throughput experimental workflows inside a laboratory. For multi-step chemical processes, differences in hardware capacities can complicate the digital framework by introducing constraints on the maximum number of samples in each step of the experiment, hence causing varying batch sizes in variable selection within the same batch. Therefore, designing flexible sampling algorithms is necessary to accommodate the multi-step synthesis with practical constraints unique to each high-throughput workflow. In this work, we designed and employed three strategies on a high-throughput robotic platform to optimize the sulfonation reaction of redox-active molecules used in flow batteries. Our strategies adapt to the multi-step experimental workflow, where their formulation and heating steps are separate, causing varying batch size requirements. By strategically sampling using clustering and mixed-variable batch Bayesian optimization, we were able to iteratively identify optimal conditions that maximize the yields. Our work presents a flexible approach that allows tailoring the machine learning decision-making to suit the practical constraints in individual high-throughput experimental platforms, followed by performing resource-efficient yield optimization using available open-source Python libraries.

Tamura, Clara [Univ. of Washington, Seattle, WA (U↗
DOE OSTI2021

Carbon and Hydrocarbon Particle Seeding in Air-Breathing Rotating Detonation Engine

Within the power generation community, the rotating detonation engine (RDE) is only growing in popularity with its increased performance, simple mechanism, and operation. Although significant testing is underway to characterize the RDE for integration with conventional gas turbines, this entire system is still at a relatively low technology readiness level. In the midst of RDE research, there is an initiative to understand solid particle seeding effects in the detonation performance. Under investigation at the University of Central Florida is a Department of Energy (DOE) 15.24 cm (6 in.) RDE, with a solid particle seeder in parallel with its H2 and air flow lines. Previous work on this system involved carbon particle detonation; however, the tested particles were taken one step further to include more sustainable, greener hydrocarbon particles. Testing of powdered sugar, peanut flour, and cornstarch, along with previous carbon black tests have shown not only successful detonability, but a noticeable effect on the detonation wave dynamics. Side-by-side with a particle burning model being developed, an operational map can be determined for the hydrocarbon particles particularly, which can be tuned with the local flow conditions to achieve peak operability while replacing fuels with sustainable alternatives that could even be grown.

Engineering↗
DOE OSTI2023

A numerical investigation of coal particle modeling for the inlet section of a pressurized oxy-combustion burner

Concerns over climate change have led to numerous efforts to develop low-carbon technologies, and pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in the power industry. Designing an effective burner for such technologies is vital for the development of these and other coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the pressurized oxy-combustor burner is close to or even higher than the maximum limit for commercial CFD codes (e.g., ANSYS FLUENT). At these high particle volume fractions, the interactions among particles, fluid flow and wall need to be re-evaluated. The present computational work is a first step in a systematic analysis of the influence of various parameters, like method of particle release, release location, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In the POC process, pulverized coal is burned under elevated pressure in an O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing Ansys FLUENT commercial sodtware using the Reynolds-Averaged Navier-Stokes (RANS) approach. It is revealed that for this pilot-scale, pressurized burner, velocity profiles in the near-wall region exhibit some anomalies. In order to investigate the influence of particle loading in the near-wall region, particle release location was investigated. The numerical simulations incorporate the coupling between the turbulent flow and the particles. A sensitivity investigation of particle release location found that by tuning the release location, the velocity profile can be consistent with the pure gas flow velocity profile. More importantly, the particle releasing location also affects flame stability. Particle size was also found to have a significant impact on particle trajectory, flame stability and temperature. Finally, Large Eddy Simulations (LES) were performed and compared with the results from two-dimensional RANS.

Li, Lei↗
DOE OSTI2022

Uranium Oxide Elutriation at Higher Flow Rates and Longer Times

This work supports the recovery of high-assay low-enriched uranium (i.e., U enriched in 235 U to >5% and <20%) from used nuclear fuel. One step includes elutriating triuranium octoxide (U 3 O 8 ) from a fluidized bed of alumina (Al 2 O 3 ) that fills the main reaction chamber. The experiments outlined in this report assessed the effects of the time and flow rate on the elutriation of U 3 O 8 powder from the reaction vessel. Testing at Oak Ridge National Laboratory (ORNL) was performed in a one-fourth scale experimental apparatus based on a pilot-scale system, which is the Material Recovery Pilot Plant (MRPP) at Idaho National Laboratory (INL). The experimental system comprises a supply of pressurized nitrogen (N 2 ), a gas heater, the reaction vessel, a knock-out pot, and a water trap where elutriated particles are collected for sampling. An Al 2 O 3 fluidized bed is contained within the reaction vessel. A bed of Al 2 O 3 with a nominal size of 180 µm and U 3 O 8 with a nominal size of 7 µm was fluidized at 2 different flow rates so the U 3 O 8 physically separated from the bed. The apparatus was simple and had no valves or sharp bends downstream from the reactor. The flow exited the reactor through a side port at the top. The flow passed through a knock-out vessel before the flow was passed through a bubbler to capture the U 3 O 8 . Seven tests were completed with U 3 O 8 using an elutriating gas of N 2 heated to 200°C. Tests were performed with bed loadings that comprise 25.0 g of U 3 O 8 , or 3.6 wt% of the bed mass. Except for one test performed at 12 SLPM, the gas flow rate through the bed for the other experiments was set at 10 SLPM as measured by the mass flow meter. Linear velocities through the bed were calculated as 28 and 34 cm/s, or 0.9 and 1.1 ft·s -1 . The duration of the tests ranged from 20 to 180 min, and one test had a flow cycled between 0 and 5 SLPM every 5 min for 40 min. The testing successfully demonstrated elutriation of U 3 O 8 from the fluidized bed as up to a 100% of the U 3 O 8 was transferred out of the bed. The removal of U 3 O 8 had a logarithmic dependence on flow rate. The design changes made the apparatus easier to clean, and the mass balances were better than those used in previous studies. Some elutriated Al 2 O 3 collected in the tubing that connected the reactor to the knock-out pot, but the amount of Al 2 O 3 was minimal for 10 SLPM. The flow at 12 SLPM showed considerable transport of Al 2 O 3 bed material into the reaction-vessel headspace and the transfer line to the knock-out pot.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗