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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An index to characterize gas‐solid and solid‐solid mixing from average volume fraction fields

Abstract A mixing index based on solid volume fraction fields is developed for gas‐solid flows. Conventional mixing indices are based on particle realizations of granular mixing and are applicable to experimental data or discrete element method simulations. However, these indices cannot be used as‐is for multifluid models, and an index for characterizing mixing in gas‐solid flows from continuous fields is needed. The performance of the new mixing index is tested in two applications. The first is a 3D simulation of the mixing of biomass and sand in a fluidized bed reactor, and the second is a 2D simulation of binary particle segregation in a fluidized bed. The simulations are performed using OpenFOAM®. The mixing index is used to quantify gas‐solid mixing using solid volume fractions and solid‐solid mixing using solid fractions. The formulation of conventional mixing indices is extended to be used with solid volume fractions fields, and methods for performance improvement are presented.

09 BIOMASS FUELS↗
DOE OSTI2023

Finite element modeling of biomass hopper flow

Hoppers are widely used biomass handling devices that channel bulk biomass from storage to subsequent handling equipment. Jenike’s longstanding approach, based on the Mohr-Coulomb model, has been successfully used to design hoppers handling cohesionless granular materials such as grains and other agricultural produces. However, designing a hopper to ensure reliable biomass flow is found to be challenging due to cohesion, irregular particle shape, and bulk material elastoplasticity. This study aims to address the biomass handling engineering challenge with alternative constitutive material models concerning the flow behavior of bulk solids. Finite element modeling is an approach that allows for implementation of different material models, whose underlying constitutive theories assist in investigating the origin and manifestation of bulk mechanical behavior of granular materials. This study focuses on the incipient gravity hopper flow of two types of biomass feedstocks, i.e., ground corn stover and Douglas fir wood. Three widely used constitutive material models, i.e., Mohr-Coulomb model, modified Cam-Clay model, and Drucker-Prager/Cap model, are implemented. Using the flow pattern represented by the volume of biomass exhibiting more than 7% of axial strain (Kamath and Puri, 1999), the finite element model predicts that the bulk corn stover particulate material forms an arch, which represents a hampered transition from the static state to the dynamic flow-state out of the hopper, whereas bulk Douglas fir wood particulate material develops a reliable mass flow pattern. A laboratory scale hopper was used to experimentally determine the biomass flow conditions, which were subsequently compared with the predicted onset of flow by a finite element model (FEM). The developed FEM was found to correctly predict the initiation of mass flow for the milled Douglas fir wood, whereas corn stover was predicted to establish a strong core flow suggesting an unreliable handling characteristic. This observation aligns with the reported poor handling of milled corn stover.

09 BIOMASS FUELS↗
DOE OSTI2026

Detector architecture and data flow of the CMS HGCAL Phase-2 Endcap Calorimeter Upgrade

The CMS High Granularity Calorimeter (HGCAL) is the Phase-2 endcap calorimeter upgrade for the High-Luminosity Large Hadron Collider, designed to provide precise spatial, energy, and timing measurements in a high-radiation, high-pileup environment. This work presents an overview of the HGCAL assembly process, detector architecture, and end-to-end data flow. The data flow goes from signal generation in silicon sensors and scintillator tiles through front-end electronics, optical transmission, and back-end data acquisition. The study highlights how the integrated detector, electronics, and readout systems enable efficient event reconstruction and support the physics objectives of the HL-LHC.

Osei Boakye, Prince [Grambling State U.]↗
DOE OSTI2022

The SiD Digital ECal Based on Monolithic Active Pixel Sensors

The SiD detector concept capitalizes on high granularity in its tracker and calorimeter to achieve the momentum resolution and particle flow calorimetry physics goals in a compact design. The collaboration has had a long interest in the potential for improved granularity in both the tracker and ECal with an application of monolithic active pixel sensors (MAPS) and a study of MAPS in the SiD ECal was described in the ILC TDR. Work is progressing on the MAPS application in an upgraded SiD design with a prototyping design effort for a common SiD tracker/ECal design based on stitched reticules to achieve 10 × 10 cm2 sensors with 25 × 100 micron2 pixels. Application of large area MAPS in these systems would limit delicate and expensive bump-bonding, provide possibilities for better timing, and should be significantly cheaper than the TDR concept due to being a more conventional CMOS foundry process. The small pixels significantly improve shower separation. Recent simulation studies confirm previous performance projections, indicating electromagnetic energy resolution based on digital hit cluster counting provides better performance than the SiD TDR analog design based on 13 mm2 pixels. Furthermore, the two shower separation is excellent down to the millimeter scale. Geant4 simulation results demonstrate these expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Fluid-driven fractures in granular media: Insights from numerical investigations

We investigate the mechanisms of opening-mode fracture initiation in granular media. The study is based on a simulation of grain-scale fluid-grain interactions through a coupled numerical approach in which the discrete element method is used to solve for the mechanics of a solid granular medium, and computational fluid dynamics is used to model fluid flow and drag forces. In this work, we present benchmark problems with analytical solutions and validate this numerical model against experiments on a viscous-drag-driven cavity in the literature. Additional simulation results show fracture initiation mechanisms in a random granular packing subjected to constant boundary stresses and to fluid injection with a localized source. The dimensionless variable $F_s/F_{sk}$ (ratio of seepage force $F_s$ and skeletal force $F_{sk}$) incorporates the impacts of physical properties and injection parameters including fluid viscosity, injection velocity, grain size, and effective stresses, and it has been used as a criterion separating regimes of fluid invasion and drag-driven fracture opening. Our simulation results show that $F_s/F_{sk}$ in combination with $τ_1$ (ratio of diffusion time from hydromechanical coupling and injection time) serves as a prediction of fracture opening within granular packing. We suggest a simple criterion ($F_s/F_{sk}$ > 1 or $τ_1$ > 0.17) that is valid for various types of granular media and injection conditions to determine if fracture opening will occur. Among other applications, this study is useful to predict the initiation and propagation of fractures in natural sediments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Standing Shock Regulates Sparks in Explosive Flows

Electric sparks and explosive flows have long been associated with each other. Flowing dust particles originate charge through contact electrification and separate based on inertia, resulting in strong electric fields supporting sparks. These sparks can cause explosions in dusty environments, especially those rich in carbon, such as coal mines and grain elevators. Recent observations of explosive events in nature and decompression experiments indicate that supersonic flows of explosions may alter the electrical discharge process. Shocks may suppress parts of the hierarchy of the discharge phenomena, such as leaders. In our decompression experiments, a shock tube ejects a flow of gas and particles into an expansion chamber. We imaged an illuminated plume from the decompression of a mixture of argon and < 100 mg of diamond particles. We also performed hydrodynamics simulations of the decompression event that provide insight into the conditions supporting the observed behavior. The sparks occur below the sharp boundary of a condensation cloud. These results agree closely with the Mach disk shock shape and height in the simulation. This represents direct evidence that the sparks are sculpted by the outflow. The spatial and temporal scale of the sparks transmit an impression of the shock tube flow, a connection that could enable novel instrumentation to diagnose currently inaccessible supersonic granular phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2026

CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters

High-precision calorimeter simulation at current and future colliders imposes rapidly growing computational demands, motivating the development of machine-learning surrogates for traditional Monte Carlo tools such as Geant4. Flow matching and diffusion-based generative models have become leading approaches for high-dimensional fast simulation because of their sample quality, but typically require ${\cal O}(100)$ function evaluations at inference and often rely on auxiliary networks to constrain global observables, compromising streamlined end-to-end generation. We introduce a unified framework that improves the balance between speed, shower quality, and physics fidelity. The method combines: (i) an average velocity field integrator that enables sampling in one or a few evaluations; (ii) a learned generative prior in shower space, constructed from data rather than random noise; and (iii) physics-guided loss terms that impose inductive biases on key observables during training. These elements are training time regularizers, preserving end-to-end inference with no additional cost. With only one or a few evaluation steps, the model achieves shower quality competitive with state-of-the-art flow and diffusion approaches, tested on several public high granularity calorimeter datasets. The results demonstrate inter-layer shower structure consistent with the underlying physics, providing a strong candidate for future fast simulation workflows.

Jiang, Cheng [Edinburgh U.]↗
DOE OSTI2025

The efficacy and ecological impact of mercury sorbents on the physiology and reproductive fitness of Daphnia magna

Environmental mercury (Hg) contamination threatens ecosystems due to its bioaccumulation and toxicity. Effective and sustainable remediation strategies are essential, with carbon-based sorbents like biochar (BC) and activated carbon (AC) gaining attention for their high adsorption capacity and cost-effectiveness. However, their ecological impacts remain poorly understood. This study evaluates the Hg removal efficacy and ecological effects of three sorbents—BC, granular AC (GAC), and AC fiber (ACF)—in a flow-through column system with and without Hg additions. We tested Hg removal at two concentrations (1 and 4 µg/L Hg) and assessed chronic exposure effects on a sentinel and sensitive freshwater organism, Daphnia magna, over 30 days of exposure to the columns’ effluent. GAC removed 100 % of Hg, while BC and ACF achieved 99 % removal. The ACF + 4 µg/L Hg effluent induced 70 % lethality in D. magna after nearly three weeks of exposure, while the GAC effluent significantly reduced fecundity, even in the absence of Hg exposure. In contrast, the BC effluent enhanced reproductive output, likely due to inputs of carbon and nitrogen in the effluent. These findings highlight the need to balance Hg removal efficacy with ecological safety, emphasizing the importance of considering both remediation effectiveness and potential environmental impacts.

Activated carbon↗
DOE OSTI2023

On the Scaling and Growth Limit of Fluvial Dunes

Abstract Bedforms emerge in a variety of shapes and sizes when a granular erodible surface is subject to a strong enough shear flow, as observed in topographic data from submarine canyons, rivers, deserts, and planetary bodies. The two salient features of bedforms are the ability to collectively transport particles, and to generate form drag thus increasing flow resistance. These two mechanisms are in competition and contribute to force bedforms of increasing size migrating more slowly. In a dedicated large‐scale open channel flow facility, hierarchies of fluvial bedforms were generated and measured in equilibrium conditions. The corresponding scale‐dependent migration velocity and mass flux contributions were quantified in the wave number and frequency domains. Experimental results are paired with a validated set of theoretical models to demonstrate that ripples or dunes reach an equilibrium state when drag partitioning ensures high enough frictional drag to sustain the bedload transport of sediment, and low enough form drag to enable the migration of the largest bedform size. This mechanism is inferred to constrain the growth of bedforms when sediment supply is not the limiting factor.

58 GEOSCIENCES↗
DOE OSTI2024

Evaluation of Lost Circulation Material Sealing for Geothermal Drilling

Lost circulation is a pervasive problem in geothermal wells that can create prohibitive costs during drilling. The main issue with treatment is that the mechanism of plug formation is poorly understood. Here we applied two experimental approaches to characterize the clogging effectiveness of different materials. Fracture flow tests with different geometries were conducted with various individual materials and mixtures at relevant conditions. A high-temperature flow loop system was also developed to inject single- and mixed-material plugs into a gravel pack with a non-uniform geometry to compare with the fracture tests. The fracture tests revealed that single materials tended to form no plug or an unstable plug, while mixtures of materials were uniformly better at sealing fractures. Gravel pack tests at high temperatures show most of the materials are intact but degraded. The fibrous materials can create partial or unstable plugs in the gravel pack, but mixed-material plugs are far more effective at clogging. Both test types suggest that (1) mixed materials are more effective at blocking fluid flow and (2) fibrous materials seal fracture openings better, while granular materials seal inside fractures or pore throats better. Further research is needed to study the long-term stability of different plug configurations.

clogging tests↗
DOE OSTI2025

Compact Counter Flow Fluidized Bed Heat Exchanger (Final Report)

Generation 3 concentrating solar power systems which utilize solid granular media as the heat transfer and storage media hold promise in reducing the levelized cost of electricity relative to generation 2 systems which utilize molten salt. The particles can be heated to temperatures exceeding 800 °C which enables the use of high efficiency supercritical CO 2 Brayton power cycles. A key challenge associate with the use of solid media is its low bulk thermal conductivity which limits the ability to transfer heat from the particles to a working fluid, such as supercritical CO 2 . Tradition shell and tube and shell and plate heat exchangers feature gravity driven particle flow which limits the maximum particle side heat transfer coefficient in these systems to approximately 400 W/m 2 K. A fluidized bed heat exchanger does not rely solely on gravity for particle flow. Instead, enhanced mixing and horizontal conveyance is achieved through fluidization induced through air injection at the bottom of a bed of particles. A tube bundle within the bed conveys the supercritical CO 2 which is heated via the turbulent particle motion at the tube wall.

14 SOLAR ENERGY↗
DOE OSTI2023

Colliding localized, lumpy holographic shocks with a granular nuclear structure

We apply a recent and simple technique which speeds up the calculation of localized collisions in holography to study more realistic models of the pre-hydrodynamic phase of heavy ion collisions using gauge/gravity duality. Our initial data reflects the lumpy nuclear structure of real heavy ions and our projectiles’ aspect ratio mimics the Lorentz contraction of nuclei during RHIC collisions. At the hydrodynamization time of the central region of the quark gluon plasma developed during the collision, we find that most of the system’s vorticity is located well outside the hydrodynamized part of the plasma. Only the relativistic corrections to the thermal vorticity within the hydrodynamized region are non-negligible. We compare the transverse flow shortly after the collision with previous results which did not use granular initial conditions and determine the proper energy density and fluid velocity in the hydrodynamized subregion of the plasma.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors

Abstract Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event reconstruction in electron-positron collisions based on a full detector simulation. Particle-flow reconstruction can be formulated as a supervised learning task using tracks and calorimeter clusters. We compare a graph neural network and kernel-based transformer and demonstrate that we can avoid quadratic operations while achieving realistic reconstruction. We show that hyperparameter tuning significantly improves the performance of the models. The best graph neural network model shows improvement in the jet transverse momentum resolution by up to 50% compared to the rule-based algorithm. The resulting model is portable across Nvidia, AMD and Habana hardware. Accurate and fast machine-learning based reconstruction can significantly improve future measurements at colliders.

Physics↗
DOE OSTI2020

Jamming, fragility and pinning phenomena in superconducting vortex systems

Abstract We examine driven superconducting vortices interacting with quenched disorder under a sequence of perpendicular drive pulses. As a function of disorder strength, we find four types of behavior distinguished by the presence or absence of memory effects. The fragile and jammed states exhibit memory, while the elastic and pinning dominated regimes do not. In the fragile regime, the system organizes into a pinned state during the first pulse, flows during the second perpendicular pulse, and then returns to a pinned state during the third pulse which is parallel to the first pulse. This behavior is the hallmark of the fragility proposed for jamming in particulate matter. For stronger disorder, we observe a robust jamming state with memory where the system reaches a pinned or reduced flow state during the perpendicular drive pulse, similar to the shear jamming of granular systems. We show signatures of the different states in the spatial vortex configurations, and find that memory effects arise from coexisting elastic and pinned components of the vortex assembly. The sequential perpendicular driving protocol we propose for distinguishing fragile, jammed, and pinned phases should be general to the broader class of driven interacting particles in the presence of quenched disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Corona splashing triggered by a loose monolayer of particles

In nature, high-speed raindrops often impact and spread on particulate surfaces (e.g., soil, plant leaves with spores or pollen). We study the dynamics of droplet impact on a loosely packed monolayer of particles by combining experimental and mathematical approaches. We find that the presence of mobile particles lowers the critical impact velocity at which the droplet exhibits corona splashing, as the particle area fraction is systematically increased. We rationalize this experimental observation by considering the jamming of frictional particles at the spreading rim. Elucidating the splashing transition of the drop on a particulate bed can lead to a better understanding of soil loss and erosion from falling raindrops

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

MLPF: efficient machine-learned particle-flow reconstruction using graph neural networks

In general-purpose particle detectors, the particle-flow algorithm may be used to reconstruct a comprehensive particle-level view of the event by combining information from the calorimeters and the trackers, significantly improving the detector resolution for jets and the missing transverse momentum. In view of the planned high-luminosity upgrade of the CERN Large Hadron Collider (LHC), it is necessary to revisit existing reconstruction algorithms and ensure that both the physics and computational performance are sufficient in an environment with many simultaneous proton–proton interactions (pileup). Machine learning may offer a prospect for computationally efficient event reconstruction that is well-suited to heterogeneous computing platforms, while significantly improving the reconstruction quality over rule-based algorithms for granular detectors. We introduce MLPF, a novel, end-to-end trainable, machine-learned particle-flow algorithm based on parallelizable, computationally efficient, and scalable graph neural network optimized using a multi-task objective on simulated events. We report the physics and computational performance of the MLPF algorithm on a Monte Carlo dataset of top quark–antiquark pairs produced in proton–proton collisions in conditions similar to those expected for the high-luminosity LHC. The MLPF algorithm improves the physics response with respect to a rule-based benchmark algorithm and demonstrates computationally scalable particle-flow reconstruction in a high-pileup environment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A level set approach for the computational study of a yield stress fluid filling a thin mold

Many important engineering and scientific applications such as cement slurries, foams, crude oil, and granular avalanches involve the concept of yield stress. Therefore, modeling yield stress fluids in different flow configurations, including the accurate prediction of the yield surface, is important. In this paper, we present a computational model based on the finite element method to study the flow of yield stress fluids in a thin mold and compare the results with data from flow visualization experiments. Here, we use the level set method to describe the interface between the filling fluid and air. We use polypropylene glycol as a model Newtonian fluid and Carbopol for the model yield stress fluid, as the Carbopol solution demonstrates yielding without thixotropy. To describe the yielding and shear-thinning behavior, we use a generalized Newtonian constitutive equation with a Bingham–Carreau–Yasuda form. We compare the results obtained from the mold filling experiments with the results from the three-dimensional (3D) model and from a reduced-order Hele-Shaw (HS) model that is two-dimensional, including the effect of shear-thinning along the thin direction only approximately. We show that both the 3D and the HS model can capture the experimental meniscus shape reasonably well for all the fluids considered at three different flow rates. This indicates that the shape evolution is insensitive to the dimensionality of the model. However, the viscosity and yield surfaces predicted by the 3D and HS models are different. The HS model underestimates the high viscosity and unyielded regions compared to the estimation by the 3D model.

42 ENGINEERING↗
DOE OSTI2020

Removal of radionuclides from acidic solution by activated carbon impregnated with methyl- and carboxy-benzotriazoles

The removal efficiencies of metals commonly used to model the fate and transport of aqueous uranium and radioactive its daughter products, were observed on activated carbons impregnated with different benzotriazole derivatives. Acidic solutions containing U(VI), Sr(II), Eu(III), and Ce(III) were used to determine the immobilization potential of carboxybenzotriazole (CBT) and methylbenzotriazole (MeBT), where these derivatives were sorbed to different types of granular activated carbon (GAC). This sorption behavior can be predicted by Redlich–Peterson model. Flow-through column tests showed that the immobilization of uranium and some of its daughter products, significantly improves in response to oxidized GACs saturated with carboxybenzotrzole (CBT), which reached a maximum elimination for U(VI) at 260 BV, Eu(III) at 114 BV, Ce(III) at 126 BV, and Sr(II) at 100. MeBT significantly desorbed from GAC under acidic conditions. Trace amounts of CBT were observed in some column effluents, but this did not appear to alter the effectiveness of metal removal, regardless of the model radionuclide studied. These results suggest that enhanced immobilization of selected metals on GAC, can be achieved by impregnating oxidized activated carbon with carboxylated benzotriazoles, and that metal removal efficiency on this media, is related to their valence and ionic radius in acidic environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗