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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Simulation of Fluid Flow and Collection Efficiency for an SEA Multi-element Probe

Numerical simulations of fluid flow and collection efficiency for a Science Engineering Associates (SEA) multi-element probe are presented. Simulation of the flow field was produced using the Glenn-HT Navier-Stokes solver. Three-dimensional unsteady results were produced and then time averaged for the heat transfer and collection efficiency results. Three grid densities were investigated to enable an assessment of grid dependence. Simulations were completed for free stream velocities ranging from 85-135 meters per second, and free stream total pressure of 44.8 and 93.1 kilopascals (6.5 and 13.5 pounds per square inch absolute). In addition, the effect of angle of attack and yaw were investigated by including 5 degree deviations from straight for one of the flow conditions. All but one of the cases simulated a probe in isolation (i.e. in a very large domain without any support strut). One case is included which represents a probe mounted on a support strut within a finite sized wind tunnel. Collection efficiencies were generated, using the LEWICE3D code, for four spherical particle sizes, 100, 50, 20, and 5 micron in diameter. It was observed that a reduction in velocity of about 20% occurred, for all cases, as the flow entered the shroud of the probe. The reduction in velocity within the shroud is not indicative of any error in the probe measurement accuracy. Heat transfer results are presented which agree quite well with a correlation for the circular cross section heated elements. Collection efficiency results indicate a reduction in collection efficiency as particle size is reduced. The reduction with particle size is expected, however, the results tended to be lower than the previous results generated for isolated two-dimensional elements. The deviation from the two-dimensional results is more pronounced for the smaller particles and is likely due to the reduced flow within the protective shroud. As particle size increases differences between the two-dimensional and three dimensional results become negligible. Taken as a group, the total collection efficiency of the elements including the effects of the shroud has been shown to be in the range of 0.93 to 0.99 for particles above 20 microns. The 3D model has improved the estimated collection efficiency for smaller particles where errors in previous estimates were more significant.

Water Content↗
DOE OSTI2023

Micro-Transfer Printing of Repeaters on Passive Interposer

Silicon-based sensors are central to particle physics experiments and particle tracking detectors. New-generation Large Focal Plane Arrays (LFPAs) cover areas that extend beyond several square meters. Distributing power and transporting data across such areas while maintaining good signal integrity is a complicated challenge. Tiling the detector on an organic interposer would be far too expensive and take too much space while offering little to no advantage regarding signal integrity. Passive silicon interposers are much less expensive and more integrable but would worsen signal integrity because of their inherent higher dielectric constant. Active interposers are a good compromise from the economic and signal integrity standpoint; unfortunately, their yield trends to zero for areas greater than a reticle size, making this technology incompatible with our application. NHanced proposes to duplicate the behavior of a high-yield, low-cost active interposer by printing active microcomponents on a passive interposer with our die-to-wafer micro-transfer printing (MTP) technology. This resolves the signal integrity and power distribution limitations. In Phase I, we designed and simulated analog and digital repeaters to be MTPed onto a passive silicon interposer test wafer.

2.5D↗
NASA NTRS2005

Medical and Scientific Evaluations aboard the KC-135. Microgravity-Compatible Flow Cytometer

A spaceflight-compatible flow cytometer would be useful for the diagnosis of astronaut illness during long duration spaceflight and for conducting in-flight research to evaluate the effects of microgravity on human physiology. Until recently, the primary limitations preventing the development of a spaceflight compatible flow cytometer have been largely mechanical. Standard commercially available flow cytometers are large, complex instruments that use high-energy lasers and require significant training to operate. Standard flow cytometers function by suspending the particles to be analyzed inside a sheath fluid for analysis. This requires the presence of several liters of sheath fluid for operation, and generates a corresponding amount of liquid hazardous waste. The particles are then passed through a flow cell which uses the fluid mechanical property of hydrodynamic focusing to place the cells in single-file (laminar flow) as they pass through a laser beam for scanning and evaluation. Many spaceflight experiments have demonstrated that fluid physics is dramatically altered in microgravity (MSF [Manned Space Flight] Fluid Physics Data Sheet-August 1997) and previous studies have shown that sheath-fluid based hydrodynamic focusing may also be altered during microgravity (Crucian et al, 2000). For these reasons it is likely that any spaceflight compatible design for a flow cytometer would abandon the sheath fluid requirement. The elimination of sheath fluid would remove both the problems of weight associated with large volumes of liquids as well as the large volume of liquid waste generated. It would also create the need for a method to create laminar particle flow distinct from the standard sheath-fluid based method. The spaceflight prototype instrument is based on a recently developed commercial flow cytometer possessing a novel flow cell design that creates single-particle laser scanning and evaluation without the need for sheath-fluid based hydrodynamic focusing. This instrument also possesses a number of design advances that make it conditionally microgravity compatible: it is highly miniaturized and lightweight, uses a low energy diode laser, has a small number of moving parts, does not use sheath fluid and does not generate significant liquid waste. Although possessing certain limitations, the commercial cytometer functions operationally like a standard bench top laboratory flow cytometer, aspirating liquid particle samples and generating histogram or dot-plot data in standard FCS file format. In its current configuration however, the cytometer is limited to three parameter/two-color capability (two color PMTs + forward scatter), does not allow compensation between colors, does not allow linear analysis and is operated by rather inflexible software with limited capabilities. This is due to the fact that the cytometer has been designed and marketed as an instrument specific to a few particular assays, not as a multipurpose cytometer.

Crucian, Brian↗
DOE OSTI2022

Flow structures of the cross-flow over a five-layer helically coiled steam generator geometry

The helically-coiled heat exchanger (HCSG) offers advantages over straight tubes such as compactness in geometry, increased heat transfer coefficients, and capability to absorb thermal expansion. In this study, the time-resolved velocity field data of shell-side crossflow over a five-layer helically coiled steam generator geometry was obtained using Particle Image Velocimetry (PIV) between adjacent rods in four regions with up to 5000 frames per second (5 kHz) at approximately Re u = 3600. The slant rod bundle created different flow patterns in different regions. Proper Orthogonal Decomposition (POD) revealed high-energy-mode flow structures. Due to the confined flow channel geometry, the large flow structures were not advected resulting in no strong POD mode paring. Continuous Wavelet Transform (CWT) visualized the characteristics of flow fluctuation in time and frequency domain simultaneously, which ranged in Strouhal number, S u , between 0.03 and 1.17. In the wake regions of the rods, flows changed in both pattern and magnitude over time. Once a pattern formed, it continued for relatively shorter than straight tube arrays, before changing the pattern again. The histograms of the POD time coefficients presented this multimodal flow characteristics. The current study focuses more on whole flow field analyses in the selected regions rather than local point-wise analyses. Finally, this study revealed that various Strouhal numbers can exist in the helically coiled heat exchanger geometry, which was not observed in straight tube arrays. In particular, Strouhal numbers smaller than 0.1 do not seem to be caused by vortex shedding but seem to be the result of the combination of complex geometry and possible multimodal trends. Based on the current observation, further works would involve intensive instantaneous point-wise analyses on the interactions between important locations such as separation points, stagnation points, shear layers, etc.

42 ENGINEERING↗
DOE OSTI2020

Insights into Mechanisms of Screw Feeder Plugging by Heated Pine Forestry Residues Using in-situ and Correlative Microscopy

Increasing concerns about global carbon emissions due to fossil fuel use has created interest in renewable fuel alternatives, such as lignocellulosic biomass. With an estimated global biomass production probability ten-fold higher than projected need, functionalizing and scaling biomass conversion processes, like pyrolysis, is a promising component of a diverse sustainable energy program (Kan, Strezov, & Evans, 2016). Pyrolysis reactors employed in biomass conversion often encounter the known problem of screw feeder plugging, halting work and reducing efficiency of biorefineries. Although the screw feeder is not heated directly, conductive heat transfer from the fluidized bed pyrolysis reactor creates a temperature gradient, where particles experience temperatures between 22°C and 500°C from the time they enter the feeder to being emptied into the reactor (Digman, Joo, & Kim, 2009; Nieminen & Folke, 1982). The impact of unintentional heating on this highly variable feedstock may result in particle morphology modification, surface texture transformation, and the evolution of viscous compounds and may contribute to screw feeder plugging (Haas, Nimlos, & Donohoe, 2009; Ingram et al., 2008). We hypothesized that particles of various anatomical fractions (including needles, branches, bark, cambium, and whitewood) will experience dramatic changes during this heating regime, which will be characterized by decreased particle size, increased surface roughness, degradation of key structural macromolecules, and generation of viscous compounds that would result in increased particle friction and cohesion, contributing to screw feeder plugging.

biofuels↗
DOE OSTI2023

LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows

Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1985

Exploring results of the possibility on detecting cosmic ray particles by acoustic way

It has been demonstrated experimentally and theoretically that high energy particles produce detectable sounds in water. However, no one has been able to detect an acoustic signal generated by a high energy cosmic ray particle in water. Results show that transient ultrasonic signals in a large lake or reservoir are fairly complex and that the transient signals under water may arise mainly from sound radiation from microbubbles. This field is not explored in detail. Perhaps, the sounds created by cosmic ray particles hide in these ultrasonic signals. In order to develop the technique of acoustic detection, it is most important to make a thorough investigation of these ultrasonic signals in water.

Jiang, Y.↗
DOE OSTI2025

Testing strong-field QED with the avalanche precursor

A two-beam high-power laser facility is essential for the study of one of the most captivating phenomena predicted by strong-field quantum electrodynamics (QED) and yet unobserved experimentally: the avalanche-type cascade. In such a cascade, the energy of intense laser light can be efficiently transformed into high-energy radiation and electron–positron pairs. The future 50-petawatt-scale laser facility NSF OPAL will provide unique opportunities for studying such strong-field QED effects, as it is designed to deliver two ultra-intense, tightly focused laser pulses onto the interaction point. In this work, we investigate the potential of such a facility for studying elementary particle and plasma dynamics deeply in the quantum radiation-dominated (RD) regime, and the generation of QED avalanches. With three-dimensional particle-in-cell simulations, we demonstrate that QED avalanche precursors can be reliably triggered under realistic laser parameters and layout (namely, focusing f/2, tilted optical axes, and non-ideal co-pointing) with the anticipated capabilities of NSF OPAL. We demonstrate that seed electrons can be efficiently injected into the laser focus by using targets of three types: a gas of heavy atoms, an overcritical plasma, and a thin foil. A strong positron and high-energy photon signal is generated in all cases. The cascade properties can be identified from the final particle distributions, which have a clear directional pattern. At increasing laser field intensity, such distributions provide signatures of the transition, first, to the RD interaction regime, and then to a QED avalanche. Our findings can also be used for designing related future experiments.

Lasers↗
DOE OSTI2026

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗
DOE OSTI2025

Directed flow from parton spin-orbit coupling in $pp$ and $pA$ collisions

We point out a novel mechanism to generate cos φ two-particle azimuthal correlation (‘directed flow’) in unpolarized proton-proton and proton-nucleus collisions in the forward rapidity region of the projectile proton. This is a direct consequence of the recently discovered strong spin-orbit coupling in gluons at small-x. The observable simultaneously serves as a unique probe into the double helicity parton distribution functions of the proton.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Simulation of the radiological impact during selected space travel scenarios using the Monte Carlo code FLUKA

Radiation is one of the major challenges of space exploration and can negatively impact both biological and electronic systems, particularly in the case of long-term journeys or if the spaceship features inadequate shielding. Here, in this work, the cumulative dose levels from prompt radiation in the spacecraft are quantified alongside the residual dose contributions arising from activation of vessel components. The radiological impact was assessed for various space exploration scenarios, considering the same spaceship model featuring three shielding design variants. In each scenario, the radiation environment was generated with the Monte Carlo particle transport and interaction code FLUKA. These results can be used to quantify the contribution of prompt and residual dose in spacefaring ventures and help determine optimal radiation shielding needed to mitigate the overall radiological impact on both astronauts and equipment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Advancing the physics basis for quasi-helically symmetric stellarators

A new optimized quasi-helically symmetric configuration is described that has the desirable properties of improved energetic particle confinement, reduced turbulent transport by three-dimensional shaping and non-resonant divertor capabilities. The configuration presented in this paper is explicitly optimized for quasi-helical symmetry, energetic particle confinement, neoclassical confinement and stability near the axis. Post optimization, the configuration was evaluated for its performance with regard to energetic particle transport, ideal magnetohydrodynamic stability at various values of plasma pressure and ion temperature gradient instability induced turbulent transport. The effects of discrete coils on various confinement figures of merit, including energetic particle confinement, are determined by generating single-filament coils for the configuration. Preliminary divertor analysis shows that coils can be created that do not interfere with expansion of the vessel volume near the regions of outgoing heat flux, thus demonstrating the possibility of operating a non-resonant divertor.

Physics↗
DOE OSTI2025

Density Functional Tight Binding Insights into Plasmonic Silver–Platinum Nanoparticles and Alloys for Enhanced Photocatalysis

Developing accurate and efficient Slater-Koster (SK) tight-binding parameter sets is essential for quantum plasmonic studies of alloyed metal nanoparticles, as conventional time dependent density functional theory (TD-DFT) calculations are computationally prohibitive for larger clusters. In this work, we develop and validate density functional tight binding (DFTB) parameter sets for both ground state (GS-SK) and excited state (ES-SK) calculations to study the structural, electronic, and optical properties of silver (Ag), platinum (Pt), and Ag–Pt nanoalloys. Our investigation of the ground state properties demonstrates that the GS-SK parameters enable DFTB to closely reproduce the electronic structures of platinum clusters with diverse sizes and geometries – showing qualitative agreement with DFT for density of states (DOS) profiles and energy levels. The ES-SK parameters accurately describe excited-state properties compared to TD-DFT reference calculations, including the broad, featureless absorption profiles of Pt that are dominated by interband transitions. Using the ES-SK parameters within a real-time TD-DFTB framework, we compute size-dependent optical absorption spectra of Ag, Pt and Ag-Pt nanocubes containing up to 1099 atoms (size ∼4.18 nm). A detailed study of Ag–Pt and Pt-Ag core–shell nanoparticles shows quenching of the Ag plasmon resonance even at monolayer coverage for Ag-Pt, but not for Pt-Ag. We also show how to define submonolayer Ag-core Pt-shell cubic structures that have similar optical properties to those generated experimentally for much larger particles, which offers potential for describing plasmon-enhanced photocatalysis. Collectively, the GS-SK and ES-SK parameter sets provide an accurate, computationally efficient approach for modeling the complex optical and electronic behavior of noble–transition metal nanostructures and their alloys.

SPR↗
DOE OSTI2024

Physics-constrained machine learning for electrodynamics without gauge ambiguity based on Fourier transformed Maxwell’s equations

We utilize a Fourier transformation-based representation of Maxwell’s equations to develop physics-constrained neural networks for electrodynamics without gauge ambiguity, which we label the Fourier–Helmholtz–Maxwell neural operator method. In this approach, both of Gauss’s laws and Faraday’s law are built in as hard constraints, as well as the longitudinal component of Ampère–Maxwell in Fourier space, assuming the continuity equation. An encoder–decoder network acts as a solution operator for the transverse components of the Fourier transformed vector potential, $\hat{A}_⟂(k,t)$, whose two degrees of freedom are used to predict the electromagnetic fields. This method was tested on two electron beam simulations. Among the models investigated, it was found that a U-Net architecture exhibited the best performance as it trained quicker, was more accurate and generalized better than the other architectures examined. We demonstrate that our approach is useful for solving Maxwell’s equations for the electromagnetic fields generated by intense relativistic charged particle beams and that it generalizes well to unseen test data, while being orders of magnitude quicker than conventional simulations. We show that the model can be re-trained to make highly accurate predictions in as few as 20 epochs on a previously unseen data set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Operator learning for predicting multiscale bubble growth dynamics

We report simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investigated systematically by deep neural networks (DNNs). Herein, we develop a framework based on operator regression, the so-called deep operator network (DeepONet), with the long-term objective to simplify multiscale modeling by avoiding the fragile and time-consuming “hand-shaking” interface algorithms for stitching together heterogeneous descriptions of multiscale phenomena. To this end, as a first step, we investigate if a DeepONet can learn the dynamics of different scale regimes, one at the deterministic macroscale and the other at the stochastic microscale regime with inherent thermal fluctuations. Specifically, we test the effectiveness and accuracy of the DeepONet in predicting multirate bubble growth dynamics, which is described by a Rayleigh–Plesset (R–P) equation at the macroscale and modeled as a stochastic nucleation and cavitation process at the microscale by dissipative particle dynamics (DPD). First, we generate data using the R–P equation for multirate bubble growth dynamics caused by randomly time-varying liquid pressures drawn from Gaussian random fields (GRFs). Our results show that properly trained DeepONets can accurately predict the macroscale bubble growth dynamics and can outperform long short-term memory networks. We also demonstrate that the DeepONet can extrapolate accurately outside the input distribution using only very few new measurements. Subsequently, we train the DeepONet with DPD data corresponding to stochastic bubble growth dynamics. Although the DPD data are noisy and we only collect sparse data points on the trajectories, the trained DeepONet model is able to predict accurately the mean bubble dynamics for time-varying GRF pressures. Taken together, our findings demonstrate that DeepONets can be employed to unify the macroscale and microscale models of the multirate bubble growth problem, hence providing new insight into the role of operator regression via DNNs in tackling realistic multiscale problems and in simplifying modeling with heterogeneous descriptions.

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

Shock-driven dispersal of a corrugated finite-thickness particle layer

A research area emerging in the multiphase flow community is the study of shock-driven multiphase instability (SDMI), a gas–particle analog of the traditional fluid-fluid Richtmyer–Meshkov instability (RMI). In this work, we study the interaction of planar air shocks with corrugated glass particle curtains through the use of numerical simulations with an Eulerian–Lagrangian approach. One objective of this study is to compare the simulated particle curtains to a comparable set of shock tube experiments performed to analyze traditional RMI of a gas curtain. The simulations are set to match the experimental shock Mach numbers and perturbation wavelengths (3.6 and 7.2 mm) while also matching the Atwood number of the experiments to the multiphase Atwood number of the simulations. Varying particle diameters are tested in the simulations to explore the impact of particle diameter on the evolution of the particle curtain. This simulation setup allows for a one-to-one comparison between RMI and SDMI under comparable conditions while also allowing for a separate study into the validity of the use of the multiphase Atwood number to compare the single-phase and multiphase instabilities. In particular, we show that the comparison depends on the diameter of the particles (thus, dependent on the Stokes number of the flow). A second objective of this study is to analyze the effect of the initial particle volume fraction on the evolution of the curtain and the behavior of the instability. This is done through analyzing the effect of the multiphase terms of the vorticity evolution equation on the vorticity deposition in SDMI. Also discussed is the effect of the particle diameter on the multiphase generation terms as well as in the baroclinic vorticity generation term in SDMI as the shock passes over the curtain.

42 ENGINEERING↗
DOE OSTI2026

Nozzle geometry optimization for high-current aluminum ion beam acceleration via direct plasma injection scheme

We report the generation of a record aluminum ion beam current exceeding 58 mA at the Al 11+ charge state, accelerated to an energy of 5.5 MeV using the direct plasma injection scheme, which integrates a laser ion source (LIS) with a radio frequency quadrupole (RFQ) accelerator. The effect of nozzle geometry on beam extraction was systematically investigated using 8 and 12 mm tapered designs and an 18 mm cylindrical configuration. The 18 mm nozzle achieved the highest Al 11+ beam current, while the 12 mm aperture provided a favorable balance between beam intensity and current density. Beam extraction simulations confirmed effective RFQ matching across multiple charge states, and solenoidal field tuning further enhanced plasma collimation. This work not only establishes a new benchmark for high-current ion beam generation but also provides a fundamental understanding of plasma–beam interface dynamics crucial for the next generation of high-intensity particle accelerators, particularly those employing LIS-RFQ systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗