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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Helium diffusion in the sun

We calculate improved standard solar models using the new Livermore (OPAL) opacity tables, an accurate (exportable) nuclear energy generation routine which takes account of recent measurements and analyses, and the recent Anders-Grevesse determination of heavy element abundances. We also evaluate directly the effect of the diffusion of helium with respect to hydrogen on the calculated neutrino fluxes, on the primordial solar helium abundance, and on the depth of the convective zone. Helium diffusion increases the predicted event rates by about 0.8 SNU, or 11 percent of the total rate, in the chlorine solar neutrino experiment, by about 3.5 SNU, or 3 percent, in the gallium solar neutrino experiments, and by about 12 percent in the Kamiokande and SNO solar neutrino experiments. The best standard solar model including helium diffusion and the most accurate nuclear parameters, element abundances, and radiative opacity predicts a value of 8.0 SNU +/- 3.0 SNU for the C1-37 experiment and 132 +21/-17 SNU for the Ga - 71 experiment, where the uncertainties include 3 sigma errors for all measured input parameters.

Bahcall, J. N.↗
DOE OSTI2025

Diffusion behavior of lanthanide fission products in bcc Fe cladding: A first-principles study

Fuel-cladding chemical interaction poses significant challenges in nuclear reactors, where fission products generated from nuclear fuel interact with Fe-based cladding materials, potentially compromising their structural integrity. This study investigates the diffusion behavior of lanthanide fission products, Lanthanum (La), Cerium (Ce), Praseodymium (Pr), and Neodymium (Nd), within body-centered cubic (bcc) Fe cladding using the density functional theory, nudged elastic band method, and self-consistent mean field theory. Our results reveal significant vacancy binding energies, particularly with the 1st and 2nd nearest neighbors, which diminish beyond the 5th nearest neighbor, with La exhibiting the strongest binding affinity, followed by Nd, Ce, and Pr. The nudged elastic band calculations indicate significant high barriers for the dissociation of 1st nearest neighbor vacancy-solute pairs for all fission products. The tracer diffusion coefficients of these fission products were derived in an Arrhenius form, with a magnetic correction that accounts for the high-temperature paramagnetic state. The significant trapping effect of vacancies caused by a very dilute concentration of fission products reduces vacancy mobility, potentially leading to modifications in point defect supersaturation, void nucleation, and swelling under irradiation. These represent critical challenges for irradiated cladding materials. The tracer diffusion coefficients indicate that Nd diffuses the fastest, followed by La, Ce, and Pr. Furthermore, this study provides essential insights for understanding fission product transport in cladding materials and informs future design strategies to mitigate fuel-cladding chemical interaction, ultimately enhancing nuclear reactor safety and performance.

Diffusion↗
DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗
NASA NTRS1983

Numerical experiments with a stochastic zonal climate model

A zonally averaged energy balance climate model is developed to generate zonal temperature variability through fluctuating meridional energy transports. Stochastic transport fluctuations are included in the model by multiplying the eddy diffusion coefficients by Gaussian random deviates. For a variability of eddy coefficients of 50 percent, the model is found to generate an interannual temperature variability of 0.03 K for the global temperature, and 0.04 and 0.05 K for the Northern and Southern Hemispheres, respectively. It is shown that the temperature variability level generated is linearly related to the transport variability level introduced. An increase in the level of model-generated temperature variability and a change in the shape of variance spectra of temperature anomaly time series are obtained by switching from the multiplicative noise model to an additive noise model. The results of these model studies are compared with a time series of central England temperatures as well as GCM generated climate variability.

Schneider, S. H.↗
DOE OSTI2024

Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments

Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), variational autoencoders, and normalizing flows, have been widely used and studied as efficient alternatives for traditional scientific simulations. However, they have several drawbacks, including training instability and inability to cover the entire data distribution, especially for regions where data are rare. This is particularly challenging for whole-event, full-detector simulations in high-energy heavy-ion experiments, such as sPHENIX at the Relativistic Heavy Ion Collider and Large Hadron Collider experiments, where thousands of particles are produced per event and interact with the detector. This work investigates the effectiveness of denoising diffusion probabilistic models (DDPMs) as an AI-based generative surrogate model for the sPHENIX experiment that includes the heavy-ion event generation and response of the entire calorimeter stack. DDPM performance in sPHENIX simulation data is compared with a popular rival, GANs. Results show that both DDPMs and GANs can reproduce the data distribution where the examples are abundant (low-to-medium calorimeter energies). Nonetheless, DDPMs significantly outperform GANs, especially in high-energy regions where data are rare. Additionally, DDPMs exhibit superior stability compared to GANs. The results are consistent between both central and peripheral centrality heavy-ion collision events. Moreover, DDPMs offer a substantial speedup of approximately a factor of 100 compared to the traditional Geant4 simulation method.

42 ENGINEERING↗
NASA NTRS1978

Use of coherence and phase data between two receivers in evaluation of noise environments

For certain types of noise control problems, where transducers cannot be mounted on suspected sources, valuable information can often be obtained by comparing the coherence and phase data measured between two closely spaced microphones with analytical models deduced from the physics of the problem. However, the application of such analysis techniques must be pursued with care, particularly when the measurements are made in a reverberant area. A simple illustration is presented where the acoustic field in the test section of a wind tunnel is evaluated by modelling the field as a combination of diffuse noise due to the boundary layer turbulence in the test section and propagating noise generated by the tunnel fan and possible flow disturbances outside the test section. The coherence and phase between two closely spaced microphones in the tunnel test section are predicted for various ratios of diffuse to propagating noise contributions and compared to actual measurements under several different tunnel operating conditions.

Piersol, A. G.↗
DOE OSTI2025

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗
DOE OSTI2025

Measurement of Zero-Frequency Fluctuations Generated by Coupling between Alfvén Modes in the JET Tokamak

We report the first experimental detection of a zero-frequency fluctuation that is pumped by an Alfvén mode in a magnetically confined plasma. Core-localized Alfvén modes of frequency inside the toroidicity-induced gap (and its harmonics) exhibit three-wave coupling interactions with a zero-frequency fluctuation. The observation of the zero-frequency fluctuation is consistent with theoretical and numerical predictions of zonal modes pumped by Alfvén modes, and is correlated with an increase in the deep core ion temperature, temperature gradient, confinement factor H 89,P , and a reduction in the main ion heat diffusivity. Despite the energetic particle transport induced by the Alfvén eigenmodes, the generation of a zero-frequency fluctuation that can suppress the turbulence leads to an overall improvement of confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1998

The Origin and Time Dependence of the Amount and Composition of Non-Constituent Gases Present in Crystal Growth Systems

Presence of different, non-constituent gases may be a critical factor in crystal growth systems. In Physical Vapor Transport processes the cras(es) can be used intentionally (to prevent excessively high, unstable growth conditions), or can evolve unintentionally during the course of the process (which may lead to undesired reduction in the -rowth rate). In melt growth, particularly under low gravity conditions (reduced hydrostatic pressure) the gas present in the system may contribute to formation of voids in the growing crystals and even to a separation of the crystal and the liquid phase [1]. On the other hand, some amount of gas may facilitate 'contactless' crystal growth particularly under reduced gravity conditions [2 - 6]. Different non-constituent gases may be present in growth ampoules, and their amount and composition may change during the crystallization process. Some gases can appear even in empty ampoules sealed originally under high vacuum: they may diffuse in from the outside, and/or desorb from the ampoule walls. Residual gases can also be generated by the source materials: even very high purity commercial elements and compounds may contain trace amounts of impurities, particularly oxides. The oxides may have low volatilities themselves but their reaction with other species, particularly carbon and hydrogen, may produce volatile compounds like water or carbon oxides. The non-constituent gases, either added initially to the system or evolved during the material processing, may diffuse out of the ampoule during the course of the experiment. Gases present outside (e.g. as a protective atmosphere or thermal conductor) may diffuse into the ampoule. In either case the growth conditions and the quality of the crystals may be affected. The problem is of a particular importance in sealed systems where the amount of the gases cannot be directly controlled. Therefore a reasonable knowledge and understanding of the origin, composition, magnitude, and change with time of gases present in sealed ampoules may be important for a meaningful control and interpretation of crystal growth processes. This problem is of a particular importance for processing of electronic materials in space because (i) safety considerations require using sealed systems only, and (ii) high cost of crystal growth experiments in microgravity calls for a throughout, accurate description of the processing conditions necessary for a meaningful, efficient, and conclusive interpretation of the space results. In this paper we present the results of our extensive studies on gases in closed crystal growth systems which include: (a) Degassing properties of fused silica; (b) Generation of inert gases by source materials (CdTe, ZnTe, CdZnTe, ZnSe, PbTe, PbSe, PbSeTe); (c) Diffusive cas losses from silica glass ampoules.

Palosz, Witold↗
NASA NTRS2023

Oxidation of Silicon Particles Suspended in Mullite Matrix With Dual-Mode Vacancy Diffusion of Oxygen

Mullite bond coats filled with silicon particles have recently been proposed for the next generation of environmental barrier coatings (EBCs). The sacrificial oxidation of the silicon particles eliminates some of the environmental durability issues associated with traditional EBC designs. To investigate this novel design approach, a mathematical formulation and resulting numerical method have been developed for simulating the oxidation of silicon particles embedded in a mullite matrix. The focus is on the oxidation of the silicon in a dry oxygen environment where the oxidant is presumably oxygen. Oxygen transport from the exterior environment through the mullite is assumed to occur via two lattice defect diffusion mechanisms. As a result, the rate of oxygen transport is dictated by the self-diffusivity of the lattice defects. The numerical method is implemented using the COMSOL Multiphysics® program (COMSOL, Inc.). The method is applied to simulate the oxidation of silicon particles in a mullite pellet in recent oxidation experiments. Numerical results compare favorably with the oxidation behavior observed in the oxidation experiments. The numerical method is also used to investigate the effects of various features of the mullite-silicon particle system on the oxidation behavior.

silicon oxidation↗
NASA NTRS1999

Low-Frequency Oscillations and Transport Processes Induced by Multiscale Transverse Structures in the Polar Wind Outflow: A Three-Dimensional Simulation

Multiscale transverse structures in the magnetic-field-aligned flows have been frequently observed in the auroral region by FAST and Freja satellites. A number of multiscale processes, such as broadband low-frequency oscillations and various cross-field transport effects are well correlated with these structures. To study these effects, we have used our three-dimensional multifluid model with multiscale transverse inhomogeneities in the initial velocity profile. Self-consistent-frequency mode driven by local transverse gradients in the generation of the low field-aligned ion flow and associated transport processes were simulated. Effects of particle interaction with the self-consistent time-dependent three-dimensional wave potential have been modeled using a distribution of test particles. For typical polar wind conditions it has been found that even large-scale (approximately 50 - 100 km) transverse inhomogeneities in the flow can generate low-frequency oscillations that lead to significant flow modifications, cross-field particle diffusion, and other transport effects. It has also been shown that even small-amplitude (approximately 10 - 20%) short-scale (approximately 10 km) modulations of the original large-scale flow profile significantly increases low-frequency mode generation and associated cross-field transport, not only at the local spatial scales imposed by the modulations but also on global scales. Note that this wave-induced cross-field transport is not included in any of the global numerical models of the ionosphere, ionosphere-thermosphere, or ionosphere-polar wind. The simulation results indicate that the wave-induced cross-field transport not only affects the ion outflow rates but also leads to a significant broadening of particle phase-space distribution and transverse particle diffusion.

Ganguli, Supriya B.↗
NASA NTRS1984

Analysis of the electron-beam-induced current of a polycrystalline p-n junction when the diffusion lengths of the material on either side of a grain boundary differ

The short circuit current generated by the electron beam of a scanning electron microscope in p-n junctions is reduced by enhanced recombination at grain boundaries in polycrystalline material. Frequently, grain boundaries separate the semiconductor into regions possessing different minority carrier life times. This markedly affects the short circuit current I(sc) as a function of scanning distance from the grain boundary. It will be shown theoretically that (1) the minimum of the I(sc) in crossing the grain boundary with the scanning electron beam is shifted away from the grain boundary toward the region with smaller life time (shorter diffusion length), (2) the magnitude of the minimum differs markedly from those calculated under the assumption of equal diffusion lengths on either side of the grain boundary, and (3) the minimum disappears altogether for small surface recombination velocities (s less than 10,000 cm/s). These effects become negligible, however, for large recombination velocities s at grain boundaries. For p-type silicon this happens for s not less than 100,000 cm/s.

Von Roos, O.↗
DOE OSTI2025

High‐Asymmetry Metasurface: A New Solution for Terahertz Resonance via Active Learning‐Augmented Diffusion Model

Terahertz (THz) metamaterials with high‐figure‐of‐merit (high‐FoM) performance resonance are essential for advancing sensors, detectors, and imagers. Conventional designs focus on symmetric or low‐asymmetry geometric structures, leaving high‐asymmetry designs largely unexplored due to the inefficiency of trial‐and‐error‐based rational design. Recent deep learning techniques offer automation and acceleration but are constrained by the need for large datasets inherent to their data‐driven nature. Here, a novel prior knowledge‐guided generative model augmented by a physics‐constrained active learning mechanism to design high‐asymmetry metamaterials. An advanced diffusion model learns features from a small set of classical structures with high‐FoM THz resonance and generates new high‐asymmetry structures. To mitigate the limited number of classical structures, the generated high‐asymmetry structures are actively selected and integrated into the initial training dataset based on their physical characteristics. Experimental results demonstrate the superior resonance performance of the generated high‐asymmetry metamaterials over classical designs, exhibiting improvements exceeding 30% in key resonance metrics. Remarkably, this performance is attained using only 68 classical structures as the initial training dataset, significantly reducing the data requirements for deep learning‐based metamaterial design. The proposed scheme for generating high‐asymmetry structures provides a new effective and efficient solution for high‐FoM resonance, expanding applications in high‐sensitivity THz metadevices.

diffusion model↗
DOE OSTI2024

How does negative triangularity mitigate ITG turbulence and transport?

Improved confinement in negative triangularity (NT) experiments is attributed to reduced fluxes driven by micro-turbulence. The physical mechanism of why thermal confinement improves in NT relative to PT is unknown. This study employs gyrokinetic flux tube simulations using the GENE code with local Miller equilibrium to elucidate the physical mechanisms behind the beneficial effects of NT flux surface shapes. The focus is on collisionless ion temperature gradient (ITG) driven turbulence with adiabatic electrons. The kinetic profiles are held fixed across a scan of triangularity values, thus enabling comparisons on a level playing field. The reduced linear growth rates for NT is shown to be due to a reduced eigenmode averaged magnetic drift frequency and a wider, stronger negative local magnetic shear region about the outboard mid-plane. The nonlinear heat flux is lower for NT than that for PT, due to reduced radial correlation length and increased correlation time (τ c ) of fluctuations. These, in turn, are due to a comparatively higher level of self-generated zero-frequency E × B zonal shearing rate ω E in NT as compared to PT. Though the linear zonal potential residual is lower for NT, the nonlinearly generated E × B zonal shearing rate is higher for NT than for PT. This outcome is linked to the distinctive features of the radial wavenumber spectra of the zonal potential and the zonal shearing rate. The dimensionless parameter ω E τ c is suggested as a figure of merit. This is higher for NT than for PT. Thus, the reduced heat diffusivity for NT is linked to increased ω E τ c . Self-generated temperature corrugations (i.e. zonal temperature gradients) are much weaker than the background mean temperature gradient. Nevertheless, temperature corrugations are more pronounced in NT than in PT.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1992

Nonlinear restrictions on dynamo action

Astrophysical dynamos operate in the limit of small magnetic diffusivity. In order for magnetic reconnection to occur, very small magnetic structures must form so that diffusion becomes effective. The formation of small-scale fields is accompanied by the stretching of the field lines and therefore by an amplification of the magnetic field strength. The back reaction of the magnetic field on the motions leads to the eventual saturation of the dynamo process, thus posing a constraint on the amount of magnetic flux that can be generated by dynamo action, It is argued that in the limit of small diffusivity only a small amount of flux, many orders of magnitude less than the observed fluxes, can be created by dynamo processes.

Vainshtein, Samuel I.↗
NASA NTRS1986

Flow in out-of-plane double S-bonds

Developing flows in two out-of-plane double S-bend configurations have been measured by laser-Doppler anemometry. The first duct had a rectangular cross-section 40mmx40mm at the inlet and consisted of a uniform area 22.5 deg. - 22.5 deg. S-duct upstream with a 22.5 deg.- 22.5 deg. S- diffuser downstream. The second duct had a circular cross-section and consisted of a 45 deg. - 45 deg. uniform area S-duct upstream with a 22.5 deg. -22.5 deg. S-diffuser downstream. In both configurations the ratio of the mean radius of curvature to the inlet hydraulic diameter was 7.0, the exit-to-inlet area ratio of the diffusers was 1.5 and the ducts were connected so that the centerline of the S-duct lay in a plane normal to that of the S-diffuser. Streamwise and cross-stream velocity components were measured in laminar flow for the rectangular duct and in turbulent flow for both configurations; measurements of the turbulence levels, cross-correlations and wall static pressures were also made in the turbulent flow cases. Secondary flows of the first kind are present in the first S-duct and they are complemented or counteracted by the secondary flows generated by the area expansion and by the curvature of the S-diffusers downstream. Cross-stream velocities with magnitudes up to 0.19 and 0.11 of the bulk velocity were measured in the laminar and turbulent flows respectively in the rectangular duct and six cross-flow vortices were evident at the exit of the duct in both flow cases. The turbulent flow in the circular duct was qualitatively similar to that in the rectangular configuration, but the cross-stream velocities measured at the exit plane were smaller in the circular geometry. The results are presented in sufficient detail and accuracy for the assessment of numerical calculation methods and are listed in tabular form for this purpose.

Schmidt, M. C.↗
NASA NTRS1990

Design considerations for Mars photovoltaic power systems

Considerations for operation of a photovoltaic power system on Mars are discussed with reference to Viking Lander data. The average solar insolation at Mars is 590 W/sq m, which is reduced yet further by atmospheric dust. Of major concern are dust storms, which have been observed to occur on local as well as on global scales, and their effect on solar array output. While atmospheric opacity may rise to values ranging from 3 to 9, depending on storm severity, there is still an appreciable large diffuse illumination, even at high opacities, so that photovoltaic operation is still possible. If the power system is to continue to generate power even on high-optical-opacity (i.e., dusty atmosphere) days, it is important that the photovoltaic system be designed to collect diffuse irradiance as well as direct. Energy storage will be required for operation during the night. Temperature and wind provide additional considerations for array design.

Landis, Geoffrey A.↗