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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Search for heavy diboson resonances in semileptonic final states in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper reports on a search for heavy resonances decaying into WW , ZZ or WZ using proton–proton collision data at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. The data, corresponding to an integrated luminosity of 139 fb -1 , were recorded with the ATLAS detector from 2015 to 2018 at the Large Hadron Collider. The search is performed for final states in which one W or Z boson decays leptonically, and the other W boson or Z boson decays hadronically. The data are found to be described well by expected backgrounds. Upper bounds on the production cross sections of heavy scalar, vector or tensor resonances are derived in the mass range 300–5000 GeV within the context of Standard Model extensions with warped extra dimensions or including a heavy vector triplet. Production through gluon–gluon fusion, Drell–Yan or vector-boson fusion are considered, depending on the assumed model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Quantifying the Temperature Dependence of the Multi-Species, Multi-Reaction Model: Part II. Estimation of Entropy Coefficient for Meso-Carbon Micro-Bead Graphite

In Part 1 of this paper, the temperature impact on the Multi-Species, Multi Reaction (MSMR) model was studied. This was accomplished by acquiring data from slow rate lithiation and delithiation of a meso-carbon micro-bead (MCMB) graphite. Through this analysis, the temperature impact on the total fraction of available host sites in a particular MSMR gallery (X j ), the impact on the reference potential (U$^o_j$), and the impact on the parameter detailing the deviation from Nernstian behavior (ω j ) was determined. Here, the intercalation material is discussed, compared to traditional methods of acquiring the entropy coefficient, and comparison is made to previous mathematical estimates. Some of the challenges in using temperature dependent constant rate charge and discharge data as compared to the potentiodynamic entropy coefficient calculation method are also discussed, and a recommendation for future applications is proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Generalized parton distributions from symbolic regression

AI/ML informed Symbolic Regression is the next stage of scientific modeling. We utilize a highly customizable symbolic regression package “PySR” to model the x and t dependence of the flavor isovector combination Hu-d(x, t, ) at = 0. These PySR models were trained on GPD results provided by both Lattice QCD and phenomenological sources GGL, GK, and VGG. We demonstrate, for the first time, the consistency and systematic convergence of Symbolic Regression by quantifying the disparate models through their Taylor expansion coefficients. In addition to PySR penalizing models with higher complexity and mean-squared error, we implement schemes that test specific physics hypotheses, including force-factorized x and t dependence and Regge behavior in PySR GPDs. We show that PySR can identify factorizing GPD sources based on their response to the Force-Factorized model. Here, knowing the precise behavior of the GPDs, and their uncertainties in a wide range in x and t, crucially impacts our ability to concretely and quantitatively predict hadronic spatial distributions and their derived quantities.

Dotson, Andrew [New Mexico State University, Las C↗
DOE OSTI2025

Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning

We propose a deep learning model, WaveCastNet, to forecast high-dimensional wavefields. WaveCastNet integrates a convolutional long expressive memory architecture into a sequence-to-sequence forecasting framework, enabling it to model long-term dependencies and multiscale patterns in both space and time. By sharing weights across spatial and temporal dimensions, WaveCastNet requires significantly fewer parameters than more resource-intensive models such as transformers, resulting in faster inference times. Crucially, WaveCastNet also generalizes better than transformers to rare and critical seismic scenarios, such as high-magnitude earthquakes. Here, we show the ability of the model to predict the intensity and timing of destructive ground motions in real time, using simulated data from the San Francisco Bay Area. Furthermore, we demonstrate its zero-shot capabilities by evaluating WaveCastNet on real earthquake data. Our approach does not require estimating earthquake magnitudes and epicenters, steps that are prone to error in conventional methods, nor does it rely on empirical ground-motion models, which often fail to capture strongly heterogeneous wave propagation effects.

Geophysics↗
DOE OSTI2021

Phase-field model of precipitation processes with coherency loss

A phase-field model is proposed to simulate coherency loss coupled with microstructure evolution. A special field variable is employed to describe the degree of coherency loss of each particle and its evolution is governed by a Ginzburg-Landau type kinetic equation. For the sake of computational efficiency, a flood-fill algorithm is introduced that can drastically reduce the required number of field variables, which allows the model to efficiently simulate a large number of particles sufficient for characterizing their statistical features during Ostwald ripening. The model can incorporate size dependence of coherency loss, metastability of coherent particles, and effectively incorporate the underlying mechanisms of coherency loss by introducing a so-called differential energy criterion. The model is applied to simulate coarsening of Al 3 Sc precipitates in aluminum alloy and comprehensively compared with experiments. Our results clearly show how the particle size distribution is changed during coherency loss and affects the coarsening rate.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigating laser ablated plume dynamics of carbon and aluminum targets

Recently acquired high-resolution images of nanosecond laser ablation plumes suggest a strong correlation between the internal plume structure and the type of material being ablated. However, the details of this relation are currently not well understood. In this work, we attempt to explore this correlation using a 2D radiation hydrodynamics model to study the dependence of internal plume structure formation on the ablation material. Here spatio-temporal emission maps and plume expansion velocities from experimental measurements are compared with the model predictions, including synthetic emission maps. The shape and expansion rate of an outer air plume region are found to be in good agreement for both carbon and aluminum, as are the inner material plume dynamics for carbon ablation. The largest disagreement is observed in the case of a polished aluminum target, where the chaotic inner plume features seen in the experimental images are not observed in the model. The possible physical mechanisms responsible for this discrepancy are discussed. This effort constitutes a continued development toward a predictive model of ablation plume dynamics and chemistry for various materials in extreme environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Dynamic pulse propagation modelling for predictive femtosecond-laser-microbonding of transparent materials

A dynamic pulse propagation modeling for femtosecond laser bonding of Borofloat glass is presented. The temperature evolution and internal modifications are predicted by incorporating the nonlinear electron dynamics along with temperature dependent thermal properties. The modelling predicts the spatial and temporal distribution of absorption coefficient and plasma density that gives quantitative estimations of the heat affected zone and weld geometry. The impact of focusing condition on heat affected zone and weld geometry is investigated, which for the first time to our knowledge allows to numerically determine the desired relative position between the geometrical focus of a femtosecond-laser-pulse and the interface of the two substrates to be welded. The prediction of the modelling on the offset distance is applied to weld Borofloat glass plates having optical contact and can be applied to other dielectric solids.

Sahoo, Pankaj K. (ORCID:0000000209437319)↗
DOE OSTI2025

Differential Seismic Phase Detection Probability as a Potential Discriminant of Explosions and Earthquakes

Deep learning models trained to estimate the probability of seismic P and S phases are rapidly expanding the scale of local event detections. Here, we evaluate the potential for deep learning model output phase detection probabilities to contribute to event‐type classification, particularly discrimination of single‐fired borehole explosions and earthquakes at local distances (<300 km). Motivated by the empirical success of P/S amplitude ratios, we consider the difference between P and S pick probability output from previously developed phase detection models, P prob −S prob ⁠, as a discriminant. Test data include M L ∼1–4 earthquakes and explosions observed by common seismographs in ten geologically diverse localities. Depending on the picking model and training data, binary classification using P prob −S prob with at least three stations can achieve approximately equivalent classification accuracy as P/S amplitude ratios without requiring any customization. Joint classification with P/S and P prob −S prob improves accuracy for most quality control scenarios. Pick probabilities are an efficient attribute to consider in explosion discrimination because they can be automated byproducts of event detection. They avoid the binary choice of picking or not picking weakly visible S waves common to explosions.

Duan, Chenglong [Rice Univ., Houston, TX (United S↗
DOE OSTI2024

A non-isothermal breakage-damage model for plastic-bonded granular materials incorporating temperature, pressure, and rate dependencies

Plastic-bonded granular materials (PBM) are widely used in industrial sectors, including building construction, abrasive applications, and defense applications such as plastic-bonded explosives. The mechanical behavior of PBM is highly nonlinear, irreversible, rate dependent, and temperature sensitive governed by various micromechanical attributions such as grain crushing and binder damage. This paper presents a thermodynamically consistent, microstructure-informed constitutive model to capture these characteristic behaviors of PBM. Key features of the model include a breakage internal variable to upscale the grain-scale information to the continuum level and to predict grain size evolution under mechanical loading. In addition, a damage internal state variable is introduced to account for the damage, deterioration, and debonding of the binder matrix upon loading. Temperature is taken as a fundamental external state variable to handle non-isothermal loading paths. The proposed model is able to capture with good accuracy several important aspects of the mechanical properties of PBM, such as pressure-dependent elasticity, pressure-dependent yield strength, brittle-to-ductile transition, temperature dependency, and rate dependency in the post-yielding regime. Furthermore, the model is validated against multiple published datasets obtained from confined and unconfined compression tests, covering various PBM compositions, confining pressures, temperatures, and strain rates.

Breakage↗
DOE OSTI2025

Impact of Time Dependent Reactor and Sensor Physics on Core Power Synthesis

Online synthesis of the power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins, and to provide essential knowledge associated with the burnup of the fuel. In light water reactors (LWRs), power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report aims to study the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a LWR. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative pressurized water reactor low-enriched uranium (LEU) core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used, as well, to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative (PBI) method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly under- or over-approximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumption leads to severe levels of error, approaching 25% at maximum. The authors also discovered that V SPNDs are extraordinarily robust in the low-enriched uranium fuel cycle considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Pseudo-rapidity distributions of charged particles in asymmetric collisions using Tsallis thermodynamics

Abstract The pseudo-rapidity distributions of the charged particles produced in the asymmetric collision systems p+Al, p+Au and$$^3$$ 3 He+Au at$$\sqrt{s_\text {NN}} = 200$$ s NN = 200 GeV are evaluated in the framework of a fireball model with Tsallis thermodynamics. The fireball model assumes that the experimentally measured particles are produced by fireballs following the Tsallis distribution and it can effectively describe the experimental data. Our results as well as previous results for d+Au collisions at$$\sqrt{s_\text {NN}} = 200$$ s NN = 200 GeV and p+Pb collisions at$$\sqrt{s_\text {NN}} = 5.02$$ s NN = 5.02 TeV validate that the fireball model based on Tsallis thermodynamics can provide a universal framework for pseudo-rapidity distribution of the charged particles produced in asymmetric collision systems. We predict the centrality dependence of the total charged particle multiplicity in the p+Al, p+Au and$$^3$$ 3 He+Au collisions. Additionally, the dependences of the fireball model parameters ($$y_{0a}$$ y 0 a ,$$y_{0A}$$ y 0 A ,$$\sigma _{a}$$ σ a and$$\sigma _{A}$$ σ A ) on the centrality and system size are studied.

Nuclear Science & Technology↗
DOE OSTI2020

Size effect in stainless steel thin wires under tension

Miniaturization of modern devices drives the exploration into how materials behave in small dimensions. However, the mechanical behaviors of micro-scale specimens under varied loading conditions are still challenging to characterize and predict. In this work, specimen size-dependent weakening effect was experimentally revealed in 316L stainless steel thin wires under tension with wire diameter decreasing from 200 μm down to 61 μm. The underlying mechanisms were primarily associated with surface grain softening and strain localization, which were largely dependent on the number of grains across wire diameter. Through an analog composite model with surface and interior grains that follows the Hall-Petch relation, the extent of surface grain softening was found to coincide with the flow stress reduction due to lack of boundary strengthening. Further using elasto-plastic self-consistent polycrystal modeling, the stress-strain behaviors of interior and surface grains were well described in analogy to those of bulk materials with similar-size grains and extremely large grains, respectively. Subsequently, the analog composite model well simulated the specimen size-dependent weakening effect under tension. This article provided more insights into the size effect exploration and proposed a practical model for describing size-dependent mechanical behaviors of small-scale materials to be applied to miniaturized devices.

316L stainless steel↗
DOE OSTI2021

Deciphering Time-Dependent DNA Damage Complexity, Repair, and Oxygen Tension: A Mechanistic Model for FLASH-Dose-Rate Radiation Therapy

Irradiation with ultrahigh dose rates (FLASH) has reemerged as a promising radiation therapy approach to effectively lower potential damage burden on normal tissue without sacrificing tumor control. However, the large number of recent FLASH studies have been conducted under vastly different experimental conditions and circumstances (ie, investigated biological endpoint, radiation quality, and environmental oxygen level), with unverified biological mechanisms of action and unexplored interplay effect of the main dependencies. To facilitate radiobiological investigation of FLASH phenomena and assessment of clinical applicability, we present an extension of the mechanistic radiobiological model “UNified and VERSatile bio response Engine” (UNIVERSE).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

A quantitative comparison between velocity dependent SIDM cross-sections constrained by the gravothermal and isothermal models

One necessary step for probing the nature of self-interacting dark matter (SIDM) particles with astrophysical observations is to pin down any possible velocity dependence in the SIDM cross-section. Major challenges for achieving this goal include eliminating, or mitigating, the impact of the baryonic components and tidal effects within the dark matter halos of interest – the effects of these processes can be highly degenerate with those of dark matter self-interactions at small scales. In this work, we select 9 isolated galaxies and brightest cluster galaxies (BCGs) with baryonic components small enough such that the baryonic gravitational potentials do not significantly influence the halo gravothermal evolution processes. We then constrain the parameters of Rutherford and Møller scattering cross-section models with the measured rotation curves and stellar kinematics through the gravothermal fluid formalism and isothermal method. Cross-sections constrained by the two methods are consistent at $1\sigma$ confidence level, but the isothermal method prefers cross-sections greater than the gravothermal approach constraints by a factor of ~ 3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Deep glassy state dynamic data challenge glass models: Configurational entropy models

This work was the result of the student's (Dongjie Chen) qualifying exam response. In it the experimental observation from our labs that the relaxation times of ultrastable glasses (a 20 million year old amber and a vapor deposited amorphous teflon) do not follow the expected Vogel-Fulcher or WLF types of divergence as the temperatures fall below the glass transition temperature. In the work we evaluated several theories by considering them in different ways. We used them as generally used and show that they do not capture the non-diverging behavior. Because the models were all entropy-based models, we also considered the possibility that the temperature dependence of the entropy used in the models is incorrect and chose two ways of estimating the entropy that do not follow the classical theoretical models. First we used the actually measured calorimetric response for the two ultrastable glasses, and we used the Milchev model, which does not go to zero above 0 Kelvin. Both of these approaches led to improved agreement between the theories and the experimental data. Finally, we also asked what the temperature dependence of the entropy would have to be so that the models agreed with the observed data. In some cases the entropy so-calculated was reasonable, while in others it was unphysical. In sum, the important point of the work is that the observation of non-diverging time-scales that suggest that there is no ideal glass transition can be reasonably captured by current theories if they take more realistic models of the entropy than is usually the case.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease

Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, setting, an participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main outcomes and measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Embedding condition describing shearing, dissipative collapse

Highlights: • Perturbative approach to the time-dependent Karmarkar condition in shearing collapse. • Analysis of the (in)stability of the collapsing fluid using the TOV equation. • Study of the temperature profiles using a causal heat transport equation. In this work we employ the time-dependent Karmarkar condition to model dissipative gravitational collapse in the presence of shear which leads to a final static configuration. We believe that this is a first attempt at using the time-dependent Karmarkar condition describing a radiating star with shear in which the collapsing core dissipates energy in the form of a radial heat flux. The final static configuration which is described by an embedding class I spacetime was obtained by Hansraj and Moodly who showed that this solution satisfies all the physical requirements for a static compact object. As the collapse proceeds and the heat flux tends to zero the dynamical core evolves into a static compact core with the exterior spacetime being described by the vacuum Schwarzschild solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Error Characteristics and Scale Dependence of Current Satellite Precipitation Estimates Products in Hydrological Modeling

Satellite precipitation estimates (SPEs) are promising alternatives to gauge observations for hydrological applications (e.g., streamflow simulation), especially in remote areas with sparse observation networks. However, the existing SPEs products are still biased due to imperfections in retrieval algorithms, data sources and post-processing, which makes the effective use of SPEs a challenge, especially at different spatial and temporal scales. In this study, we used a distributed hydrological model to evaluate the simulated discharge from eight quasi-global SPEs at different spatial scales and explored their potential scale effects of SPEs on a cascade of basins ranging from approximately 100 to 130,000 km 2 . The results indicate that, regardless of the difference in the accuracy of various SPEs, there is indeed a scale effect in their application in discharge simulation. Specifically, when the catchment area is larger than 20,000 km2, the overall performance of discharge simulation emerges an ascending trend with the increase of catchment area due to the river routing and spatial averaging. Whereas below 20,000 km 2 , the discharge simulation capability of the SPEs is more randomized and relies heavily on local precipitation accuracy. Our study also highlights the need to evaluate SPEs or other precipitation products (e.g., merge product or reanalysis data) not only at the limited station scale, but also at a finer scale depending on the practical application requirements. Here we have verified that the existing SPEs are scale-dependent in hydrological simulation, and they are not enough to be directly used in very fine scale distributed hydrological simulations (e.g., flash flood). More advanced retrieval algorithms, data sources and bias correction methods are needed to further improve the overall quality of SPEs.

DTVGM↗