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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The NANOGrav nine-year data set: Limits on the isotropic stochastic gravitational wave background

We compute upper limits on the nanohertz-frequency isotropic stochastic gravitational wave background (GWB) using the 9 year data set from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration. Well-tested Bayesian techniques are used to set upper limits on the dimensionless strain amplitude (at a frequency of 1 yr{sup −1}) for a GWB from supermassive black hole binaries of A{sub gw}<1.5×10{sup −15}. We also parameterize the GWB spectrum with a broken power-law model by placing priors on the strain amplitude derived from simulations of Sesana and McWilliams et al. Using Bayesian model selection we find that the data favor a broken power law to a pure power law with odds ratios of 2.2 and 22 to one for the Sesana and McWilliams prior models, respectively. Using the broken power-law analysis we construct posterior distributions on environmental factors that drive the binary to the GW-driven regime including the stellar mass density for stellar-scattering, mass accretion rate for circumbinary disk interaction, and orbital eccentricity for eccentric binaries, marking the first time that the shape of the GWB spectrum has been used to make astrophysical inferences. Returning to a power-law model, we place stringent limits on the energy density of relic GWs, Ω{sub gw}(f)h{sup 2}<4.2 × 10{sup −10}. Our limit on the cosmic string GWB, Ω{sub gw}(f)h{sup 2}<2.2 × 10{sup −10}, translates to a conservative limit on the cosmic string tension with Gμ<3.3×10{sup −8}, a factor of four better than the joint Planck and high-l cosmic microwave background data from other experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Neutrino-driven Winds in Three-dimensional Core-collapse Supernova Simulations

Abstract In this paper, we analyze the neutrino-driven winds that emerge in 12 unprecedentedly long-duration 3D core-collapse supernova simulations done using the code F ornax . The 12 models cover progenitors with zero-age main-sequence mass between 9 and 60 solar masses. In all our models, we see transonic outflows that are at least 2 times as fast as the surrounding ejecta and that originate generically from a proto−neutron star surface atmosphere that is turbulent and rotating. We find that winds are common features of 3D simulations, even if there is anisotropic early infall. We find that the basic dynamical properties of 3D winds behave qualitatively similarly to those inferred in the past using simpler 1D models, but that the shape of the emergent wind can be deformed, very aspherical, and channeled by its environment. The thermal properties of winds for less massive progenitors very approximately recapitulate the 1D stationary solutions, while for more massive progenitors they deviate significantly owing to aspherical accretion. The Y e temporal evolution in winds is stochastic, and there can be some neutron-rich phases. Though no strong r -process is seen in any model, a weak r -process can be produced, and isotopes up to 90 Zr are synthesized in some models. Finally, we find that there is at most a few percent of a solar mass in the integrated wind component, while the energy carried by the wind itself can be as much as 10%–20% of the total explosion energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Directionally supervised cellular automaton for the initial peopling of Sahul

Reconstructing the patterns of Homo sapiens expansion out of Africa and across the globe has been advanced using demographic and travel-cost models. However, modelled routes are ipso facto influenced by migration rates, and vice versa. We combined movement ‘superhighways’ with a demographic cellular automaton to predict one of the world's earliest peopling events — Sahul between 75000 and 50000 years ago. Novel outcomes from the superhighways-weighted model include (i) an approximate doubling of the predicted time to continental saturation (~10,000 years) compared to that based on the directionally unsupervised model (~5000 years), suggesting that rates of migration need to account for topographical constraints in addition to rate of saturation; (ii) a previously undetected movement corridor south through the centre of Sahul early in the expansion wave based on the scenarios assuming two dominant entry points into Sahul; and (iii) a better fit to the spatially de-biased, Signor-Lipps-corrected layer of initial arrival inferred from dated archaeological material. Our combined model infrastructure provides a data-driven means to examine how people initially moved through, settled, and abandoned different regions of the globe.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

The Dependence of the Strength and Thickness of Field-Aligned Currents on Solar Wind and Ionospheric Parameters

Sheared plasma flows at the low-latitude boundary layer correlate well with early afternoon auroral arcs and eld-aligned currents [Sonnerup, 1980; Lundin and Evans, 1985]. We present a simple analytic model that relates solar wind and ionospheric parameters to the strength and thickness of field-aligned currents in a region of sheared velocity, such as the low latitude boundary layer. We compare the predictions of the model with DMSP observations and nd remarkably good scaling of the currents with solar wind and ionospheric parameters. The sheared boundary layer thickness is inferred to be around 3000km consistent with observational studies. The analytic model provides a simple way to organize data and to infer boundary layer structures from ionospheric data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

High frequency impedance characteristics of a tunable microplasma device

Computational studies on high frequency impedance characteristics of a microplasma device are reported. While microplasma is ignited using a primary excitation signal, frequency response of plasma impedance is determined by a secondary high frequency probe signal with significantly lower voltage amplitude such that it does not influence the plasma parameters. Here, the computational model utilizing the drift–diffusion approximation is first validated by comparing with experimental data for microplasmas ignited at pressures ranging from 1 to 5 Torr. In spite of quantitative discrepancies, good overall agreement is obtained between the measured frequency response of impedance of the discharge. Comparisons are also presented for various plasma parameters including mean electron number density, sheath thickness, mean electron temperature, and collision frequency that were inferred from the impedance measurements. The computational model is then used to perform simulations of near-atmospheric pressure microplasmas with the probe signal frequency ranging from 3 to 20 GHz. The simulations demonstrate the presence of a resonance frequency at which the impedance vanishes. More importantly, it is shown that this resonant frequency can be tuned effectively by suitably modifying the operating parameters (gap size, pressure, and excitation voltage). The simulated impedance characteristics are used to determine the effective plasma inductance and capacitance using a non-linear fitting approach, thereby showing the dependence of these electrical parameters on the plasma operating conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference

Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from a simplified galaxy cluster observation analysis. Using data generated from the Quijote simulation suite and analytical models, we train a machine learning algorithm to learn the probability function between cosmological parameters and the possible galaxy cluster observables. The posterior distribution of the cosmological parameters at a given observation is then obtained by sampling the predictions from the trained algorithm. Our results show that the SBI method can successfully recover the truth values of the cosmological parameters within the 2σ limit for this simplified galaxy cluster analysis, and acquires similar posterior constraints obtained with a likelihood-based Markov Chain Monte Carlo method, the current state-of the-art method used in similar cosmological studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗
DOE OSTI2013

A Systems Biology Platform for Characterizing Regulatory and Metabolic Pathways that Influence and Control Microbial Hydrogen Production

In this project, we created a novel systems biology technology platform and resources that can be used to reverse engineer and analyze gene regulatory networks and metabolic pathways that influence and control microbial hydrogen production. We constructed genome-scale transcriptional regulatory and metabolic models using automated model reconstruction methods, and subsequently integrated the regulatory and metabolic models for computational analysis. We devised novel algorithms for inferring putative regulatory architectures of metabolic pathways based on their topology, and for integrating gene expression information in flux balance analysis (FBA) models towards computing dynamical changes in metabolic objectives. From a metabolic engineering perspective, we improved and applied a method for predicting optimal environmental conditions and genetic modifications towards maximal productions of multiple desired metabolic outputs. We also developed and tested an improved flux balance approach for predicting the response of metabolic networks to genetic perturbations, proving that errors in model predictions are approaching the limit of experimental uncertainty. We also used the metabolic and regulatory models to identify relevant metabolic processes and pathways involved in hydrogen production. Below we provide a summary and details of our achievements.

Collins, James J.↗
DOE OSTI2025

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2017

The Atmospheric Response to High Nonthermal Electron Beam Fluxes in Solar Flares. I. Modeling the Brightest NUV Footpoints in the X1 Solar Flare of 2014 March 29

The 2014 March 29 X1 solar flare (SOL20140329T17:48) produced bright continuum emission in the far- and near-ultraviolet (NUV) and highly asymmetric chromospheric emission lines, providing long-sought constraints on the heating mechanisms of the lower atmosphere in solar flares. We analyze the continuum and emission line data from the Interface Region Imaging Spectrograph (IRIS) of the brightest flaring magnetic footpoints in this flare. We compare the NUV spectra of the brightest pixels to new radiative-hydrodynamic predictions calculated with the RADYN code using constraints on a nonthermal electron beam inferred from the collisional thick-target modeling of hard X-ray data from Reuven Ramaty High Energy Solar Spectroscopic Imager . We show that the atmospheric response to a high beam flux density satisfactorily achieves the observed continuum brightness in the NUV. The NUV continuum emission in this flare is consistent with hydrogen (Balmer) recombination radiation that originates from low optical depth in a dense chromospheric condensation and from the stationary beam-heated layers just below the condensation. A model producing two flaring regions (a condensation and stationary layers) in the lower atmosphere is also consistent with the asymmetric Fe ii chromospheric emission line profiles observed in the impulsive phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The complex accretion geometry of GX 339–4 as seen by NuSTAR and Swift

We present spectral analyses of five Nuclear Spectroscopic Telescope Array and Swift observations of GX 339–4 taken during a failed outburst during the summer of 2013. These observations cover Eddington luminosity fractions in the range ≈0.9%–6%. Throughout this outburst GX 339–4 stayed in the hard state and all five observations show similar X-ray spectra, with a hard power law with a photon index near 1.6, and significant contribution from reflection. Using simple reflection models we find unrealistically high iron abundances. Allowing for different photon indices for the continuum incident on the reflector relative to the underlying observed continuum results in a statistically better fit and reduced iron abundances. With a photon index around 1.3, the input power law on the reflector is significantly harder than that which is directly observed. We study the influence of different emissivity profiles and geometries and consistently find an improvement when using separate photon indices. The inferred inner accretion disk radius is strongly model dependent, but we do not find evidence for a truncation radius larger than 100 r{sub g} in any model. The data do not allow independent spin constraints, but the results are consistent with the literature (i.e., a>0). Our best-fit models indicate an inclination angle in the range 40°–60°, consistent with limits on the orbital inclination but higher than reported in the literature using standard reflection models. The iron line around 6.4 keV is clearly broadened, and we detect a superimposed narrow core as well. This core originates from a fluorescent region outside the influence of the strong gravity of the black hole. Additionally, we discuss possible geometries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The Double-edged Sword of Data-driven Super-Resolution: Adversarial Super-resolution Models

Data-driven super-resolution (SR) methods are often integrated into imaging pipelines as preprocessing steps to improve downstream tasks such as classification and detection. However, these SR models introduce a previously unexplored attack surface into imaging pipelines. In this paper, we present AdvSR, a framework demonstrating that adversarial behavior can be embedded directly into SR model weights during training, requiring no access to inputs at inference time. Unlike prior attacks that perturb inputs or rely on backdoor triggers, AdvSR operates entirely at the model level. By jointly optimizing for reconstruction quality and targeted adversarial outcomes, AdvSR produces models that appear benign under standard image quality metrics while inducing downstream misclassification. We evaluate AdvSR on three SR architectures (SRCNN, EDSR, SwinIR) paired with a YOLOv11 classifier and demonstrate that AdvSR models can achieve high attack success rates with minimal quality degradation. These findings highlight a new model-level threat for imaging pipelines, with implications for how practitioners source and validate models in safety-critical applications.

Sullivan, Haley [ORNL] (ORCID:0000000274069217)↗
DOE OSTI2021

Experimentally Inferred Fusion Yield Dependencies of OMEGA Inertial Confinement Fusion Implosions

Statistical modeling of experimental and simulation databases has enabled the development of an accurate predictive capability for deuterium-tritium layered cryogenic implosions at the OMEGA laser. Here, a physics-based statistical mapping framework is described and used to uncover the dependencies of the fusion yield. This model is used to identify and quantify the degradation mechanisms of the fusion yield in direct-drive implosions on OMEGA. The yield is found to be reduced by the ratio of laser beam to target radius, the asymmetry in inferred ion temperatures from the $l$ = 1 mode, the time span over which tritium fuel has decayed, and parameters related to the implosion hydrodynamic stability. When adjusted for tritium decay and $l$ = 1 mode, the highest yield in OMEGA cryogenic implosions is predicted to exceed 2 × 10 14 fusion reactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Learning from Imperfections: Predicting Structure and Thermodynamics from Atomic Imaging of Fluctuations

In materials characterization, traditionally a single experimental sample is used to derive information about a single point in the composition space, while the imperfections, impurities, and stochastic details of material structure are deemed irrelevant or complicating factors in the analysis. Here we demonstrate that atomic-scale studies of a single nominal composition can provide information about microstructures and thermodynamic response over a finite area of chemical space. Using the principles of statistical inference, we develop a framework for incorporating structural fluctuations into statistical mechanical models and use it to solve the inverse problem of deriving effective interatomic interactions responsible for elemental segregation in a La 5/8 Ca 3/8 MnO 3 thin film. Here, the results are further analyzed by a variational autoencoder to detect anomalous behavior in the composition phase diagram. This study provides a framework for creating generative models from a combination of multiple experimental data and provides direct insight into the driving forces for cation segregation in manganites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
DOE OSTI2017

Shocks and Tides Quantified in the “Sausage” Cluster, CIZA J2242.8+5301 Using N-body/Hydrodynamical Simulations

The colliding cluster, CIZA J2242.8+5301, displays a spectacular, almost 2 Mpc long shock front with a radio based Mach number M≃5, that is puzzlingly large compared to the X-ray estimate of M≃2.5. The extent to which the X-ray temperature jump is diluted by cooler unshocked gas projected through the cluster currently lacks quantification. Here we apply our self-consistent N-body/hydrodynamical code (based on FLASH) to model this binary cluster encounter. We can account for the location of the shock front and also the elongated X-ray emission by tidal stretching of the gas and dark matter between the two cluster centers. The required total mass is 8.9×10{sup 14} M{sub ⊙} with a 1.3:1 mass ratio favoring the southern cluster component. The relative velocity we derive is ≃2500 km s{sup −1} initially between the two main cluster components, with an impact parameter of 120 kpc. This solution implies that the shock temperature jump derived from the low angular resolution X-ray satellite Suzaku is underestimated by a factor of two, due to cool gas in projection, bringing the observed X-ray and radio estimates into agreement. Finally, we use our model to generate Compton-y maps to estimate the thermal Sunyaev–Zel’dovich (SZ) effect. At 30 GHz, this amounts to ΔS{sub n}=−0.072 mJy/arcmin{sup 2} and ΔS{sub s}=−0.075 mJy/arcmin{sup 2} at the locations of the northern and southern shock fronts respectively. Our model estimate agrees with previous empirical estimates that have inferred the measured radio spectra of the radio relics can be significantly affected by the SZ effect, with implications for charged particle acceleration models.

79 ASTRONOMY AND ASTROPHYSICS↗