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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Uncertainty quantification for competing failure mechanisms in unidirectionally reinforced carbon–carbon composites

Microstructure-informed finite element models play a key role in the carbon–carbon composite design process. Variability in manufacturing process parameters and experimental limitations introduce model parameter uncertainty. This study quantifies the effect of model parameter uncertainty on transverse tensile fracture behavior and proposes a methodology to predict the failure mode based on competing microscale damage mechanisms. Finite element simulations incorporate fiber–matrix interface debonding with cohesive zones and matrix damage with a smeared crack band approach in a unidirectional carbon–carbon composite. Results from a variance-based global sensitivity analysis identifies interfacial and matrix damage parameters as the primary source of variability in fracture behavior. Sobol’ indices indicate that matrix and cohesive zone strengths contribute 94% of the variance in the effective ultimate stress. A local analysis elucidates the relationship between these constituent strength parameters and failure mode by estimating the probability of cohesive, matrix, and mixed-mode dominated failure. Based on the results for 4000 simulations, 93% exhibit mixed-mode or interfacial dominated failure, which underscores the crucial role of fiber–matrix interface debonding in the transverse tensile failure of carbon–carbon composites. These uncertainty quantification results facilitate more efficient model calibration and provide a framework for microstructure-informed failure predictions in the face of manufacturing-induced uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid High-Resolution Analysis of Polysaccharide-Lignin Interactions in Secondary Plant Cell Walls Using Proton-Detected Solid-State NMR

The plant secondary cell wall, a complex matrix composed of cellulose, hemicellulose, and lignin, is crucial for the mechanical strength and water-proofing properties of plant tissues, and serves as a primary source of biomass for biorenewable energy and biomaterials. Structural analysis of these polymers and their interactions within the secondary cell wall has been heavily relying on 13 C-based solid-state NMR techniques. In this study, we explore the application of 1 H-detected solid-state NMR techniques for rapid, high-resolution structural characterization of polysaccharides and lignin, demonstrated on the stems of hardwood eucalyptus. We explored the use of synthesized 2D spectra to resolve central 1 H resonances and the combined application of 3D hCCH and hCHH experiments for complete resonance assignment and unambiguous identification of lignin-carbohydrate interactions. Our findings emphasize the central role of acetylated three-fold xylan conformers, rather than two-fold, in stabilizing the carbohydrate-lignin interface, with glucuronic acid sidechains in eucalyptus glucuronoxylan colocalizing with lignin, revised cellulose-lignin interactions involving uncoated microfibril surfaces, and pectin-lignin interactions indicative of early-stage lignification. These results present a novel approach for rapid structural analysis of lignocellulosic biomaterials without the need for solubilization or extraction.

09 BIOMASS FUELS↗
DOE OSTI2024

Multicriteria screening evaluation of geothermal resources on mine lands for direct use heating

Abstract Direct use of geothermal energy is the oldest and most versatile form of utilizing geothermal energy. In the last decade, this utilization has significantly increased, especially with the installation of geothermal (ground-source) heat pumps. Many current and inactive mine land sites across the U.S. could be redeveloped with clean energy technologies such as direct use geothermal, which would revitalize former mining communities, help with reducing greenhouse gas emissions, and accelerate the transition to a clean energy economy. We present a multicriteria screening framework to evaluate various aspects of direct-use geothermal projects on mine lands. The criteria are divided into three categories: (1) technical potential, (2) demand and benefits, and (3) regulatory and permitting. We demonstrate the framework using publicly available data on a national scale (continental U.S.). Then, using an example of abandoned coal mines in Illinois and focusing on resource potential, we illustrate how this evaluation can be applied at the state or more local scales when a region’s characteristics drive spatial variability estimates. The strength of this approach is the ability to combine seemingly disparate parameters and inputs from numerous sources. The framework is very flexible—additional criteria can be easily incorporated and weights modified if input data support them. Vice versa, the framework can also help identify additional data needed for evaluating those criteria. The multicriteria screening evaluation methodology provides a framework for identifying potential candidates for detailed site evaluation and characterization.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

The Davis–Chandrasekhar–Fermi method revisited

ABSTRACT Despite the rich observational results on interstellar magnetic fields in star-forming regions, it is still unclear how dynamically significant the magnetic fields are at varying physical scales, because direct measurement of the field strength is observationally difficult. The Davis–Chandrasekhar–Fermi (DCF) method has been the most commonly used method to estimate the magnetic field strength from polarization data. It is based on the assumption that gas turbulent motion is the driving source of field distortion via linear Alfvén waves. In this work, using MHD simulations of star-forming clouds, we test the validity of the assumption underlying the DCF method by examining its accuracy in the real 3D space. Our results suggest that the DCF relation between turbulent kinetic energy and magnetic energy fluctuation should be treated as a statistical result instead of a local property. We then develop and investigate several modifications to the original DCF method using synthetic observations, and propose new recipes to improve the accuracy of DCF-derived magnetic field strength. We further note that the biggest uncertainty in the DCF analysis may come from the linewidth measurement instead of the polarization observation, especially since the line-of-sight gas velocity can be used to estimate the gas volume density, another critical parameter in the DCF method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Binary neutron star mergers as potential sources for ultrahigh-energy cosmic rays and high-energy neutrinos

Recent studies suggest that the most energetic cosmic rays, exceeding 100 EeV, may primarily consist of 𝑟-process nuclei. This highlights binary neutron star mergers and collapsars as promising sources of ultrahigh-energy cosmic rays (UHECRs). Building on these insights, we examine the conditions that facilitate the efficient production of UHE 𝑟-process nuclei during the prompt radiation (PR), extended emission (EE), and plateau emission phases of short gamma-ray bursts (sGRBs) following neutron star mergers. Our study reveals that jets associated with the PR phase, characterized by typical bulk Lorentz factors (≳ 400–500), dissipation radii, and magnetic field strengths, can accelerate 𝑟-process nuclei to energies ≳ 100 EeV, while preserving them during propagation within the source. Additionally, we investigate the production of HE neutrinos from photomeson and hadronic interactions, as well as from the 𝛽 decay of accelerated 𝑟-process nuclei. We find that the HE neutrino fluxes from sGRBs, mainly produced via photomeson interactions, are significantly limited to preserve the accelerated heavy nuclei, leading to lower fluxes than the predictions without allowing for contributions to UHECRs. Our results suggest that sGRBs may potentially contribute to UHECRs during the PR phase and to HE neutrinos during the EE phase—a scenario that can be tested by future neutrino observatories.

Cosmic ray sources↗
DOE OSTI2024

Catalytic Reduction of Carbon Monoxide to Liquid Fuels with Recyclable Hydride Donors

Solar light absorption and catalysis are physically separated processes in natural photosynthesis. Natural cofactors, such as nicotinamide adenine dinucleotides (NADH), transport electrons and hydrogen to regulate and activate enzymes at remote locations. The physical separation of light absorption from catalysis provides some inspiration for artificial photosynthesis. One rather extreme implementation is to use copper wires to transport carriers from photovoltaic cells to dark electrodes, where catalysis occurs. Indeed, with a futuristic electrical grid powered solely by photovoltaics, solar capture could be separated from catalysis by hundreds of miles. An alternative approach, that bares more similarity to natural photosynthesis, employs mobile NADH/NAD + -like species that shuttle between the light absorber and a proximate, yet unilluminated, location where catalysis occurs. Additionally, such a remote approach to solar photocatalysis was recently proposed for the reduction of carbon oxides, CO 2 and CO, to methanol by cascade catalysis. This developing artificial photosynthetic approach offers the promise of catalytic generation of methanol and oxygen gas with sunlight as the sole energy source and CO 2 and water as the only chemical feedstocks. This Viewpoint evaluates the strengths and weaknesses of this approach with an emphasis on CO reduction catalysis with photorecyclable hydride donors while looking forward to what might reasonably be achieved with continued research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗
DOE OSTI2021

First detection of VHE gamma-ray emission from TXS 1515–273, study of its X-ray variability and spectral energy distribution

ABSTRACT We report here on the first multiwavelength (MWL) campaign on the blazar TXS 1515–273, undertaken in 2019 and extending from radio to very-high-energy gamma-rays (VHE). Up until now, this blazar had not been the subject of any detailed MWL observations. It has a rather hard photon index at GeV energies and was considered a candidate extreme high-synchrotron-peaked source. MAGIC observations resulted in the first-time detection of the source in VHE with a statistical significance of 7.6σ. The average integral VHE flux of the source is 6 ± 1 per cent of the Crab nebula flux above 400 GeV. X-ray coverage was provided by Swift-XRT, XMM–Newton, and NuSTAR. The long continuous X-ray observations were separated by ∼9 h, both showing clear hour scale flares. In the XMM–Newton data, both the rise and decay time-scales are longer in the soft X-ray than in the hard X-ray band, indicating the presence of a particle cooling regime. The X-ray variability time-scales were used to constrain the size of the emission region and the strength of the magnetic field. The data allowed us to determine the synchrotron peak frequency and classify the source as a flaring high, but not extreme synchrotron-peaked object. Considering the constraints and variability patterns from the X-ray data, we model the broad-band spectral energy distribution. We applied a simple one-zone model, which could not reproduce the radio emission and the shape of the optical emission, and a two-component leptonic model with two interacting components, enabling us to reproduce the emission from radio to VHE band.

Acciari, V. A.↗
DOE OSTI2022

Dislocation dynamics in heterogeneous nanostructured materials

Crystalline materials can be strengthened by introducing dissimilar phases that impede dislocation glide. At the same time, the changes in microstructure and chemistry usually make the materials less ductile. One way to circumvent the strength–ductility dilemma is to take advantage of heterogeneous nanophases which simultaneously serve as dislocation barriers and sources. Owing to their superior mechanical properties, heterogeneous nanostructured materials (HNMs) have attracted a lot of attention worldwide. Nevertheless, it has been difficult to characterize dislocation dynamics in HNMs using classical continuum models, mainly due to the challenges in describing the elastic and plastic heterogeneity among the phases. Here, in this work, we advance a phase-field dislocation dynamics (PFDD) model to treat multi-phase materials, consisting of phases differing in composition, structural order, and size in the same system. We then apply the advanced PFDD model to exploring two important but divergent materials design problems in HNMs: dislocation/obstacle interactions and dislocation/interface interactions. Results show that the interactions between a dislocation and distribution of obstacles varying in structure and composition cannot be understood by simply interpolating from their individual interactions with a dislocation. It is also found that materials containing interfaces with nanoscale thicknesses and compositional gradients have a much higher dislocation bypass stress than those with sharp interfaces, providing an explanation for the simultaneous high strength and toughness of thick interface-containing nanolaminates as observed in recent experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Validation of the TOPAS Monte Carlo toolkit for HDR brachytherapy simulations

The goal of this work is to validate the user-friendly Geant4-based Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for brachytherapy applications. Brachytherapy simulations performed with TOPAS were systematically compared with published TG-186 reference data. The photon emission energy spectrum, the air-kerma strength, and the dose-rate constant of the model-based dose calculation algorithm (MBDCA)-WG generic Ir-192 source were extracted. For dose calculations, a track-length estimator was implemented. Additionally, the four Joint AAPM/ESTRO/ABG MBDCA-WG test cases were evaluated through histograms of the local and global dose difference volumes. A prostate, a palliative lung, and a breast case were simulated. For each case, the dose ratio map, the histogram of the global dose difference volume, and cumulative dose-volume histograms were calculated. The air-kerma strength was (9.772 ± 0.001) × 10 -8 U Bq -1 (within 0.3% of the reference value). The dose-rate constant was 1.1107 ± 0.0005 cGy h -1 U -1 (within 0.01% of the reference value). For all cases, at least 96.9% of voxels had a local dose difference within [-1%, 1%] and at least 99.9% of voxels had a global dose difference within [-0.1%, 0.1%]. The implemented track-length estimator scorer was more efficient than the default analog dose scorer by a factor of 237. For all clinical cases, at least 97.5% of voxels had a global dose difference within [-1%, 1%]. Dose-volume histograms were consistent with the reference data. TOPAS was validated for high-dose-rate brachytherapy simulations following the TG-186 recommended approach for MBDCAs. Built on top of Geant4, TOPAS provides broad access to a state-of-the-art Monte Carlo code for brachytherapy simulations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Exploring the link between C iv outflow kinematics and sublimation-temperature dust in quasars

ABSTRACT Using data from SDSS, UKIDSS, and WISE, we investigate the properties of the high-frequency cutoff to the infrared emission in ≃5000 carefully selected luminous (Lbol ∼ 1047) type 1 quasars. The strength of ≃2 μm emission, corresponding to emission from the hottest ($T\gt 1200\rm \, K$) dust in the sublimation zone surrounding the central continuum source, is observed to correlate with the blueshift of the C iv λ1550 emission line. We therefore find that objects with stronger signatures of nuclear outflows tend to have a larger covering fraction of sublimation-temperature dust. When controlling for the observed outflow strength, the hot dust covering fraction does not vary significantly across our sample as a function of luminosity, black hole mass, or Eddington fraction. The correlation between the hot dust and the C iv line blueshifts, together with the lack of correlation between the hot dust and other parameters, therefore provides evidence of a link between the properties of the broad emission line region and the infrared-emitting dusty regions in quasars.

Temple, Matthew J.↗
DOE OSTI2023

Crystal plasticity modeling for the strengthening effect of multilayered copper–graphene nanocomposites

The paper explores plastic deformation mechanisms in metal–graphene nanocomposites, illustrating their material strengthening effects through a crystal plasticity finite element (CPFE) model. This model is compared with published experimental results, which have previously shown that the two-dimensional shape of graphene effectively controls dislocation motion and significantly enhances the strength of metals. Simulated nanopillar compression tests, using a physics-based CP model that incorporates surface nucleation and single-arm source dislocation mechanisms, help us understand dislocation motions at submicron length scales. The crystal plasticity models are applied to nanolayered composites with copper grain layers and monolayer graphene, featuring repeat layer spacings of 200 nm, 125 nm, and 70 nm, respectively. This study quantifies the accumulation of dislocations at the graphene interfaces, contributing to the ultra-high strength of copper–graphene composites. Furthermore, a Hall–Petch-like correlation is established between yield strength and the number of embedded graphene layers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Detectable gravitational wave signals from inflationary preheating

We consider gravitational wave (GW) production during preheating in hybrid inflation models where an axion-like waterfall field couples to Abelian gauge fields. Based on a linear analysis, we find that the GW signal from such models can be within the reach of a variety of foreseeable GW experiments such as LISA, AEDGE, ET and CE, and is close to that of LIGO A+, both in terms of frequency range and signal strength. Furthermore, the resultant GW signal is helically polarized and thus may distinguish itself from other sources of stochastic GW background. Finally, such models can produce primordial black holes that can compose dark matter and lead to merger events detectable by GW detectors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

From Feast to Famine: A Systematic Study of Accretion onto Oblique Pulsars with 3D GRMHD Simulations

Disk-fed accretion onto neutron stars can power a wide range of astrophysical sources ranging from X-ray binaries, to accretion-powered millisecond pulsars, ultraluminous X-ray sources, and gamma-ray bursts. A crucial parameter controlling the gas–magnetosphere interaction is the strength of the stellar dipole. In addition, coherent X-ray pulsations in many neutron star systems indicate that the star's dipole moment is oblique relative to its rotation axis. Therefore, it is critical to systematically explore the 2D parameter space of the star's magnetic field strength and obliquity, which is what this work does, for the first time, in the framework of 3D general-relativistic magnetohydrodynamics. If the accretion disk carries its own vertical magnetic field, this introduces an additional factor: the relative polarity of the disk and stellar magnetic fields. We find that depending on the strength of the stellar dipole and the star–disk relative polarity, the neutron star's jet power can either increase or decrease with increasing obliquity. For weak dipole strength (equivalently, high accretion rate), the parallel polarity results in a positive correlation between jet power and obliquity, whereas the antiparallel orientation displays the opposite trend. For stronger dipoles, the relative-polarity effect disappears, and jet power always decreases with increasing obliquity. The influence of the relative polarity gradually disappears as obliquity increases. Highly oblique pulsars tend to have an increased magnetospheric radius, a lower mass accretion rate, and enter the propeller regime at lower magnetic moments than aligned stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Investigation of hot-spots due to trapped flux in niobium superconducting radiofrequency cavities

One of the significant sources of residual losses in superconducting radio-frequency cavities is magnetic flux trapped during the cool-down due to the incomplete Messier effect. If the trapped vortices are non-uniformly distributed on the cavity surface, the temperature mapping revealed the “hotspots” at the location of high density of pinned vortices. Here, we performed a rf test on 1.3 GHz single cell cavity with the combination of the temperature mapping system. The temperature mapping reveled the development of the hot spots with the increase in rf field inside the cavity. When magnetic field is trapped locally on the surface of cavity, the hot-spots strength increase rapidly, showing the direct correlation of vortex induced hot spot and corresponding rf loss.

Accelerator Physics↗
DOE OSTI2023

Numerical Modeling of Air-Blast Suppression as a Function of Explosive-Charge Burial Depth

As a chemical explosion is buried, the mechanism for acoustic wave generation transitions from fully gas-generated at the surface to completely spall-induced at full containment depth. The fully gas-generated and completely spall-induced signals in the acoustic waveform are well described; however, the transition between these two end-members eludes numerical modeling because of the complex phenomena that are involved. The phenomena of crater formation and explosive cloud evolution are simulated using an Eulerian hydrocode that incorporates geomaterials with strength and porosity. Having accurately modeled these phenomena, we can confidently predict the propagation and relative strength of the gas-generated and spall-induced pulses in the recorded acoustic waveform. The numerical predictions agree with observations from the historical Stagecoach experiment as well as modern recordings from the Source Physics Experiment. In particular, the peak pressure p generated by an explosion is initially due to the gas-generated mechanism and decays with scaled depth of burial d s (depth d scaled by the cube-root of explosive yield w 1/3 ) as exp(-d s ) but then transitions near a scaled depth of 6 m/ton 1/3 to the spall-generated mechanism in which the decay is d$_{s}^{-7/4}$. This decay form is related to the strong ground-motion attenuation relationship that affects spall strength. So these results can improve seismoacoustic inverse models for the explosive source that need to account for the gas-generated and spall-induced signals and their effect on peak pressures and other acoustic signal features.

58 GEOSCIENCES↗