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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Statistical and Machine Learning Approaches to Analyzing Pipeline Incidents in the United States (2010–2024)

This study applies machine learning methods to analyze natural gas pipeline incidents in the United States using the Pipeline and Hazardous Materials Safety Administration (PHMSA) Gas Distribution Incident Dataset (2010–2024). The dataset includes over 600 variables describing incident characteristics, infrastructure attributes, and contributing factors associated with unintentional gas releases. The objective is to assess whether these features can reliably predict the underlying cause of pipeline failures. Multinomial logistic regression and Random Forest models were developed to classify incident causes, including excavation damage, corrosion, equipment failure, and natural forces. Results show that excavation damage is both the most frequent and most predictable cause, with models achieving strong performance for this category. However, when excavation damage is excluded, model accuracy declines significantly, with some models performing near random levels. Across all approaches, severe class imbalance and limited variability in key predictors constrain predictive performance. Pipeline age and diameter emerge as the most influential variables, but they provide insufficient discriminatory power to distinguish among less frequent failure types. These findings indicate that non-excavation-related incidents are rare, heterogeneous, and weakly represented in the dataset, limiting the effectiveness of machine learning classification. Overall, this study highlights the structural limitations of the PHMSA dataset for predictive modeling and underscores the need for improved data balance and feature enrichment. The results reinforce excavation damage prevention as the most impactful strategy for reducing pipeline incidents.

03 NATURAL GAS↗
DOE OSTI2021

Elucidating Mass Transport Regimes in Gas Diffusion Electrodes for CO 2 Electroreduction

Gas diffusion electrodes (GDEs) have shown promising performance for the electrochemical reduction of CO 2 (CO 2 R). In this study, a resolved, pore scale model of electrochemical reduction of CO 2 within a liquid-filled catalyst layer is developed. Three CO 2 mass transport regimes are identified in which the CO 2 penetration depth is controlled by CO 2 consumption in the electrolyte, CO 2 conversion along the solid-electrolyte double-phase boundaries (DPBs), and CO 2 conversion concentrated around the gas–solid–electrolyte triple-phase boundaries (TPBs). While it is possible for CO 2 R to be localized around the TPBs, in systems with submicron pore radii operating at <1 A cm –2 CO 2 R will be distributed across the DPBs within the catalyst layer. This validates the assumption of pore-scale uniformity implicit in popular, volume-averaged GDE models. Overall, the CO 2 conversion efficiency depends strongly on the governing mass transport regime, and operational-phase diagrams are constructed to guide the catalyst layer design.

10 SYNTHETIC FUELS↗
DOE OSTI2023

New thermal decomposition pathway for TATB

Abstract Understanding the thermal decomposition behavior of TATB (1,3,5-triamino-2,4,6-trinitrobenzene) is a major focus in energetic materials research because of safety issues. Previous research and modelling efforts have suggested benzo-monofurazan condensation producing H 2 O is the initiating decomposition step. However, early evolving CO 2 (m/z 44) along with H 2 O (m/z 18) evolution have been observed by mass spectrometric monitoring of head-space gases in both constant heating rate and isothermal decomposition studies. The source of the CO 2 has not been explained, until now. With the recent successful synthesis of 13 C 6 -TATB ( 13 C incorporated into the benzene ring), the same experiments have been used to show the source of the CO 2 is the early breakdown of the TATB ring, not adventitious C from impurities and/or adsorbed CO 2 . A shift in mass m/z 44 (CO 2 ) to m/z 45 is observed throughout the decomposition process indicating the isotopically labeled 13 C ring breakdown occurs at the onset of thermal decomposition along with furazan formation. Partially labeled (N 18 O 2 ) 3 -TATB confirms at least some of the oxygen comes from the nitro-groups. This finding has a significant bearing on decomposition computational models for prediction of energy release and deflagration to detonation transitions, with respect to conditions which currently do not recognize this oxidation step.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Flyby reaction trajectories: Chemical dynamics under extrinsic force

Dynamic effects are an important determinant of chemical reactivity and selectivity, but the deliberate manipulation of atomic motions during a chemical transformation is not straightforward. In this work, we demonstrate that extrinsic force exerted upon cyclobutanes by stretching pendant polymer chains influences product selectivity through force-imparted nonstatistical dynamic effects on the stepwise ring-opening reaction. The high product stereoselectivity is quantified by carbon-13 labeling and shown to depend on external force, reactant stereochemistry, and intermediate stability. Computational modeling and simulations show that, besides altering energy barriers, the mechanical force activates reactive intramolecular motions nonstatistically, setting up “flyby trajectories” that advance directly to product without isomerization excursions. A mechanistic model incorporating nonstatistical dynamic effects accounts for isomer-dependent mechanochemical stereoselectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

β-Barrel proteins tether the outer membrane in many Gram-negative bacteria

Gram-negative bacteria have a cell envelope that comprises an outer membrane (OM), a peptidoglycan (PG) layer and an inner membrane (IM). The OM and PG are load-bearing, selectively permeable structures that are stabilized by cooperative interactions between IM and OM proteins. In Escherichia coli , Braun’s lipoprotein (Lpp) forms the only covalent tether between the OM and PG and is crucial for cell envelope stability; however, most other Gram-negative bacteria lack Lpp so it has been assumed that alternative mechanisms of OM stabilization are present. In this work we used a glycoproteomic analysis of PG to show that β-barrel OM proteins are covalently attached to PG in several Gram-negative species, including Coxiella burnetii, Agrobacterium tumefaciens and Legionella pneumophila . In C. burnetii , we found that four different types of covalent attachments occur between OM proteins and PG, with tethering of the β-barrel OM protein BbpA becoming most abundant in the stationary phase and tethering of the lipoprotein LimB similar throughout the cell cycle. Using a genetic approach, we demonstrate that the cell cycle-dependent tethering of BbpA is partly dependent on a developmentally regulated L,D-transpeptidase (Ldt). We use our findings to propose a model of Gram-negative cell envelope stabilization that includes cell cycle control and an expanded role for Ldts in covalently attaching surface proteins to PG.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Universal spin dynamics in infinite-temperature one-dimensional quantum magnets

Here, we address the nature of spin dynamics in various integrable and non-integrable, isotropic and anisotropic quantum spin-$S$ chains, beyond the paradigmatic $S=1/2$ Heisenberg model. In particular, we investigate the algebraic long-time decay $\propto t^{-1/z}$ of the spin-spin correlation function at infinite temperature, using state-of-the-art simulations based on tensor network methods. We identify three universal regimes for the spin transport, independent of the exact microscopic model: (i) superdiffusive with $z=3/2$, as in the Kardar-Parisi-Zhang universality class, when the model is integrable with extra symmetries such as spin isotropy that drive the Drude weight to zero, (ii) ballistic with $z=1$ when the model is integrable with a finite Drude weight, and (iii) diffusive with $z=2$ with easy-axis anisotropy or without integrability, at variance with previous observations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Spatiotemporal Crossover between Low- and High-Temperature Dynamical Regimes in the Quantum Heisenberg Magnet

The stranglehold of low temperatures on fascinating quantum phenomena in one-dimensional quantum magnets has been challenged recently by the discovery of anomalous spin transport at high temperatures. Whereas both regimes have been investigated separately, no study has attempted to reconcile them. For instance, the paradigmatic quantum Heisenberg spin-$1/2$ chain falls at low-temperature within the Tomonaga-Luttinger liquid framework, while its high-temperature dynamics is superdiffusive and relates to the Kardar-Parisi-Zhang universality class in $1+1$ dimensions. This work aims at reconciling the two regimes. Building on large-scale matrix product state simulations, we find that they are connected by a temperature-dependent spatiotemporal crossover. In this work, as the temperature $T$ is reduced, we show that the onset of superdiffusion takes place at longer length and time scales $\propto 1/T$. This prediction has direct consequences for experiments including nuclear magnetic resonance: it is consistent with earlier measurements on the nearly ideal Heisenberg $S=1/2$ chain compound Sr$_2$CuO$_3$ yet calls for new and dedicated experiments.

1-dimensional spin chains↗
DOE OSTI2022

RAFT (Response Amplitudes of Floating Turbines) [SWR-22-40]

RAFT is a Python code for frequency-domain analysis of floating wind turbines. RAFT works in the frequency domain to provide efficient computations of a floating wind system's response spectra accounting for platform hydrodynamics, quasi-static mooring reactions, rotor aerodynamics, and linearized control. It can be used to calculate response amplitude operators (RAO's), power spectral densities, mean/static properties, and response metrics based on mean and root-mean-square values of each output. RAFT serves as the Level 1 model in the WEIS (Wind Energy with Integrated Servo-control) toolkit, and features an OpenMDAO wrapper.

Hall, Matthew↗
DOE OSTI2023

Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling

This submission from AMEC (the Atlantic Marine Energy Center) includes data from an ocean field deployment of a wave powered water pump in March 2023. The wave pump is an upweller device, designed to enhance macroalgal aquaculture. The wave pump device was deployed off the coast of Isles of Shoals Appledore Island in Maine, USA. The data were collected using a custom-built DAQ module comprised of Arduino Unos. GPS time stamp accompanies the data. The data are volumetric flow rate from the wave pump, and relative motion of the device between float and spar buoys. Flow rate is measured by flow meter, and relative motion is measured by lidar. Calibration data for the lidar and flow meter sensors are included. This data set also includes synchronous Sofar Spotter buoy data from a mooring approximately 300 feet away from the wave pump mooring. Video data from the deployment are included from both on-board the device sporadically throughout the deployment, and from a webcam for a short duration of the deployment. Hydrophone data were also taken co-currently, and are available by contacting Martin Wosnik at the University of New Hampshire. The Matlab code used to process the field data is incorporated. A biological assessment is included which aided the NEPA consultation process, prior to conducting the field deployment. A WEC-Sim numerical model of the wave pump, and a re-design effort are part of this work. Code used to validate the WEC-Sim model from the field data are also included.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Strong Coulomb coupling influences ion and neutral temperatures in atmospheric pressure plasmas

Molecular dynamics simulations are used to model ion and neutral temperature evolution in partially-ionized atmospheric pressure plasma at different ionization fractions. Results show that ion–ion interactions are strongly coupled at ionization fractions as low as 10 –5 and that the temperature evolution is influenced by effects associated with the strong coupling. Specifically, disorder-induced heating is found to rapidly heat ions on a timescale of the ion plasma period (~10 s ps) after an ionization pulse. This is followed by the collisional relaxation of ions and neutrals, which cools ions and heats neutrals on a longer (~ns) timescale. Slight heating then occurs over a much longer (~100 s ns) timescale due to ion-neutral three-body recombination. An analytic model of the temperature evolution is developed that agrees with the simulation results. Finally, a conclusion is that strong coupling effects are important in atmospheric pressure plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Modeling and simulation of oxygen transport in high burnup LWR fuel

We have developed a formulation for oxygen transport in uranium dioxide nuclear fuel that accounts for the effects of irradiation. The overall simulation combines the evolving isotopic composition, thermochemistry, and oxygen transport in irradiated fuel. The driving forces for oxygen transport are computed from local thermodynamic equilibrium calculations and account for the effects of temperature gradients and composition, including fission products. The proposed method provides a mechanism for including complex thermodynamic models of nuclear fuel in modeling of mass redistribution, and alleviates difficulties associated with the common thermodiffusion formulation. Here, the transport model has been implemented within the nuclear fuel performance code BISON utilizing the thermochemistry code Thermochimica, with burnup calculations provided by the ORIGEN isotopic transmutation code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

3D seismic imaging of a fracture damage zone controlling reservoir compartmentalization at the Raft River EGS using multi-azimuth walkaway VSP

Accurate imaging of steeply dipping fracture zones in crystalline enhanced geothermal systems (EGS) is critical for constraining permeability architecture and guiding stimulation design. However, such structures remain poorly resolved by conventional surface seismic methods. We present a fully three-dimensional (3D) elastic-waveform inversion-migration workflow applied to multi-azimuth walkaway vertical seismic profiling (VSP) data acquired in a deviated borehole at the Raft River EGS. The workflow integrates first-arrival traveltime tomography, multi-scale elastic waveform inversion (EWI), and elastic least-squares reverse-time migration (ELSRTM) to recover high-resolution compressional-and shear-wave velocity models and to image structural discontinuities in the crystalline basement. The results reveal a laterally continuous low-velocity anomaly, with shear-wave velocity reductions of 25-30%, consistent with fractureinduced mechanical weakening. Two steeply dipping discontinuities bound a 50-80 m wide fracture damage zone. Independent constraints from microseismic clustering and geochemical compartmentalization corroborate the geometry and structural significance of this feature. Synthetic modeling further confirms that structures of this scale are resolvable (~30 m). These findings indicate that the Narrows structure is a distributed fracture damage zone rather than a discrete fault plane. By resolving fracture-zone geometry at the tens-of-meters scale using a single borehole, this workflow provides a practical and transferable approach for improving structural characterization, reducing uncertainty in permeability architecture, and supporting reservoir modeling and stimulation design in fractured crystalline EGS reservoirs.

58 GEOSCIENCES↗
DOE OSTI2024

High-throughput determination of Hubbard $U$ and Hund $J$ values for transition metal oxides via the linear response formalism

DFT+U provides a convenient, cost-effective correction for the self-interaction error (SIE) that arises when describing correlated electronic states using conventional approximate density functional theory (DFT). The success of a DFT+U(+J) calculation hinges on the accurate determination of its Hubbard U and Hund J parameters, and the linear response (LR) methodology has proven to be computationally effective and accurate for calculating these parameters. This study provides a high-throughput computational analysis of the U and J values for transition metal d-electron states in a representative set of over 1000 magnetic transition metal oxides (TMOs), providing a frame of reference for researchers who use DFT+U to study transition metal oxides. In order to perform this high-throughput study, an ATOMATE workflow is developed for calculating U and J values automatically on massively parallel supercomputing architectures. Here, to demonstrate an application of this workflow, the spin-canting magnetic structure and unit cell parameters of the multiferroic olivine LiNiPO4 are calculated using the computed Hubbard U and Hund J values for Ni-d and O-p states, and are compared with experiment. Both the Ni-d U and J corrections have a strong effect on the Ni-moment canting angle. Additionally, including a O-pU value results in a significantly improved agreement between the computed lattice parameters and experiment

36 MATERIALS SCIENCE↗
DOE OSTI2021

Neural Density Estimation and Uncertainty Quantification for ChemCam Spectra [Slides]

The ChemCam instrument of Curiosity uses laser-induced breakdown spectroscopy (LIBS). It fires a laser at target and vaporizes rock surfaces, creating a plasma. Three spectrographs divide the plasma light into wavelengths for chemical analysis: ultraviolet, violet, and visible near-infrared. Regression methods (SVR, PCR, CNN) have been employed for calibration (prediction of the elemental composition of samples); however, labeled ChemCam samples are limited. Here, we focus on unsupervised learning and employ generative models from ChemCam analysis. Further, we use labels (supervised) in combination to the generative model to compute uncertainties related to predictions. We report generative modeling can be successfully applied to model real-world data. Normalizing flow models can be efficiently constructed on latent spaces for fast downstream inference. Unsupervised and supervised learning can be combined to form an uncertainty quantification framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

BSEC ecohydrological and water quality fluxes from RHESSys Simulations in USGS gauged watersheds

Baltimore Environmental Social Collaborative (BSEC) Water and Water Quality Simulations from RHESSys Model The repository contains RHESSys (Tague & Band, 2004; source code) simulated ecohydrological and nutrient (nitrogen only) fluxes at daily, basin-average (RHESSys_basin_output) and monthly, grid (RHESSys_patch_output) levels. We currently simulated the following 8 watersheds in Baltimore: Dead Run Baisman Run Scotts Level Branch Moores Run Powder Mill Run Maidens Choice Run Stony Run The watershed boundaries of all studied watersheds are stored in Watershed_Boundary folder. Variables and their units are listed in the metadata. Spatial projection, NAD83 / UTM zone 18N (EPSG:26918) is used for patch-level, netCDF-format files. For more information, please contact Ruoyu Zhang (rz3jr@virginia.edu).

Baltimore MD↗
DOE OSTI2022

Coexistence of non-Abelian chiral spin liquid and magnetic order in a spin-1 antiferromagnet

We study the ground-state properties of a spin-1 Heisenberg model on a square lattice with the first- and second-nearest-neighbor antiferromagnetic couplings $J_1$ and $J_2$ and a three-spin scalar chirality term $J_\chi$. Using the density matrix renormalization group calculation, we map out a global phase diagram including various magnetic order phases and an emergent quantum spin liquid phase. The nature of the spin liquid is identified as a bosonic non-Abelian Moore-Read state from the fingerprint of the entanglement spectra and identification of a full set of topological sectors. We further unveil a stripe magnetic order coexisting with this spin liquid. Furthermore, our results not only establish a rare example of non-Abelian spin liquids in simple spin systems but also demonstrate the coexistence of fractionalized excitations and magnetic order beyond mean-field descriptions.

2-dimensional systems↗