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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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The US Department of Energy’s Regional and Global Climate Modeling program supported much of the initial development of the Radiative Forcing Model Intercomparision Project protocol. This final report details those efforts.
Understanding the mixing between two fluids of disparate densities (i.e., variable density mixing) is important for the lab's mission. Experiments are required to validate our codes, such as RAGE, FLAG, and the BHR mix model. The role initial conditions (ICs) have on instability growth and the transition to turbulence is not completely understood and comparisons with experiments are needed. The Extreme Fluids team focuses on experiments at Los Alamos that utilize gases and low shock velocities (Mach <2 in air). These experiments have the advantage of high fidelity diagnostics capable of temporally and spatially resolved velocity and density measurements. One main difficulty is setting up a specific interface profile between the two gases. While attempts have been made to do so without the aid of a solid structure (i.e., a membrane), the results are limited in the range of possible shapes and reproducibility. Membranes provide the best way to provide a deterministic initial condition. However, fragments from the membrane can interfere with the flow and instability growth, as well as the diagnostics. In this project, we focused on exploring the materials and techniques available via modern additive manufacturing (i.e., 3D printing) to test if they could address some of the shortcomings of prior membrane designs. Our goal was to find a material that would have minimal impact on our experiment while also providing us with a means to produce complex initial conditions. This report details our work to explore the range of additive manufacturing capabilities and the jet-like structures we were able to generate using three-dimensional initial conditions.
Quantifying in-situ subsurface stresses and predicting fracture development are critical to reducing risks of induced seismicity and improving modern energy activities in the subsurface. In this work, we developed a novel integration of controlled mechanical failure experiments coupled with microCT imaging, acoustic sensing, modeling of fracture initiation and propagation, and machine learning for event detections and waveform characterization. Through additive manufacturing (3D printing), we were able to produce bassanite-gypsum rock samples with repeatable physical, geochemical and structural properties. With these "geoarchitected" rock, we provided the role of mineral texture orientation on fracture surface roughness. The impact of poroelastic coupling on induced seismicity has been systematically investigated to improve mechanistic understanding of post shut-in surge of induced seismicity. This research will set the groundwork for characterizing seismic waveforms by using multiphysics and machine learning approaches and improve the detection of low-magnitude seismic events leading to the discovery of hidden fault/fracture systems.
This work plan is part of an effort to complete an updated evaluation of the potential for adverse effects from miscellaneous treatment unit emissions to potential ecological receptors within and surrounding Site 200. It will address potential pathways between air emissions from the Lawrence Livermore National Laboratory’s (LLNL) Decontamination and Waste Treatment Facility (DWTF), single emission stack, and ecological receptors (i.e., plants and wildlife) present onsite and within a one-mile radius from the DWTF stack. This work plan outlines the procedures by which data collected as part of the previous investigations will be evaluated to assess risks to ecological receptors. It presents the problem formulation, initial conceptual site models, methods for characterizing exposure, toxicity, and risks that will be used if a more detailed “baseline” ecological risk assessment (BERA) is required.
Diffraction experiments produce datasets with rich multidimensional physics information such as microstructure, equations of state, crystal structure, elastoplastic properties, and other key inputs to LANL mission-essential multiphysics models. This information is typically extracted through a process called Rietveld refinement, which involves selecting appropriate models of the instrument, crystal structure, and microstructure, identifying suitable starting values, and then fitting often hundreds of model parameters using a sequence of empirical parameter turnon/off sequences within a non-global gradient-based optimization. Extensive user expertise is required to properly setup a refinement, identify appropriate models, and select initial parameter values close to truth, such that the refinement will yield parameter values that are optimally predictive. This is a very tedious manual process performed far after the beamline campaign has ended. As facilities have become capable of generating larger volumes of data, the limitation in throughput due to Rietveld refinement has led to a dramatic increase in unanalyzed data as opposed to an intended increase in new science. In our FY22 TED, we demonstrated an integrated toolset providing near real-time automated Rietveld analysis. If this toolset can be optimized to provide automated Rietveld analysis in real-time, this could alleviate the bottleneck in unanalyzed diffraction data, aid in decision-making during experiments, and increase efficiency of the facility.
During the operation of the Continuous Electron Beam Accelerator Facility (CEBAF), one or more unstable superconducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detect fast transient instabilities during these trip events. These challenges make the identification of an unstable cavity out of the hundreds installed at CEBAF a difficult and time-consuming task. To tackle these issues, a fast data acquisition system (DAQ) for the legacy SRF cavities has been developed, which records the sample at 5 kHz. A Principal Component Analysis (PCA) approach is being developed to identify anomalous SRF cavity behavior. We will discuss the present status of the DAQ system and PCA model, along with initial performance metrics. Overall, our method offers a practical solution for identifying unstable SRF cavities, contributing to increased beam availability and machine reliability.
The increasing need for optimal and sustainable use of cryogenic resources to support Fermilab’s scientific mission has highlighted the necessity of improving the Laboratory’s helium management practices. An assessment of cryogenic test facilities identified the Technical Division’s Industrial Building 3a (IB3A) as a key site requiring upgrades to integrate a helium recovery system. The IB3A facility is essential for characterizing and testing superconductors, cables, and coils for various R&D projects, including the US High-Luminosity LHC Accelerator Upgrade Project (AUP), Mu2e, and other external collaborations. Currently, the facility relies on 500 L helium Dewars and vents the vaporized helium directly into the atmosphere, leading to significant helium loss. Given the non-renewable nature of helium, recovering and reusing this resource is critical for the sustainability of Fermilab’s operations. To address this challenge, a project has been initiated to connect IB3A to an existing helium purification station and refrigeration system located in another building via a dedicated pipeline pass over the roof of several buildings. This solution will enable the efficient capture of vented helium, its transfer to the purification station, and subsequent liquefaction for reuse in future operations. The project includes a detailed design phase, specifying the pipeline route, flow control mechanisms, and integration with the existing cryogenic infrastructure, followed by phased implementation and commissioning. By implementing this pipeline connection and upgrading IB3A, Fermilab aims to significantly reduce helium waste, lower operational costs, and align with its commitment to sustainability. This initiative provides a model for resource-efficient cryogenic operations and reinforces the Laboratory’s capacity to support its science mission for the long term.
In an increasingly more data-driven world, the project set out to uncover the first principles of data-structure design, chart the immense design space they form, and build automation that can synthesize an optimal structure, or even a whole storage engine, for any given workload, hardware platform, and cost target. Data structures are at the center of every computational system and are directly responsible for its performance. Two core technical thrusts were defined: 1) Mapping design spaces for key data-centric abstractions (filters, hash functions, storage-engine layouts, neural-network topologies, blockchain protocols, image layouts, etc.). 2) Developing search & synthesis algorithms, initially analytical cost models, later neural-guided bi-level optimisers that navigate sextillions of candidate designs in seconds and materialise the best one as ready‐to-run code. This report distills the key insights, accomplishments, and impact.
Oak Ridge National Laboratory (ORNL) is leveraging its established capabilities and subject matter expertise in data curation, governance, management, national security, and risk assessment and mitigation to support the US Department of Energy (DOE) Grid Modernization Initiative. Using standards modeled by the National Institute of Standards and Technology (NIST), the Data Curation Network (DCN), the Oak Ridge Leadership Computing Facility (OLCF), and other leading organizations in the fields of energy research, high-performance computing, and national and homeland security, ORNL seeks to provide a federated approach to research data discovery, use, and interoperability.
This work aims to fabricate a small-scale battery module with the baseline RBD-CFRC and conduct mechanical crush test to develop an initial thermal runaway model. Test the adhesive properties of the RBD-CFRCs using their resin constituent, ultrasonic welding, and other resins employed today. Recommend a future direction for resin development to enable the welding of RBDCFRCs to dissimilar materials. Time and Cost Permitting. Iterate on resin development for flame resistance and adhesive properties, demonstrating how thermal runaway can be reduced or joining properties can be improved.
The study of multiparticle correlations and collectivity in the hot and dense matter created in collisions of heavy-ions as well as those of smaller systems such as proton--heavy-ion collisions has progressed to the point where detailed knowledge of the three-dimensional structure of the proton is needed to confront experimental data. We discuss results from a simple proof-of-principle initial state parton model which reproduces many features of the data on proton--heavy-ion collisions that are often ascribed to hydrodynamic flow. We outline how this model can be further improved with particular emphasis on missing elements in our understanding of the dynamical spatial and momentum structure of the proton.
This study evaluates the ability of a random forest classifier to identify tropical cyclone (TC) intensification or weakening prior to landfall over the western region of the Southwest Pacific Ocean (SWPO) basin. For both Australia mainland and SWPO island cases, when a TC first crosses land after spending ≥24 h over the ocean, the closest hour prior to the intersection is considered as the landfall hour. If the maximum wind speed (V max ) at the landfall hour increased or remained the same from the 24-h mark prior to landfall, the TC is labeled as intensifying and if the V max at the landfall hour decreases, the TC is labeled as weakening. Geophysical and aerosol variables closest to the 24 h before landfall hour were collected for each sample. The random forest model with leave-one-out cross validation and the random oversampling example technique was identified as the best-performing classifier for both mainland and island cases. The model identified longitude, initial intensity, and sea skin temperature as the most important variables for the mainland and island landfall classification decisions. Incorrectly classified cases from the test data were analyzed by sorting the cases by their initial intensity hour, landfall hour, monthly distribution, and 24-h intensity changes. TC intensity changes near land strongly impact coastal preparations such as wind damage and flood damage mitigations; hence, this study will contribute to improve identifying and prioritizing prediction of important variables contributing to TC intensity change before landfall.
A data-driven workflow approach is presented in this study for optimizing fracture spacing of multifractured horizontal wells (MFHW) in shale oil reservoirs. The workflow employs a simple well productivity model for the initial design of hydraulic fracturing well completions. This provides a transparent approach to the identification of key fracturing parameters affecting well productivity. The workflow uses transient pressure or production data to identify fracture interference. This offers a reliable and cost-effective means for assessment of well production potential in terms of optimization of fracture spacing in the MFHW. Result of a field case study indicated that three wells were drilled in an area with dense natural fractures, and the fracture spacing of MFHW in this area was short enough to effectively drain the stimulated reservoir volume (SRV), while the other three wells were drilled in an area with less natural fractures, and the fracture spacing of MFHW in this area could be shortened to double well productivity.
In this paper, we propose a method to estimate the position, orientation, and gain of a magnetic field sensor using a set of (large) electromagnetic coils. We apply the method for calibrating an array of optically pumped magnetometers (OPMs) for magnetoencephalography (MEG). We first measure the magnetic fields of the coils at multiple known positions using a well-calibrated triaxial magnetometer, and model these discreetly sampled fields using vector spherical harmonics (VSH) functions. We then localize and calibrate an OPM by minimizing the sum of squared errors between the model signals and the OPM responses to the coil fields. We show that by using homogeneous and first-order gradient fields, the OPM sensor parameters (gain, position, and orientation) can be obtained from a set of linear equations with pseudo-inverses of two matrices. The currents that should be applied to the coils for approximating these low-order field components can be determined based on the VSH models. Computationally simple initial estimates of the OPM sensor parameters follow. As a first test of the method, we placed a fluxgate magnetometer at multiple positions and estimated the RMS position, orientation, and gain errors of the method to be 1.0 mm, 0.2°, and 0.8%, respectively. Lastly, we calibrated a 48-channel OPM array. The accuracy of the OPM calibration was tested by using the OPM array to localize magnetic dipoles in a phantom, which resulted in an average dipole position error of 3.3 mm. The results demonstrate the feasibility of using electromagnetic coils to calibrate and localize OPMs for MEG.
We present the open-source radiative transfer code named HELIOS, which is constructed for studying exoplanetary atmospheres. In its initial version, the model atmospheres of HELIOS are one-dimensional and plane-parallel, and the equation of radiative transfer is solved in the two-stream approximation with nonisotropic scattering. A small set of the main infrared absorbers is employed, computed with the opacity calculator HELIOS-K and combined using a correlated-k approximation. The molecular abundances originate from validated analytical formulae for equilibrium chemistry. We compare HELIOS with the work of Miller-Ricci and Fortney using a model of GJ 1214b, and perform several tests, where we find: model atmospheres with single-temperature layers struggle to converge to radiative equilibrium; k-distribution tables constructed with ≳0.01 cm{sup −1} resolution in the opacity function (≲10{sup 3} points per wavenumber bin) may result in errors ≳1%–10% in the synthetic spectra; and a diffusivity factor of 2 approximates well the exact radiative transfer solution in the limit of pure absorption. We construct “null-hypothesis” models (chemical equilibrium, radiative equilibrium, and solar elemental abundances) for six hot Jupiters. We find that the dayside emission spectra of HD 189733b and WASP-43b are consistent with the null hypothesis, while the latter consistently underpredicts the observed fluxes of WASP-8b, WASP-12b, WASP-14b, and WASP-33b. We demonstrate that our results are somewhat insensitive to the choice of stellar models (blackbody, Kurucz, or PHOENIX) and metallicity, but are strongly affected by higher carbon-to-oxygen ratios. The code is publicly available as part of the Exoclimes Simulation Platform (exoclime.net).
Electron acceleration in solar flares is well known to be efficient at generating energetic particles that produce the observed bremsstrahlung X-ray spectra. One mechanism proposed to explain the observations is electron acceleration within contracting magnetic islands formed by magnetic reconnection in the flare current sheet. In a previous study, a numerical magnetohydrodynamic simulation of an eruptive solar flare was analyzed to estimate the associated electron acceleration due to island contraction. That analysis used a simple analytical model for the island structure and assumed conservation of the adiabatic invariants of particle motion. In this paper, we perform the first-ever rigorous integration of the guiding-center orbits of electrons in a modeled flare. An initially isotropic distribution of particles is seeded in a contracting island from the simulated eruption, and the subsequent evolution of these particles is followed using guiding-center theory. We find that the distribution function becomes increasingly anisotropic over time as the electrons’ energy increases by up to a factor of five, in general agreement with the previous study. In addition, we show that the energized particles are concentrated on the Sunward side of the island, adjacent to the reconnection X-point in the flare current sheet. Furthermore, our analysis demonstrates that the electron energy gain is dominated by betatron acceleration in the compressed, strengthened magnetic field of the contracting island. Fermi acceleration by the shortened field lines of the island also contributes to the energy gain, but it is less effective than the betatron process.
Using data from the NASA spacecraft Kepler , we study solar-like oscillations in red giant stars in the open cluster NGC 6811. We determine oscillation frequencies, frequency separations, period spacings of mixed modes, and mode visibilities for eight cluster giants. The oscillation parameters show that these stars are helium-core-burning red giants. The eight stars form two groups with very different oscillation power spectra; the four stars with the lowest Δ ν values display rich sets of mixed l = 1 modes, while this is not the case for the four stars with higher Δ ν . For the four stars with lowest Δ ν , we determine the asymptotic period spacing of the mixed modes, Δ P , which together with the masses we derive for all eight stars suggest that they belong to the so-called secondary clump. Based on the global oscillation parameters, we present initial theoretical stellar modeling that indicates that we can constrain convective-core overshoot on the main sequence and in the helium-burning phase for these ∼2 M {sub ⊙} stars. Finally, our results indicate less mode suppression than predicted by recent theories for magnetic suppression of certain oscillation modes in red giants.
We present the results of a Hubble Space Telescope ACS/HRC FUV, ACS/WFC optical study into the cluster populations of a sample of 22 Luminous Infrared Galaxies in the Great Observatories All-Sky LIRG Survey. Through integrated broadband photometry, we have derived ages and masses for a total of 484 star clusters contained within these systems. This allows us to examine the properties of star clusters found in the extreme environments of LIRGs relative to lower luminosity star-forming galaxies in the local universe. We find that by adopting a Bruzual and Charlot simple stellar population model and Salpeter initial mass function, the age distribution of the clusters declines as dN/dτ=τ{sup −0.9+/−0.3}, consistent with the age distribution derived for the Antennae Galaxies, and interpreted as evidence for rapid cluster disruption occurring in the strong tidal fields of merging galaxies. The large number of 10{sup 6} M{sub ⊙} young clusters identified in the sample also suggests that LIRGs are capable of producing more high-mass clusters than what is observed to date in any lower luminosity star-forming galaxy in the local universe. The observed cluster mass distribution of dN/dM=M{sup −1.95+/−0.11} is consistent with the canonical −2 power law used to describe the underlying initial cluster mass function (ICMF) for a wide range of galactic environments. We interpret this as evidence against mass-dependent cluster disruption, which would flatten the observed CMF relative to the underlying ICMF distribution.