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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Liquid Structure and Transport Properties of the Deep Eutectic Solvent Ethaline

A range of techniques including physical property measurements, neutron scattering experiments, ab initio molecular dynamics, and classical molecular dynamics simulations are used to probe the structural, thermodynamic, and transport properties of a deep eutectic solvent comprised of a 1:2 molar ratio of choline chloride and ethylene glycol. This mixture, known as Ethaline, has many desirable properties for use in a range of applications, and therefore, understanding its liquid structure and transport properties is of interest. Simulation results are able to capture experimental densities, diffusivities, viscosities, and structure factors extremely well. Here, the solvation environment is dynamic and dominated by different hydrogen bonding interactions. Dynamic heterogeneities resulting from hydrogen bonding interactions are quantified. Rotational dynamics of molecular dipole moments of choline and ethylene glycol are computed and found to exhibit a fast and slow mode.

25 ENERGY STORAGE↗
DOE OSTI2024

Learning dynamical systems from data: An introduction to physics-guided deep learning

Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely on strong modeling assumptions and expensive numerical integration, requiring significant computational resources and domain expertise. While deep learning (DL) provides efficient alternatives for modeling complex dynamics, they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret. Physics-guided DL aims to integrate first-principled physical knowledge into data-driven methods. It has the best of both worlds and is well equipped to better solve scientific problems. Recently, this field has gained great progress and has drawn considerable interest across discipline Here, we introduce the framework of physics-guided DL with a special emphasis on learning dynamical systems. We describe the learning pipeline and categorize state-of-the-art methods under this framework. We also offer our perspectives on the open challenges and emerging opportunities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

TorchBraid: High-Performance Layer-Parallel Training of Deep Neural Networks with MPI and GPU Acceleration

TorchBraid is a high-performance implementation of layer-parallel training for deep neural networks (DNNs) supporting MPI-based parallelism and GPU acceleration. Layer-parallel training has been developed to overcome the serialization inherent in forward and backward propagation of DNNs that limits utilization of computational resources in the strong scaling limit. To achieve this, TorchBraid integrates the PyTorch neural network framework with the state-of-the-art XBraid time-parallel library. Furthermore, this article presents the use and performance of TorchBraid, in addition to solutions for overcoming the algorithmic challenges inherent in combining automatic differentiation with layer-parallel. Results are presented with and without GPU acceleration for the Tiny ImageNet and MNIST image classification data sets, as well as recurrent neural networks. Overall, TorchBraid enables fast training of DNNs, both in a strong and weak scaling context. In addition to the TorchBraid software, several new advances in applying layer-parallel algorithms are detailed. Integration of layer-parallel with data-parallel algorithms is presented for the first time, showing the computational advantages of the combination. Standard deep learning techniques, like batch-normalization, are developed for layer-parallel training. Finally, a new approach combining layer-parallel with spatial coarsening in order to accelerate training for 3D image classification shows roughly a 10× speedup over serial execution.

Layer-parallel↗
DOE OSTI2021

Cellular mRNA triggers structural transformation of Ebola virus matrix protein VP40 to its essential regulatory form

The Ebola virus matrix protein VP40 forms distinct structures linked to distinct functions in the virus life cycle. Dimeric VP40 is a structural protein associated with virus assembly, while octameric, ring-shaped VP40 is associated with transcriptional control. In this study, we show that suitable nucleic acid is sufficient to trigger a dynamic transformation of VP40 dimer into the octameric ring. Deep sequencing reveals a binding preference of the VP40 ring for the 3' untranslated region of cellular mRNA and a guanine- and adenine-rich binding motif. Complementary analyses of the nucleic-acid-induced VP40 ring by native mass spectrometry, electron microscopy, and X-ray crystal structures at 1.8 and 1.4 Å resolution reveal the stoichiometry of RNA binding, as well as an interface involving a key guanine nucleotide. The host factor-induced structural transformation of protein structure in response to specific RNA triggers in the Ebola virus life cycle presents unique opportunities for therapeutic inhibition.

3′ UTR↗
DOE OSTI2020

Analysis of Geothermal Resources in Three Texas Counties

This project updates the geothermal resources beneath our oil and gas fields, as part of the research for the Texas GEO project. This report "Analysis of Geothermal Resources in Three Texas Counties" (October 2020) improves on previous mapping of the Texas resources for the counties of Crockett (West Texas), Jackson (central Gulf Coast) and Webb (South Texas). Through additional bottom-hole temperatures (BHT), the number of well sites increased from 532 to 5,410 in total for these counties. The improved methodology to calculate formation temperatures from 3.5 km (11,500 ft) to 10 km (32,800 ft) includes thermal conductivity values more closely related to the actual county geological formations, incorporated radiogenic heat production of formations, and the related mapped depth to basement. The results show deep temperatures as hotter than previously calculated, with temperatures of 150 degrees Celcius possible for Webb County between depths of 2.6 - 5.1 km, Jackson County between depths 3.0 - 5.4 km, and Crockett County between depths of 2.7 - 8.0 km.

10 km↗
DOE OSTI2023

Systematic Validation of Ensemble Cloud-Process Simulations using Polarimetric Radar Observations and Simulator over the NASA Wallops Flight Facility

The BiLateral Operational Storm-Scale Observation and Modeling (BLOSSOM) project was initiated to establish a long-term supersite to improve understanding of cloud physical states and processes as well as to support satellite and climate model programs over the WFF site via a bilateral approach of storm-scale observations and process modeling. This study highlights a noble systematic validation framework of the BLOSSOM ensemble cloud-process simulations through mixed-phase, light-rain, and deep-convective precipitation cases. The framework consists of creating a domain-shifted ensemble of large-scale forcing datasets, and configuring and performing cloud-process simulations with three different bulk microphysics schemes. Validation uses NASA S-band dual-POLarimetric radar (NPOL) observations in the form of statistical composites and skill scores via a polarimetric radar simulator and newly developed CfRad Data tool (CfRAD). While the simulations capture the overall structures of the reflectivity composites, polarimetric signals are still poorly simulated, mainly due to a lack of representation of ice microphysics diversity in shapes, orientation distributions, and their complex mixtures. Despite the limitation, this new ensemble-based validation framework demonstrates that 1) no particular forcing or microphysics scheme outperforms the rest and 2) the skill scores of coarse- and fine-resolution ensemble simulations with different domain-shifted forcing and microphysics schemes are highly correlated with each other with no clear improvement. On the other hand, this suggests that coarse-resolution ensemble simulations are relevant for selecting the best meteorological forcing and microphysics scheme before conducting computationally demanding large eddy simulations (LESs) in support of aircraft and satellite instrument development as well as cloud-precipitation-convection parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Multiagent Deep Reinforcement Learning-Enabled Dual-Branch Damping Controller for Multimode Oscillation

Here, this study develops a multiagent deep reinforcement learning (MADRL)-enabled framework for the decentralized cooperative control of a novel dual-branch (DB) damping controller for both low-frequency oscillation (LFO) and ultralow-frequency oscillation (ULFO). It has two branches, each of which consists of a proportional resonance (PR) and a second-order polynomial that is designed to handle target oscillation modes. To improve the robustness of the controller to system uncertainties, MADRL is developed, where multiagents are centrally trained to obtain the coordinated adaptive control policy while being executed in a decentralized manner to provide the optimal parameter setting for each controller with only local states. Comparisons with the IEEE 10-machine 39-bus system demonstrate that the proposed method achieves better robustness to uncertainties, lower communication delay, and single-point failure, as well as damping control performances for both LFO and ULFO.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Opportunities at the Sanford Underground Research Facility

The Sanford Underground Research Facility (SURF) has been operating for more than 15 years as an international facility dedicated to advancing compelling multidisciplinary underground scientific research in rare-process physics, as well as offering research opportunities in other disciplines. SURF laboratory facilities include a Surface Campus as well as campuses at the 4850-foot level (1490 m, 4300 m.w.e.) that host a range of significant physics experiments, including the LUX-ZEPLIN (LZ) dark matter experiment and the MAJORANA DEMONSTRATOR neutrinoless double-beta decay experiment. The CASPAR nuclear astrophysics accelerator completed the first phase of operation and is planning for the second phase beginning in 2024. SURF is also home to the Long-Baseline Neutrino Facility (LBNF) that will host the international Deep Underground Neutrino Experiment (DUNE). SURF offers world-class service, including an ultra-low background environment, low-background assay capabilities, and electroformed copper is produced at the facility. SURF is preparing to increase underground laboratory space. Plans are advancing for construction of new large caverns (nominally 100m L x 20m W x 24m H) on the 4850L (1485 m, 4100 mwe) on the timeframe of next-generation experiments (~2030). SURF plans to leverage existing advisory and community committees as well as engage the underground science community to inform plans for future laboratory space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Analysis of short‐ and long‐term system response during gas production from a gas hydrate deposit at the UBGH2‐6 site of the Ulleung Basin in the Korean East Sea

Abstract This study is a continuation of an investigation into the feasibility of long‐term production from a marine hydrate accumulation that has the properties and conditions of the UBGH2‐6 (UBGH2, Ulleung Basin Gas Hydrates 2; 2 is the number of the scientific expedition) site at the Ulleung Basin in the Korean East Sea. The 12.7 m‐thick system is in deep water (2157 m), but at 140 m below the seafloor. It is characterized by alternating hydrate‐free clays and muds and hydrate‐rich sand layers. The layered stratigraphy and the presence of mud layers favours the use of vertical wells rather than horizontal wells for production. The analysis indicates that production from such a hydrate accumulation is technically feasible, but the gas production rates are generally low. Water production accompanying gas production from this deposit appears manageable under all the scenarios investigated in this study, however, the water‐to‐gas ratio is high. Subsidence at the ocean floor at the end of a 14 day test is quite limited. However, there is significant uncertainty in the predictions of the geomechanical system's behaviour because they are not based on measured system properties but only on estimates/assumptions from analogues. The long‐term production potential of the reservoir at the site investigated here appears challenging because of the limited effectiveness of dissociation and large water production, in addition to substantial subsidence.

Moridis, George J.↗
DOE OSTI2023

ECCE unpolarized TMD measurements

For this work, we performed feasibility studies for various measurements that are related to unpolarized TMD distribution and fragmentation functions for the ECCE detector proposal. The processes studied include semi-inclusive Deep inelastic scattering (SIDIS) where single hadrons (pions and kaons) were detected in addition to the scattered DIS lepton. The single hadron cross sections and multiplicities were extracted as a function of the DIS variables x and Q 2 , as well as the semi-inclusive variables z, which corresponds to the momentum fraction the detected hadron carries relative to the struck parton and P T , which corresponds to the transverse momentum of the detected hadron relative to the virtual photon. The expected statistical precision of such measurements is extrapolated to accumulated luminosities of 10 fb –1 and potential systematic uncertainties are approximated given the deviations between true and reconstructed yields. The expected uncertainties are then used to obtain the expected impact on the related TMD distribution and fragmentation functions. We find that the ECCE detector proposal fulfills the physics requirements on these channels as detailed in the EIC Yellow Report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Are Supercells Resistant to Entrainment because of Their Rotation?

This research investigates a hypothesis posed by previous authors, which argues that the helical nature of the flow in supercell updrafts makes them more resistant to entrainment than nonsupercellular updrafts because of the suppressed turbulence in purely helical flows. It was further supposed that this entrainment resistance contributes to the steadiness and longevity of supercell updrafts. A series of idealized large-eddy simulations were run to address this idea, wherein the deep-layer shear and hodograph shape were varied, resulting in supercells in the strongly sheared runs, nonsupercells in the weakly sheared runs, and variations in the percentage of streamwise vorticity in updrafts among runs. Fourier energy spectrum analyses show well-developed inertial subranges in all simulations, which suggests that the percentages of streamwise and crosswise vorticity have little effect on turbulence in convective environments. Additional analyses find little evidence of updraft-scale centrifugally stable flow within updrafts, which has also been hypothesized to limit horizontal mass flux across supercell updrafts. Results suggest that supercells do have smaller fractional entrainment rates than nonsupercells, but these differences are consistent with theoretical dependencies of entrainment on updraft width, and with supercells being wider than nonsupercells. Thus, while supercells do experience reduced fractional entrainment rates and entrainment-driven dilution, this advantage is primarily attributable to increased supercell updraft width relative to ordinary convection, and has little to do with updraft helicity and rotation.

Peters, John M.↗
DOE OSTI2023

Chemical abrasion: the mechanics of zircon dissolution

Chemical abrasion is a technique that combines thermal annealing and partial dissolution in hydrofluoric acid (HF) to selectively remove radiation-damaged portions of zircon crystals prior to U–Pb isotopic analysis, and it is applied ubiquitously to zircon prior to U–Pb isotope dilution thermal ionization mass spectrometry (ID-TIMS). The mechanics of zircon dissolution in HF and the impact of different leaching conditions on the zircon structure, however, are poorly resolved. We present a microstructural investigation that integrates microscale X-ray computed tomography (µCT), scanning electron microscopy, and Raman spectroscopy to evaluate zircon dissolution in HF. We show that µCT is an effective tool for imaging metamictization and complex dissolution networks in three dimensions. Acid frequently reaches crystal interiors via fractures spatially associated with radiation damage zoning and inclusions to dissolve soluble high-U zones, some inclusions, and material around fractures, leaving behind a more crystalline zircon residue. Other acid paths to crystal cores include the dissolution of surface-reaching inclusions and the percolation of acid across zones with high defect densities. In highly crystalline samples dissolution is crystallographically controlled with dissolution proceeding almost exclusively along the c axis. Increasing the leaching temperature from 180 to 210 °C results in deeper etching textures, wider acid paths, more complex internal dissolution networks, and greater volume losses. How a grain dissolves strongly depends on its initial radiation damage content and defect distribution as well as the size and position of inclusions. As such, the effectiveness of any chemical abrasion protocol for ID-TIMS U–Pb geochronology is likely sample-dependent. We also briefly discuss the implications of our findings for deep-time (U-Th)/He thermochronology.

58 GEOSCIENCES↗
DOE OSTI2023

Lignin with controlled structural properties by N-heterocycle-based deep eutectic solvent extraction

The complex and heterogeneous nature of the lignin macromolecule has presented a lasting barrier to its utilization. To achieve high lignin yield, the technical lignin extraction process usually severely modifies and condenses the native structure of lignin, which is a critical drawback for its utilization in conversion processes. In addition, there is no method capable of separating lignin from plant biomass with controlled structural properties. Here, we developed an N-heterocycle-based deep eutectic solvent formed between lactic acid and pyrazole (La–Py DES) with a binary hydrogen bonding functionality resulting in a high affinity toward lignin. In this study, up to 93.7% of lignin was extracted from wheat straw biomass at varying conditions from 90 °C to 145 °C. Through careful selection of treatment conditions as well as lactic acid to pyrazole ratios, lignin with controlled levels of ether linkage content, hydroxyl group content, and average molecular weight can be generated. Under mild extraction conditions (90 °C to 120 °C), light-colored native-like lignin can be produced with up to 80% yield, whereas ether linkage–free lignin with low polydispersity can be obtained at 145 °C. Overall, this study offers a new strategy for native lignin extraction and generating lignin with controlled structural properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Environmental Life Cycle Assessment Spreadsheet tool for Deep Direct-Use Geothermal at the University of Illinois at Urbana-Champaign Campus

A Life Cycle Assessment (LCA) spreadsheet tool was developed to analyze potential environmental benefits of a deep direct-use (DDU) geothermal energy system (GES) at the University of Illinois at Urbana-Champaign (U of IL) campus. The LCA spreadsheet tool is a unique contribution to the feasibility study that provides further insight into the cradle-to-grave environmental impacts associated with the GES over the operating life time, as well as other DDU GES with similar objectives. The tool allows for a more in-depth analysis of the feasibility of DDU GES with respect to the overall environmental impacts. For the U of IL assessment, a doublet (two-well) system is evaluated, which is connected to aboveground mechanical system to supply heating to six agricultural research facilities. The additional of new equipment are assessed for the technical and economic feasibility. The results from this study will also allow geothermal resources from the entirety of the Illinois Basin (ILB) to be assessed and allow the DDU technology to be extended to additional areas of the ILB and other low-temperature sedimentary basins with similar characteristics.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Counter-Intuitive Structural Instability Aroused by Transition Metal Migration in Polyanionic Sodium Ion Host

The structure of polyanionic materials is conventionally known to be free of transition metal migration and structurally stable when storing/releasing sodium ions. Herein, the observation of enhanced cycling stability of a typical polyanionic cathode, Na 3 VCr(PO 4 ) 3 (NVCP) at lower temperature (-15 degrees C vs 30 degrees C), triggers the exploration of its structural origins with a surprising finding that the migratable nature of vanadium in NVCP leads to detrimental structural degradation of the polyanionic host upon cycling. The correlation between long range and short range structural change associated with this atomic migration is established via a strong combination of various in situ/ex situ characterization tools, revealing the essential V-to-Na1 site migration. Such transition metal migration is effectively suppressed when V atoms are pinned to their original position in the lattice by lowering the temperature. More importantly and practically, a room temperature-based deep sodiation strategy is further developed to recover the structure. Overall, this work challenges the long-standing assumption of the stability of the polyanionic framework structure and calls for urgent attention to the structural understanding of the NVCP system as well as strategy development for property enhancement.

25 ENERGY STORAGE↗
DOE OSTI2020

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗
DOE OSTI2026

Understanding neutrinos with accelerator beams and liquid argon time-projection chambers: ICARUS and DUNE

A global program of experiments has worked towards characterizing neutrino oscillation over the past few decades. However, important parameters remain to be measured, and mysteries remain to be elucidated. Current and upcoming experiments are targeting the open questions and probing the consistency of the neutrino oscillation paradigm. Likewise, the liquid argon (LAr) time-projection chamber (TPC) has emerged as a sensitive particle detection technology for neutrino experiments. A current generation of LAr TPC detectors are being used to study neutrinos while also gaining important experience in operating and analyzing with this technology. SBND, MicroBooNE, and ICARUS have collected or are collecting data from beams at Fermilab (near Chicago) to explore the possibility of a sterile neutrino and/or other beyond Standard Model (BSM) physics. SBND and ICARUS will be used to conduct a two-detector analysis as part of the Short Baseline Neutrino (SBN) Program. Additionally, these detectors are enabling important neutrino interaction studies necessary to prepare for the next generation of oscillation experiments. One such oscillation experiment that will come online over the next years is the Deep Underground Neutrino Experiment (DUNE), which will install multiple 10 kiloton LAr TPCs underground in South Dakota (south of Saskatchewan) to conduct oscillation measurements with neutrinos originating in a beamline at Fermilab. A detector complex will be installed at Fermilab as well, to study the beam before the expected flavour oscillations. This “near detector” will also employ a LAr TPC, with a segmented and pixel-based design, as well as other technologies to constrain uncertainties in the oscillation measurement by characterizing the beam and neutrino interactions. This talk will discuss the ICARUS and DUNE experiments, the LAr TPC detector technology, and the efforts to realize and leverage these experiments to better understand the properties of neutrinos.

Howard, Bruce L. [Fermilab]↗
DOE OSTI2020

Finding Strong Gravitational Lenses in the DESI DECam Legacy Survey

We perform a semi-automated search for strong gravitational lensing systems in the 9000 deg 2 Dark Energy Camera Legacy Survey (DECaLS), part of the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys. The combination of the depth and breadth of these surveys are unparalleled at this time, making them particularly suitable for discovering new strong gravitational lensing systems. We adopt the deep residual neural network architecture developed by Lanusse et al. for the purpose of finding strong lenses in photometric surveys. We compile a training sample that consists of known lensing systems in the Legacy Surveys and the Dark Energy Survey as well as non-lenses in the footprint of DECaLS. In this paper we show the results of applying our trained neural network to the cutout images centered on galaxies typed as ellipticals in DECaLS. The images that receive the highest scores (probabilities) are visually inspected and ranked. Here we present 335 candidate strong lensing systems, identified for the first time.

79 ASTRONOMY AND ASTROPHYSICS↗