Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “unprecedented”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database

As hydrokinetic turbine technologies continue to advance towards commercialization, public datasets on the performance characteristics for these devices and their flow field effects are invaluable to advance our understanding of these technologies and to validate analytical and numerical models. The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) collaborated with Sandia National Laboratories and the University of California at Davis to design, fabricate (at a 1:8.7 scale), and experimentally test a novel hydrokinetic turbine rotor design to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, the near-wake flow, cavitation effects, and noise generation. These state-of-the-art measurements demonstrate much of the complex physics associated with the flow through an unducted, horizontal-axis turbine, and they elucidate the performance characteristics and flow field effects at an unprecedented fidelity, accuracy and resolution. Measurements of powering coefficients (power, torque and thrust) as a function of tip-speed-ratio were performed. The dataset also includes unsteady measurements of driveshaft loading, blade strain, tower pressures, and radiated noise. Detailed flow mapping using laser Doppler velocimetry, and planar and stereo particle image velocimetry includes measurements of mean velocity and Reynolds stresses. Although the wake measurements are limited to less than half a diameter, they reveal the complex flow patterns in the near-wake structure of the rotor. The full database, available at the United States Department of Energy’s marine and hydrokinetic data repository, includes tunnel and model Computer Aided Design geometry files and inflow data sufficient for a “Model-the-Test” computational Verification and Validation study.

13 HYDRO ENERGY↗
DOE OSTI2020

A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication

We report accurate estimation of cropping intensity (CI), an indicator of food production, is well aligned with the ongoing efforts to achieve sustainable development goals (SDGs) under diminishing natural resources. The advancement in satellite remote sensing provides unprecedented opportunities for capturing CI information in a spatially continuous manner. However, challenges remain due to the lack of generalizable algorithms for accurately and efficiently mapping global CI with a fine spatial resolution. In this study, we developed a 30-m planetary-scale CI mapping framework with the reconstructed time series of Normalized Difference Vegetation Index (NDVI) from multiple satellite images. Using a binary crop phenophase profile indicating growing and non-growing periods, we estimated pixel-by-pixel CI by enumerating the total number of valid cropping cycles during the study years. Based on the Google Earth Engine cloud computing platform, we implemented the framework to estimate CI during 2016–2018 in eight geographic regions across continents that are representative of global cropping system diversity. Comparison with PhenoCam network data in four cropland sites suggests that the proposed framework is capable of capturing the seasonal dynamics of cropping practices. Spatially, overall accuracies based on validation samples range from 80.0% to 98.9% across different regions worldwide. Regarding the CI classes, single cropping systems are associated with more robust and less biased estimations than multiple cropping systems. Finally, our CI estimates reveal high agreement with two widely used land surface phenology products, including Vegetation Index and Phenology V004 (VIP4) and Moderate Resolution Imaging Spectroradiometer Land Cover Dynamics (MCD12Q2), meanwhile providing much more spatial details. Due to its robustness, the developed CI framework can be potentially generalized to produce global fine resolution CI products for food security and other applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

TROPOMI observations allow for robust exploration of the relationship between solar-induced chlorophyll fluorescence and terrestrial gross primary production

Solar-induced chlorophyll fluorescence (SIF) observed by satellites has advanced the monitoring of terrestrial photosynthesis regionally and globally. The relationship between SIF and gross primary production (GPP) at leaf, canopy, and ecosystem scales has received tremendous attention in recent years. It remains controversial whether the SIF-GPP relationship at the ecosystem scale is universal or dependent upon vegetation type. New SIF observations from the TROPOspheric Monitoring Instrument (TROPOMI) with unprecedented high spatial and temporal resolution provide a new opportunity to elucidate the SIF-GPP relationship. Here, we examine the SIF-GPP relationship for seven major vegetation types across the U.S. with TROPOMI SIF and in-situ GPP data for 83 eddy covariance flux sites. We find that TROPOMI SIF shows a strong and consistent relationship with tower-based GPP at both satellite footprint and grid-cell levels. The slope of the SIF-GPP relationship is similar among all the vegetation types except croplands, demonstrating a nearly universal (converging to ~13.5 g C m -2 d -1 /W m -2 μm -1 sr -1) rather than vegetation type-specific SIF-GPP relationship. This confirms that TROPOMI SIF can be used as a proxy for GPP across a wide variety of vegetation types and can also be used to quantify GPP by avoiding uncertainty associated with land cover maps. The C 4 crops have a much higher slope than the C 3 crops, and therefore croplands tend to have a higher slope than C 3 -dominated vegetation types (e.g., forests, shrublands, savannas). We also find that the TROPOMI SIF is well correlated with GPP under normal or wetter conditions, while their relationship becomes weaker under water stress. In conclusion, our TROPOMI-based study could improve our understanding of the SIF-GPP relationship at the ecosystem scale and advance the mapping of GPP globally with SIF observations from space.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites

In tropical forests, leaf phenology signals leaf-on/off status and exhibits considerable variability across scales from a single tree-crown to the entire forest ecosystem. Such phenology signals importantly regulate large-scale biogeochemical cycles and regional climate. PlanetScope CubeSats data with a 3-m resolution and near-daily global coverage provide an unprecedented opportunity to monitor both fine- and ecosystem-scale phenology variability along large environmental gradients. However, a scalable method that accurately characterizes leaf phenology from PlanetScope with biophysically meaningful metrics remains lacking. Here we developed an index-guided, ecologically constrained autoencoder (IG-ECAE) method to automatically derive a deciduousness metric (i.e. percentage of tree canopies with leaf-off status within an image pixel) from PlanetScope. The IG-ECAE first estimated the reflectance spectra of leafy/leafless canopies based on their spectral indices characteristics, then used the derived reflectance spectra to guide an autoencoder deep learning method with additional ecological constraints to refine the reflectance spectra, and finally used linear spectral unmixing to estimate the relative abundance of leafless canopies (or deciduousness) per PlanetScope image pixel. We tested the IG-ECAE method at 16 tropical forest sites spanning multiple continents and a large precipitation gradient (1470-2819 mm year -1 ). Among these sites, we evaluated the PlanetScope-derived deciduousness with corresponding measures derived from WorldView-2 (n=9 sites) and local phenocams (n=9 sites). Our results show that PlanetScope-derived deciduousness agrees: 1) with that derived from WorldView-2 at the patch level (90m×90m) with r 2 =0.89 across all sites; and 2) with that derived from phenocams to quantify ecosystem-scale seasonality with r 2 ranging from 0.62-0.96. These results demonstrate the effectiveness and scalability of IG-ECAE in characterizing the wide variability in deciduousness across scales from pixels to forest ecosystems, and from a single date to the full annual cycle, indicating the potential for using high-resolution satellites to track the large-scale phenological patterns and response of tropical forests to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Reversible magnetism transition at ferroelectric oxide heterointerface

Oxide heterointerface is a platform to create unprecedented two-dimensional electron gas, superconductivity and ferromagnetism, arising from a polar discontinuity at the interface. In particular, the ability to tune these intriguing effects paves a way to elucidate their fundamental physics and to develop novel electronic/magnetic devices. Here, we report for the first time that a ferroelectric polarization screening at SrTiO 3 /PbTiO 3 interface is able to drive an electronic construction of Ti atom, giving rise to room-temperature ferromagnetism. Surprisingly, such ferromagnetism can be switched to antiferromagnetism by applying a magnetic field, which is reversible. A coupling of itinerant electrons with local moments at interfacial Ti 3d orbital was proposed to explain the magnetism. The localization of the itinerant electrons under a magnetic field is responsible for the suppression of magnetism. These findings provide new insights into interfacial magnetism and their control by magnetic field relevant interfacial electrons promising for device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Efimov-like states and quantum funneling effects on synthetic hyperbolic surfaces

Engineering lattice models with tailored inter-site tunnelings and onsite energies could synthesize essentially arbitrary Riemannian surfaces with highly tunable local curvatures. Here, we point out that discrete synthetic Poincaré half-planes and Poincaré disks, which are created by lattices in flat planes, support infinitely degenerate eigenstates for any nonzero eigenenergies. Such Efimov-like states exhibit a discrete scaling symmetry and imply an unprecedented apparatus for studying quantum anomaly using hyperbolic surfaces. Furthermore, all eigenstates are exponentially localized in the hyperbolic coordinates, signifying the first example of quantum funneling effects in Hermitian systems. As such, any initial wave packet travels towards the edge of the Poincaré half-plane or its equivalent on the Poincaré disk, delivering an efficient scheme to harvest light and atoms in two dimensions. Furthermore, our findings unfold the intriguing properties of hyperbolic spaces and suggest that Efimov states may be regarded as a projection from a curved space with an extra dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. In this study, using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (–0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (–0.12 ± 0.08 °C/10a), despite some daynight process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Shining light on nanoscale ‘vine-on-stick’ eutectic structures in the Al-Ce-Ni system

Multiphase eutectics often comprise entangled solid phases with nanoscale periodicity, making it difficult to unravel their 3D connectivity using conventional 2D techniques. Among such systems, the three-phase eutectic Al-Al 11 Ce 3 -Al 3 Ni stands out for its ultrafine (∼100 nm) interphase spacing and promising creep resistance, yet its microstructure remains relatively unexplored despite its potential for high-temperature applications. Here, we use scanning hard X-ray microscopy with an unprecedented ∼10 nm pixel size to resolve its 3D morphology. Reconstructions reveal a novel “vine-on-stick” motif, wherein Al 11 Ce 3 wraps around Al 3 Ni pillars. Analysis of phase tortuosities confirms that Al 11 Ce 3 exhibits more convoluted morphologies than Al 3 Ni. No orientation relationship was observed between the two intermetallics, suggesting that growth is controlled by local solute gradients rather than epitaxy. Fragmentation of intermetallics along their longitudinal axis suggests a Rayleigh-type breakup mechanism in solid state. The “vine-on-stick” pattern may generalize to other alloy systems with variable interfacial anisotropies and low mutual solubilities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗
DOE OSTI2022

2.0 - MOOSE: Enabling massively parallel multiphysics simulation

The last 2 years have been a period of unprecedented growth for the MOOSE community and the software itself. The number of monthly visitors to the website has grown from just over 3,000 to now averaging 5,000. In addition, over 1,800 pull requests have been merged since the beginning of 2020, and the new discussions forum has averaged 600 unique visitors per month. The previous publication has been cited over 200 times since it was published 2 years ago. This paper serves as an update on some of the key additions and changes to the code and ecosystem over the last 2 years, as well as recognizing contributions from the community.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Moisture-mineral interactions drive bacterial and organic matter turnover in glacier-sourced riparian sediments undergoing pedogenesis

Glacial recession is occurring at unprecedented rates resulting in increased sediment accumula-tions in some riverine ecosystems. Increased sediment deposition has implications for ecosystem stability (e.g., floods and river paths) and environmental services (e.g., carbon sequestration). Soils and sediments have an enormous potential to retain carbon (C), predominantly due to sorp-tion to mineral surfaces. However, C persistence may be sensitive to climate-change induced temperature and moisture variations. We coupled ultrahigh resolution organic matter composition classification with bacterial characterization and respiration measurements to test the combined effects of temperature (4 vs 20°C) and moisture (50 vs 100% water-filled pore space) on C turn-over in sediments maintained under different mineralogical conditions (illite-amended vs non-amended). Here we show that the inhibition of CO 2 emissions from the combined effect of in-creased moisture content and illite was reflected in the turnover of key molecular signatures, such as the nominal oxidation state of C, often irrespective of temperature. However, shifts in bacteri-al communities from a coupled moisture-mineral interaction, were temperature-dependent. Our results highlight the importance of moisture in driving mineral-organic interactions and suggest that C in clay-rich, water-saturated sediments is both thermodynamically unfavorable and miner-al-protected from microbial consumption.

58 GEOSCIENCES↗
DOE OSTI2025

New directions and principles for solvent extraction for recovery of lithium from aqueous brines and mineral leachates: A brief review

Increasing demand for lithium for manufacturing of batteries is fueling the unprecedented search for improved recovery and alternative sources. Wider source distribution, lower energy consumption, and greater sustainability make extraction of lithium from brines, both natural and process-derived, an attractive alternative to mineral ores. Solvent extraction, used industrially for production of metals, salts, and pharmaceuticals, has been investigated as a methodology for lithium recovery for several decades. However, industrial application of solvent extraction for lithium recovery has so far been limited. In contrast, direct lithium extraction using adsorbents based on inorganic minerals has rapidly advanced from research to commercialization. A comparison of solvent extraction processes to adsorption highlights these issues and explains the preference for adsorbents. Although the application of solvent extraction has been criticized for use of large amounts of acid, alkali, and organic solvents, steady progress has been made to improve its potential for industrial lithium production, spurred on generally by the advantages of solvent extraction in selectivity and throughput. Previously developed beta-diketone, organophosphate, and crown ether ligands are being adapted and improved. Their novel use with ionic liquids, deep eutectic solvents, and membrane technologies promises to expand capabilities for extraction of lithium from dilute aqueous sources while improving sustainability. Possibilities for further discovery and innovation abound. In this review, we provide a unique perspective from the field of solvent extraction starting with fundamentals such as ion-transfer theory and apply them to understanding lithium selectivity and extraction behavior. In conclusion, the results are cast in the light of the practical realities of developing economical solvent extraction processes.

Brine↗
DOE OSTI2022

Diversity in the soil virosphere: to infinity and beyond?

Viruses are key members of Earth’s microbiomes, shaping microbial community composition and metabolism. Here, we describe recent advances in 'soil viromics', that is, virus-focused metagenome and metatranscriptome analyses that offer unprecedented windows into the soil virosphere. Given the emerging picture of high soil viral activity, diversity, and dynamics over short spatiotemporal scales, we then outline key eco-evolutionary processes that we hypothesize are the major diversity drivers for soil viruses. We argue that a community effort is needed to establish a 'global soil virosphere atlas' that can be used to address the roles of viruses in soil microbiomes and terrestrial biogeochemical cycles across spatiotemporal scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Unraveling plant–microbe symbioses using single-cell and spatial transcriptomics

Plant-microbe symbioses require intense interaction and genetic coordination to successfully establish in specific cell types of the host and symbiont. Traditional RNA-seq methodologies lack the cellular resolution to fully capture these complexities, but single-cell and spatial transcriptomics (ST) are now allowing scientists to probe symbiotic interactions at an unprecedented level of detail. Here, we discuss the advantages that novel spatial and single-cell transcriptomic technologies provide in studying plant-microbe endosymbioses and highlight key recent studies. Finally, we consider the remaining limitations of applying these approaches to symbiosis research, which are mainly related to the simultaneous capture of both plant and microbial transcripts within the same cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Circular dichroism in hard X-ray photoelectron diffraction observed by time-of-flight momentum microscopy

X-ray photoelectron diffraction (XPD) is a powerful technique that yields detailed structural information of solids and thin films that complements electronic structure measurements. Among the strongholds of XPD we can identify dopant sites, track structural phase transitions, and perform holographic reconstruction. High-resolution imaging of k ll -distributions (momentum microscopy) presents a new approach to core-level photoemission. It yields full-field k x -k y XPD patterns with unprecedented acquisition speed and richness in details. Here, we show that beyond the pure diffraction information, XPD patterns exhibit pronounced circular dichroism in the angular distribution (CDAD) with asymmetries up to 80%, alongside with rapid variations on a small k ll -scale (0.1 Å -1 ). Measurements with circularly-polarized hard X-rays (hν = 6 keV) for a number of core levels, including Si, Ge, Mo and W, prove that core-level CDAD is a general phenomenon that is independent of atomic number. The fine structure in CDAD is more pronounced compared to the corresponding intensity patterns. Additionally, they obey the same symmetry rules as found for atomic and molecular species, and valence bands. Further, the CD is antisymmetric with respect to the mirror planes of the crystal, whose signatures are sharp zero lines. Calculations using both the Bloch-wave approach and one-step photoemission reveal the origin of the fine structure that represents the signature of Kikuchi diffraction. To disentangle the roles of photoexcitation and diffraction, XPD has been implemented into the Munich SPRKKR package to unify the one-step model of photoemission and multiple scattering theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Development of a liquid-helium free cryogenic sample holder with mK temperature control for autonomous electron microscopy

The automated and autonomous cryogenic transmission electron microscopy (Cryo-EM) demands a sample holder capable of maintaining temperatures below 10 K with precise control, long holding times, and minimal helium use. Rising to this challenge, we initiated an ambitious project to develop a novel closed-cycle cryocooler-based cryogenic sample holder that operates without the use of liquid helium and the consumption of gaseous helium. Here, this article presents the design, construction, and experimental testing of the initial prototype, which achieves an ultimate temperature of 5.6 K with exceptional stability close to 1mK, while providing a wide temperature control range from 295 K to 5.6 K, marking a clear advancement in cryo-EM holder development. While the prototype was not designed for atomic resolution imaging and thus lacks a sturdy support system to mitigate mechanical vibrations from the cryocooler's pulsed tube, this innovative approach successfully demonstrates proof of concept. It offers unprecedented capabilities for state-of-the-art cryogenic microscopy and microanalysis in materials and biological sciences.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Detecting Magnon-phonon coupling in yttrium iron garnet with variable temperature STEM-EELS

Magnons, quanta of spin wave excitations in magnetically ordered materials, have been identified as candidates for several potentially transformative technologies in recent years. Macroscopic techniques, such as neutron scattering or Raman spectroscopy, can be used to identify and analyze magnons, but provide relatively delocalized information about the sample. Understanding how the bonding and local structure of a material interacts with, and influences, the magnon population in a material is a crucial step toward the ability to produce any real-world application utilizing magnons. By leveraging the combined spatial resolution of scanning transmission electron microscopy (STEM) and the energy resolution of monochromated electron energy-loss spectroscopy (EELS) nanoscale analysis of magnons can be performed. While the weak interaction of magnons with the electron beam makes magnon EELS challenging on reasonable timescales, magnon-phonon coupling can be leveraged to understand magnons through their effect on the more easily measured phonons. Here, we examine yttrium iron garnet (YIG) flakes, and demonstrate non-linear, temperature-dependent shifts in the phonon frequencies, consistent with previously described magnon-phonon coupling effects. The ability to measure the temperature-dependence of vibrational frequencies with high precision in individual nanoscale flakes, demonstrates the ability to study magnon-phonon coupling in the STEM with unprecedented spatial resolution.

Reifsnyder, Alexander [ORNL]↗
DOE OSTI2024

Multivariate prognosis of battery advanced state of health via transformers

De-risking energy storage investments necessary to meet CO 2 reduction targets requires a deep understanding of the connections between battery health, design, and use. The historical definition of the battery state of health (SOH) as the percentage of current versus initial capacity is inadequate for this purpose, motivating an expanded SOH consisting of an interrelated set of descriptors including capacity, energy, ionic and electronic impedances, open-circuit voltages, and microstructure metrics. In this work, we introduce deep transformer networks for the simultaneous prognosis of 28 battery SOH descriptors using two cycling datasets representing six lithium-ion cathode chemistries, multiple electrolyte/anode compositions, and different charge-discharge scenarios. The accuracy of these predictions for battery life (with an unprecedented mean absolute error of 19 cycles in predicting end of life for a lithium-iron-phosphate fast-charging dataset) illustrates the promise of deep learning toward providing enhanced understanding and control of battery health.

25 ENERGY STORAGE↗