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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Physics-based Induced Earthquake Forecasting: Process Understanding, and Hazards Mitigation

Disposal of saltwater co-produced with oil and gas is linked to elevated seismicity in the Central and Midwest US. There is a concern that these events may lead to widespread damage and an overall increase in seismicity. Thus an improved understanding of the spatially and temporally variable deformation and stress field associated with fluid injection operation is critically necessary for evaluating time-varying seismic hazards. Despite the improvements in seismic monitoring capacity and the resulting decrease in the magnitude detection threshold, estimates of induced earthquake probability remain elusive due to insufficient models incapable of accounting for the complex physics governing the process of induced seismicity. The proposed research effort will comprehensively analyze, integrate, and interpret geodetic, injection, and seismic data in the vicinity of the injection sites in Oklahoma to resolve the 4-dimensional distribution of pore pressure and stress in the shallow crust. This project, in particular, is focused on exploring the statistical relation between injection operation and increased earthquake hazard. The amplitude of and the extent to which pore pressure changes are determined by some factors, in particular, the hydrogeological properties of the rocks, such as diffusivity. Thus the available deformation data will be used to constrain hydrogeological properties of the medium, to accurately resolve the evolution of crustal stresses due to fluid injection. Having the time-varying models of stress changes, a statistical framework will be implemented to estimate the time-dependent probability of large earthquakes on the nearby fault systems. These data and models help to improve seismic hazard estimates and aid in constructing operational-induced earthquake forecast models. This information can also be integrated into the updated U.S. National Seismic Hazard Map, which local communities and authorities use in their earthquake risk estimates and mitigation efforts.

58 GEOSCIENCES↗
DOE OSTI2023

Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels

Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22–20 μm) and micro-eukaryotes (20–200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Getting Warmer: IceCube Nears Freeze Out

IceCube has recently detected a diffuse population of high-energy neutrinos arising from the Milky Way. We use this high-significance detection to place new limits on dark matter (DM) annihilation to neutrinos with two complementary approaches. The first method uses the background-subtracted Galactic longitude distribution of shower events to place a conservative bound on the DM annihilation cross section that does not rely on any assumed Galactic cosmic ray emission model; the resulting limits on the velocity-averaged annihilation cross section improve upon existing bounds by factors of a few. The second method uses the template-dependent neutrino energy spectra from the Inner Galaxy, inferred under different Galactic cosmic ray emission models. This complementary approach shows that the inferred Galactic neutrino intensities are already sensitive to DM contributions near the thermal-relic benchmark for a range of TeV-scale DM masses, though this comparison is more model-dependent. Our results demonstrate that measurements of diffuse Galactic neutrino emission can be used as a powerful probe of DM annihilation into neutrinos. Future observations with IceCube-Gen2 and KM3NeT will substantially extend this sensitivity, potentially allowing a decisive test of the thermal freeze-out mechanism with Galactic neutrino observations.

Mukhopadhyay, Mainak [Fermilab; Chicago U., KICP; ↗
DOE OSTI2022

Emerging Trends and Systemic Issues Influencing Today’s U.S. Electric Grid

With increasing shifts from vertically integrated to horizontally structured operations and from centralized to distributed electric power delivery, today’s electric power grid (the “grid”) operators and designers face the challenge of creating an architecture that accommodates a host of diverse requirements. The grid’s modes of operation must address concerns of reliability and stability, new deployments of renewable energy sources, threats from cyber-attacks and natural disasters, and increasingly distributed system operations. Grid modernization calls for a reliable, affordable, sustainable, agile, secure, and resilient grid. However, the modernization of the U.S. power grid is hampered by mounting complexity and diverging objectives from owners and operators and is consequently risky and fraught with potential missteps. Flawed architecture, design, and implementation will lead to stranded investments and lost opportunities. A principled approach to minimize risk and develop a robust grid of the future is to begin with a sound architecture for the grid to inform the design process. Architecture development starts with the context of influencing factors that provide constraints as well as driving goals. This report provides the context of emerging trends and cross-cutting systemic issues in the U.S. electric power grid and serves as a vital input for grid architecture development.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗
DOE OSTI2021

Chemical Understanding of Actinide Separations

This work provides a broad overview of the separation processes used to isolate actinides and the experimentally and computationally determined chemical characteristics that define those separations. The redox chemistry of the actinides plays a pivotal role in both aqueous and pyrochemical processing separations. The near-overlapping energies of the 6d and 5f orbitals in the light actinides allow for facile adjustment of actinide oxidation states, which is used in many established separation methods. In contrast, the stable, generally 3+ oxidation states of the mid- and heavy actinides can make it difficult to separate them from the similarly lanthanides(III). In aqueous separations, the tendency of the actinides to form anionic and neutral aqueous complexes with a variety of complexants (especially soft donors) is used to achieve high separation factors between chemically similar elements in both solid–liquid separations and liquid–liquid extraction. This selectivity can be further tuned through the use of specialized organic or solid-phase ligands. Pyroprocessing separations utilize the unique redox behavior of the actinides to adjust their distribution between a molten salt electrolyte and either a solid electrode or molten metal phase. Atomic-level insights into the mechanisms underlying actinide separation processes, with the ultimate goal of predicting separation behavior, can be provided by electronic structure and statistical mechanical-based calculation methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

(La 0.8 Sr 0.2 ) 0.98 MnO 3-δ -Zr 0.92 Y 0.16 O 2-δ :PrOx for oxygen electrode supported solid oxide cells

(La 0.8 Sr 0.2 ) 0.98 MnO 3-δ (LSM)- Zr 0.92 Y 0.16 O 2-δ (YSZ) has been widely studied as the cathode for solid oxide fuel cells (SOFCs), but its low activity has been a cell performance limiting factor. Herein, LSM-YSZ:PrO x composite is developed as an active electrocatalyst for both oxygen reduction and evolution reactions. A single step PrO x infiltration into LSM-YSZ lowers the polarization resistance (Rp) 10–20 times depending on the test temperature. Distribution of relaxation times (DRT) calculation reveals that adding PrO x affects surface exchange between adsorbed/desorbed oxygen and lattice oxygen, and oxygen dissociative adsorption/desorption. A symmetrical cell with a thin YSZ electrolyte sandwiched between thick LSM-YSZ:PrO x electrode-supports is developed and its oxygen generation performance and stability are evaluated under various current densities and temperatures. Finally, reversible solid oxide cell (ReSOC) performance is also reported for LSM-YSZ:PrO x supported cells with the oxide fuel electrode Sr 0.95 (Ti 0.3 Fe 0.63 Ni 0.07 )O 3-δ (STFN).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Relative Activities of the β-Ketoacyl-CoA and Acyl-CoA Reductases Influence the Product Profile and Flux in a Reversed β-Oxidation Pathway

The β-oxidation pathway, normally involved in the catabolism of fatty acids, can be functionally made to act as a fermentative, iterative, elongation pathway when driven by the activity of a trans-enoyl-CoA reductase (TER). Here, the terminal acyl-CoA reduction to alcohol can occur on substrates with varied chain lengths, leading to a broad distribution of fermentation products in vivo. Tight control of the average chain length and product profile is desirable, as the chain length greatly influences the molecular properties and the commercial value. Lacking a termination enzyme with a narrow chain length preference, we sought alternative factors that could influence the product profile and pathway flux in the iterative pathway. In this study, we reconstituted the reversed β-oxidation (R-βox) pathway in vitro with a purified tri-functional complex (FadBA) responsible for the thiolase, enoyl-CoA hydratase, and hydroxyacyl-CoA dehydrogenase activities, a TER, and an acyl-CoA reductase. Using this system, we determined the rate-limiting step of the elongation cycle and demonstrated that by controlling the ratio of these three enzymes and the ratio of NADH and NADPH, we can influence the average chain length of the alcohol product profile.

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

Effects of Cloud Liquid-Phase Microphysical Processes in Mixed-Phase Cumuli Over the Tibetan Plateau

Numerical simulations often overpredict precipitation over the Tibetan Plateau (TP). To examine the factors causing precipitation overprediction, different parameterizations of liquid-phase microphysical processes (accretion, autoconversion, and entrainment-mixing) are implemented into the Morrison microphysics scheme to simulate a TP precipitation event in summer with the Weather Research and Forecasting (WRF) model. The general spatial distribution and temporal trend of precipitation are captured by all simulations, but the precipitation rate is overpredicted. The results from sensitivity experiments suggest that compared to other examined liquid-phase processes, the accretion process is more important in precipitation simulation over the TP region. Further investigation with the Heidke skill scores reveals that accretion parameterization that takes into account the raindrop size produces the most accurate results in terms of the total surface precipitation. This parameterization suppresses spurious accretion and does not produce liquid-phase precipitation until cloud droplets are big enough. Here, it is also confirmed that increasing the model resolution can reduce precipitation overprediction. Results from the case study are confirmed by the use of a one-month simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of Autoconversion Representation in E3SMv2 Using an Ensemble of Large-Eddy Simulations of Low-Level Warm Clouds

In numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate (Au), which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local Au is commonly parameterized as a function of DSD moments: cloud droplet number (n c ) and mass (q c ) concentrations. When applied in a large-scale model, the grid-mean Au must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large-eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local Au, as well as its spatial variability. The analysis of an ensemble of warm low-level cloud cases shows that the E3SMv2 formulation represents the Au reasonably well compared to the horizontally averaged explicitly computed rate from LES. The agreement, however, comes from a combination of an underestimated E3SM-tuned local Au rate and an overestimated subgrid cloud variability enhancement factor. The latter bias is traced to neglecting the horizontal variability of n c and its co-variability with q c in parameterizing the grid-mean Au.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Light absorption enhancement of black carbon in a pyrocumulonimbus cloud

Abstract Pyrocumulonimbus (pyroCb) firestorm systems have been shown to inject significant amounts of black carbon (BC) to the stratosphere with a residence time of several months. Injected BC warms the local stratospheric air, consequently perturbing transport and hence spatial distributions of ozone and water vapor. A distinguishing feature of BC-containing particles residing within pyroCb smoke is their thick surface coatings made of condensed organic matter. When coated with non-refractory materials, BC’s absorption is enhanced, yet the absorption enhancement factor ( E abs ) for pyroCb BC is not well constrained. Here, we perform particle-scale measurements of BC mass, morphology, and coating thickness from inside a pyroCb cloud and quantify E abs using an established particle-resolved BC optics model. We find that the population-averaged E abs for BC asymptotes to 2.0 with increasing coating thickness. This value denotes the upper limit of E abs for thickly coated BC in the atmosphere. Our results provide observationally constrained parameterizations of BC absorption for improved radiative transfer calculations of pyroCb events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Energy and particle balance during plasma detachment in a long-leg divertor configuration

Abstract Comprehensive studies of energy and particle balances in the transition to plasma detachment in an alternative divertor configuration with long outer legs are shown. Numerical simulations are performed with the 2D code suite SOLPS 4.3, using a disconnected double null grid with narrow, tightly baffled long poloidal leg divertors at the outer lower target and outer upper target. A particle count scan is performed using the ‘closed gas box’ model, where the tunable parameter in the simulations is the total number of deuterium particles in the simulation space and all other parameters are held fixed, including a constant input power and trace neon impurity radiation, to assess the physics of the transition to detachment in the system as the particle count increases. Three main aspects of the physics of divertor detachment are addressed: the criteria for the local onset of divertor detachment in each of the divertors, the distribution of heat flux and other plasma parameters between the four divertors as each divertor transitions to detachment, and the role of perpendicular transport in the transition to the detached regime. A synergistic mechanism by which the cross-field transport is reduced by factors associated with the onset of plasma recombination effects is identified. These results are compared to the existing understanding of the physics of the transition to plasma detachment in standard divertors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Fourier coefficients of noninterdependent collective motions in heavy-ion collisions

Here, we present a scenario in heavy-ion collisions where different modes of collective motions are noninterdependent, driven by factorized actions in the created nuclear medium. Such physics mechanisms could each dominate at a distinct evolution stage, or coexist simultaneously. If the probability of particle emission is modulated by each nondependent collective motion with a single-harmonic Fourier expansion, the particle azimuthal distribution should be the product of all these expansions. Consequently, nonleading cross terms between collectivity modes appear, and their contributions to experimental observables could be significant. In particular, we argue that the chiral magnetic effect (CME) and elliptic flow can develop separately, with their convolution affecting the observable that is sensitive to the shear-induced CME. We will use the event-by-event anomalous-viscous fluid dynamics model to illustrate the effects of this scenario. Besides giving insights into searches for the CME, we also propose feasible experimental tests based on conventional flow harmonics, and demonstrate the emergence of nonleading cross terms with a multiphase transport model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Optimizing Fast Charging and Wetting in Lithium-Ion Batteries with Optimal Microstructure Patterns Identified by Genetic Algorithm

To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ∼6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%–2%) is required to dramatically improve the wetting (5–20 times) compared to an unstructured electrode.

25 ENERGY STORAGE↗
DOE OSTI2022

Massively distributed fiber strain sensing using Brillouin lasing

Brillouin based distributed fiber sensors present a unique set of characteristics amongst fiber sensing architectures. They are able to measure absolute strain and temperature over long distances, with high spatial resolution, and very large dynamic range in off-the-shelf fiber. However, Brillouin sensors traditionally provide only modest sensitivity due to the weak dependence of the Brillouin frequency on strain and the high signal to noise ratio required to identify the resonance’s peak frequency to within a small fraction of its linewidth. Recently, we introduced a technique which substantially improves the precision of Brillouin fiber sensors by exciting a series of lasing modes in a fiber loop cavity that experience Brillouin amplification at discrete locations in the fiber. The narrow-linewidth and high intensity of the lasing modes enabled ultra-low noise Brillouin sensors with large dynamic range. However, our initial demonstration was only modestly distributed: measuring strain at 40, non-contiguous positions along a 400 m fiber. In this work, we greatly extend this methodology to enable fully distributed sensing at 1000 contiguous locations along 3.5 km of fiber—an order of magnitude increase in sensor count and range. This highly-multiplexed Brillouin fiber laser sensor provides a strain noise as low as 34 nɛ/√Hz and we analyze the limiting factors in this approach.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Dynamic performance and reflection sensitivity of quantum dot distributed feedback lasers with large optical mismatch

This work reports on a high-efficiency InAs/GaAs distributed feedback quantum dot laser. The large optical wavelength detuning at room temperature between the lasing peak and the gain peak causes the static, dynamic, and nonlinear intrinsic properties to all improve with temperature, including the lasing efficiency, the modulation dynamics, the linewidth enhancement factor, and consequently the reflection insensitivity. Results reported show an optimum operating temperature at 75°C, highlighting the potential of the large optical mismatch assisted single-frequency laser for the development of uncooled and isolator-free high-speed photonic integrated circuits.

Dong, Bozhang (ORCID:0000000158266723)↗