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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Local and utility-wide cost allocations for a more equitable wildfire-resilient distribution grid

Climate-induced extreme weather conditions make electricity infrastructure more vulnerable. They increase the risk of power-line-ignited wildfires which can, in turn, jeopardize electric power delivery. Here, leveraging machine learning, we show that lower-income communities in California not only have lower fractions of power distribution lines undergrounded, but overhead lines and poles in their neighbourhoods are also more vulnerable to wildfires. Should they bear the cost of undergrounding fire-prone lines themselves, they would have to pay a disproportionately higher cost per household. We propose a cost allocation scheme with an income threshold below which the cost is borne by utility-wide ratepayers and above which the cost is borne locally. This scheme can not only minimize the average of undergrounding costs per household as a share of income, but also homogenize such cost–income ratios across communities. Furthermore, our research demonstrates the opportunity to appropriately integrate existing policies to make electricity infrastructure affordable, equitable and reliable amidst climate change.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

The influence of submarine canyons-related processes on recent benthic foraminiferal distribution, Espírito Santo Basin, Southeastern Brazil

The complex topography of submarine canyons may result in different composition of benthic foraminifera assemblages. To understand how trophic, hydrological and sedimentological conditions in submarine canyons can influence the distribution of benthic foraminifera, and to use this information to corroborate paleoenvironmental interpretations for the Holocene, we investigated recent benthic foraminiferal assemblages (total fauna >63 μm) and sedimentological data in two canyons (CANWN and CAND) in the Espírito Santo Basin (ESB) between 18°20' and 21°20' S. Surface sediment samples (0–2 cm) were collected inside the canyons (150 to 1300 m water depth) and in shelf-slope adjacent transects (50 to 1300 m water depth). The density, taxonomic diversity, and assemblage composition of benthic foraminifera change with depth and location. The distinct ecological preferences of the most abundant taxa allowed us to recognize five benthic foraminiferal groups. Three groups (V, III, and I) are present in different bathymetric sectors; Group V: outer shelf (50 m), Group III: upper, and middle – lower slope (150 to 400 m), and Group I: middle – lower slope (1000 to 1300 m). Groups II and IV show no characteristic bathymetric distribution and are present only in CAND and in CANWN, respectively. Group V consists of Hanzawaia boueana, Peneroplis planatus, and Quinqueloculina lamarckiana; Group III is dominated by Globocassidulina rossensis and Trifarina spp.; Group I consists of Globocassidulina crassa, Bolivina lowmani, Gavelinopsis versiformis, Alabaminella weddellensis, and Epistominella exigua. The main species in Group II (CAND, 150, 1000 to 1300 m) are Trifarina angulosa, Globocassidulina subglobosa, and Discorbis vilardeboanus. Group IV (middle – lower CANWN, 1000 to 1300 m), consists mainly of agglutinated species Glomospira charoides, Rhabdammina abyssorum, and Psammosphaera fusca. Further, our data suggest that the quantity (and quality) of food supply, hydrodynamic conditions and sediment properties are the main drivers controlling the bathymetric distribution of benthic foraminiferal assemblages in both canyons. The middle – lower CANNW revealed unstable trophic conditions, related to terrigenous sediment input due to turbidity currents. In CAND, the foraminiferal assemblages ecology indicated sufficient organic matter supply that favors species establishment and diversity, indicating a more productive and less unstable environment than in CANWN.

58 GEOSCIENCES↗
DOE OSTI2021

Computer-aided Abnormality Detection in Chest Radiographs in a Clinical Setting via Domain-adaptation

Deep learning (DL) models are being deployed at medical centers to aid radiologists for diagnosis of lung conditions from chest radiographs. Such models are often trained on a large volume of publicly available labeled radiographs. These pre-trained DL models’ ability to generalize in clinical settings is poor because of the changes in data distributions between publicly available and privately held radiographs. In chest radiographs, the heterogeneity in distributions arises from the diverse conditions in X-ray equipment and their configurations used for generating the images. In the machine learning community, the challenges posed by the heterogeneity in the data generation source is known as domain shift, which is a mode shift in the generative model. In this work, we introduce a domain-shift detection and removal method to overcome this problem. Our experimental results show the proposed method’s effectiveness in deploying a pre-trained DL model for abnormality detection in chest radiographs in a clinical setting.

Dubey, Abhishek↗
DOE OSTI2024

Successful Cleanroom Installation of PIP-II SSR2 Coupler Using Robotic Arm

The Fermilab Side-Coupled Linac accelerates H- beam from 116 MeV to 400 MeV through seven 805 MHz modules. Twelve wire scanners are present in the Side Coupled Linac and four are present in the transfer line between the Linac and the Booster synchrotron ring. These wire scanners act as important diagnostic instruments to directly collect information on the beam s transverse distribution. The manipulation of the conditions of wire scanner data collection enables further characterization of the beamline, such as calculating emittance and the Twiss parameters of the beam at select regions. Here we present the results of these studies and characterization of the non-Gaussian transverse beam distribution observed.

Narug, C.↗
DOE OSTI2022

Early Failure of Lithium–Sulfur Batteries at Practical Conditions: Crosstalk between Sulfur Cathode and Lithium Anode

Lithium–sulfur (Li–S) batteries are one of the most promising next-generation energy storage technologies due to their high theoretical energy and low cost. However, Li–S cells with practically high energy still suffer from a very limited cycle life with reasons which remain unclear. Here, through cell study under practical conditions, it is proved that an internal short circuit (ISC) is a root cause of early cell failure and is ascribed to the crosstalk between the S cathode and Li anode. The cathode topography affects S reactions through influencing the local resistance and electrolyte distribution, particularly under lean electrolyte conditions. The inhomogeneous reactions of S cathodes are easily mirrored by the Li anodes, resulting in exaggerated localized Li plating/stripping, Li filament formation, and eventually cell ISC. Manipulating cathode topography is proven effective to extend the cell cycle life under practical conditions. The findings of this work shed new light on the electrode design for extending cycle life of high-energy Li–S cells, which are also applicable for other rechargeable Li or metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

A Particle Method for the Multispecies Landau Equation

Abstract The multispecies Landau collision operator describes the two-particle, small scattering angle or grazing collisions in a plasma made up of different species of particles such as electrons and ions. Recently, a structure preserving deterministic particle method (Carrillo et al. in J. Comput. Phys. 7:100066, 2020) has been developed for the single species spatially homogeneous Landau equation. This method relies on a regularization of the Landau collision operator so that an approximate solution, which is a linear combination of Dirac delta distributions, is well-defined. Based on a weak form of the regularized Landau equation, the time dependent locations of the Dirac delta functions satisfy a system of ordinary differential equations. In this work, we extend this particle method to the multispecies case, and examine its conservation of mass, momentum, and energy, and decay of entropy properties. We show that the equilibrium distribution of the regularized multispecies Landau equation is a Maxwellian distribution, and state a critical condition on the regularization parameters that guarantees a species independent equilibrium temperature. A convergence study comparing an exact multispecies Bobylev-Krook-Wu (BKW) solution to the particle solution shows approximately 2nd order accuracy. Important physical properties such as conservation, decay of entropy, and equilibrium distribution of the particle method are demonstrated with several numerical examples.

Mathematics↗
DOE OSTI2022

Heavy ion irradiation effects on CrFeMnNi and AlCrFeMnNi high entropy alloys

Co-free but Al-included medium/high entropy alloys (M/HEAs) have gained increasing interests due to their lower cost and the potential to tune the multi-phase microstructure. The irradiation response of two Co-free HEAs, face-centered cubic (FCC) CrFeMnNi with limited Cr enriched α' phase and body-centered cubic (BCC) AlCrFeMnNi with B2s phase and nanoprecipitates were explored. Ion irradiations using 5 MeV Fe 2+ ions were performed at 500°C to a peak fluence of 50 and/or 100 displacements per atom (dpa). In dual-phase AlCrFeMnNi, there was no significant radiation induced segregation or chemical intermixing at the coherent matrix (FeCrMn-rich)/second phase (AlNi-rich) boundaries. In CrFeMnNi, limited voids were only detected at the peak damage location of ~ 50 dpa. On the other hand, voids were widely distributed in AlCrFeMnNi: under 50 and 100 dpa irradiation conditions, voids were found with larger dimension and denser distribution in the FeCrMn-rich matrix, smaller and slightly lower density in an AlNi-rich second phase. In addition, the diameter of the FeCMn-rich nanoprecipitates didn't reveal any tendency of dissolution or growth. This is correlated with their superior structural stability against irradiation. Significant radiation-induced hardening (increases from 3.8 ± 0.2 GPa to 4.7 ± 0.6 GPa) was measured in CrFeMnNi, but only ~ 4% hardness increase (from 7.4 ± 0.8 GPa to 7.7 ± 0.4 GPa) was noted in AlCrFeMnNi. Finally, in addition to the radiation-induced defects, such as voids, dislocation loops and point defects, other factors, such as chemical short-range ordering may play an important role.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multiarea Distribution System State Estimation via Distributed Tensor Completion

Here, this paper proposes a model-free distribution system state estimation method based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system and a large-scale real utility feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Online Optimization for Networked Distributed Energy Resources With Time-Coupling Constraints

This paper proposes a Lyapunov optimization-based online distributed (LOOD) algorithmic framework for active distribution networks (ADNs) with numerous photovoltaic inverters and inverter air conditionings (IACs). In the proposed scheme, ADNs can track an active power setpoint reference at the substation in response to transmission-level requests while concurrently minimizing the social utility loss and ensuring the security of voltages. Conventional distributed optimization methods are rarely feasible to track the optimal solutions in fast variable environments using a fine-grained sampling interval where the underlying optimization problem evolves with the iterations of the algorithms. In contrast, based on the framework of online convex optimization (OCO), the developed approach uses a distributed algebraic update to compute the next round decisions relying on the current feedback of measurements. Notably, the time-coupling constraints of IACs are decoupled for online implementation with Lyapunov optimization technique. An incentive scheme is tailored to coordinate the customer-owned assets in lieu of the direct control from network operators. Optimality and convergency are characterized analytically. Finally, we corroborate the proposed method on a modified version of 33-node test feeder. Benchmark tests show that the proposed method is computationally and economically efficient, and outperforming existing algorithms.

active distribution networks↗
DOE OSTI2024

3002 Humidified Tandem Differential Mobility Analyzer (HTDMA) Instrument Handbook

The Brechtel Manufacturing Inc. (BMI) Humidified Tandem Differential Mobility Analyzer (HT-DMA Model 3002) (Brechtel and Kreidenweis 2000a,b, Henning et al. 2005, Xerxes et al. 2014) measures how aerosol particles of different initial dry sizes grow or shrink when exposed to changing relative humidity (RH) conditions. It uses two different mobility analyzers (DMA) and a humidification system to make the measurements. One DMA selects a narrow size range of dry aerosol particles, which are exposed to varying RH conditions in the humidification system. The second (humidified) DMA scans the particle size distribution output from the humidification system. Scanning a wide range of particle sizes enables the second DMA to measure changes in size or growth factor (growth factor = humidified size/dry size), due to water uptake by the particles. A Condensation Particle Counter (CPC) downstream of the second DMA counts particles as a function of selected size in order to obtain the number size distribution of particles exposed to different RH conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.

Tabassum, Anika↗
DOE OSTI2024

Machine learning assisted bayesian inference of mix and hot-spot conditions in NIF implosions

Experiments on the National Ignition Facility (NIF) have provided clear evidence of ablator material mixing into the Hot-Spot, leading to degraded performance. However, inferring the amount of mix and Hot-Spot conditions from typical experimental observations (e.g. x-ray spectra and images) is highly challenging. Here, we have developed an analysis method that utilizes machine learning assisted Bayesian inference to find the probability distributions of the Hot-Spot and mix conditions. This approach uses a neural network, trained on an idealized 2-dimensional representation of the Hot-Spot and mix distribution, and Bayesian inference to find the statistical distributions of Hot-Spot conditions that provide a match with observations. We have tested this method with synthetic data from simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Kinetics Measurements in Resistive Electrolytes Using Ring-Disk Electrode: Ring as Current “Shield” Enables Uniform Disk Current Distribution

Rotating disk electrodes are commonly used for electrochemical kinetics measurements. A major disadvantage of these types of electrodes is their nonuniform secondary current distribution, especially when performing electroanalytical measurements in resistive electrolytes. Such nonuniform current distribution can render the values of kinetics constants extracted from the disk electrode to be highly inaccurate. Furthermore, one emerging class of electrolytes that suffer from low ionic conductivities is deep eutectic solvents (DES). DES are a promising class of electrolytes for various emerging applications; however, due to their resistive nature, the secondary current distribution when using them is typically highly nonuniform. For example, the Wagner number when measuring Cu²⁺/Cu⁺ kinetics in choline chloride–ethylene glycol DES (1:4 molar ratio of ChCl:EG) is very low (<0.1), indicating highly nonuniform current distribution over the disk electrode. We show here that the Cu²⁺/Cu⁺ exchange current density measured using disk electrodes is very inaccurate due to the aforementioned nonuniform current distribution. To obtain uniform disk current distribution, we employ here a coplanar concentric rotating ring-disk electrode (RRDE), where the ring serves the function of a current “shield.” Specifically, we show using modeling that the ring minimizes the current distribution nonuniformity at the disk by effectively shielding the disk against current spikes near the disk edge. This enables improved precision in electrode kinetics measurements for the Cu²⁺/Cu⁺ couple in resistive DES. To enable broad applicability of this technique, an analytical expression based on the Wagner number is integrated into an iterative algorithm to help users identify ring conditions to achieve uniform current distribution and thus improved electroanalytics at the disk.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tri-Level Linear Programming Model for Automatic Load Shedding Using Spectral Clustering

Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shedding areas have been predefined by grid operators, they have remained fixed, and may be sub-optimal due to dynamic operating conditions. In this work, a distributed tri-level linear programming model for automatic load shedding to avoid system islanding is presented. Preventing islanding is preferred because it reduces the need for additional load shedding besides the disconnection of transmission lines between islands. This is crucial as maintaining the local generation-demand balance is necessary to preserve frequency stability. Furthermore, uneven distribution of generation resources among islands can lead to increased load shedding, causing economic and reliability challenges. This issue is further compounded in modern power systems heavily dependent on non-dispatchable resources like wind and solar. The upper-level model uses complex power flow measurements to determine the system areas to shed load depending on actual operating conditions using a spectral clustering approach. The mid-level model estimates the area system state, while the lower-level model determines the locations and load values to be shed. The solution is practical and promising for real-world applications.

Baquedano-Aguilar, Mario D.↗
DOE OSTI2022

Measurement of Triple-Differential Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report the first measurement of the differential cross section $d^2σ(E_ν)/dcos(θ_µ)dP_µ$for inclusive muon neutrino charged-current scattering on argon. This measurement utilizes data from6.5×10 20 protons on target of exposure collected using the MicroBooNE liquid argon time projection chamber located on-axis in the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. In this note, the mapping from reconstructed kinematics to truth quantities, particularly from reconstructed to true neutrino energy, is validated by comparing the distribution of reconstructed hadronic energy in data to that of the model prediction in different muon scattering angle bins after conditional constraint from the muon momentum distribution in data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well-modeled within its uncertainties in simulation, enabling the unfolding to an energy-dependent triple-differential measurement over muon momentum, muon scattering angle, and neutrino energy. The unfolded measurement covers an extensive phase space, providing a wealth of information useful for future LArTPC experiments measuring neutrino oscillations. Comparisons with model predictions show the best agreement with Neut 5.4.0.1 at low energy, and with NuWro 19.02.01 at higher energies, particularly at forward muon scattering angles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Development and Evaluation of Chemistry‐Aerosol‐Climate Model CAM5‐Chem‐MAM7‐MOSAIC: Global Atmospheric Distribution and Radiative Effects of Nitrate Aerosol

Abstract An advanced aerosol treatment, with a focus on semivolatile nitrate formation, is introduced into the Community Atmosphere Model version 5 with interactive chemistry (CAM5‐chem) by coupling the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) with the 7‐mode Modal Aerosol Module (MAM7). An important feature of MOSAIC is dynamic partitioning of all condensable gases to the different fine and coarse mode aerosols, as governed by mode‐resolved thermodynamics and heterogeneous chemical reactions. Applied in the free‐running mode from 1995 to 2005 with prescribed historical climatological conditions, the model simulates global distributions of sulfate, nitrate, and ammonium in good agreement with observations and previous studies. Inclusion of nitrate resulted in ∼10% higher global average accumulation mode number concentrations, indicating enhanced growth of Aitken mode aerosols from nitrate formation. While the simulated accumulation mode nitrate burdens are high over the anthropogenic source regions, the sea‐salt and dust modes respectively constitute about 74% and 17% of the annual global average nitrate burden. Regional clear‐sky shortwave radiative cooling of up to −5 W m −2 due to nitrate is seen, with a much smaller global average cooling of −0.05 W m −2 . Significant enhancements in regional cloud condensation nuclei (at 0.1% supersaturation) and cloud droplet number concentrations are also attributed to nitrate, causing an additional global average shortwave cooling of −0.8 W m −2 . Taking into consideration of changes in both longwave and shortwave radiation under all‐sky conditions, the net change in the top of the atmosphere radiative fluxes induced by including nitrate aerosol is −0.7 W m −2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Universal method for the optimization of HDC coating uniformity on non-planar, non-stationary substrates for inertial confinement fusion targets

The thickness uniformity of chemical vapor deposited (CVD) diamond coatings on non-planar, non-stationary substrates depends on both the intrinsic instantaneous coating thickness distribution (ICTD) of the coating conditions used and, if applicable, on the frequency of substrate reorientation. While important for many CVD diamond applications, the relative impact of the ICTD and substrate reorientation on the coating thickness uniformity has not been studied. In this work, we systematically investigate the effect of these factors for microwave-plasma chemical vapor deposition (MPCVD) of diamond (referred to as high density carbon (HDC) in the inertial confinement fusion (ICF) community) coatings on spherical, rolling substrates. This coating technique is used to fabricate capsules for ICF experiments, which require extreme coating uniformity with <0.3 % thickness variation (so-called Mode 1 or M1) to ensure symmetric compression of imploding targets. To extract the otherwise unobservable reorientation timescale (Δt), Monte Carlo simulations were performed using experimental ICTD data as input. This combined approach confirms scaling relationships between the substrate reorientation timescale as well as coating thickness and coating uniformity, as expected from a 3D random walk. Simulations confirm that M1 is Rayleigh-distributed and scales as (Δt) 1/2 , consistent with the randomization of two angles that determine orientation of a sphere. We also demonstrate that, under the conditions studied, Δt is the dominant factor in determining thickness uniformity while the intrinsic ICTD has minimal impact. Finally, experiments show that Δt can be affected by total batch size under constant agitation conditions due to space constraints that limit the capsule reorientation kinetics. In conclusion, this study highlights the utility of a combined experiment-simulation approach as a general methodology for understanding and improving coating uniformity on non-planar, non-stationary substrates.

Capsule↗
DOE OSTI2021

Experimental investigation of the effect of pore size distribution on nano-particle capture efficiency within ceramic particulate filters

The effect of the pore size distribution on size-resolved filtration efficiency was investigated for two ceramic particulate filters using particulate matter (PM) generated by a spark-ignition direct-injection engine fueled with gasoline. The cordierite filter tested had a porosity of 43%, a median pore diameter (d_50) of 12 µm, and a wide pore size distribution with a lognormal standard deviation (s’) of 0.3. The aluminum titanate filter had very similar porosity, d_50, and thickness, but significantly narrower pore size distribution (s’ = 0.1). The testing of two filters under identical experimental conditions enabled the impact of the pore size distribution on filtration performance to be evaluated. Filtration experiments were performed focusing on just the filter wall, starting from a clean filter until the transition to cake filtration (filtration efficiency > 99%). Time-resolved particle size distribution measurements were used to evaluate the progression of filtration performance and estimate trapped mass within the filter. The aluminum titanate filter, with a narrow pore size distribution, exhibited significantly better diffusion capture efficiency. The negative impact of higher flow velocity on diffusion capture efficiency was more pronounced for a narrower pore size distribution. Flow distributions measured using capillary-flow porometry were used to develop a cylindrical pore flow model to understand the impact of the differences in pore size distribution on observed trends in diffusion capture efficiency within a clean filter. The model helps demonstrate how large pores on the high end of a wider pore size distribution can carry a large fraction of the flow, with less efficient capture of small particles by diffusion. The experimental results and data demonstrate that the bubble point diameter and width of the pore size distribution significantly influence diffusion capture efficiencies for filters with very similar median pore diameter, porosity, and thickness.

aerosol filtration, Aftertreatment, ceramic exhaus↗