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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Comprehensive quantification of height dependence of entrainment mixing between stratiform cloud top and environment

Different entrainment-mixing processes of turbulence are crucial to processes related to clouds; however, only a few qualitative studies have been concentrated on the vertical distributions of entrainment-mixing mechanisms with low vertical resolutions. To quantitatively study vertical profiles of entrainment-mixing mechanisms with a high resolution, the stratiform clouds observed in the Physics of Stratocumulus Top (POST) project are examined. The unique sawtooth flight pattern allows for an examination of the vertical distributions of entrainment-mixing mechanisms with a 5 m vertical resolution. Relative standard deviation of volume mean radius divided by relative standard deviation of liquid water content is introduced to be a new estimation of microphysical homogeneous mixing degree, to overcome difficulties of determining the adiabatic microphysical properties required in existing measures. The vertical profile of this new measure indicates that entrainment-mixing mechanisms become more homogeneous with decreasing altitudes and are consistent with the dynamical measures of Damköhler number and transition scale number. Further analysis shows that the vertical variation of entrainment-mixing mechanisms with decreasing altitudes is due to the increases of turbulent dissipation rate in cloud and relative humidity in droplet-free air and the decrease of size of droplet-free air. The results offer insights into the theoretical understanding and parameterizations of vertical variation of entrainment-mixing mechanisms.

54 ENVIRONMENTAL SCIENCES↗
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 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 OSTI2023

A numerical solver for investigating the space charge effect on the electric field in liquid argon time projection chambers

This paper reports the development of a numerical solver aimed to simulate the interaction between the space charge (i.e. ions) distribution and the electric field in liquid argon time projection chamber (LArTPC) detectors. The ion transport equation is solved by a time-accurate, cell-centered finite volume method and the electric potential equation by a continuous finite element method. The electric potential equation updates the electric field which provides the drift velocity to the ion transport equation. The ion transport equation updates the space charge density distribution which appears as the source term in the electric potential equation. The interaction between the space charge distribution and the electric field is numerically simulated within each physical time step. The convective velocity in the ion transport equation can include the background flow velocity in addition to the electric drift velocity. The numerical solver has been parallelized using the Message Passing Interface (MPI) library. Numerical tests show and verify the capability and accuracy of the current numerical solver. It is planned that the developed numerical solver, together with a Computational Fluid Dynamics (CFD) package which provides the flow velocity field, can be used to investigate the space charge effect on the electric field in large-scale particle detectors.

42 ENGINEERING↗
DOE OSTI2020

The star formation properties of the observed and simulated AGN Universe: BAT versus EAGLE

ABSTRACT In this paper, we present data from 72 low-redshift, hard X-ray selected active galactic nucleus (AGN) taken from the Swift–BAT 58 month catalogue. We utilize spectral energy distribution fitting to the optical to infrared photometry in order to estimate host galaxy properties. We compare this observational sample to a volume- and flux-matched sample of AGN from the Evolution and Assembly of GaLaxies and their Environments (EAGLE) hydrodynamical simulations in order to verify how accurately the simulations can reproduce observed AGN host galaxy properties. After correcting for the known +0.2 dex offset in the SFRs between EAGLE and previous observations, we find agreement in the star formation rate (SFR) and X-ray luminosity distributions; however, we find that the stellar masses in EAGLE are 0.2–0.4 dex greater than the observational sample, which consequently leads to lower specific star formation rates (sSFRs). We compare these results to our previous study at high redshift, finding agreement in both the observations and simulations, whereby the widths of sSFR distributions are similar (∼0.4–0.6 dex) and the median of the SFR distributions lie below the star-forming main sequence by ∼0.3–0.5 dex across all samples. We also use EAGLE to select a sample of AGN host galaxies at high and low redshift and follow their characteristic evolution from z = 8 to z = 0. We find similar behaviour between these two samples, whereby star formation is quenched when the black hole goes through its phase of most rapid growth. Utilizing EAGLE we find that 23 per cent of AGN selected at z ∼ 0 are also AGN at high redshift, and that their host galaxies are among the most massive objects in the simulation. Overall, we find EAGLE reproduces the observations well, with some minor inconsistencies (∼0.2 dex in stellar masses and ∼0.4 dex in sSFRs).

Jackson, Thomas M.↗
DOE OSTI2024

Multiscale investigation of the mechanism of biomass deconstruction in the dimethyl isosorbide/water Co-solvent pretreatment system

In the context of promoting a circular bioeconomy, the development of green and efficient lignocellulosic biomass pretreatment technologies so as to realize high value-added biomass utilization is of intense interest. We demonstrated the potential of the bio-based green solvent dimethyl isosorbide (DMI) for the fractionation of Eucalyptus biomass with excellent performance. Here, to investigate the mechanisms involved in biomass fractionation, microimaging and microspectroscopic techniques were employed together with molecular dynamics (MD) simulation and COSMO-RS quantum chemical calculations to derive multiscale information. Both the microstructure and regional chemistry of the cell wall vary significantly with the volume ratio of DMI/H 2 O. The strongest effects were found at DMI/H 2 O = 9:1 and showed visible cell wall tearing cracks and cell wall deformation and collapse as well as the lowest values of cell wall thickness and circularity. From the MD simulations, lignin exhibits collapsed-like structure in pure H 2 O with low solvent accessibility surface area (SASA) and radius of gyration (R g ). In contrast, lignin in DMI/H 2 O shows extended structure with high SASA and solvent interactions dominated by van der Waals forces, with maximal contact in the 9:1 (v/v) system. Further, the COSMO-RS calculated sigma (σ-) potential suggests the intermolecular interactions in DMI and DMI/H 2 O co-solvent are weak, leading to stronger interaction with lignin and correspondingly higher lignin dissolution. The radial distribution functions and σ-potential all show that again DMI/H 2 O at 9:1 is an optimal volume ratio for high lignin dissolution. Finally, this study provides a solvent-ratio dependent mechanism for the action of polar aprotic solvents in the deconstruction of biomass.

09 BIOMASS FUELS↗
DOE OSTI2025

Business Models for Scaling Demand Flexibility Volume III – Stakeholder ecosystem management challenges, and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on demand flexibility program stakeholder ecosystem management strategies, which provide information on value delivery and describe how program implementers leverage partner capabilities and collaborate to deliver customer and grid benefits. This report discusses the role of stakeholder ecosystem management in demand flexibility programs, identifies existing challenges to effective stakeholder management, and describes lessons learned. This report is part of a series that includes reports on value propositions, customer relationship management strategies, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Business Models for Scaling Demand Flexibility Volume I – Value proposition characteristics, challenges, and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on demand flexibility value propositions, which provide information on value creation and describe how programs deliver clear benefits that address customer and grid needs. This report discusses the role of value propositions in demand flexibility programs, provides an overview of value propositions for a range of demand flexibility stakeholders, identifies existing challenges to establishing an effective value proposition, and describes lessons learned. This report is part of a series that includes reports on customer relationship management strategies, stakeholder ecosystem management, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Business Models for Scaling Demand Flexibility Volume IV – Program life cycle challenges and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on the life cycle of demand flexibility programs, which provides information on value creation and describes the various deployment phases program implementers navigate from initial program conceptualization through to program expansion and replication to new customer segments and regions. This report characterizes the key phases of the demand flexibility program life cycle, identifies existing challenges across the program deployment phases, and describes lessons learned. This report is part of a series that includes reports on customer relationship management strategies, stakeholder ecosystem management, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗
DOE OSTI2023

Stable Cycling with Intimate Contacts Enabled by Crystallinity–Controlled PTFE–Based Solvent–Free Cathodes in All–Solid–State Batteries

All-solid-state batteries (ASSBs) employing Li-metal anodes and inorganic solid electrolytes are attracting great attention due to high safety and energy density for next-generation energy storage devices. However, the volume change of cathode active materials can cause contact loss, resulting in charge carrier isolation, heterogeneous current distribution, and poor electrochemical properties in ASSBs. Here, a simple, yet effective, solvent-free electrode engineering approach with polytetrafluoroethylene (PTFE) as a binder for ASSBs is reported, enabling intimate contact and stable interfaces with the cathode. It is substantiated that the crystallinity of PTFE can be controlled depending on the heat history, and highly crystalline PTFE displays robust mechanical properties. High-nickel LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathode prepared with crystalline PTFE show improved cycle and rate performances in ASSBs. In addition, it is revealed that the intimate contact between cathode particles with a stable cathode electrolyte layer is maintained during cycling by postmortem studies. Furthermore, this simple engineering method can be applied to prepare cathodes with a variety of active materials and solid electrolytes in ASSBs.

25 ENERGY STORAGE↗
DOE OSTI2021

Role of silicon-graphite homogeneity as promoted by low molecular weight dispersants

This study explores low molecular weight polymers with the same chemical repeat structure as high molecular weight poly acrylic acid (PAA) and lithium poly acrylic acid (LiPAA) binders which act as a dispersant to improve the silicon-graphite electrode performance. The electrodes which utilize LiPAA as a dispersant perform, on average, the best with respect to the maximum capacity (compared to theoretical), rate performance, and capacity retention with time. These electrodes also have the poorest dispersion of binder, indicating that the poor binder dispersion is essential to electrode performance. In contrast, this study shows that electrodes formulated using PAA had good dispersion and performs the worst in cycling. Finally, this work demonstrates that the binder is not uniformly distributed in the electrode, but rather resides in local regions. Overall, the results indicate these regions accommodate volume expansion during cycling.

25 ENERGY STORAGE↗
DOE OSTI2022

Net-particle number fluctuations in a hydrodynamic description of heavy-ion collisions

Utilizing viscous hydrodynamic simulations of heavy-ion collisions, we study the behavior of cumulants of (net-)(anti)proton number distributions at RHIC beam energy scan energies, incorporating non-critical contributions like baryon conservation and excluded volume. The experimental data on net-proton cumulants at √S NN > 20 GeV are consistent with simultaneous effects of global baryon conservation and repulsive interactions in baryon sector, whereas the data at lower collision energies show possible indications for sizable attractive interactions among baryons. We discuss the behavior of factorial cumulants in addition to the ordinary cumulants, and also address the quantitative difference between proton and baryon number cumulants.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Cross Entropy Benchmark for Measurement-Induced Phase Transitions

Here, we investigate prospects of employing the linear cross entropy to experimentally access measurement-induced phase transitions without requiring any postselection of quantum trajectories. For two random circuits that are identical in the bulk but with different initial states, the linear cross entropy χ between the bulk measurement outcome distributions in the two circuits acts as an order parameter, and can be used to distinguish the volume law from area law phases. In the volume law phase (and in the thermodynamic limit) the bulk measurements cannot distinguish between the two different initial states, and χ = 1. In the area law phase χ < 1. For circuits with Clifford gates, we provide numerical evidence that χ can be sampled to accuracy ϵ from O⁢(1/ϵ 2 ) trajectories, by running the first circuit on a quantum simulator without postselection, aided by a classical simulation of the second. We also find that for weak depolarizing noise the signature of the measurement-induced phase transitions is still present for intermediate system sizes. In our protocol we have the freedom of choosing initial states such that the “classical” side can be simulated efficiently, while simulating the “quantum” side is still classically hard.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

ARM Aerial Facility (AAF) - Unmanned Aircraft Systems, Cloud Droplet Probe

The Cloud Droplet Probe (CDP) is designed to measure cloud droplet size distribution from 2 µm to 50 µm. The CDP and an appropriate data system can also calculate various other parameters including particle concentrations, effective diameter (ED), Median Volume Diameter (MVD), and Liquid Water Content (LWC).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

EGS Collab Experiment 2: Distributed Fiber Optic Temperature Data (DTS)

Distributed fiber optic sensing was an important part of the monitoring system for EGS Collab Experiment #2. A single loop of custom fiber package was grouted into the four monitoring boreholes that bracketed the experiment volume. This fiber package contained two multi-mode fibers and four single-mode fibers. These fibers were connected to an array of fiber optic interrogator units, each targeting a different measurement. The distributed temperature system (DTS) consisted of a Silixa XT-DTS unit, connected to both ends of one of the two multi-mode fibers. This system measured absolute temperature along the entire length of fiber for the duration of the experiment at a sampling rate of approximately 10 minutes. This dataset includes both raw data in XML format from the XT-DTS, as well as a processed dataset with the sections of data pertaining only to the boreholes are extracted. We have also included a report that provides all of the relevant details necessary for users to process and interpret the data for themselves. Please read this accompanying report. If, after reading it, there are still outstanding questions, please do not hesitate to contact us. Happy processing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Business Models for Scaling Demand Flexibility Volume II – Customer relationship management strategies, challenges, and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on demand flexibility program customer relationship management strategies, which provide information on value creation and focus on ensuring customers can navigate programs smoothly. This report discusses the role of customer relationship management strategies in demand flexibility programs, characterizes customer relationship management strategies that can be considered during program design and implementation, identifies existing challenges to customer relationship management strategies, and describes lessons learned. This report is part of a series that includes reports on value propositions, stakeholder ecosystem management, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Fiber orientation effects on ultra-high performance concrete formed by 3D printing

Despite the growing interest in 3D concrete printing, its current progress is limited by reinforcing methods. Inclusion of steel fibers is a potential reinforcing solution; however, the effect of printing process on orientation of the fibers is still unknown. This study aims to quantitatively investigate the orientation distribution of steel fibers in 3D printed ultra-high performance concrete. The effects of extrusion nozzle size, Cartesian print speed, and fiber volume fraction on the orientation of fibers were evaluated using digital image analysis. The consequent effects of the fiber orientation on the mechanical properties of the 3D-printed specimens were also determined. The results were compared with those of the conventionally mold-cast specimens. The results revealed that the smaller nozzle size and higher fiber volume fraction significantly enhanced the fiber alignment parallel to the printing direction. This preferential fiber alignment led to superior mechanical performance of the printed specimens to the mold-cast specimens.

36 MATERIALS SCIENCE↗