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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

Observations of Aerosol, Cloud, Turbulence, and Radiation Properties at the Top of the Marine Boundary Layer over the Eastern North Atlantic Ocean: The ACORES Campaign

We report on the Azores Stratocumulus Measurements of Radiation, Turbulence and Aerosols (ACORES) campaign, which took place around Graciosa and Pico Islands/Azores in July 2017. The main objective was to investigate the vertical distribution of aerosol particles, stratocumulus microphysical and radiative properties, and turbulence parameters in the eastern North Atlantic. The vertical exchange of mass, momentum, and energy between the free troposphere (FT) and the cloudy marine boundary layer (MBL) was explored over a range of scales from submeters to kilometers. To cover these spatial scales with appropriate measurements, helicopter-borne observations with unprecedented high resolution were realized using the Airborne Cloud Turbulence Observation System (ACTOS) and Spectral Modular Airborne Radiation Measurement System–Helicopter-Borne Observations (SMART-HELIOS) instrumental payloads. Here, the helicopter-borne observations were combined with ground-based aerosol measurements collected at two continuously running field stations on Pico Mountain (2,225 m above sea level, in the FT), and at the Atmospheric Radiation Measurement (ARM) station on Graciosa (at sea level). First findings from the ACORES observations we are discussing in the paper are as follows: (i) we have observed a high variability of the turbulent cloud-top structure on horizontal scales below 100 m with local temperature gradients of up to 4 K over less than 1 m vertical distance, (ii) we have collected strictly collocated radiation measurements supporting the relevance of small-scale processes by revealing significant inhomogeneities in cloud-top brightness temperature to scales well below 100 m, and (iii) we have concluded that aerosol properties are completely different in the MBL and FT with often-complex stratification and frequently observed burst-like new particle formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Turbulence modelling in neutron star merger simulations

Observations of neutron star mergers have the potential to unveil detailed physics of matter and gravity in regimes inaccessible by other experiments. Quantitative comparisons to theory and parameter estimation require nonlinear numerical simulations. However, the detailed physics of energy and momentum transfer between different scales, and the formation and interaction of small scale structures, which can be probed by detectors, are not captured by current simulations. This is where turbulence enters neutron star modelling. This review will outline the theory and current status of turbulence modelling for relativistic neutron star merger simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

CO 2 Capture Using Electrochemically Mediated Amine Regeneration

We describe the current status of our research on, and the development of, the Electrochemically Mediated Amine Regeneration (EMAR) process for the capture of CO2 from flue gases. The absorption step in the EMAR process is the same as in the widely used amine process, but the desorption step is accomplished electrochemically as opposed to by a thermal swing used in the amine process. Our laboratory unit has operated continuously for over 200 h, spanning 130 absorption/desorption cycles. We have established an understanding of the thermodynamics of the EMAR process and provided engineering estimates of key features (energetics and sizing) of this technology. The EMAR system does not rely on steam integration, making it a truly plug-and-play unit that can be easily deployed for a range of applications. The EMAR system can also be scaled-down for distributed, modular, and small-scale operations (e.g., stainless steel mini-mills, etc.). Here, results to date indicate that the EMAR process has the potential to be a viable option for post-combustion CO2 capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2025

Multiprobe cosmology from the abundance of SPT clusters and DES galaxy clustering and weak lensing

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the Universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3 × 2 ⁢pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining Λ cold dark matter (Λ ⁢CDM) parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure Ω m = 0.300 ± 0.017 and 𝜎 8 = 0.797 ± 0.026. Compared to constraints from Planck primary cosmic microwave background (CMB) anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 (1.2⁢𝜎) for the two-parameter difference. We further obtain 𝑆 8 ≡𝜎 8 ⁢(Ω m /0.3) 0.5 = 0.796 ± 0.013 which is lower than the Planck measurement at the 1.6⁢𝜎 level. The combined SPT cluster, DES 3 ×2 ⁢pt, and Planck datasets mildly prefer a nonzero positive neutrino mass, with a 95% upper limit ∑ 𝑚 𝜈 < 0.25 eV on the sum of neutrino masses. Assuming a 𝑤⁢CDM model, we constrain the dark energy equation of state parameter 𝑤 = −1.1⁢5$^{+0.23}_{−0.17}$ and when combining with Planck primary CMB anisotropies, we recover 𝑤 = −1.2⁢0$^{+0.15}_{−0.09}$, a 1.7⁢𝜎 difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology and our analysis paves the way for upcoming joint analyses of next-generation datasets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Bias Characterization, Vertical Interpolation, and Horizontal Interpolation for Distributed Wind Siting Using Mesoscale Wind Resource Estimates

Much like their counterparts in utility-scale wind energy, developers of industrial, small-scale and distributed wind turbine deployments need to understand and accurately characterize the wind resource to properly assess the power generation and financial ramifications during siting and planning. National Renewable Energy Laboratory’s WIND (Wind Integration National Dataset) Toolkit (WTK) provides a best-in-class wind resource dataset generated using the Weather Research and Forecasting (WRF) model. This dataset includes parameters such as the wind speed, wind direction, and temperature at various heights, plus atmospheric stability near the surface. This data is available at 2-km spatial resolution and five-minute temporal resolution across 7 years, from 2007 to 2013 through a publicly accessible API interface. The Tools Assessing Performance (TAP) project seeks to extend this dataset to allow long term resource estimates and leverage it to better equip distributed wind equipment manufacturers, owner-operators, and installation professionals with better tools for practical siting applications. In this report, we present the results from our investigation within the TAP project focused on characterization of bias in WTK-based wind speed estimates and evaluation of vertical and horizontal interpolation techniques. We discuss the tradeoffs between different techniques and their combinations, as well as describe the lower bounds we determine for the studied validation errors. While the specific estimates we present are specific to WTK and the validation dataset we have chosen for this investigation (NREL's Wind Resource Meteorological Database), the overall analysis and the studied techniques are general enough to be applied to a broader set of wind datasets, both simulation-based and observational.

17 WIND ENERGY↗
DOE OSTI2020

Experimental methodology and theoretical framework in describing constrained plastic flow of FCC microscale tensile specimens

Small scale mechanical testing (SSMT) allows for the quantification of the mechanical responses for microscale and nanoscale material volumes. It has significant potential in improving our fundamental understanding of plastic deformation and in providing an engineering solution for testing complex and/or critical materials. Importantly, previous studies have revealed that plastic intermittency, manifested as strain bursts, are characteristic of the plastic flow behavior at the small length scale. In this work, interfacial constraint has been utilized to suppress strain bursts in order to stabilize plasticity. A new parameter, blocked volume ratio (BVR), is introduced to quantify the degree of constraint for a microscale specimen due to an interface. Here, we showed that the plastic flow behavior in FCC Ni-based metals is highly dependent on the BVR of the specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Weak lensing combined with the kinetic Sunyaev–Zel’dovich effect: a study of baryonic feedback

ABSTRACT Extracting precise cosmology from weak lensing surveys requires modelling the non-linear matter power spectrum, which is suppressed at small scales due to baryonic feedback processes. However, hydrodynamical galaxy formation simulations make widely varying predictions for the amplitude and extent of this effect. We use measurements of Dark Energy Survey Year 3 weak lensing (WL) and Atacama Cosmology Telescope DR5 kinematic Sunyaev–Zel’dovich (kSZ) to jointly constrain cosmological and astrophysical baryonic feedback parameters using a flexible analytical model, ‘baryonification’. First, using WL only, we compare the $S_8$ constraints using baryonification to a simulation-calibrated halo model, a simulation-based emulator model, and the approach of discarding WL measurements on small angular scales. We find that model flexibility can shift the value of $S_8$ and degrade the uncertainty. The kSZ provides additional constraints on the astrophysical parameters, with the joint WL + kSZ analysis constraining $S_8=0.823^{+0.019}_{-0.020}$. We measure the suppression of the non-linear matter power spectrum using WL + kSZ and constrain a mean feedback scenario that is more extreme than the predictions from most hydrodynamical simulations. We constrain the baryon fractions and the gas mass fractions and find them to be generally lower than inferred from X-ray observations and simulation predictions. We conclude that the WL + kSZ measurements provide a new and complementary benchmark for building a coherent picture of the impact of gas around galaxies across observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Production of desensitized, ultrafine PETN powder

Pentaerythritol tetranitrate (PETN) is a widely studied high explosive (HE), most commonly used in detonator applications. In this work, we use a spray drying technique to manufacture a new “nano-powder” morphology of PETN. The spray dried PETN is several orders of magnitude smaller in particle size than traditionally prepared PETN powders. The spray dried PETN has a mostly spherical and smooth morphology, while traditional crystalline PETN typically has sharp edges and crystal facets. Small-scale sensitivity tests including drop-weight impact, friction, and electrostatic discharge (ESD) indicate the spray dried PETN is less sensitive than traditionally used forms of PETN powders. Furthermore, we also observed no changes in chemical properties (melt temperature and onset of decomposition) after spray drying, and the material remains in the tetragonal, crystalline phase.

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

Advancing coupled fire-atmosphere research with HIGRAD/FIRETEC (w20_firetec) (CY 2021 Institutional Computing Annual Progress Report) [Slides]

LANL’s HIGRAD and FIRETEC models were used in a multi-scale simulation framework to investigate impacts of small-scale fuel heterogeneities on large-scale Pyro-Cb formation. Forest structural diversity is found to increase canopy fire spread, and thus risk of tree mortality in FIRETEC simulations. Structural diversity is associated with an increase in ladder fuels, which facilitate fire spread into the canopy. Low-intensity fire burning in marginal conditions is highly sensitive to small perturbation in atmospheric turbulence. These results highlight predictive limitations of individual fire simulations, and emphasize the need for ensemble simulations, especially for low-intensity, prescribed fire.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Leveraging a Southern California Energy Innovation Cluster to Pilot and Validate Emerging Energy Technologies

The EPIC Pilot Program, led by the Los Angeles Cleantech Incubator (LACI), was designed to help early-stage clean technology startups accelerate technical validation, investment readiness, and market entry. The project focused on supporting startups in designing and deploying small-scale pilots with the guidance of EPIC Partners, a network of regional stakeholders in the Southern California energy ecosystem, including but not limited to: the Los Angeles Department of Water and Power (LADWP), the California Energy Commission (CEC), Los Angeles County Metropolitan Transportation Authority (LA Metro), and Edison International, among others. Through mentorship, funding, and site access for technology deployments, the program provided a structured pathway for startups to test and refine their technologies in real-world settings.

14 SOLAR ENERGY↗
DOE OSTI2022

Integrated simulation, machine learning, and experimental approach to characterizing fracture instability in indentation pillar-splitting of materials

Measuring fracture toughness of materials at small scales remains challenging due to limited experimental testing configurations. A recently developed indentation pillar-splitting method has shown promise of improved flexibility in fracture toughness measurements at the microscale, partly due to the occurrence of an unusual fracture instability, i.e., a transition from stable to unstable crack propagation. In spite of growing interest in this method, the underlying mechanism of this phenomenon is yet to be elucidated. Furthermore, we provide a comprehensive description of fracture instability in indentation pillar-splitting by combining in situ experiments with high-fidelity simulations based on cohesive zone and J-integral methods. In addition, a machine-learning-based solution for predicting the critical indentation load of fracture instability is established through Gaussian processes regression for broad use of this method by the community.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Vitrification of High-Cr Glass in Research-Scale Melter

This test report describes the experimental results from a small-scale test using the research-scale melter (RSM) at Pacific Northwest National Laboratory to demonstrate processing of a high-Cr simulated feed stream, designated HLW-HCr-16. The RSM is a small, joule-heated melter capable of processing melter feed continuously. The melter is equipped with Inconel ® 693 electrodes, Monofrax ® K-3 refractory, and an Inconel 690 pour spout. An electric kiln surrounds the melter body and minimizes heat loss from the melter body during operation. The RSM is equipped with an offgas treatment system that employs quenching, wet scrubbing, and high-efficiency mist elimination. The glass-discharge section is heated to facilitate pouring of the glass. The melter is fitted with a melt cavity that is ~25 cm (10 in.) in diameter with a nominal glass depth of 8.9 cm (3.5 in.). The melter was operated with a target glass temperature of 1150°C and target plenum temperature between 550°C and 700°C for this test. The air bubbling rate was 4.2 L/min. Overall, during the continuous operation of the melter for ~ 103 hours, ~ 141 kg of glass was produced. At the conclusion of the test, the melter and exhaust lines were visually inspected for particulate deposition and corrosion. Entrained material had adhered to the underside of the melter lid and to the exhaust piping. Enrichments in elements such as Cl, F, B, K, Li, P, Na, and S were measured in these deposits through inductively coupled plasma–optical emission spectroscopy and X-ray fluorescence analysis. When the melter electrodes and air bubbler tube were removed from the glass in the RSM, the electrodes appeared discolored, but no significant loss of metal was observed. The processing of a high-Cr simulant, HLW-HCr-16, in the RSM produced glass at an average rate of 1.36 kg/h, equaling a melter-surface-area normalized glass generation rate of 654 kg/day/m 2 . The resulting glass met the toxicity characteristic leaching procedure requirement. Test results of crystallinity, electrical conductivity, and viscosity showed good processing properties of this high-Cr high-level waste glass. RSM offgas was also sampled and analyzed at periodic intervals during steady-state operating conditions. The total decontamination factor averaged by four sampling periods was 134. The concentrations of CO and NO x in emissions were 237 to 422 and 69 to 94 parts per million by volume, respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Symmetry structure of a Riccati equation appearing in penetration mechanics

In the design of projectile penetration experiments a matter of considerable interest is scaling: that is, the potential relevance of small-scale experiments to their full-scale counterparts, in a manner analogous to that most often encountered in the context of fluid mechanics. From the theoretical standpoint, phenomena associated with scaling and scalability can be assessed using the well-established tools of dimensional analysis and the Buckingham-Pi Theorem. However, the familiar precepts of dimensional analysis are themselves a specific manifestation of the broader group invariance properties or symmetries of a mathematical model. Here, this work explores these notions – that is, dimensional analysis, the conditions for realizing complete similarity, and any additional symmetry structures – in the context of a Riccati differential equation appearing in the context of penetration mechanics. The aim of the investigation is twofold: 1) to complement existing empirical considerations with a concrete theoretical basis, and 2) to provide a deeper theoretical understanding of the projectile penetration model and its many implications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Hierarchical-embedding autoencoder with a predictor as efficient architecture for learning time-evolution in multi-scale turbulent flows

We introduce a scale-aware, data-driven deep learning modeling framework for accurately predicting the time evolution of multi-scale turbulent plasma and liquid flows. The approach is motivated by the idea of scale separation. Structures of vastly different length scales emerge in these systems, and interactions between these structures occur only locally. To exploit this structure, the flow state is transformed by a hierarchical, fully convolutional autoencoder, not into a single embedding layer as in conventional convolutional surrogate models, but into a series of embedding layers. A stepwise training strategy ensures that fine-scale features are encoded on a high-resolution grid, while larger structures are represented on progressively coarser layers. The time evolution predictor advances all embedding layers in sync, capturing local interactions between features at the same scale as well as between all scales. This approach enables efficient modeling of multi-scale systems since negligible interactions between distant, small-scale structures do not need to be directly modeled. Our hierarchical-embedding autoencoder with a predictor framework is evaluated on canonical examples of multi-scale turbulence: two-dimensional Kolmogorov flow and Hasegawa–Wakatani plasma turbulence. In both cases, the proposed framework significantly improves predictive accuracy relative to conventional convolutional network architectures. A significant improvement in prediction accuracy was observed for crucial statistical characteristics of the Hasegawa–Wakatani plasma as well as for individual trajectories of the Kolmogorov flow turbulence. Importantly, the model's rollout for the Hasegawa–Wakatani problem demonstrates a four-order-of-magnitude speedup compared to traditional numerical solvers.

Khrabry, Alexander I. [Princeton Univ., NJ (United↗
DOE OSTI2023

Plasmoid-mediated reconnection during nonlinear peeling–ballooning edge-localized modes

Abstract Plasmoid-mediated reconnection is investigated for nonlinear peeling–ballooning edge-localized modes (P-B ELMs). The formation of current sheets and the transition to 3D current sheet instability is demonstrated through fully nonlinear resistive MHD simulations of P-B ELMs in DIII-D discharges. Large-scale axisymmetric current sheets, as well as small-scale poloidally extended current sheets, are formed as the coherent P-B ELM filaments nonlinearly evolve. It is observed that, at high Lundquist numbers, these current sheets break during a reconnection burst, i.e. a secondary exponential growth of intermediate modes followed by relaxation due to the suppression of P-B drive.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Code for the manuscript "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Mode

We disclose a python/pytorch implementation of the physics-informed machine learning algorithm described in "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Modeling", LA-UR-24-30678. Direct numerical simulation (DNS) of ubiquitous turbulence phenomena is computationally infeasible for realistic flows. As a result, reduced modeling for turbulent flows aim to reduce the number of resolved scales while retaining accurate representations of the small-scale physics. The dynamics of the velocity gradient tensor (VGT) is a key ingredient in reduced or subgrid turbulence models. The evolution equation for the VGT involves nonlocal terms, requiring closure modeling. This implementation of the novel methodology of Lagrangian Attention Tensor Networks (LATN), utilizes a structured representation of the history of the VGT to inform a physics-informed machine learning algorithm. This addition of structured memory terms is shown to outperform previous models when trained and evaluated on DNS data.

Livescu, Daniel [LANL]↗
DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗