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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Particle Tracking Methods for Battery Precipitation Reactions

Precipitation and deposition reactions at solid–liquid interfaces play a key role in a number of battery chemistries, including Li-ion, so-called “anode free” batteries, zinc-based battery chemistries, and lithium–sulfur, among others. Although models with heterogeneous nucleation and growth phenomena are present in the literature, papers have not to date provided much detail on the numerical algorithms used to track the temporal evolution of the particle size distribution of deposits on electrode surfaces. In this paper we examine several approaches to discretize and track the particle size distribution, demonstrating that common approaches lead to anomalous flattening of the particle size distribution. We conclude by presenting an algorithm that preserves the appropriate particle size distribution during particle growth.

Algorithms↗
DOE OSTI2020

Tracking Seasonal and Interannual Variability in Photosynthetic Downregulation in Response to Water Stress at a Temperate Deciduous Forest

Abstract The understanding and modeling of photosynthetic dynamics affected by climate variability can be highly uncertain. In this paper, we examined a well‐characterized eddy covariance site in a drought‐prone temperate deciduous broadleaf forest combining tower measurements and satellite observations. We find that an increase in spring temperature usually leads to enhanced spring gross primary production (GPP), but a GPP reduction in late growing season due to water limitation. We evaluated how well a coupled fluorescence‐photosynthesis model (SCOPE) and satellite data sets track the interannual and seasonal variations of tower GPP from 2007 to 2016. In SCOPE, a simple stress factor scaling of Vcmax as a linear function of observed predawn leaf water potential ( ψ pd ) shows a good agreement between modeled and measured interannual variations in both GPP and solar‐induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment‐2 (GOME‐2). The modeled and satellite‐observed changes in SIF yield are ~30% smaller than corresponding changes in light use efficiency (LUE) under severe stress, for which a common linear SIF to GPP scaling would underestimate the stress reduction in GPP. Overall, GOME‐2 SIF tracks interannual tower GPP variations better than satellite vegetations indices (VIs) representing canopy “greenness.” However, it is still challenging to attribute observed SIF variations unequivocally to greenness or physiological changes due to large GOME‐2 footprint. Higher‐resolution SIF data sets (e.g., TROPOMI) already show the potential to well capture the downregulation of late‐season GPP and could pave the way to better disentangle canopy structural and physiological changes in the future.

He, Liyin↗
DOE OSTI2020

Landfalling Droughts: Global Tracking of Moisture Deficits From the Oceans Onto Land

Abstract Droughts threaten food, energy, and water security, causing death and displacement of millions of people and billions of dollars in damages. However, there are still important gaps in the understanding of drought mechanisms and behaviors, inhibiting the accuracy of early‐warning systems designed to protect communities worldwide. We use an object‐tracking algorithm to track clusters of precipitation‐minus‐evaporation moisture deficits across land and ocean areas of the globe from 1981–2018. This analysis reveals a new type of “landfalling drought” that originates over the ocean and “migrates” onto land. We find that 16% of droughts that affected the continents worldwide from 1981–2018 were landfalling droughts. These droughts were significantly larger (220–425%) and more intense (4–30%)—and grew (253–285%) and intensified (9–28%) faster—than droughts that developed solely over the land or ocean. To identify potential underlying mechanisms, we analyze moisture transport associated with landfalling droughts over western North America. We find that landfalling droughts in this region are associated with anomalously anticyclonic atmospheric pressure patterns that reduce moisture fluxes over the Pacific Ocean toward the continent. By advancing understanding of the spatiotemporal evolution of droughts, our findings offer the potential to improve seasonal‐scale prediction and long‐term projection of global drought risks.

Herrera‐Estrada, Julio E.↗
DOE OSTI2024

Source Levels of In‐Cloud Air in Shallow Cumulus: Consistency Between Paluch Diagram and Lagrangian Particle Tracking

Abstract The Paluch diagram is a widely used tool for interpreting aircraft measurements of shallow cumulus clouds. A prior study conducted by Heus et al. (2008,https://doi.org/10.1175/2008jas2572.1) concluded that the source levels of in‐cloud air inferred from the Paluch diagram exhibit biases, sometimes of several hundred meters, in comparison to those derived from Lagrangian particle tracking. In this short study we revisit this comparison. The results indicate that the upper source levels of in‐cloud air determined from the Lagrangian Particle Tracking and the Paluch diagram are consistent, and the choice of statistical methods is crucial. The significance of this research lies in confirming the reliability of the Paluch analysis, enabling its confident application to aircraft data.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

The Influence of African Easterly Waves on Atlantic Tropical Cyclone Tracks and Landfall in Large Ensembles

African easterly waves (AEWs) are an important precursor or “seed” for Atlantic tropical cyclones (TCs), with 60%–80% of major hurricanes observed to originate from AEWs. However, climate model simulations indicate that AEWs are not necessary to maintain annual Atlantic TC frequency. Furthermore, small ensembles suggest that AEWs may impact the spatial distribution and landfall of Atlantic TCs. Here, we investigated the influence of AEWs on the spatial distribution of Atlantic TC tracks and landfall using 50-member ensembles of TC-permitting regional model simulations for five hurricane seasons characterized by different levels of TC activity. The control simulations are seasonal hindcasts in which AEWs were prescribed through the eastern lateral boundary condition using reanalysis. In the experiments, we suppressed AEWs by applying a 2–10 day filter to the eastern lateral boundary condition. In response to AEW suppression, we discovered statistically significant increases in Atlantic TC frequency (10%–26%) and landfall (16%–44%), a westward shift in TC genesis location and tracks with increased landfall over the Caribbean Islands, southwestern Gulf Coast, and southeastern US coast, and increases in mid-tropospheric relative humidity in the main development region. In addition, we evaluated TC genesis mechanisms in the absence of AEWs and found evidence that the intertropical convergence zone (ITCZ) intensified and extended northward, resulting in ITCZ wave-breaking that shed vortices which served as TC seeds. By uncovering the connections between TC seed types and the likelihood of TC landfall, this research can provide Atlantic coastal and island communities with useful information to prepare for TC impacts.

African easterly waves↗
DOE OSTI2022

Instantaneous tracking of earthquake growth with elastogravity signals

Rapid and reliable estimation of large earthquake magnitude (above 8) is key to mitigating the risks associated with strong shaking and tsunamis. Standard early warning systems based on seismic waves fail to rapidly estimate the size of such large earthquakes. Geodesy-based approaches provide better estimations, but are also subject to large uncertainties and latency associated with the slowness of seismic waves. Recently discovered speed-of-light prompt elastogravity signals (PEGS) have raised hopes that these limitations may be overcome, but have not been tested for operational early warning. Here we show that PEGS can be used in real time to track earthquake growth instantaneously after the event reaches a certain magnitude. We develop a deep learning model that leverages the information carried by PEGS recorded by regional broadband seismometers in Japan before the arrival of seismic waves. After training on a database of synthetic waveforms augmented with empirical noise, we show that the algorithm can instantaneously track an earthquake source time function on real data. Our model unlocks ‘true real-time’ access to the rupture evolution of large earthquakes using a portion of seismograms that is routinely treated as noise, and can be immediately transformative for tsunami early warning.

58 GEOSCIENCES↗
DOE OSTI2022

Tracking blobs in the turbulent edge plasma of a tokamak fusion device

Abstract The analysis of turbulence in plasmas is fundamental in fusion research. Despite extensive progress in theoretical modeling in the past 15 years, we still lack a complete and consistent understanding of turbulence in magnetic confinement devices, such as tokamaks. Experimental studies are challenging due to the diverse processes that drive the high-speed dynamics of turbulent phenomena. This work presents a novel application of motion tracking to identify and track turbulent filaments in fusion plasmas, called blobs, in a high-frequency video obtained from Gas Puff Imaging diagnostics. We compare four baseline methods (RAFT, Mask R-CNN, GMA, and Flow Walk) trained on synthetic data and then test on synthetic and real-world data obtained from plasmas in the Tokamak à Configuration Variable (TCV). The blob regime identified from an analysis of blob trajectories agrees with state-of-the-art conditional averaging methods for each of the baseline methods employed, giving confidence in the accuracy of these techniques. By making a dataset and benchmark publicly available, we aim to lower the entry barrier to tokamak plasma research, thereby greatly broadening the community of scientists and engineers who might apply their talents to this endeavor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Differentiating multi-MeV, multi-ion spectra with CR-39 solid-state nuclear track detectors

The development of high intensity petawatt lasers has created new possibilities for ion acceleration and nuclear fusion using solid targets. In such laser-matter interaction, multiple ion species are accelerated with broad spectra up to hundreds of MeV. To measure ion yields and for species identification, CR-39 solid-state nuclear track detectors are frequently used. However, these detectors are limited in their applicability for multi-ion spectra differentiation as standard image recognition algorithms can lead to a misinterpretation of data, there is no unique relation between track diameter and particle energy, and there are overlapping pit diameter relationships for multiple particle species. In this report, we address these issues by first developing an algorithm to overcome user bias during image processing. Second, we use calibration of the detector response for protons, carbon and helium ions (alpha particles) from 0.1 to above 10 MeV and measurements of statistical energy loss fluctuations in a forward-fitting procedure utilizing multiple, differently filtered CR-39, altogether enabling high-sensitivity, multi-species particle spectroscopy. To validate this capability, we show that inferred CR-39 spectra match Thomson parabola ion spectrometer data from the same experiment. Filtered CR-39 spectrometers were used to detect, within a background of ~ 2 × 10 11 sr -1 J -1 protons and carbons, (1.3 ± 0.7) × 10 8 sr -1 J -1 alpha particles from laser-driven proton-boron fusion reactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

U redox state tracked in mineralized hydrothermal carbonate with implications for U-Pb geochronology

U-Pb carbonate geochronology can directly constrain the timing and rates of important geological processes. However, the mechanisms and controls on U incorporation, distribution, and retention in carbonate minerals remain unclear, limiting geological interpretations. Here X-ray absorption spectroscopy (µXAS) and in-situ U-Pb carbonate geochronology are combined to temporally track U distribution and redox state in a porphyry-epithermal system. In this setting, multiple generations of carbonate minerals record fluid conditions and processes which control the solubility and deposition of metals, including U. This novel approach provides the first evidence of both oxidized UO 2 2+ and reduced U 4+ species in temporally distinct generations of carbonate within a single sample. Preservation of two different U oxidation states during discrete precipitation events requires U retentivity within older domains, demonstrating that the U-Pb carbonate geochronometer is robust under hydrothermal conditions. Furthermore, crystal zones with abundant fluid/vapour inclusions linked to boiling processes coincide with relatively high levels of U and favourable U/Pb. Targeting carbonate domains with these textures may therefore increase success in U-Pb geochronology. U-Pb carbonate dating combined with µXAS can track the temporal evolution of processes critical for metal deposition in long-lived and multistage hydrothermal-magmatic ore deposit settings.

58 GEOSCIENCES↗
DOE OSTI2023

Geolocation tracking for human identification and activity recognition using radar deep transfer learning

Abstract Human identification and activity recognition (HIAR) is crucial for many applications, such as surveillance, smart homes, and assisted living. As a sensing modality, radar has many unique characteristics including privacy protection, and contactless sensing. Single classification systems have shown to be accurate, but for long‐term solutions both human identification (ID) and human activity recognition (HAR) will need to be integrated in one system where it can be utilised simultaneously. In this article, a novel radar‐based human tracking system is presented where three classifiers are utilised to identify the subject and his/her behaviour. For any kind of motion, the system tracks the subject and detect the type of his/her motion. Based on the detected type of motion, the three classifiers are utilised for identification and activity recognition. The classifiers are built utilising deep transfer learning where three radar datasets are established to train and validate each of the deep networks. To recognise six activities and 10 human subjects, the three classifiers, namely, HAR, Gait ID, and Heart sound ID, achieve superior performance compared to the best reported results in literature with classification accuracies of 97.6%, 100%, and 41.8% respectively. Three successful examples are presented to demonstrate the introduced concept.

Alkasimi, Ahmad↗
DOE OSTI2024

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to provide the necessary computational power to meet the challenge. The current programming models for compute accelerators often involve using architecture-specific programming languages promoted by the hardware vendors and hence limit the set of platforms that the code can run on. Developing software with platform restrictions is especially unfeasible for HEP communities as it takes significant effort to convert typical HEP algorithms into ones that are efficient for compute accelerators. Multiple performance portability solutions have recently emerged and provide an alternative path for using compute accelerators, which allow the code to be executed on hardware from different vendors. We apply several portability solutions, such as Kokkos, SYCL, C++17 std::execution::par, Alpaka, and OpenMP/OpenACC, on two mini-apps extracted from the mkFit project: p2z and p2r. These apps include basic kernels for a Kalman filter track fit, such as propagation and update of track parameters, for detectors at a fixed z or fixed r position, respectively. The two mini-apps explore different memory layout formats. We report on the development experience with different portability solutions, as well as their performance on GPUs and many-core CPUs, measured as the throughput of the kernels from different GPU and CPU vendors such as NVIDIA, AMD and Intel.

Kwok, Ka Hei Martin↗
DOE OSTI2022

Tracking Volumetric Units in Modular Factories for Automated Progress Monitoring Using Computer Vision

The construction industry is increasingly adopting off-site and prefabricated methods due to advantages offered in safety, quality, and lead time. Applying industrialized methods for plant management in offsite construction factories requires the collection of large volumes of production process data, which is a tedious task when performed manually. Recent attempts to automate this process have relied on sensor-based data collection methods which are susceptible to noise, expensive, and difficult to validate. Computer vision methods, however, enable process data collection from videos without the limitations of the other sensor-based methods. This technology has not been applied for offsite construction except in very few instances and therefore, this study proposes a novel method to reliably collect the production process data using computer vision method in near real-time from widely used surveillance cameras in offsite construction. The proposed method allows the user to annotate the workstations of interest on the video as ground truths and process these areas throughout the entire video to track the units entering and leaving stations, while continuously updating a near real-time schedule of the production line. This framework was validated by implementing on the surveillance videos of the production process of modular home manufacturing in a factory. The results consistently provided 100% accuracy, after denoising, for all the videos processed including 60 h of work for a station. The developed method enables real-time tracking of station performance, which can enable continuous improvement methods for factory management and resource allocation.

computer vision↗
DOE OSTI2020

CR-39 nuclear track detector response to inertial confinement fusion relevant ions

The detection properties of CR-39 were investigated for protons, deuterons, and tritons of various energies. Two models for the relationship between the track diameter and particle energy are presented and demonstrated to match experimental data for all three species. Data demonstrate that CR-39 has 100% efficiency for protons between 1 MeV and 4 MeV, deuterons between 1 MeV and 12.2 MeV, and tritons between 1 MeV and 10 MeV. The true upper bounds for deuterons and tritons exceed what could be measured in data. Simulations were developed to further explore the properties of CR-39 and suggest that the diameter–energy relationship of alpha particles cannot be captured by the conventional c-parameter model. These findings provide confidence in CR-39 track diameter based spectroscopy of all three species and provide invaluable insight for designing filtering for all CR-39 based diagnostics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Real-time charged track reconstruction for CLAS12

Abstract This paper presents the results of charged particle track reconstruction in CLAS12 using artificial intelligence. In our approach, we use machine learning algorithms to reconstruct tracks, including their momentum and direction, with high accuracy from raw hits of the CLAS12 drift chambers. The reconstruction is performed in real-time, with the rate of data acquisition, and allows for the identification of event topologies in real-time. This approach revolutionizes the Nuclear Physics experiments' data processing, allowing us to identify and categorize the experimental data on the fly, and will lead to a significant reduction in experiment data processing. It can also be used in streaming readout applications leading to more efficient data acquisition and post-processing.

Instruments & Instrumentation↗
DOE OSTI2024

Methods to Track Effective Doses from Airborne Radioactive Emissions for Compliance with 40 CFR 61, SUBPART H

US Department of Energy national laboratories can play an integral role in not only the advancement of science but also in the treatment of various medical conditions through research and development activities conducted at radioisotope production facilities. Here, a project has been underway at Oak Ridge National Laboratory since 2016 whose mission is to produce and supply the radioisotope 227 Ac, which is used in a radiopharmaceutical developed to treat certain types of prostate cancer and bone metastases. Production activities result in the environmental release of airborne radioactive emissions, which are governed by Clean Air Act regulations described in 40 CFR Part 61, Subpart H. Stack 3039, the source that emits radioactive effluents from 227 Ac production, is subject to additional requirements outlined in American National Standards Institute (ANSI) N13.1-1969 due to its grandfathered status. Radioactive emissions are limited to levels below those that would cause annual compliance dose standards for members of the public to be exceeded and stack 3039 to lose its grandfathered status. To allow for maximum production of 227 Ac without exceeding relevant dose limits, monthly tracking of project emissions and resulting CAP88-PC modeled effective doses to a maximally exposed individual have been implemented. Four years of tracking data were compiled and analyzed to identify additional methods that could be used to estimate project doses more frequently, potentially further optimizing 227 Ac production while maintaining compliance with applicable regulations.

atmospheric emissions↗
DOE OSTI2022

Demonstration of the neutron tracking capability of NEXT array in time-of-flight measurements to improve energy resolution

Precise neutron-energy measurements are required to probe the nuclear structure effects of neutron-rich nuclei, where β-delayed neutron emission becomes a dominant decay mode. The Neutron dEtector with Xn Tracking (NEXT) array has been designed and constructed to measure β-delayed neutrons with better energy resolution. The new design localizes the neutron interaction position by optically segmenting the detector along the direction of the neutron flight path, reducing the associated uncertainties in the neutron time-of-flight measurements. This significantly improves the energy resolution without losing the necessary detection efficiency. The proof-of-principle and efficiency measurements showed promising results. Herein, this article details the implementation of the neutron tracking capability of NEXT array in time-of-flight measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for In-Situ Use Case

As we enter the exascale computing regime, powerful supercomputers continue to produce much higher amounts of data than what can be stored for offline data processing. To utilize such high compute capabilities on these machines, much of the data processing needs to happen in situ, when the full high-resolution data is available at the supercomputer memory. In this article, we discuss our MFiX-Exa simulation, which models multiphase flow by tracking a very large number of particles through the simulation domain. In one of the use cases, the carbon particles interact with air to produce carbon dioxide bubbles from the reactor. These bubbles are of primary interest to the domain experts for these simulations. For this particle-based simulation, we propose a streaming technique that can be deployed in situ to efficiently identify the bubbles, track them over time, and use them to down-sample the data with minimal loss in these features.

97 MATHEMATICS AND COMPUTING↗