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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

4D Multimodal Co-attention Fusion Network with Latent Contrastive Alignment for Alzheimer’s Diagnosis

Multimodal neuroimaging provides complementary structural and functional insights into both human brain organization and disease-related dynamics. Recent studies demonstrate enhanced diagnostic sensitivity for Alzheimer’s disease (AD) through synergistic integration of neuroimaging data (e.g., sMRI, fMRI) with tabular data (e.g., behavioral and cognitive tests). However, the intrinsic heterogeneity across modalities (e.g., 4D spatiotemporal fMRI dynamics vs. 3D anatomical sMRI structure) presents critical challenges for discriminative feature fusion, often leading to information loss or biased fusion. To bridge this gap, we propose M2M-AlignNet: a multimodal co-attention network with latent alignment for early AD diagnosis using sMRI and fMRI. At the core of our approach is a multi-patch-to-multi-patch (M2M) contrastive loss function that quantifies and reduces representational discrepancies via weighted patch correspondence, explicitly aligning fMRI components across brain regions with their sMRI structural substrates without one-to-one constraints. Additionally, we propose a latent-as-query co-attention module to autonomously discover fusion patterns, circumventing modality prioritization biases while minimizing feature redundancy. We conduct extensive experiments to confirm the effectiveness of our method and highlight the correspondence between fMRI and sMRI as AD biomarkers.

Wei, Yuxiang [Georgia Institute of Technology]↗
DOE OSTI2017

Root morphology and mycorrhizal type strongly influence root production in nutrient hot spots of mixed forests

Plants compete for nutrients using a range of strategies. We investigated nutrient foraging within nutrient hot-spots simultaneously available to plant species with diverse root traits. We hypothesized that there would be more root proliferation by thin-root species than by thick-root species, and that root proliferation by thin-root species would limit root proliferation by thick-root species. We conducted a root ingrowth experiment in a temperate forest in eastern USA where root systems of different tree species could interact. Tree species varied in the thickness of their absorptive roots, and were associated with either ectomycorrhizal (EM) or arbuscular mycorrhizal (AM) fungi. Thus, there were thin- and thick-root AM and thin- and thick-root EM plant functional groups. Half the ingrowth cores were amended with organic nutrients (dried green leaves). Relative root length abundance, the proportion of total root length in a given soil volume occupied by a particular plant functional group, was calculated for the original root population and ingrowth roots after 6 months. The shift in relative root length abundance from original to ingrowth roots was positive in thin-root species but negative in thick-root species (p < .001), especially in unamended patches (AM: +6% vs. -7%; EM: +8% vs. -9%). Being thin-rooted may thus allow a species to more rapidly recolonize soil after a disturbance, which may influence competition for nutrients. Moreover, we observed that nutrient additions amplified the shift in root length abundance of thin over thick roots in AM trees (+13% vs. -14%), but not in EM trees (+1% vs -3%). In contrast, phospholipid fatty acid biomarkers suggested that EM fungal hyphae strongly proliferated in nutrient hot-spots whereas AM fungal hyphae exhibited only modest proliferation. We found no evidence that when growing in the shared patch, the proliferation of thin roots inhibited the growth of thick roots. As a result, knowledge of root morphology and mycorrhizal type of co-existing tree species may improve prediction of patch exploitation and nutrient acquisition in heterogeneous soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-performance data management for whole slide image analysis in digital pathology

When dealing with giga-pixel digital pathology in whole-slide imaging, a notable proportion of data records holds relevance during each analysis operation. For instance, when deploying an image analysis algorithm on whole-slide images (WSI), the computational bottleneck often lies in the input-output (I/O) system. This is particularly notable as patch-level processing introduces a considerable I/O load onto the computer system. However, this data management process could be further paralleled, given the typical independence of patch-level image processes across different patches. This paper details our endeavors in tackling this data access challenge by implementing the Adaptable IO System version 2 (ADIOS2). Our focus has been constructing and releasing a digital pathology-centric pipeline using ADIOS2, which facilitates streamlined data management across WSIs. Additionally, we’ve developed strategies aimed at curtailing data retrieval times. The performance evaluation encompasses two key scenarios: (1) a pure CPU-based image analysis scenario (“CPU scenario”), and (2) a GPU-based deep learning framework scenario (“GPU scenario”). Our findings reveal noteworthy outcomes. Under the CPU scenario, ADIOS2 showcases an impressive two-fold speed-up compared to the brute-force approach. In the GPU scenario, its performance stands on par with the cutting-edge GPU I/O acceleration framework, NVIDIA Magnum IO GPU Direct Storage (GDS). From what we know, this appears to be among the initial instances, if any, of utilizing ADIOS2 within the field of digital pathology. The source code has been made publicly available at https://github.com/hrlblab/adios.

Wang, Xiao↗
DOE OSTI2013

Resolution enhancement of lung 4D-CT via group-sparsity

Purpose: 4D-CT typically delivers more accurate information about anatomical structures in the lung, over 3D-CT, due to its ability to capture visual information of the lung motion across different respiratory phases. This helps to better determine the dose during radiation therapy for lung cancer. However, a critical concern with 4D-CT that substantially compromises this advantage is the low superior-inferior resolution due to less number of acquired slices, in order to control the CT radiation dose. To address this limitation, the authors propose an approach to reconstruct missing intermediate slices, so as to improve the superior-inferior resolution.Methods: In this method the authors exploit the observation that sampling information across respiratory phases in 4D-CT can be complimentary due to lung motion. The authors’ approach uses this locally complimentary information across phases in a patch-based sparse-representation framework. Moreover, unlike some recent approaches that treat local patches independently, the authors’ approach employs the group-sparsity framework that imposes neighborhood and similarity constraints between patches. This helps in mitigating the trade-off between noise robustness and structure preservation, which is an important consideration in resolution enhancement. The authors discuss the regularizing ability of group-sparsity, which helps in reducing the effect of noise and enables better structural localization and enhancement.Results: The authors perform extensive experiments on the publicly available DIR-Lab Lung 4D-CT dataset [R. Castillo, E. Castillo, R. Guerra, V. Johnson, T. McPhail, A. Garg, and T. Guerrero, “A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets,” Phys. Med. Biol. 54, 1849–1870 (2009)]. First, the authors carry out empirical parametric analysis of some important parameters in their approach. The authors then demonstrate, qualitatively as well as quantitatively, the ability of their approach to achieve more accurate and better localized results over bicubic interpolation as well as a related state-of-the-art approach. The authors also show results on some datasets with tumor, to further emphasize the clinical importance of their method.Conclusions: The authors have proposed to improve the superior-inferior resolution of 4D-CT by estimating intermediate slices. The authors’ approach exploits neighboring constraints in the group-sparsity framework, toward the goal of achieving better localization and noise robustness. The authors’ results are encouraging, and positively demonstrate the role of group-sparsity for 4D-CT resolution enhancement.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

WE-G-BRF-04: Robust Real-Time Volumetric Imaging Based On One Single Projection

Purpose: Real-time volumetric imaging is highly desirable to provide instantaneous image guidance for lung radiation therapy. This study proposes a scheme to achieve this goal using one single projection by utilizing sparse learning and a principal component analysis (PCA) based lung motion model. Methods: A patient-specific PCA-based lung motion model is first constructed by analyzing deformable vector fields (DVFs) between a reference image and 4DCT images at each phase. At the training stage, we “learn” the relationship between the DVFs and the projection using sparse learning. Specifically, we first partition the projections into patches, and then apply sparse learning to automatically identify patches that best correlate with the principal components of the DVFs. Once the relationship is established, at the application stage, we first employ a patchbased intensity correction method to overcome the problem of different intensity scale between the calculated projection in the training stage and the measured projection in the application stage. The corrected projection image is then fed to the trained model to derive a DVF, which is applied to the reference image, yielding a volumetric image corresponding to the projection. We have validated our method through a NCAT phantom simulation case and one experiment case. Results: Sparse learning can automatically select those patches containing motion information, such as those around diaphragm. For the simulation case, over 98% of the lung region pass the generalized gamma test (10HU/1mm), indicating combined accuracy in both intensity and spatial domain. For the experimental case, the average tumor localization errors projected to the imager are 0.68 mm and 0.4 mm on the axial and tangential direction, respectively. Conclusion: The proposed method is capable of accurately generating a volumetric image using one single projection. It will potentially offer real-time volumetric image guidance to facilitate lung radiotherapy. This study is supported in part by NIH (1R01CA154747-01), The Core Technology Research in Strategic Emerging Industry, Guangdong, China(2011A081402003)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Metal artifact correction for x-ray computed tomography using kV and selective MV imaging

Purpose: The overall goal of this work is to improve the computed tomography (CT) image quality for patients with metal implants or fillings by completing the missing kilovoltage (kV) projection data with selectively acquired megavoltage (MV) data that do not suffer from photon starvation. When both of these imaging systems, which are available on current radiotherapy devices, are used, metal streak artifacts are avoided, and the soft-tissue contrast is restored, even for regions in which the kV data cannot contribute any information. Methods: Three image-reconstruction methods, including two filtered back-projection (FBP)-based analytic methods and one iterative method, for combining kV and MV projection data from the two on-board imaging systems of a radiotherapy device are presented in this work. The analytic reconstruction methods modify the MV data based on the information in the projection or image domains and then patch the data onto the kV projections for a FBP reconstruction. In the iterative reconstruction, the authors used dual-energy (DE) penalized weighted least-squares (PWLS) methods to simultaneously combine the kV/MV data and perform the reconstruction. Results: The authors compared kV/MV reconstructions to kV-only reconstructions using a dental phantom with fillings and a hip-implant numerical phantom. Simulation results indicated that dual-energy sinogram patch FBP and the modified dual-energy PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in the kV projections. The root-mean-square errors of soft-tissue patterns obtained using combined kV/MV data are 10–15 Hounsfield units smaller than those of the kV-only images, and the structural similarity index measure also indicates a 5%–10% improvement in the image quality. The added dose from the MV scan is much less than the dose from the kV scan if a high efficiency MV detector is assumed. Conclusions: The authors have shown that it is possible to improve the image quality of kV CTs for patients with metal implants or fillings by completing the missing kV projection data with selectively acquired MV data that do not suffer from photon starvation. Numerical simulations demonstrated that dual-energy sinogram patch FBP and a modified kV/MV PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in kV projections. Combined kV/MV images may permit the improved delineation of structures of interest in CT images for patients with metal implants or fillings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

MO-DE-207A-11: Sparse-View CT Reconstruction Via a Novel Non-Local Means Method

Purpose: Sparse-view computed tomography (CT) reconstruction is an effective strategy to reduce the radiation dose delivered to patients. Due to its insufficiency of measurements, traditional non-local means (NLM) based reconstruction methods often lead to over-smoothness in image edges. To address this problem, an adaptive NLM reconstruction method based on rotational invariance (RIANLM) is proposed. Methods: The method consists of four steps: 1) Initializing parameters; 2) Algebraic reconstruction technique (ART) reconstruction using raw projection data; 3) Positivity constraint of the image reconstructed by ART; 4) Update reconstructed image by using RIANLM filtering. In RIANLM, a novel similarity metric that is rotational invariance is proposed and used to calculate the distance between two patches. In this way, any patch with similar structure but different orientation to the reference patch would win a relatively large weight to avoid over-smoothed image. Moreover, the parameter h in RIANLM which controls the decay of the weights is adaptive to avoid over-smoothness, while it in NLM is not adaptive during the whole reconstruction process. The proposed method is named as ART-RIANLM and validated on Shepp-Logan phantom and clinical projection data. Results: In our experiments, the searching neighborhood size is set to 15 by 15 and the similarity window is set to 3 by 3. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, the ART-RIANLM produces higher SNR (35.38dB<24.00dB) and lower MAE (0.0006<0.0023) reconstructed image than ART-NLM. The visual inspection demonstrated that the proposed method could suppress artifacts or noises more effectively and preserve image edges better. Similar results were found for clinical data case. Conclusion: A novel ART-RIANLM method for sparse-view CT reconstruction is presented with superior image. Compared to the conventional ART-NLM method, the SNR and MAE from ART-RIANLM increases 47% and decreases 74%, respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Verification of Flux Sensitivity Estimates Using the MCNP Tally Perturbation Tool

Nuclear data is commonly used in applications such as nuclear nonproliferation, safeguards, and criticality safety. More specifically, nuclear data is used in predictive simulation codes like the Monte-Carlo N-Particle (MCNP ® ) transport code, Serpent, and similar radiation transport codes. The improvement of nuclear data enables more precise and accurate simulations, which result in higher fidelity designs and reduced operational/procedural costs. Therefore, the improvement of nuclear data is of paramount importance across the nuclear community. Nuclear data is improved and validated through integral benchmark experiments. The design of benchmark experiments is an extensive process; therefore, these experiments are often optimized on multiple characteristics, including sensitivity to the nuclear data, during the design process. Sensitivity is a measure of how much a quantity changes due to changes in independent variables such as experimental configuration. An experimental design that has a larger sensitivity to the nuclear data of interest will have a larger impact on the accuracy and precision of the validated data. Past integral benchmark experiments have primarily used the effective multiplication factor ($k_{eff}$) as the predominant measured quantity; however, experiments designed with other quantities in mind would be able to optimize on validating different areas of the nuclear data. A primary goal of the EUCLID project is to design, constrain, and reduce compensating errors in experiments focused on quantities other than $k_{eff}$ to better validate nuclear data across the board. Currently, there is a capability in MCNP to easily calculate the sensitivity of $k_{eff}$ to specific nuclear data of numerous reactions types and isotopes (KSEN card); however, the sensitivity of other quantities must be estimated in more strenuous manners. For example, the perturbation feature (PERT card) of MCNP can be used to estimate first-order sensitivities of some response in fixed source simulations. A recent announcement revealed that the first- and second-order perturbation features in previous releases of MCNP contained a bug. It was identified that particles were being scored into the wrong energy bin. The bug is in the most recent public release (MCNP6.2); however, a patch has been added to the most up to date version (MCNP6.2.2) that has not been released publicly. A direct comparison of the PERT card results for an F4 (neutron flux averaged over a cell) tally before and after the patch are shown in figure 1. All simulations used in the sensitivity estimates in this report were performed with MCNP6.2.2. This work verifies the patched MCNP perturbation tool by comparing first order sensitivities made using the PERT card to estimates made using manual perturbation of the compact ENDF (ACE) files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Spatial arrangement of canopy structure and land-use history alter the effect that herbivores have on plant growth

The spatial arrangement of past and present human activities could affect the strength of species interactions through changes to environmental conditions. To better understand how land-use history might mediate the effect of insect herbivory on the growth of four herbaceous plant species at the edges between woodlands and open savannas, we coupled large-scale manipulations of canopy structure by thinning overstory trees to create savanna habitat in non-agricultural and post-agricultural longleaf pine woodlands with local-scale herbivore exclosures at two distances from habitat edges. Light availability, grasshopper abundance, and herbaceous plant cover all increased in patches that received overstory tree thinning. Land-use history altered the effect that edges created by the overstory thinning treatments had on grasshopper herbivory for one plant species (Carphephorus bellidifolius). The edge between land-use histories also altered herbivore effects on three plant species in thinned patches. These edge effects were driven in part by changes in availability of alternative resources for grasshoppers, shady edges, or grasshopper abundance. Canopy manipulation also had important effects on herbivory that were independent of the habitat edge: grasshopper herbivory reduced plant growth of the smallest species (C. bellidifolius) regardless of canopy manipulation, whereas herbivory on two larger species (Solidago nemoralis and So. odora) reduced plant growth mainly in patches with an intact overstory canopy. Collectively, this work suggests that the species-specific effects of grasshopper herbivory on plant growth were driven by both plant traits (e.g., size or growth rates) and landscape-mediated changes to grasshopper abundance, light availability, or availability of alternative resources for grasshoppers created by land-use history and canopy structure. Furthermore, because the heterogeneity in herbivory revealed by our large-scale experiment is likely linked to plant traits, our results provide a means for understanding the profound, but often idiosyncratic, effects of land-use legacies and edges on plant populations and communities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Connected Lighting Systems Efficiency Study: PoE Cable Energy Losses, Part 2

DOE published a report in November 2017 (herein referred to as “Part 1”) summarizing the results of an exploratory study investigating power losses in Ethernet cables used between PoE switches and luminaires in PoE connected lighting systems. Testing was conducted at the Pacific Northwest National Laboratory (PNNL) Connected Lighting Test Bed (CLTB) in September 2017. The results were analyzed to explore the impact of cable selection on PoE lighting system energy efficiency, as well as the effectiveness of guidelines published by the American National Standards Institute (ANSI) C137 Lighting Systems Committee in 2017. The guidance offered in ANSI C137.3-2017 was found to be effective in limiting cable energy losses to 5% in PoE lighting applications, provided that the average cable length on a project does not exceed 50 m. This Part 2 report summarizes the results of a continued investigation of the power losses in Ethernet cables used between PoE switches and luminaires in PoE connected lighting systems. Testing was conducted at the PNNL CLTB in July-August 2018. A test setup comprising a PoE switch, a set of luminaires, and a reference meter was again used to test multiple cable models of varying design. The results were analyzed to explore the impact of cable selection and installation practices (e.g., cable bending, cable bundling, and installation in conduit) on PoE lighting system energy efficiency, as well as the effectiveness of the ANSI C137.3 guidelines. Notably, three cables—two of which were shielded—were previously excluded from the Part 1 study due to compatibility issues. All three cables were included in this Part 2 study, along with a fourth model cable introduced in Part 2. In addition, whereas no patch cords were used in Part 1, patch cords were used in some Part 2 testing. The ANSI C137.3 guidance was again shown to effectively limit power losses to less than 5% in the cables tested (varying in AWG, Category, shielding, fire rating, and manufacturer), and AWG again proved to be the most important cable design variable for energy performance, as expected. However, these findings should not be construed as being representative of all cable models and installation practices. For example, energy losses would be greater when cables are connected to patch cords, bundled in conduit, and loaded with powered devices (PDs) approaching 100 W input power. The other key finding was that with 44 W luminaires as PDs and room ambient temperatures below 30°C, cable energy losses were not substantially increased by cable bending or bundling in uninsulated conduit. However, environments with higher ambient temperatures will have greater energy losses due to increased conductor DCR. In addition, product selection and installation practices will have increased importance as PDs approaching 100 W input power—conveyed by a single Ethernet cable—are introduced following publication of the forthcoming Institute of Electrical and Electronics Engineers (IEEE) Standard 802.3bt. The report also provides recommendations and next steps, which include plans for additional PoE cable energy losses testing with higher-power PDs to more fully explore the potential of PoE lighting systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Integrating NDVI-Based Within-Wetland Vegetation Classification in a Land Surface Model Improves Methane Emission Estimations

Earth system models (ESMs) are a common tool for estimating local and global greenhouse gas emissions under current and projected future conditions. Efforts are underway to expand the representation of wetlands in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) by resolving the simultaneous contributions to greenhouse gas fluxes from multiple, different, sub-grid-scale patch-types, representing different eco-hydrological patches within a wetland. However, for this effort to be effective, it should be coupled with the detection and mapping of within-wetland eco-hydrological patches in real-world wetlands, providing models with corresponding information about vegetation cover. In this short communication, we describe the application of a recently developed NDVI-based method for within-wetland vegetation classification on a coastal wetland in Louisiana and the use of the resulting yearly vegetation cover as input for ELM simulations. Processed Harmonized Landsat and Sentinel-2 (HLS) datasets were used to drive the sub-grid composition of simulated wetland vegetation each year, thus tracking the spatial heterogeneity of wetlands at sufficient spatial and temporal resolutions and providing necessary input for improving the estimation of methane emissions from wetlands. Our results show that including NDVI-based classification in an ELM reduced the uncertainty in predicted methane flux by decreasing the model’s RMSE when compared to Eddy Covariance measurements, while a minimal bias was introduced due to the resampling technique involved in processing HLS data. Our study shows promising results in integrating the remote sensing-based classification of within-wetland vegetation cover into earth system models, while improving their performances toward more accurate predictions of important greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

High-wavenumber solar f-mode strengthening prior to active region formation

We report a systematic strengthening of the local solar surface or fundamental f-mode one to two days prior to the emergence of an active region (AR) in the same (corotating) location. Except for a possibly related increase in the kurtosis of the magnetic field, no indication can be seen in the magnetograms at that time. Our study is motivated by earlier numerical findings of Singh et al., which showed that, in the presence of a nonuniform magnetic field that is concentrated a few scale heights below the surface, the f-mode fans out in the diagnostic kω diagram at high wavenumbers. Here we explore this possibility using data from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory and show for six isolated ARs, 11130, 11158, 11242, 11105, 11072, and 11768, that at large latitudinal wavenumbers (corresponding to horizontal scales of around 3000 km), the f-mode displays strengthening about two days prior to AR formation and thus provides a new precursor for AR formation. Furthermore, we study two ARs, 12051 and 11678, apart from a magnetically quiet patch lying next to AR 12529, to demonstrate the challenges in extracting such a precursor signal when a newly forming AR emerges in a patch that lies in close proximity to one or several already existing ARs, which are expected to pollute neighboring patches. We then discuss plausible procedures for extracting precursor signals from regions with crowded environments. The idea that the f-mode is perturbed days before any visible magnetic activity occurs at the surface can be important in constraining dynamo models aimed at understanding the global magnetic activity of the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Magnetic Separatrix as the Source Region of the Plasma Supply for an Active-region Filament

Solar filaments can be formed via chromospheric evaporation followed by condensation in the corona or by the direct injection of cool plasma from the chromosphere to the corona. We here confirm with high-resolution H α data observed by the 1.6 m New Solar Telescope of the Big Bear Solar Observatory on 2015 August 21 that an active-region filament is maintained by the continuous injection of cold chromospheric plasma. We find that the filament is rooted along a bright ridge in H α , which corresponds to the intersection of a magnetic quasi-separatrix layer with the solar surface. This bright ridge consists of many small patches whose sizes are comparable to the width of the filament threads. It is found that upflows originate from the brighter patches of the ridge, whereas the downflows move toward the weaker patches of the ridge. The whole filament is composed of two opposite-direction streams, implying that longitudinal oscillations are not the only cause of the counterstreamings, and unidirectional siphon flows with alternative directions are another possibility.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Complex Solar Coronal Jet with Two Phases

Jets often occur repeatedly from almost the same location. In this paper, a complex solar jet was observed with two phases to the west of NOAA AR 11513 on 2012 July 2. If it had been observed at only moderate resolution, the two phases and their points of origin would have been regarded as identical. However, at high resolution we find that the two phases merge into one another and the accompanying footpoint brightenings occur at different locations. The phases originate from different magnetic patches rather than being one phase originating from the same patch. Photospheric line of sight (LOS) magnetograms show that the bases of the two phases lie in two different patches of magnetic flux that decrease in size during the occurrence of the two phases. Based on these observations, we suggest that the driving mechanism of the two successive phases is magnetic cancellation of two separate magnetic fragments with an opposite-polarity fragment between them.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Magnetic Flux Cancellation as the Origin of Solar Quiet-region Pre-jet Minifilaments

We investigate the origin of 10 solar quiet-region pre-jet minifilaments , using EUV images from the Solar Dynamics Observatory ( SDO )/Atmospheric Imaging Assembly (AIA) and magnetograms from the SDO Helioseismic and Magnetic Imager (HMI). We recently found that quiet-region coronal jets are driven by minifilament eruptions, where those eruptions result from flux cancellation at the magnetic neutral line under the minifilament. Here, we study the longer-term origin of the pre-jet minifilaments themselves. We find that they result from flux cancellation between minority-polarity and majority-polarity flux patches. In each of 10 pre-jet regions, we find that opposite-polarity patches of magnetic flux converge and cancel, with a flux reduction of 10%–40% from before to after the minifilament appears. For our 10 events, the minifilaments exist for periods ranging from 1.5 hr to 2 days before erupting to make a jet. Apparently, the flux cancellation builds a highly sheared field that runs above and traces the neutral line, and the cool transition region plasma minifilament forms in this field and is suspended in it. We infer that the convergence of the opposite-polarity patches results in reconnection in the low corona that builds a magnetic arcade enveloping the minifilament in its core, and that the continuing flux cancellation at the neutral line finally destabilizes the minifilament field so that it erupts and drives the production of a coronal jet. Thus, our observations strongly support that quiet-region magnetic flux cancellation results in both the formation of the pre-jet minifilament and its jet-driving eruption.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Block-induced Complex Structures Building the Flare-productive Solar Active Region 12673

Solar active region (AR) 12673 produced 4 X-class, 27 M-class, and numerous lower-class flares during its passage across the visible solar disk in 2017 September. Our study is to answer the questions why this AR was so flare-productive and how the X9.3 flare, the largest one of the past decade, took place. We find that there was a sunspot in the initial several days, and then two bipolar regions emerged nearby it successively. Due to the standing of the pre-existing sunspot, the movement of the bipoles was blocked, while the pre-existing sunspot maintained its quasi-circular shaped umbra only with the disappearance of a part of penumbra. Thus, the bipolar patches were significantly distorted, and the opposite polarities formed two semi-circular shaped structures. After that, two sequences of new bipolar regions emerged within the narrow semi-circular zone, and the bipolar patches separated along the curved channel. The new bipoles sheared and interacted with the previous ones, forming a complex topological system, during which numerous flares occurred. At the highly sheared region, a great deal of free energy was accumulated. On September 6, one negative patch near the polarity inversion line began to rapidly rotate and shear with the surrounding positive fields, and consequently the X9.3 flare erupted. Our results reveal that the block-induced complex structures built the flare-productive AR and the X9.3 flare was triggered by an erupting filament due to the kink instability. To better illustrate this process, a block-induced eruption model is proposed for the first time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator

Abstract. Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, as well as the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, canopy structure, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) by mimicking the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events, splitting the logged forest patch into disturbed and intact patches; determine the survivorship of cohorts in the disturbed patch; and modifying the biomass and necromass (total mass of coarse woody debris and litter) pools following logging. We parameterized the logging module to reproduce a selective logging experiment at the Tapajós National Forest in Brazil and benchmarked model outputs against available field measurements. Our results suggest that the model permits the coexistence of early and late successional functional types and realistically characterizes the seasonality of water and carbon fluxes and stocks, the forest structure and composition, and the ecosystem succession following disturbance. However, the current version of FATES overestimates water stress in the dry season and therefore fails to capture seasonal variation in latent and sensible heat fluxes. Moreover, we observed a bias towards low stem density and leaf area when compared to observations, suggesting that improvements are needed in both carbon allocation and establishment of trees. The effects of logging were assessed by different logging scenarios to represent reduced impact and conventional logging practices, both with high and low logging intensities. The model simulations suggest that in comparison to old-growth forests the logged forests rapidly recover water and energy fluxes in 1 to 3 years. In contrast, the recovery times for carbon stocks, forest structure, and composition are more than 30 years depending on logging practices and intensity. This study lays the foundation to simulate land use change and forest degradation in FATES, which will be an effective tool to directly represent forest management practices and regeneration in the context of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

A practical method of determining water current velocities and diffusion coefficients in coastal waters by remote sensing techniques

A simplified procedure is presented for determining water current velocities and diffusion coefficients. Dye drops which form dye patches in the receiving water are made from an aircraft. The changes in position and size of the patches are recorded from two flights over the area. The simplified data processing procedure requires only that the ground coordinates about the dye patches be determined at the time of each flight. With an automatic recording coordinatograph for measuring coordinates and a computer for processing the data, this technique provides a practical method of determining circulation patterns and mixing characteristics of large aquatic systems. This information is useful in assessing the environmental impact of waste water discharges and for industrial plant siting.

James, W. P.↗