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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

ICESat 2/ATLAS Onboard Flight Science Receiver Algorithms: Purpose, Process, and Performance

The Advanced Topographic Laser Altimetry System (ATLAS) is the sole instrument on the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2). Without some method of reducing the transmitted data, the volume of ATLAS telemetry would far exceed the normal X-band downlink capability or require many more ground station contacts. The ATLAS Onboard Flight Science Receiver Algorithms (hereinafter Receiver Algorithms or Algorithms) control the amount of science data that is telemetered from the instrument, limiting the data volume by distinguishing surface echoes from background noise, and allowing the instrument to telemeter data from only a small vertical region about the signal. This is accomplished through the transfer of the spacecraft's location and attitude to the instrument every second, use of an onboard Digital Elevation Model, implementation of signal processing techniques, and use of onboard relief and surface type reference maps. Extensive ground testing verified the performance of the Algorithms. On-orbit analysis shows that the Algorithms are working as expected from the ground testing; they are performing well and meeting the mission requirements.

Algoritms, Signal Processing, Optimization, Flight↗
DOE OSTI2025

DEVELOPMENT OF AN INTEGRATED SECURITY AND SAFETY MONITORING SYSTEM FOR SPENT NUCLEAR FUEL AND HIGH-LEVEL WASTE TRANSPORTATION

This paper provides an overview of the progress to date, and discussion of the path forward, related to designing, fabricating, and testing an integrated security and safety monitoring system (ISSMS) for railcars used to transport spent nuclear fuel (SNF) and high-level radioactive waste (HLW) in the United States. The system will comply with the US Department of Energy’s (DOE) Order 460.2B “Departmental Materials Transportation Management” and the Association of American Railroads’ (AAR) standard S-2043 “Performance Specification for Trains Used to Carry High-level Radioactive Material” [1] developed specifically for railcars used to transport high-level radioactive material (HLRM). DOE is in the process of developing and testing an ISSMS that will satisfy both DOE requirements and AAR standards. DOE has already developed railcar designs for transportation of HLRM. In 2024, DOE’s Atlas railcar project completed the design, fabrication and testing of three railcar types: transportation cask-carrying, buffer, and security escort, resulting in AAR conditional approval to operate on freight rail networks in North America. DOE decided to combine the required security and safety systems into one system, and this combined system is the subject of the current effort. DOE is developing and proposes to implement the ISSMS for these railcars as part of the build out of the railcar fleet. DOE began planning for development of the ISSMS in February 2020. The project is divided into seven phases starting with conceptual design and continuing through production design, as shown in Figure 1. An earlier version of the system was tested as part of the Atlas railcar consist demonstration test run in 2023. This paper describes the design features and system testing using the Atlas project railcars, and laboratory testing completed to date. The paper will also describe the activities planned to support the DOE project to ship the High Burn-Up Research Cask (HBRC) in 2027.

Schultze, Michael [ORNL] (ORCID:0000000283205671)↗
DOE OSTI2025

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants

The plant community has a strong track-record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g., 10x genomics), has resulted in an explosion of outstanding single cell and nuclei datasets that can be put in an in situ context within tissues (e.g., a cell atlas)1. In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due to accessibility, ease-of-use and access to expertise along with depth of analysis benefits. On the other hand, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis2, as the search for plant-based natural products has played a significant role in improving human health throughout history. However, the employment of proteomics and metabolomics assays for characterizing plant cell processes now remains significantly behind transcriptional approaches, even though both provide a direct functional readout of cell states and phenotypes.

Anderton, Christopher R. [BATTELLE (PACIFIC NW LAB↗
DOE OSTI2022

The scientific potential and technological challenges of the High-Luminosity Large Hadron Collider program

Here, we present an overview of the High-Luminosity (HL-LHC) program at the Large Hadron Collider (LHC), its scientific potential and technological challenges for both the accelerator and detectors. The HL-LHC program is expected to start circa 2027 and aims to increase the integrated luminosity delivered by the LHC by an order of magnitude at the collision energy of 14 TeV. This requires upgrades to the injector system, accelerator complex and luminosity levelling. The two experiments, ATLAS and CMS, require substantial upgrades to most of their systems in order to cope with the increased interaction rate, and much higher radiation levels than at the current LHC. We present selected examples based on novel ideas and technologies for applications at a hadron collider. Both experiments will replace their tracking systems. We describe the ATLAS pixel detector upgrade featuring novel tilted modules, and the CMS Outer Tracker upgrade with a new module design enabling use of tracks in the level-1 trigger system. CMS will also install state-of-the-art highly segmented calorimeter endcaps. Finally, we describe new picosecond precision timing detectors of both experiments. In addition, we discuss how the upgrades will enhance the physics performance of the experiments, and solve the computing challenges posed by the expected large data sets. The physics program of the HL-LHC is focused on precision measurements probing the limits of the Standard Model (SM) of particle physics and discovering new physics. We present a selection of studies that have been carried out to motivate the HL-LHC program. A central topic of exploration will be the characterization of the Higgs boson. The large HL-LHC data samples will extend the sensitivity of searches for new particles or new interactions whose existence has been hypothesized in order to explain shortcomings of the SM. Finally, we comment on the nature of large scientific collaborations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Correlations between azimuthal anisotropy Fourier harmonics in PbPb collisions at sNN =2.76 TeV in the HYDJET++ model and in the multiphase transport model

Correlations between azimuthal anisotropy Fourier harmonics vn (n=2,3,4) are studied using the events from PbPb collisions at sNN=2.76 TeV generated by the HYDJET++ and multiphase transport (AMPT) models, and compared to the corresponding experimental results obtained by the ATLAS Collaboration. The Fourier harmonics vn are measured over a wide centrality range using the two-particle azimuthal correlation method. The slopes of the v2-v3 correlation from both models are in a good agreement with the ATLAS data. The HYDJET++ model predicts a stronger slope for the v2-v4 and v3-v4 correlations than the ones experimentally measured, while the results from the AMPT model are in a rather good agreement with the experimental results. In contrast to the HYDJET++ predictions, the AMPT model predicts a boomeranglike shape in the structure of the correlations as found in the experimental data. © 2020 American Physical Society.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Data on temporal complementarity of hybrid renewable energy systems [SWR-23-09]

These datasets describe multiple facets of the temporal complementarity of co-located hybrid renewable energy systems throughout the United States. Several metrics characterizing the complementarity of generation profiles are provided on an annual and monthly basis (for both hourly and daily aggregations). These generation profiles are underpinned by hourly resource data (e.g., the WIND Toolkit and National Solar Radiation Database (NSRDB)) spanning the multi-year period 2007-2013. The data include complementarity results for greater than 1.76 million individual locations within the continental United States (CONUS). The data are intended to accompany two publications on the topic of temporal complementarity: 1) Harrison-Atlas, Dylan, Caitlin Murphy, Anna Schleifer, and Nicholas Grue. "Temporal complementarity and value of wind-PV hybrid systems across the United States." Renewable Energy 201 (2022): 111-123, doi:10.1016/j.renene.2022.10.060; and 2) Murphy, Caitlin, Harrison-Atlas, Dylan, Nicholas Grue, Vahan Gevorgian, Juan Gallego-Calderon, Shiloh Elliot and Thomas Mosier. “A Resource Assessment for FlexPower”. NREL Technical Report.

Harrison-Atlas, Dylan↗
DOE OSTI2024

Probing Naturalness with Searches for Supersymmetric Higgs Partners at the Large Hadron Collider

The discovery of the Higgs boson at the Large Hadron Collider completed the standard model of particle physics and led to the 2013 Nobel Prize. While it has been extremely successful in describing a wide variety of phenomena, the standard model cannot be the final theory of nature because it is unable to explain why the Higgs boson mass lies at the electroweak scale rather than 16 orders of magnitude larger at the Planck scale, a theoretical flaw known as the ``hierarchy problem.'' Supersymmetry is a standard model extension that could provide a natural solution to the hierarchy problem by introducing light supersymmetric Higgs partners. This proposal focused on searches that are sensitive to supersymmetric Higgs partners in data collected by the ATLAS experiment, which were carried out by the University of Illinois high-energy physics group led by PI Ben Hooberman as part of his Department of Energy Early Career Research Program award from 2017-2023. The searches were complemented by improvements to particle identification algorithms and the ATLAS trigger system that extend the sensitivity of future supersymmetry searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2022

Using Machine Learning to Identify Novel Hydroclimate States

Anthropogenic climate change is expected to alter drought risk in the future. However, droughts are not uncommon or unprecedented, as documented in tree-ring-based reconstructions of the summer average Palmer drought severity index (PDSI). Using an unsupervised machine-learning method trained on these reconstructions of pre-industrial climate, we identify outliers: years in which the spatial pattern of PDSI is unusual relative to ‘normal' variability. We show that in many regions, outliers are more frequently identified in the twentieth and twenty-first centuries. This trend is more pronounced when the regional drought atlases are combined into a single global dataset. By definition, outlier patterns at the 10% level are expected to occur once per decade, but from 1950 to 2000 more than 6 years per decade are identified as outliers in the global drought atlas (GDA). Extending the GDA through 2020 using an observational dataset suggests that anomalous global drought conditions are present in 80% of years in the twenty-first century. Our results indicate, without recourse to climate models, that the world is more frequently experiencing drought conditions that are highly unusual in the context of past natural climate variability.

Drought risk↗
DOE OSTI2020

Molecular subtyping reveals immune alterations in IDH wild‐type lower‐grade diffuse glioma

Abstract Isocitrate dehydrogenase ( IDH ) wild‐type diffuse lower‐grade glioma (LGG) is usually associated with poor outcome, but there have been disputes over its clinical outcome and classification. We present here a robust gene expression‐based molecular classification of IDH wild‐type diffuse LGG into two subtypes with distinct biological and clinical features. A discovery cohort of 49 IDH wild‐type diffuse LGGs from the Chinese Glioma Genome Atlas (CGGA) was subjected to clustering and function analysis. Seventy‐three tumors from The Cancer Genome Atlas (TCGA) were used to validate our findings. Consensus clustering of transcriptional data uncovered concordant classification of two robust and prognostically significant subtypes of IDH wild‐type LGG. Subtype 1, associated with poorer outcomes, was characterized by significantly higher immune and cytolytic scores, M2 macrophages, and up‐regulation of immune exhaustion markers, while Subtype 2, which had elevated lymphocytes and plasma cells, showed relatively favorable survival. Somatic alteration analysis revealed that Subtype 1 showed more frequently deleted regions, such as the locus of CDKN2A / CDKN2B , DMRTA1 , C9orf53 , and MTAP . Furthermore, we developed and validated a five‐gene signature for better application of this acquired stratification. Our data demonstrate the biological and prognostic heterogeneity within IDH wild‐type diffuse LGGs and deepen our molecular understandi‐g of this tumor entity. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Wu, Fan↗
DOE OSTI2021

Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models

In this work, we provide an assessment of future daily characteristics of African precipitation by explicitly comparing the results of large ensembles of global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models, specifically highlighting the similarities and inconsistencies between them. Results for seasonal mean precipitation are not always consistent amongst ensembles: in particular, global models tend to project a wetter future compared to regional models, especially over the Eastern Sahel, Central and East Africa. However, results for other precipitation characteristics are more consistent. In general, all ensembles project an increase in maximum precipitation intensity during the wet season over all regions and emission scenarios (except the West Sahel for CORE) and a decrease in precipitation frequency (under the Representative Concentration Pathways RCP8.5) especially over the West Sahel, the Atlas region, southern central Africa, East Africa and southern Africa. Depending on the season, the length of dry spells is projected to increase consistently by all ensembles and for most (if not all) models over southern Africa, the Ethiopian highlands and the Atlas region. Discrepancies exist between global and regional models on the projected change in precipitation characteristics over specific regions and seasons. For instance, over the Eastern Sahel in July–August most global models show an increase in precipitation frequency but regional models project a robust decrease. Global and regional models also project an opposite sign in the change of the length of dry spells. CORE results show a marked drying over the regions affected by the West Africa monsoon throughout the year, accompanied by a decrease in mean precipitation intensity between May and July that is not present in the other ensembles. This enhanced drying may be related to specific physical mechanisms that are better resolved by the higher resolution models and highlights the importance of a process-based evaluation of the mechanisms controlling precipitation over the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation

Accurate cell type annotation remains a major bottleneck in plant single-cell RNA sequencing (scRNA-seq), where existing tools are often adapted from animal studies and perform sub-optimally on plant data. The lack of plant-specific computational frameworks limits the construction of plant cell atlases and downstream biological discovery. We develop and evaluate scPlantAnnotate, a Transformer-based reference annotation framework tailored for plant scRNA-seq data, and benchmark it against state-of-the-art deep learning and conventional methods across multiple plant species. Species-specific scPlantAnnotate models were trained using curated datasets from Arabidopsis thaliana, Zea mays, Oryza sativa, and Glycine max. We compared scPlantAnnotate with leading baselines under both standard random-split evaluation and a more stringent leave-one-dataset-out setting, which tests robustness to completely unseen datasets and tissue types. scPlantAnnotate consistently outperforms existing approaches across all four species under random-split evaluation. In the leave-one-dataset-out setting for A. thaliana, where performance drops markedly for all methods due to strong batch effects and dataset heterogeneity, scPlantAnnotate nonetheless achieves the highest Accuracy, Macro-F1, Balanced Accuracy, and Macro-AUROC on average and ranks first on most held-out datasets. These results demonstrate improved robustness to dataset shifts, a critical yet underexplored challenge in plant scRNA-seq analysis. A freely accessible web server enables users to annotate their own datasets using pretrained models. scPlantAnnotate provides a plant-specific, Transformer-based framework for single-cell annotation that delivers state-of-the-art performance and enhanced robustness to unseen datasets. By addressing limitations of existing tools and enabling scalable reference-based annotation, scPlantAnnotate supports the development of comprehensive plant cell atlases and facilitates broader use of single-cell genomics in plant biology.

Bioinformatics↗
DOE OSTI2020

Layout and performance of HPK prototype LGAD sensors for the High-Granularity Timing Detector

The High-Granularity Timing Detector is a detector proposed for the ATLAS Phase II upgrade. The detector, based on the Low-Gain Avalanche Detector (LGAD) technology, will cover the pseudo-rapidity region of 2.4 < |n| < 4.0 with two end caps on each side and a total area of 6.4 m 2 . The timing performance can be improved by implanting an internal gain layer that can produce signals with a fast rising edge. It significantly improves the signal-to-noise ratio. The required average timing resolution per track for a minimum ionizing particle is 30 ps at the start and 50 ps at the end of the HL-LHC operation. This is achieved with several layers of LGAD. The innermost region of the detector would accumulate a 1MeV neutron-equivalent fluence up to 2.5 10 15 n eq /cm 2 including a safety factor of 1.5 before being replaced during the scheduled shutdowns. The addition of this new detector is expected to play an important role in the mitigation of high pile-ups at the HL-LHC. The layout and performance of the various versions of LGAD prototypes produced by Hamamatsu (HPK) have been studied by the ATLAS Collaboration. The breakdown voltages, depletion voltages, inter-pad gaps, collected charge as well as the time resolution have been measured and the production yield of large size sensors has been evaluated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Humidity sensitivity of large area silicon sensors: Study and implications

The production of large area sensors is one of the main challenges that the ATLAS collaboration faces for the new Inner-Tracker full-silicon detector. During the prototype fabrication phase for the High Luminosity Large Hadron Collider upgrade, several ATLAS institutes observed indications of humidity sensitivity of large area sensors, even at relative humidities well below the dew point. Specifically, prototype Barrel and End-Cap silicon strip sensors fabricated in 6-inch wafers manifest a prompt decrease of the breakdown voltage when operating under high relative humidity, adversely affecting the performance of the sensors. In addition to the investigation of these prototype sensors, a specific fabrication batch with special passivation is also studied, allowing for a deeper understanding of the responsible mechanisms. Here we present an extensive study of this behaviour on large area sensors. The locations of the hotspots at the breakdown voltage at high humidity are revealed using different infrared thermography techniques. Several palliative treatments are attempted, proving the influence of sensor cleaning methods, as well as baking, on the device performance, but no improvement on the humidity sensitivity was achieved. Furthermore, a study of the incidence of the sensitivity in different batches is also presented, introducing a hypothesis of the origins of the humidity sensitivity associated to the sensor edge design, together with passivation thickness and conformity. Several actions to be taken during sensor production and assembly are extracted from this study, in order to minimize the impact of humidity sensitivity on the performance of large area silicon sensors for High Energy Physics experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The MATHUSLA test stand

The rate of muons from LHC pp collisions reaching the surface above the ATLAS interaction point is measured as a function of the ATLAS luminosity and compared with expected rates from decays of W and Z bosons and b- and c- quark jets. In addition, data collected during periods without beams circulating in the LHC provide a measurement of the background from cosmic ray inelastic backscattering that is compared to simulation predictions. Data were recorded during 2018 in a 2.5 × 2.5 × 6.5 m 3 active volume MATHUSLA test stand detector unit consisting of two scintillator planes, one at the top and one at the bottom, which defined the trigger, and six layers of RPCs between them, grouped into three ( x, y )-measuring layers separated by 1.74 m from each other. Triggers selecting both upward-going tracks and downward-going tracks were used.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Combined analysis of HPK 3.1 LGADs using a proton beam, beta source, and probe station towards establishing high volume quality control

The upgrades of the CMS and ATLAS experiments for the high luminosity phase of the Large Hadron Collider will employ precision timing detectors based on Low Gain Avalanche Detectors (LGADs). We present a suite of results combining measurements from the Fermilab Test Beam Facility, a beta source telescope, and a probe station, allowing full characterization of the HPK type 3.1 production of LGAD prototypes developed for these detectors. We demonstrate that the LGAD response to high energy test beam particles is accurately reproduced with a beta source. Finally, we further establish that probe station measurements of the gain implant accurately predict the particle response and operating parameters of each sensor, and conclude that the uniformity of the gain implant in this production is sufficient to produce full-sized sensors for the ATLAS and CMS timing detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗