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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Arabidopsis calcium-dependent protein kinase 3 regulates actin cytoskeleton organization and immunity

Pattern-triggered immunity and effector-triggered immunity are two primary forms of innate immunity in land plants. The molecular components and connecting nodes of pattern-triggered immunity and effector-triggered immunity are not fully understood. Here, we report that the Arabidopsis calcium-dependent protein kinase CPK3 is a key regulator of both pattern-triggered immunity and effector-triggered immunity. In vitro and in vivo phosphorylation assays, coupled with genetic and cell biology-based analyses, show that actin-depolymerization factor 4 (ADF4) is a physiological substrate of CPK3, and that phosphorylation of ADF4 by CPK3 governs actin cytoskeletal organization associated with pattern-triggered immunity. CPK3 regulates stomatal closure induced by flg22 and is required for resistance to Pst DC3000. Our data further demonstrates that CPK3 is required for resistance to Pst DC3000 carrying the effector AvrPphB. These results suggest that CPK3 is a missing link between cytoskeleton organization, pattern-triggered immunity and effector-triggered immunity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The 100-month Swift catalogue of supergiant fast X–ray transients

Supergiant fast X-ray transients (SFXTs) are high mass X-ray binaries (HMXBs) displaying X-ray outbursts that can reach peak luminosities up to 10 38 erg s -1 and spend most of their lives in more quiescent states with luminosities as low as 10 32 -10 33 erg s -1 . During the quiescent states, less luminous flares are also frequently observed with luminosities of 10 34 -10 35 erg s -1 . The main goal of the comprehensive and uniform analysis of the SFXT Swift triggers presented in this paper is to provide tools to predict whether a transient that has no known X-ray counterpart may be an SFXT candidate. These tools can be exploited for the development of future missions exploring the variable X-ray sky through large field-of-view instruments. We examined all available data on outbursts of SFXTs that triggered the Swift/Burst Alert Telescope (BAT) collected between 2005 August 30 and 2014 December 31, in particular those for which broad-band data, including the Swift/X-ray Telescope (XRT) data, are also available. This work complements and extends our previous catalogue of SFXT flares detected by BAT from 2005 February 12 to 2013 May 31, since we now include the additional BAT triggers recorded until the end of 2014 (i.e. beyond the formal first 100 months of the Swift mission). Due to a change in the mission’s observational strategy, virtually no SFXT triggers obtained a broad-band response after 2014. We processed all BAT and XRT data uniformly by using the Swift Burst Analyser to produce spectral evolution dependent flux light curves for each outburst in the sample. The BAT data allowed us to infer useful diagnostics to set SFXT triggers apart from the general γ-ray burst population, showing that SFXTs uniquely give rise to image triggers and are simultaneously very long, faint, and ‘soft’ hard-X-ray transients. We find that the BAT data alone can discriminate very well the SFXTs from other classes of fast transients, such as anomalous X-ray pulsars and soft gamma repeaters. On the contrary, the XRT data collected around the time of the BAT triggers are shown to be decisive for distinguishing SFXTs from, for instance, accreting millisecond X-ray pulsars and jetted tidal disruption events. The XRT observations of 35 (out of 52 in total) SFXT BAT triggers show that in the soft X-ray energy band, SFXTs display a decay in flux from the peak of the outburst of at least three orders of magnitude within a day and rarely undergo large re-brightening episodes, favouring in most cases a rapid decay down to the quiescent level within three to five days (at most).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Prototype Design of Global Common Module for ATLAS Experiment’s Phase-II Upgrade

A new Global Trigger subsystem will be installed in the Level-0 Trigger as part of HL-LHC Upgrade of ATLAS during the upcoming Long-Shutdown 3. It will feature new and improved trigger hardware and algorithms, and an increased maximum output rate of 1 MHz. The Global Trigger will run offline-like trigger algorithms on full-granularity data, gathered from several sub-detectors and trigger-processing subsystems. A single Global Common Module (GCM) hardware is implemented across the Global Trigger system to be used as Multiplexer Processor, Global Event Processor and CTP Interface (gCTPi). This common hardware platform method will minimize the complexity of the firmware and simplify the system design and long-term maintenance. The GCM prototype is an ATCA front form factor board with two Xilinx Virtex UltraScale+ FPGA VU13P and one ZYNQ UltraScale+ FPGA ZU19EG and seventeen 25.78125 Gb/s FireFly duplex optical modules on it. The total power consumption of this board must be less than 350 W, and the temperature of the optical modules should be less than 70 °C in the worst case. The VU13Ps serve as algorithms processor nodes such as MUX, GEP and gCTPi, and the ZU19EG with Peta Linux OS running on it, is used as Command/Control/Readout Unit to configure and monitor the board and communicate with the ATLAS Detector Control System (DCS). The development of an ATCA blade with three large FPGAs and about 200 optical links running at 25Gb/s is a very challenging task, and the successful test results have demonstrated this GCM prototype as an advancement of state-of-the-art electronics module design in HEP experiments. This paper presents the hardware design considerations, functionalities, and performance test results of this GCM prototype.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The ATLAS experiment at the CERN Large Hadron Collider: a description of the detector configuration for Run 3

The ATLAS detector is installed in its experimental cavern at Point 1 of the CERN Large Hadron Collider. During Run 2 of the LHC, a luminosity of ℒ = 2 × 10 34 cm -2 s -1 was routinely achieved at the start of fills, twice the design luminosity. For Run 3, accelerator improvements, notably luminosity levelling, allow sustained running at an instantaneous luminosity of ℒ = 2 × 10 34 cm -2 s -1 , with an average of up to 60 interactions per bunch crossing. The ATLAS detector has been upgraded to recover Run 1 single-lepton trigger thresholds while operating comfortably under Run 3 sustained pileup conditions. A fourth pixel layer 3.3 cm from the beam axis was added before Run 2 to improve vertex reconstruction and b-tagging performance. New Liquid Argon Calorimeter digital trigger electronics, with corresponding upgrades to the Trigger and Data Acquisition system, take advantage of a factor of 10 finer granularity to improve triggering on electrons, photons, taus, and hadronic signatures through increased pileup rejection. The inner muon endcap wheels were replaced by New Small Wheels with Micromegas and small-strip Thin Gap Chamber detectors, providing both precision tracking and Level-1 Muon trigger functionality. Trigger coverage of the inner barrel muon layer near one endcap region was augmented with modules integrating new thin-gap resistive plate chambers and smaller-diameter drift-tube chambers. Tile Calorimeter scintillation counters were added to improve electron energy resolution and background rejection. Upgrades to Minimum Bias Trigger Scintillators and Forward Detectors improve luminosity monitoring and enable total proton-proton cross section, diffractive physics, and heavy ion measurements. These upgrades are all compatible with operation in the much harsher environment anticipated after the High-Luminosity upgrade of the LHC and are the first steps towards preparing ATLAS for the High-Luminosity upgrade of the LHC. This paper describes the Run 3 configuration of the ATLAS detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence↗
DOE OSTI2022

High Energy Physics Research at the Energy Frontier with the CMS Experiment

The physics analysis goals are to continue improving upon the search for the Higgs to dimuon decay using the CMS experiment at the LHC to further improve the Higgs coupling measurement with the additional data from LHC Run 3, and to explore searches for long-lived particles that reach the muon system of CMS using new Level-1 muon triggers the group is developing. An additional physics goal is to further develop the science case for a novel muonion collider. The experimental goals are to continue operational support of the CMS Endcap Muon Track Finder, a key component of the CMS Level-1 trigger system. The group also proposes to continue its leadership role in muon triggering for the HL-LHC upgrade through algorithm and electronics R&D. Finally, Acosta will continue as CMS Trigger Co-Coordinator responsible for the High Level Trigger system of CMS, lead the EMTF project, and serve as USCMS Trigger Operations Level-2 manager.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Using pile-up collisions as an abundant source of low-energy hadronic physics processes in ATLAS and an extraction of the jet energy resolution

During the 2015–2018 data-taking period, the Large Hadron Collider delivered proton-proton bunch crossings at a centre-of-mass energy of 13 TeV to the ATLAS experiment at a rate of roughly 30 MHz, where each bunch crossing contained an average of 34 independent inelastic proton-proton collisions. The ATLAS trigger system selected roughly 1 kHz of these bunch crossings to be recorded to disk. Offline algorithms then identify one of the recorded collisions as the collision of interest for subsequent data analysis, and the remaining collisions are referred to as pile-up. Pile-up collisions represent a trigger-unbiased dataset, which is evaluated to have an integrated luminosity of 1.33 pb -1 in 2015–2018. This is small compared with the normal trigger-based ATLAS dataset, but when combined with vertex-by-vertex jet reconstruction it provides up to 50 times more dijet events than the conventional single-jet-trigger-based approach, and does so without adding any additional cost or requirements on the trigger system, readout, or storage. The pile-up dataset is validated through comparisons with a special trigger-unbiased dataset recorded by ATLAS, and its utility is demonstrated by means of a measurement of the jet energy resolution in dijet events, where the statistical uncertainty is significantly reduced for jet transverse momenta below 65 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Measurements of dihadron correlations relative to the event plane in Au+Au collisions at $\sqrt{s_{NN}} =200$ GeV*

Dihadron azimuthal correlations containing a high transverse momentum ($ p_{T} $) trigger particle are sensitive to the properties of the nuclear medium created at RHIC through the strong interactions occurring between the traversing parton and the medium, i.e. jet-quenching. Previous measurements revealed a strong modification to dihadron azimuthal correlations in Au+Au collisions with respect to p+p and d+Au collisions. The modification increases with the collision centrality, suggesting a path-length or energy density dependence to the jet-quenching effect. This paper reports STAR measurements of dihadron azimuthal correlations in mid-central (20%-60%) Au+Au collisions at $ \sqrt{s_{\rm{NN}}} = 200 $ GeV as a function of the trigger particle's azimuthal angle relative to the event plane, $ \phi_{s} = | \phi_{t}- \psi_{{\rm{EP}}}| $. The azimuthal correlation is studied as a function of both the trigger and associated particle $ p_{T} $. The subtractions of the combinatorial background and anisotropic flow, assuming Zero Yield At Minimum (ZYAM), are described. The correlation results are first discussed with subtraction of the even harmonic (elliptic and quadrangular) flow backgrounds. The away-side correlation is strongly modified, and the modification varies with $ \phi_{s} $, with a double-peak structure for out-of-plane trigger particles. The near-side ridge (long range pseudo-rapidity $ \Delta\eta $ correlation) appears to drop with increasing $ \phi_{s} $ while the jet-like component remains approximately constant. The correlation functions are further studied with the subtraction of odd harmonic triangular flow background arising from fluctuations. It is found that the triangular flow, while responsible for the majority of the amplitudes, is not sufficient to explain the $ \phi_{s} $-dependence of the ridge or the away-side double-peak structure. The dropping ridge with $ \phi_{s} $ could be attributed to a $ \phi_{s} $-dependent elliptic anisotropy; however, the physics mechanism of the ridge remains an open question. Even with a $ \phi_{s} $-dependent elliptic flow, the away-side correlation structure is robust. These results, with extensive systematic studies of the dihadron correlations as a function of $ \phi_{s} $, trigger and associated particle $ p_{T} $, and the pseudo-rapidity range $ \Delta\eta $, should provide stringent inputs to help understand the underlying physics mechanisms of jet-medium interactions in high energy nuclear collisions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Numerical simulation of Li-pellet injection experiments for ELM-pacing in EAST

The injection of light impurity granules into fusion research discharges has shown a great potential for ELM pacing in future nuclear devices. The present work employed a model considering both pellet ablation and transport to systematically study for the first time the evolution of both impurity Li species and target plasma in the edge plasma during single and repeated Li pellet injections, with all initial information extracted from the EAST experiments. The evolutionary distributions of atomic and ionized Li species were presented and show good consistency with experimental CCD camera images. Simulation studies were carried out for single and repeated pellet injections at the outer mid-plane, and statistical uncertainty of ELM pacing rates triggering ELMs is discussed with regard to related injection conditions. It is found that the pressure locally caused by an ELM pacing pellet (with a diameter of 0.6 ~ 0.7 mm) was 1.8–2.4 times its unperturbed magnitude in the EAST shots of interest. Accumulation from repeated pellet injections results in the rise of pedestal height at a high injection frequency and this effect becomes stronger with increasing pellet size. Pressure changes are also evident in a scenario of multiple small pellets per stroke, which could lead to a nonnegligible, probabilistic ELM triggering rate observed experimentally. The effects of other possible factors are also discussed. With the assumption that the ELM trigger rate of a Li pellet of 0.7 mm diameter is 100%, the predicted trigger rates are in good agreement with those observed in experiments. This work can help understand the statistically probabilistic behavior of ELM triggering efficiency observed in previous studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Characterization of ELM pacing via vertical jogs on DIII-D

Edge localized mode (ELM) pacing via vertical plasma oscillations or jogging has been successfully demonstrated on DIII-D. Rapid vertical movement of the plasma toward the X-point has been shown to effectively trigger ELMs. By vertically oscillating the plasma at a rate of 10 Hz, the ELM frequency increased from ~5 Hz, the natural ELM frequency in similar DIII-D discharges, to 20 Hz. Downward jogs have been observed to trigger multiple ELMs in one cycle. ELMs triggered at higher than natural frequencies lead to smaller decreases in stored energy, from 8% to as little as below 1%. As a consequence, the peak heat flux to the divertor has been observed to be reduced by a factor of ~2. In addition, a reduction in the carbon impurity concentration has been observed. During downward jogs in the lower single null (LSN) configuration, the X-point movement is slower and smaller than the top of the plasma. As a result, a reduction in the plasma cross-section and hence volume has been observed. To understand the mechanism of ELM triggering by jogging, a toy model of the edge toroidal current has been built and tested with DIII-D experiment data. The experimental data and model suggest that when the plasma moves down toward the X-point, a net positive toroidal current is locally induced in the edge region. ELITE stability analysis suggests that this current pushes the plasma state across the peeling side of the peeling–ballooning stability boundary into the unstable region triggering ELMs.

ELM pacing↗