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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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Search for inelastic dark matter with the CDMS II experiment
Results are presented from a reanalysis of the entire five-tower data set acquired with the Cryogenic Dark Matter Search (CDMS II) experiment at the Soudan Underground Laboratory, with an exposure of 969 kg-days. The analysis window was extended to a recoil energy of 150 keV, and an improved surface-event background-rejection cut was defined to increase the sensitivity of the experiment to the inelastic dark matter (iDM) model. Three dark matter candidates were found between 25 keV and 150 keV. The probability to observe three or more background events in this energy range is 11%. Because of the occurrence of these events, the constraints on the iDM parameter space are slightly less stringent than those from our previous analysis, which used an energy window of 10-100 keV.
Interpretation of proton radiography experiments of hohlraums with three-dimensional simulations [Interpretation of proton radiography experiments of hohlraums with 3D simulations]
Proton radiography experiments of laser-irradiated hohlraums performed at the OMEGA laser facility are analyzed using three-dimensional (3D) hydrodynamic simulations coupled to a proton trajectography package. Experiments with three different laser irradiation patterns were performed, and each produced a distinct proton image. By comparing these results with synthetic proton images obtained by sending protons through plasma profiles in the hohlraum obtained from 3D radiation hydrodynamic simulations, it is found that the simulated images agree favorably with the experimental images when electric fields, due to the electron pressure gradients that arise from 3D structures occurring during plasma expansion, are included. Furthermore, these comparisons provide quantitative estimates of the electric field present inside the hohlraums.
High Magnetic Shear Gain in a Liquid Sodium Stable Couette Flow Experiment: A Prelude to an {alpha}-{Omega} Dynamo
The {Omega} phase of the liquid sodium {alpha}-{Omega} dynamo experiment at New Mexico Institute of Mining and Technology in cooperation with Los Alamos National Laboratory has demonstrated a high toroidal field B{sub {phi}} that is {approx_equal}8xB{sub r}, where B{sub r} is the radial component of an applied poloidal magnetic field. This enhanced toroidal field is produced by the rotational shear in stable Couette flow within liquid sodium at a magnetic Reynolds number Rm{approx_equal}120. Small turbulence in stable Taylor-Couette flow is caused by Ekman flow at the end walls, which causes an estimated turbulence energy fraction of ({delta}v/v){sup 2{approx}}10{sup -3}.
Theory of Pump-Probe Experiments of Metallic Metamaterials Coupled to a Gain Medium
Not Available
Data Exploration Toolkit for serial diffraction experiments
This paper describes a set of tools allowing experimentalists insight into the variation present within large serial data sets. Ultrafast diffraction at X-ray free-electron lasers (XFELs) has the potential to yield new insights into important biological systems that produce radiation-sensitive crystals. An unavoidable feature of the ‘diffraction before destruction’ nature of these experiments is that images are obtained from many distinct crystals and/or different regions of the same crystal. Combined with other sources of XFEL shot-to-shot variation, this introduces significant heterogeneity into the diffraction data, complicating processing and interpretation. To enable researchers to get the most from their collected data, a toolkit is presented that provides insights into the quality of, and the variation present in, serial crystallography data sets. These tools operate on the unmerged, partial intensity integration results from many individual crystals, and can be used on two levels: firstly to guide the experimental strategy during data collection, and secondly to help users make informed choices during data processing.
Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors
Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.
Solar PV and BESS Plant-Level Voltage Control and Interactions: Experiments and Analysis
In real world operation, low-frequency oscillations associated with plant-level voltage control of inverter-based resources (IBRs) have been a concern of grid operators. Here, this research aims to demonstrate and analyze the effect of plant-level voltage control on system stability and potential interactions among IBRs. The experiment results of a 13.2-kV system interconnected with two IBRs—a 1-MW battery energy storage system (BESS) and a 430-kW solar photovoltaic (PV) plant—are presented. Both 0.5-Hz and 3-Hz oscillations become visible at certain conditions. The phenomenon is further explained by use of a feedback system consisting of the plant-level droop control and the effect of reactive power or var injection on voltage. The main components of the block diagram are obtained via frequency scan measurements. The analysis offers an understanding of the main contributors and other influencing factors of the 3-Hz and 0.5-Hz modes. It also reveals the role of the volt-var droop gain, the low-pass filter time constant, and the system impedance in stability.
Emergence and Extinction of a New Phase During On-Off Experiments Related to Flash Sintering of 3YSZ
Abstract not provided
Broadening of Diffraction Peak Widths and Temperature Nonuniformity During Flash Experiments
Not provided.
A critical comparison of 3D experiments and simulations of tricalcium silicate hydration
Abstract not provided
The Tunka experiment: From small “toy” experiments to multi-TeV gamma-ray observatory
Cherenkov experiments developed, carried out, presently being operated and under development in the Tunka Valley are reviewed. We present the physics goals of the experiments covering a wide field of studies of cosmic rays in the energy range of 10{sup 15}–10{sup 18} eV to multi-TeV gamma-ray astronomy.
Search for a new heavy gauge-boson resonance decaying into a lepton and missing transverse momentum in 36 fb$^{-1}$ of pp collisions at $\sqrt{s} = 13$ TeV with the ATLAS experiment
The results of a search for new heavy W ' bosons decaying to an electron or muon and a neutrino using proton–proton collision data at a centre-of-mass energy of √s = 13 TeV are presented. The dataset was collected in 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb –1 . As no excess of events above the Standard Model prediction is observed, the results are used to set upper limits on the W ' boson cross-section times branching ratio to an electron or muon and a neutrino as a function of the W ' mass. Here, assuming a W ' boson with the same couplings as the Standard Model W boson, W ' masses below 5.1 TeV are excluded at the 95% confidence level.
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments
This work describes the investigation of neuromorphic computing-based spiking neural network (SNN) models used to filter data from sensor electronics in high energy physics experiments conducted at the High Luminosity Large Hadron Collider. We present our approach for developing a compact neuromorphic model that filters out the sensor data based on the particle's transverse momentum with the goal of reducing the amount of data being sent to the downstream electronics. The incoming charge waveforms are converted to streams of binary-valued events, which are then processed by the SNN. We present our insights on the various system design choices - from data encoding to optimal hyperparameters of the training algorithm - for an accurate and compact SNN optimized for hardware deployment. Our results show that an SNN trained with an evolutionary algorithm and an optimized set of hyperparameters obtains a signal efficiency of about 91% with nearly half as many parameters as a deep neural network.
The Midlatitude Continental Convective Clouds Experiment (MC3E)
The Midlatitude Continental Convective Clouds Experiment (MC3E), a field program jointly led by the U.S. Department of Energy’s Atmospheric Radiation Measurement program and the NASA Global Precipitation Measurement (GPM) Mission, was conducted in south-central Oklahoma during April – May 2011. MC3E science objectives were motivated by the need to improve understanding of midlatitude continental convective cloud system lifecycles, microphysics, and GPM precipitation retrieval algorithms. To achieve these objectives a multi-scale surface- and aircraft-based in situ and remote sensing observing strategy was employed. A variety of cloud and precipitation events were sampled during the MC3E, of which results from three deep convective events are highlighted. Vertical structure, air motions, precipitation drop-size distributions and ice properties were retrieved from multi-wavelength radar, profiler, and aircraft observations for an MCS on 11 May. Aircraft observations for another MCS observed on 20 May were used to test agreement between observed radar reflectivities and those calculated with forward-modeled reflectivity and microwave brightness temperatures using in situ particle size distributions and ice water content. Multi-platform observations of a supercell that occurred on 23 May allowed for an integrated analysis of kinematic and microphysical interactions. A core updraft of 25 ms-1 supported growth of hail and large rain drops. Data collected during the MC3E campaign is being used in a number of current and ongoing research projects and is available through the DOE ARM and NASA data archives.
The Olympic Mountains Experiment (OLYMPEX)
The Olympic Mountains Experiment (OLYMPEX) took place during the 2015/16 fall–winter season in the vicinity of the mountainous Olympic Peninsula of Washington State. The goals of OLYMPEX were to provide physical and hydrologic ground validation for the U.S.–Japan Global Precipitation Measurement (GPM) satellite mission and, more specifically, to study how precipitation in Pacific frontal systems is modified by passage over coastal mountains. Four transportable scanning dual-polarization Doppler radars of various wavelengths were installed for this study. Surface stations were placed at various altitudes to measure precipitation rates, particle size distributions, and fall velocities. Autonomous recording cameras monitored and recorded snow accumulation. Four research aircraft supplied by NASA investigated precipitation processes and snow cover, and supplemental rawinsondes and dropsondes were deployed during precipitation events. Finally, numerous Pacific frontal systems were sampled, including several reaching “atmospheric river” status, warm- and cold-frontal systems, and postfrontal convection.
Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA)
With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in-situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from June 21 to July 20, 2017 and January 15 to February 18, 2018 in the Azores. The flights were designed to maximize the synergy between in-situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Lastly, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.