Suriname Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for Suriname.
ETI, Energy Transitions Initiative, Islands, Snaps↗
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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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A deep potential model with long-range electrostatic interactions
Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make molecular simulations with the accuracy of quantum mechanical density functional theory possible at a cost only moderately higher than that of empirical force fields. However, the majority of these models lack explicit long-range interactions and fail to describe properties that derive from the Coulombic tail of the forces. To overcome this limitation, we extend the DP model by approximating the long-range electrostatic interaction between ions (nuclei + core electrons) and valence electrons with that of distributions of spherical Gaussian charges located at ionic and electronic sites. The latter are rigorously defined in terms of the centers of the maximally localized Wannier distributions, whose dependence on the local atomic environment is modeled accurately by a deep neural network. In the DP long-range (DPLR) model, the electrostatic energy of the Gaussian charge system is added to short-range interactions that are represented as in the standard DP model. The resulting potential energy surface is smooth and possesses analytical forces and virial. Missing effects in the standard DP scheme are recovered, improving on accuracy and predictive power. By including long-range electrostatics, DPLR correctly extrapolates to large systems the potential energy surface learned from quantum mechanical calculations on smaller systems. We illustrate the approach with three examples: the potential energy profile of the water dimer, the free energy of interaction of a water molecule with a liquid water slab, and the phonon dispersion curves of the NaCl crystal.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
American Samoa Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for American Samoa.
ETI, Energy Transitions Initiative, Islands, Ameri↗
Puerto Rico Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for Puerto Rico.
ETI, Energy Transitions Initiative, Islands, Snaps↗
Trinidad & Tobago Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for Trinidad & Tobago.
ETI, Energy Transitions Initiative, Islands, Snaps↗
Turks & Caicos Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for Turks & Caicos.
ETI, Energy Transitions Initiative, Island, Snapsh↗
St. Lucia Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for St. Lucia.
ETI, Energy Transitions Initiative, Islands, Snaps↗
Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy
Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.
100% renewable energy↗
Probing Clustering Dynamics between Silicon and PAA or LiPAA Slurries under Processing Conditions
This work explores the complex interplay between slurry aggregation, agglomeration, and conformation (i.e., shape) of poly(acrylic acid) (PAA)- and lithiated PAA-based silicon slurries as a function of the shear rate and the resulting slurry homogeneity. These values were measured by small-angle neutron scattering (SANS) and rheology-coupled ultra-SANS at conditions relevant to battery electrode casting. Different binder solution preparation methods, either a ball milling (BM) process or a planetary centrifugal mixing (PCM) process, dramatically modify the resulting polymer dynamics and organization around a silicon material. This is due to the different energy profiles of mixing where the more violent and higher energy PCM causes extensive breakdown and reformation of the binder, which is now likely in a branched conformation, while the lower energy BM results in simply lower-molecular weight linear polymers. In conclusion, the breakdown and reorganization of the polymer structure affect silicon slurry homogeneity, which affects subsequent electrode architecture.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Compact Instrument for Measuring Profile of a Light Beam
The beamviewer is an optical device designed to be attached to a charge-coupled-device (CCD) image detector for measuring the spatial distribution of intensity of a beam of light (the beam profile ) at a designated plane intersecting the beam. The beamviewer-and-CCD combination is particularly well suited for measuring the radiant- power profile (for a steady beam) or the radiant-energy profile (for a pulsed beam) impinging on the input face or emerging from the output face of a bundle of optical fibers. The beamviewer and-CCD combination could also be used as a general laboratory instrument for profiling light beams, including beams emerging through small holes and laser beams in free space.
Papanyan, Valeri↗
Antigua & Barbuda Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for Antigua and Barbuda.
ETI, Energy Transitions Initiative, Islands, Antig↗
Marshall Islands Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for the Marshall Islands.
ETI, Energy Transitions Initiative, Snapshot, Mars↗
Dominican Republic Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for the Dominican Republic.
ETI, Energy Transitions Initiative, Islands, Snaps↗
Cayman Islands Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for the Cayman Islands.
ETI, Energy Transitions Initiative, Islands, Cayma↗
St. Kitts & Nevis Energy Snapshot 2020
This fact sheet is an update of Energy Transitions Initiative Islands series energy profile for St. Kitts & Nevis.
ETI, Energy Transitions Initiative, Islands, Snaps↗
A blessing in disguise : Characterisations of ProtoDUNE photon showers for neutrino measurements in DUNE
There are few areas of particle physics as open to new discoveries as the neutrino sector. Although these particles are among the most abundant in the universe, their weak coupling to ordinary matter makes them a challenge to study. The Deep Underground Neutrino Experiment (DUNE) is an upcoming precision experiment in neutrino physics planned to be built between Illinois and South Dakota in the US. The most powerful neutrino beam in the world will be aimed at the largest liquid argon time projection chamber in the world through 1300 km of solid rock. In order to prototype this detector, a scale model was constructed and operated at CERN in 2018 called ProtoDUNE. This thesis presents three studies performed on this detector. The first concerns the readout of detector data by the FELIX data acquisition system, as well as compression studies performed on the same data. The second study concerns the identification of photons created in neutral pion decay, which form a major background to neutrino-produced electrons. The distinction between electrons and photons is based on the differing energy deposition in the initial part of the particle showers they produce. The third study concerns the energy reconstruction of particle showers in the detector. Although photon showers created from neutral pion decay are a major background to the eventual neutrino signal, they have a known energy profile and can thus be used to calibrate the energy reconstruction of particle showers in general, a vital requirement for DUNE’s physics goals.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
A Blessing in Disguise -- Characterisations of ProtoDUNE photon showers for neutrino measurements in DUNE
This thesis presents three studies performed on ProtoDUNE, a prototype liquid argon time projection chamber for the Deep Underground Neutrino Experiment (DUNE). The first study concerns the readout of detector data by the FELIX data acquisition system, as well as compression studies performed on the same data. The second study concerns the identification of photons created in neutral pion decay, which form a major background to neutrino-produced electrons. The distinction between electrons and photons is based on the differing energy deposition in the initial part of the particle showers they produce. The third study concerns the energy reconstruction of these particle showers in the detector. They have a known energy profile and can thus be used to calibrate the energy reconstruction of particle showers in general, a vital requirement for DUNE’s physics goals.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Variability and Diversity Load Model Tool [SWR-20-03]
The motivation for the development of this tool and the underlying algorithms and methods was to enable the development of high-temporal resolution, realistic time-series data for quasi-static time-series (QSTS) analysis of distribution systems. Often, aggregated load profile data for a distribution circuit is available (e.g. feeder loading data collected via SCADA at the utility substation) and, while this data is typically accurate it masks the considerable variability of the 100’s or 1000’s of individual loads connected on the circuit. This tool was developed to model both the increased variability expected for these individual loads (e.g. the load of a single distribution transformer connected to 8-12 houses) and the expected diversity between loads on the circuit. It is important to note that the difference in variability and diversity, in the context of this tool, is that variability modeling only adds representative variability due to disaggregated load characteristics (e.g. the presence in the load profile of loads turning off and on like an air conditioner/oven) while the average energy profile remains the same as the user supplied power profile. Diversity modeling generates multiple individual load profiles which, in aggregate, sum to the user supplied power profile. Diversity is effectively variability in the energy usage over longer periods of time than seen in the variability model. Put another way, variability modeling supplies the expected variability due to the operation of various end-use loads and diversity modeling supplies the usage differences due to human behavior, schedules, etc. This load modeling tool was developed for use in generating data for distribution systems. Modeling is summarized by two major functions: 1) taking low resolution load profiles and adding intra-seconds variability onto the profiles, and 2) taking a user supplied load profile and distribution factors and adding both diversity and variability to the user supplied profile.
Zhu, Xiangqi↗