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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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Optimization of lithium vapor box divertor evaporator location on NSTX-U using SOLPS-ITER
Commercial fusion reactors will be faced with extremely high divertor target heat fluxes that will require mitigation. Simulations of detachment in an NSTX-U scenario projected to have 92 MW/m 2 unmitigated peak target heat flux are presented, which reaches sub-10 MW/m 2 target heat flux using a highly dissipating lithium vapor box divertor design. The lithium vapor box is a detached divertor design which employs lithium vapor evaporation and condensation to contain lithium below the X-point. Previous SOLPS modeling has indicated a lithium vapor box can reduce the heat flux down to 10 MW/m 2 via simultaneous evaporation from the Private Flux Region (PFR) and the Common Flux Region (CFR) sides of the vapor box. It is found here that PFR evaporation has improved access to the separatrix leading to significantly more efficient power dissipation than CFR evaporation. Simulations of target evaporation with an evaporation distribution that is self-consistent with the temperature of a Capillary Porous System with Fast flowing liquid lithium (CPSF) could reach n Li / n e ~ 0.025-0.030 at the Last Closed Flux Surface (LCFS) depending on the liquid metal flow speeds and lithium sputtering yield, while PFR-side evaporation can reach acceptable heat fluxes with n Li / n e ~ 0.038 at the LCFS. However, PFR evaporator performance can be improved if the target is allowed to be hot enough such that it reflects lithium, reaching n Li / n e ~ 0.028 and reducing required lithium evaporation. Ultimately PFR evaporation and target evaporation are found to have similar ability to produce acceptable heat flux solutions with minimal upstream concentration.
Coincidence anomaly detection for unsupervised locating of edge localized modes in the DIII-D tokamak dataset
Using supervised learning to train a machine learning model to predict an on-coming edge localized mode (ELM) requires a large number of labeled samples. Creating an appropriate data set from the very large database of discharges at a long-running tokamak, such as DIII-D, would be a very time-consuming process for a human. Considering this need and difficulty, we use coincidence anomaly detection, an unsupervised learning technique, to train an ELM-identifier to identify and label ELMs in the DIII-D discharge database. This ELM-identifier shows, simultaneously, a precision of 0.68 and a recall of 0.63 (AUC is 0.73) on identifying ELMs in example time series pulled from thousands of discharges spanning five years. In a test set of 50 discharges, the algorithm finds over 26 thousand ELM candidates, more than 5 times the existing catalog of ELMs labeled by humans.
Low Carbon Inducible2/Fatty Acid Desaturase4 locus in C. reinhardtii directs plastid peroxidase location and trans fatty acid production
Light capture and photosynthetic energy conversion depend on photosynthetic complexes that are embedded within lipid membranes. Components of these complexes are vulnerable to damage by reactive oxygen species, byproducts of photosynthesis that accumulate under environmental stress. Here we explore the basis for a lipid-based sensing mechanism allowing plants or algae to assess and respond to damage to the photosynthetic membranes. In Chlamydomonas reinhardtii, Low Carbon Inducible2 (LCI2) and Fatty Acid Desaturase4 (FAD4) are two proteins derived from the same locus by a differential splicing event, sharing an N-terminus encoded by the first two exons. FAD4 produces a 16-carbon, trans double bond-containing fatty acid found exclusively in phosphatidylglycerol of chloroplast membranes, while LCI2 recruits peroxidase activity to the membrane. The unique organization and transcriptional regulation of the LCI2/FAD4 locus represents a regulatory interface that allows cells to initiate the biosynthesis of a fatty acid unique to the photosynthetic membranes while also linking it to the production of an enzyme involved in the mitigation of reactive oxygen species.
Location and thermal evolution of the pseudogap due to spin fluctuations
We study pseudogap behavior in a metal near a spin density wave (SDW) instability due to thermal magnetic fluctuations. We consider the t–t' Hubbard model on a square lattice at a finite doping, at intermediate coupling strength, and analyze the thermal evolution of the electron spectral function between a SDW ordered state at low temperatures and a normal Fermi liquid at high temperatures. We argue that for proper description of the pseudogap one needs to sum up infinite series of diagrams for both the fermionic self-energy and the SDW order parameter in the SDW state or the magnetic correlation length in the paramagnetic state. We use the eikonal approach to sum up an infinite series of diagrammatic contributions from thermal fluctuations. Earlier studies found that in the SDW state the spectral function A k (ω) of a hot fermion at a finite T is exponentially small below the energy scale Δ(T), which scales with SDW order and vanishes at the ordering temperature T N , and has a hump at a larger frequency Δ PG , comparable to the zero-temperature SDW gap Δ(T = 0). We argue that the hump, which we associate with the pseudogap, survives in some T range above T N . We show that this range is split by regions of strong and weak pseudogap behavior. In the first region, Δ PG is weakly temperature dependent, despite the fact that it comes from thermal fluctuations. Such a behavior has been seen in numerical studies of the Hubbard model. We show that to obtain it one needs to go beyond the one-loop approximation and sum up the infinite series of diagrams. In the second regime, Δ PG decreases with increasing T and eventually vanishes. Here, we further argue that a magnetic pseudogap at a finite T emerges only if the ground state is magnetically ordered. We present the phase diagram and apply the results to high-T c cuprates.
𝛽−decay of neutron-rich 45 Cl located at the magic number 𝑁 = 28
Results from the β-decay study of 45 Cl, produced in the fragmentation of a 140-MeV/u 48 Ca beam, are presented. The half-life of 45 Cl is measured to be 513(36) ms. β – and β – 1n decay populate excited states in 45 Ar and 44 Ar, respectively, and decay schemes for both daughter nuclei are established based on γ-ray singles and γ-γ coincidence data. Comparison with shell-model calculations using the FSU interaction shows that the low-lying negative-parity states in 45 Ar are well described by single-neutron configurations near the Fermi surface, whereas positive-parity states require neutron excitations across the N = 20 shell gap, consistent with allowed Gamow–Teller decay from 45 Cl. The strong β-feeding to the 5/2 + state in 45 Ar supports a 3/2 + ground-state assignment for 45 Cl over 1/2 + . Furthermore, the high Q β – value enables population of 1p1h states above the neutron separation energy in 45 Ar, leading to positive-parity states in 44 Ar through neutron emission. Tentative spin-parity assignments for excited levels in 44 Ar are made for the first time based on comparison with shell-model predictions, and the 2978-keV level is identified as an excited 0 + state with a configuration distinct from the ground state.
Universal location of Yang-Lee edge singularity in classic O ( N ) universality classes
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Convenient Location of a Near-Threshold Proton-Emitting Resonance in B 11
The presence of cluster-like narrow resonances in the vicinity of reaction/decay thresholds is a ubiquitous phenomenon with profound consequences. Here, we argue that the continuum coupling, present in the open quantum system description of the atomic nucleus, can profoundly impact the nature of near-threshold states. In this Letter, we discuss the structure of the recently observed near-threshold resonance in 11 B, whose very existence explains the puzzling beta-delayed proton emission of the neutron-rich 11 Be.
Switch Location Identification for Integrating a Distant Photovoltaic Array Into a Microgrid
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Real-Time Power Management for Microgrids With Dynamic Boundaries and Multiple Source Locations
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Local, Single-Ended, Traveling-Wave Fault Location on Distribution Systems Using Frequency and Time-Domain Data
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Identification of Voltage Stability Critical Locations for Future Large Grids With High Renewable Mix
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Impact of IBR Location and Parameters on Inter-Area Oscillation Modes in Bulk Power Grids
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An Algorithm for Fast Fault Location and Classification Based on Mathematical Morphology and Machine Learning.
Abstract not provided.
A Machine Learning-based Method using the Dynamic Mode Decomposition for Fault Location and Classification.
Abstract not provided.
Automatic Plant Counting and Location Based on a Few-Shot Learning Technique
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A Numerical Method for Fault Location in DC Systems Using Traveling Waves.
Abstract not provided.