The RENO experiment reports more precisely measured values of θ_{13} and |Δm_{ee}^{2}| using ∼2200 live days of data. The amplitude and frequency of reactor electron antineutrino (νover ¯_{e}) ...oscillation are measured by comparing the prompt signal spectra obtained from two identical near and far detectors. In the period between August 2011 and February 2018, the far (near) detector observed 103 212 (850 666) νover ¯_{e} candidate events with a background fraction of 4.8% (2.0%). A clear energy and baseline dependent disappearance of reactor νover ¯_{e} is observed in the deficit of the measured number of νover ¯_{e}. Based on the measured far-to-near ratio of prompt spectra, we obtain sin^{2}2θ_{13}=0.0896±0.0048(stat)±0.0047(syst) and |Δm_{ee}^{2}|=2.68±0.12(stat)±0.07(syst)×10^{-3} eV^{2}.
Nuclear fusion is one of the most attractive alternatives to carbon-dependent energy sources1. Harnessing energy from nuclear fusion in a large reactor scale, however, still presents many scientific ...challenges despite the many years of research and steady advances in magnetic confinement approaches. State-of-the-art magnetic fusion devices cannot yet achieve a sustainable fusion performance, which requires a high temperature above 100 million kelvin and sufficient control of instabilities to ensure steady-state operation on the order oftens of seconds2,3. Here we report experiments at the Korea Superconducting Tokamak Advanced Research4 device producing a plasma fusion regime that satisfies most ofthe above requirements: thanks to abundant fast ions stabilizing the core plasma turbulence, we generate plasmas at a temperature of 100 million kelvin lasting up to 20 seconds without plasma edge instabilities or impurity accumulation. A low plasma density combined with a moderate input power for operation is key to establishing this regime by preserving a high fraction of fast ions. This regime is rarely subject to disruption and can be sustained reliably even without a sophisticated control, and thus represents a promising path towards commercial fusion reactors.
We report a fuel-dependent reactor electron antineutrino (νover ¯_{e}) yield using six 2.8 GW_{th} reactors in the Hanbit nuclear power plant complex, Yonggwang, Korea. The analysis uses 850 666 ...νover ¯_{e} candidate events with a background fraction of 2.0% acquired through inverse beta decay (IBD) interactions in the near detector for 1807.9 live days from August 2011 to February 2018. Based on multiple fuel cycles, we observe a fuel ^{235}U dependent variation of measured IBD yields with a slope of (1.51±0.23)×10^{-43} cm^{2}/fission and measure a total average IBD yield of (5.84±0.13)×10^{-43} cm^{2}/fission. The hypothesis of no fuel-dependent IBD yield is ruled out at 6.6σ. The observed IBD yield variation over ^{235}U isotope fraction does not show significant deviation from the Huber-Mueller (HM) prediction at 1.3 σ. The measured fuel-dependent variation determines IBD yields of (6.15±0.19)×10^{-43} and (4.18±0.26)×10^{-43} cm^{2}/fission for two dominant fuel isotopes ^{235}U and ^{239}Pu, respectively. The measured IBD yield per ^{235}U fission shows the largest deficit relative to the HM prediction. Reevaluation of the ^{235}U IBD yield per fission may mostly solve the reactor antineutrino anomaly (RAA) while ^{239}Pu is not completely ruled out as a possible contributor to the anomaly. We also report a 2.9 σ correlation between the fractional change of the 5 MeV excess and the reactor fuel isotope fraction of ^{235}U.
Abstract
The force-balanced state of magnetically confined plasmas heated up to 100 million degrees Celsius must be sustained long enough to achieve a burning-plasma state, such as in the case of ...ITER, a fusion reactor that promises a net energy gain. This force balance between the Lorentz force and the pressure gradient force, known as a plasma equilibrium, can be theoretically portrayed together with Maxwell’s equations as plasmas are collections of charged particles. Nevertheless, identifying the plasma equilibrium in real time is challenging owing to its free-boundary and ill-posed conditions, which conventionally involves iterative numerical approach with a certain degree of subjective human decisions such as including or excluding certain magnetic measurements to achieve numerical convergence on the solution as well as to avoid unphysical solutions. Here, we introduce GS-DeepNet, which learns plasma equilibria through solely unsupervised learning, without using traditional numerical algorithms. GS-DeepNet includes two neural networks and teaches itself. One neural network generates a possible candidate of an equilibrium following Maxwell’s equations and is taught by the other network satisfying the force balance under the equilibrium. Measurements constrain both networks. Our GS-DeepNet achieves reliable equilibria with uncertainties in contrast with existing methods, leading to possible better control of fusion-grade plasmas.
A
bstract
The Reactor Experiment for Neutrino Oscillation (RENO) experiment has been taking data using two identical liquid scintillator detectors since August 2011. The experiment has observed the ...disappearance of reactor neutrinos in their interactions with free protons, followed by neutron capture on hydrogen (n-H). Based on 1500 live days of data taken with 16.8 GW
th
reactors at the Hanbit Nuclear Power Plant in Korea, the near (far) detector observes 567690 (90747) electron antineutrino candidate events with the n-H data. This provides an independent measurement of neutrino mixing angle
θ
13
and a consistency check on the validity of the result obtained from the data with neutron capture on Gadolinium (n-Gd). Furthermore, it provides an important cross-check on the systematic uncertainties of the n-Gd measurement. Based on a rate-only analysis, we obtain sin
2
2
θ
13
= 0
.
086 ± 0
.
008(stat
.
) ± 0
.
014(syst
.
). The combination of this result with that of n-Gd is also reported.
Experimental observations assisted by 2-D imaging diagnostics on the KSTAR tokamak show that a solitary perturbation (SP) emerges prior to a boundary burst of magnetized toroidal plasmas, which puts ...forward SP as a potential candidate for the burst trigger. We have constructed a machine learning (ML) model based on a convolutional deep neural network architecture for a statistical study to identify the SP as a boundary burst trigger. The ML model takes sequential signals detected from 19 toroidal Mirnov coils as input and predicts whether each temporal frame corresponds to an SP. We trained the network in a supervised manner on a training set consisting of real signals with manually annotated SP locations and synthetic burst signals. The trained model achieves high performances in various metrics on a test data set. We also demonstrated the reliability of the model by visualizing the discriminative parts of the input signals that the model recognizes. Finally, we applied the trained model to new data from KSTAR experiments, which were never seen during training, and confirmed that the large burst at the plasma boundary that can fatally damage the fusion device always involves the emergence of SP. This result suggests that the SP is a key to understanding and controlling of the boundary burst in magnetized toroidal plasmas.
Abstract
Understanding the formation of start-up runaway electrons (REs) is essential to ensure successful plasma initiation in ITER. The design of ITER start-up scenarios requires not only ...predictive simulations but also a validation of assumptions. The objective of this study is to strengthen the physical background required for predictive simulations aimed at ITER plasma start-up design, by validating the model assumptions. Through kinetic simulations, this study examines the validity of steady-state models for Dreicer generation under slowly-varying time scales relevant to plasma start-up and investigates the finite energy effect, commonly neglected, on the runaway avalanche growth rate. The research findings provide insights into situations where kinetic simulations are necessary. To secure a margin-of-control scheme without kinetic simulation, we suggest a strategy of scanning the Coulomb logarithm in fluid simulations as an alternative to predict runaway current takeover and avoid RE dominant scenarios. Ultimately, this paper seeks to offer a robust physical background, practically supporting the successful design of ITER start-up scenarios.
•This manuscript is the proceeding paper from the 22nd PSI conference in Rome 2016, invited contribution I2.•Probe measurements on KSTAR augments the tokamak SOL profile database, revealing ...significant profile broadening of the far-SOL with increasing line-averaged density in L-mode plasmas.•The statistical properties of plasma fluctuations are revealed by analysis of a ion saturation current data time series of several second duration under stationary plasma conditions.•Analysis of level crossing rates and excess time statistics, ultimately determining the degree of plasma-surface interactions in reactors, is presented for the first time for a magnetically confined plasma.•All fluctuation statistics are demonstrated to be in excellent agreement with a novel stochastic model for intermittent fluctuations in the tokamak scrape-off layer.
Radial profiles of the ion saturation current and its fluctuation statistics are presented from probe measurements in L-mode, neutral beam heated plasmas at the outboard mid-plane region of KSTAR. The results are consistent with the familiar two-layer structure, seen elsewhere in tokamak L-mode discharges, with a steep near-SOL profile and a broad far-SOL profile. The profile scale length in the far-SOL increases drastically with line-averaged density, thereby enhancing plasma interactions with the main chamber walls. Time series from the far-SOL region are characterised by large-amplitude bursts attributed to the radial motion of blob-like plasma filaments. Analysis of a data time series of several seconds duration under stationary plasma conditions reveals the statistical properties of these fluctuations, including the rate of level crossings and the average duration of periods spent above a given threshold level. This is shown to be in excellent agreement with predictions of a stochastic model, giving novel predictions of plasma–wall interactions due to transient transport events.
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