Journal of Fusion Energy最新文献

This paper discusses the importance and advancements of visualization technology in fusion science research. First, visualization is an essential process for analyzing experimental and simulation data, aiding in the understanding of complex phenomena such as plasma. It emphasizes that, instead of conventional two-dimensional graphs, virtual reality (VR) technology enables researchers to observe data in three dimensions. This approach leads to a more intuitive understanding of complex phenomena. Additionally, VR technology provides an environment where multiple researchers can simultaneously discuss and analyze plasma physics, making it highly useful for research. Furthermore, VR plays a crucial role in effectively communicating research findings to the general public in an accurate and accessible manner. At the National Institute for Fusion Science, a VR visualization system has been established to efficiently analyze large-scale simulation data using CAVE-type VR devices. The latest technology, such as head-mounted displays (HMDs), has also been introduced. The applications of visualization technology are not limited to fusion science but are expected to expand into other fields as well, making it a promising area of ongoing development. This paper presents key visualization research achievements conducted at the National Institute for Fusion Science. We are also developing new capabilities to display both CAD and simulation data on HMDs as we port the VR software originally designed for large CAVE-type systems. These developments will also be described.

Three sets of neutron cameras have been developed in Large Helical Device to measure the spatial profile of energetic particles, since deuterium-deuterium neutrons are mainly produced by the reaction of thermal deuteron and energetic deuteron. One of neutron cameras is based on a stilbene scintillation detector operating in the pulse-counting mode with pulse shape discrimination ability for medium to high neutron emission discharges. The other two neutron cameras are based on an EJ-401 fast neutron scintillator detector operated in the current mode for low to medium neutron emission discharges. Neutron cameras have been a powerful tool for understanding beam ion confinement as well as beam ion transport during the beam ion-driven magnetohydrodynamic instabilities. The development and details of the neutron cameras in the Large Helical Device are described.

Diagnostics are critical for commercial and research fusion machines, since measuring and understanding plasma features is important to sustaining fusion reactions. The neutron flux (and therefore fusion power) can be indirectly calculated using neutron activation analyses, where potentially large numbers of activation foils are placed in the neutron flux, and delayed gammas from key reactions are measured via gamma spectrometry. In gamma spectrometry, absolute efficiency forms part of the activity calculation, and equals to the ratio of the total number of photons detected to the number emitted by a radioactive sample. Hence, it is imperative that they are calculated efficiently and accurately. This paper presents a novel digital efficiency calculation algorithm, the Machine Learning Based Efficiency Calculator (MaLBEC), that uses state-of-the-art supervised machine learning techniques to calculate efficiency values of a given sample, from only four inputs. In this paper, the performance of the MaLBEC is demonstrated with a fusion sample and compares the values to a traditional efficiency calculation method, Monte Carlo N-Particle (MCNP). The efficiencies from the MaLBEC were within an average 5% of the ones produced by MCNP, but with an exceptional reduction in computation time of 99.96%. When the efficiency values from both methods were used in the activity calculation, the MaLBEC was within 3% of the MCNP results.

High-confinement tokamak plasmas typically exhibit characteristics such as a small aspect ratio, large elongation, and significant triangularity configuration, with the core plasma often experiencing sawtooth mode. Experimental and simulation studies have shown that the linear stability of sawtooth mode is related to the aspect ratio, triangularity, and elongation. When numerically investigating the relationship between sawtooth mode and plasma configurations, the broad parameter space and the large number of parameter combinations require substantial computational time. Therefore, this paper builds upon previous numerical simulations of the sawtooth mode instability physical model (CLT) to construct a database containing plasma configurations and their corresponding sawtooth mode growth rates. We trained three machine learning methods—KNN Random Forest and SVR—to rapidly predict the growth rates of sawtooth mode for plasma configurations across a wide parameter domain. Experiments demonstrate that the Random Forest model achieves an R² of 99.45%, while the SVR and KNN models achieve R² values of 90.38% and 97.62%, respectively. The trained models exhibit sufficient generalization capabilities. By comprehensively comparing the predictive performance of the models, the Random Forest model, which aligns best with the simulation data, was selected for prediction. The relative error between the predicted and actual values does not exceed 2%, indicating reliable prediction performance for the growth rate of sawtooth mode.

This work focuses to develop semi-empirical formulae for calculating (n, t) nuclear reaction induced by fast neutron at energy of 14-15 MeV. The emission of triton is a weak nuclear reaction, it is presented by an excitation function of micro barns, and we use pre-compound mechanism based on exciton model to describe it. Three fitting parameters at the formulae are proposed where the even-odd contribution is taken into consideration, 31 nuclei are investigated with mass number A (17 le A le 238). Compared to previous studies, low values of (chi ^{2}) and (Sigma) are obtained, achieving 0.91 and 16.53 respectively, for even A nuclei, 1.57 and 10.98 respectively, for odd A nuclei. These formulae reproach more calculated cross sections from experiment data and predict the unmeasured ones. This work improves that, in addition to the equilibrium model, the pre-equilibrium model is useful in weak nuclear reaction description.

Electron Cyclotron Emission Imaging(ECEI) is a powerful tool for investigating MHD instabilities and turbulence in magnetically confined plasma. In the LHD, the ECEI system has been developed and successfully obtained two-dimensional images of temperature fluctuations. This paper describes the current V-band and Q-band ECEI systems including developments in their key components. The initial results of the observation of geodesic acoustic mode (GAM) are presented.

Helicon waves (HW) are fast magnetosonic waves that can efficiently drive off-axis plasma current in tokamak plasmas through electron Landau damping (ELD) and transit-time magnetic pumping (TTMP) effect. Simulation of helicon wave current drive (HCD) were conducted for the purpose of increasing the discharge current of the NCST, combined with theoretical analysis of wave absorption based on the dispersion relation. Key findings are as follows: (1) When the wave frequency f > 40 MHz, ELD becomes the dominant absorption mechanism for HW in NCST, which is confirmed by the significant increase in the Landau damping term with frequency (Fig. 1). (2) At a frequency of approximately 65 MHz, HCD effectively supplements the bootstrap current for the NCST scenario. (3) Under the optimal parameter combination (({n_parallel }= - 3.8), (beta ={10^ circ })), the maximum current drive efficiency reaches 136 kA/MW. These results clarify the parameter range for efficient HCD, validate HCD as a feasible non-inductive current drive solution for compact spherical tokamaks, and thereby provide critical theoretical guidance for the design and construction of NCST’s helicon system.

The enhancement of the D(d, n)³He fusion reaction rate, due to the production of energetic deuterons (referred to as the knock-on tail) via nuclear elastic scattering of energetic beam protons, was observed on the large helical device (LHD). The enhanced reaction rate was measured as an increase in the neutron generation rate by more than one order of magnitude. This observed phenomenon was explained through both the Boltzmann–Fokker–Planck analysis and particle simulations that consider three-dimensional particle motion in beam-heated deuterium plasma. The simulations demonstrated a good agreement with the observed phenomenon, leading to the conclusions that the knock-on tail is formed in the deuteron velocity distribution function.

IFMIF-DONES (International Fusion Materials Irradiation Facility-DEMO Oriented Neutron Source) is a key facility for the study and analysis of the materials properties exposed to irradiation conditions characterised by a high neutron flux with high energies up to 55 MeV. These irradiation conditions are expected by the future DEMOnstration fusion power plant (DEMO). Within IFMIF-DONES, the irradiation modules which host the specimens material are placed. Therefore, real-time monitoring of the neutron flux is essential to detect and correct any deviations, ensuring continuous and uniform irradiation. Among the diagnostics taken into account, the Self-Powered Neutron Detector (SPND) appears to offer strong physical characteristics in such an environment. However, they have so far only been used in fission reactors. In this work, a theoretical study has been carried out to analyse the signals that could be measured with these diagnostics.

To advance the understanding of helium transport physics, helium neutral beam (He-NB) experiments were initiated in the Large Helical Device (LHD) during the FY2021 experimental campaign. To facilitate these investigations, modifications were implemented in both the impurity exhaust system and the neutral beam (NB) injection system, enabling the use of the helium beam in a typical fusion experimental environment. In the positive-ion-source-based NB system—originally designed for hydrogen and deuterium beams—the gas supply lines were adapted to introduce helium and argon into the ion sources, while argon was injected into the neutralizer cells. These modifications allowed for the injection of a high current and high focused 78 keV He-NB into the plasma. To improve helium exhaust efficiency at main vessel, turbo-molecular pumps were installed, increasing the effective pumping speed by approximately 1.4 times. During He-NB operation, a gradual decrease in the arc current of the NB ion source was observed with each discharge. This effect was attributed to the formation of helium bubbles on the tungsten filament surface, and a recovery method using argon gas discharges was successfully demonstrated. Plasma heating by He-NB injection was confirmed, and both energetic helium ions and bulk helium ions were successfully measured. Their spatial distributions were also observed. These results contribute to a deeper understanding of helium behavior in fusion plasma and offer valuable insights for future helium transport studies.