arXiv subjects

S. G. Lee

Publications and source records attributed to S. G. Lee.

4 recordsLinked to original sources

arXiv2026

Laser-driven Ion and Neutron Sources from Medium Repetition Ultrashort PW Laser

We report the first experiment investigating ion acceleration and neutron generation irradiating thin plastic targets (CH2) and deuterated plastic targets (CD2) of thickness ranging from 30nm to 160nm using the 4PW (0.1 Hz) laser at CoReLS in South Korea. Thin wedge-shaped filters exploiting differing stopping ranges were designed to distinguish carbon 6+ ions from deuterons in shots with CD2 targets. The maximum energies of all ion species from both CH2 and CD2 targets were found to increase linearly with the laser intensity. The highest observed energy of each ion species scales as q (charge)^2/mass, which is more similar to the scaling expected for ponderomotive acceleration than to the scaling expected for TNSA. The maximum ion energies were also found to increase with target thickness. Utilizing the secondary interactions of the deuteron beam, we created a fast neutron source via deuteron breakup reactions on a copper converter. The neutron spectrum follows an exponential distribution with energy up to 15MeV. A neutron yield of 2x10^7n/J was observed from thicker targets, comparable to TNSA-regime laser-driven neutron sources and within one order of magnitude of the highest yields reported using Break-out-afterburner (BOA) acceleration with beryllium converters.

physics.plasm-ph↗

arXiv2019

Deep neural network Grad-Shafranov solver constrained with measured magnetic signals

A neural network solving Grad-Shafranov equation constrained with measured magnetic signals to reconstruct magnetic equilibria in real time is developed. Database created to optimize the neural network's free parameters contain off-line EFIT results as the output of the network from $1,118$ KSTAR experimental discharges of two different campaigns. Input data to the network constitute magnetic signals measured by a Rogowski coil (plasma current), magnetic pick-up coils (normal and tangential components of magnetic fields) and flux loops (poloidal magnetic fluxes). The developed neural networks fully reconstruct not only the poloidal flux function $ψ\left( R, Z\right)$ but also the toroidal current density function $j_ϕ\left( R, Z\right)$ with the off-line EFIT quality. To preserve robustness of the networks against a few missing input data, an imputation scheme is utilized to eliminate the required additional training sets with large number of possible combinations of the missing inputs.

physics.plasm-ph↗

arXiv2018

Bayesian with Gaussian process based missing input imputation scheme for reconstructing magnetic equilibria in real time

A Bayesian with GP(Gaussian Process)-based numerical method to impute a few missing magnetic signals caused by impaired magnetic probes during tokamak operations is developed such that the real-time reconstruction of magnetic equilibria, whose performance strongly depends on the measured magnetic signals and their intactness, are affected minimally. Likelihood of the Bayesian model constructed with the Maxwell's equations, specifically Gauss's law of magnetism and Ampère's law, results in infinite number of solutions if two or more magnetic signals are missing. This undesirable characteristic of the Bayesian model is remediated by coupling the model with the Gaussian process. Our proposed numerical method infers the missing magnetic signals correctly in less than $1$\:msec suitable for real-time reconstruction of magnetic equilibria during tokamak operations. The method can also be used for a neural network that reconstructs magnetic equilibria trained with a complete set of magnetic signals. Without our proposed imputation method, such a neural network would become useless if missing signals are not tolerable by the network.

physics.plasm-ph↗

arXiv2016

Role of explosive instabilities in high-$β$ disruptions in tokamaks

Intrinsically explosive growth of a ballooning finger is demonstrated in nonlinear magnetohydrodynamic calculations of high-$β$ disruptions in tokamaks. The explosive finger is formed by an ideally unstable n=1 mode, dominated by an m/n=2/1 component. The quadrupole geometry of the 2/1 perturbed pressure field provides a generic mechanism for the formation of the initial ballooning finger and its subsequent transition from exponential to explosive growth, without relying on secondary processes. The explosive ejection of the hot plasma from the core and stochastization of the magnetic field occur in Alfvénic time scales, accounting for the extremely fast growth of the precursor oscillations and the rapidity of the thermal quench in some high-$β$ disruptions.

physics.plasm-ph↗