Twenty barrel in situ pipe gun type solid hydrogen pellet injector for the Large Helical Device.
A 20 barrel solid hydrogen pellet injector, which is able to inject 20 cylindrical pellets with a diameter and length of between 3.0 and 3.8 mm at the velocity of 1200 m/s, has been developed for the purpose of direct core fueling in LHD (Large Helical Device). The in situ pipe gun concept with the use of compact cryo-coolers enables stable operation as a fundamental facility in plasma experiments. The combination of the two types of pellet injection timing control modes, i.e., pre-programing mode and real-time control mode, allows the build-up and sustainment of high density plasma around the density limit. The pellet injector has demonstrated stable operation characteristics during the past three years of LHD experiments.
Development of Advanced Pellet Injector Systems for Plasma Fueling
Two types of solid hydrogen pellet injection systems have been developed, and plasma refueling experiments have been performed using these pellet injectors. One is an in-situ pipe-gun type pellet injector, which has the simplest design of all pellet injectors. This in-situ pipe-gun injector has 10 injection barrels, each of which can independently inject cylindrical solid hydrogen pellets (3.4 and 3.8 mm in diameter and length, respectively) at velocities up to 1,200 m/s. The other is a repetitive pellet injector with a screw extruder, which can form a 3.0 mmφ solid hydrogen rod continuously at extrusion rates up to 55 mm/s. This extruder allows consecutive pellet injection up to 11 Hz without time limit. Both of these pellet injectors employ compact cryo-coolers to solidify hydrogen; therefore, they can be operated using only electrical input instead of a complicated liquid helium supply system. In particular, using a combination of the repetitive pellet injector with cryo-coolers provides a steady-state capability with minimum maintenance.
Distribution-free monitoring of univariate processes
We consider statistical process control (SPC) of univariate processes when observed data are not normally distributed. Most existing SPC procedures are based on the normality assumption. In the literature, it has been demonstrated that their performance is unreliable in cases when they are used for monitoring non-normal processes. To overcome this limitation, we propose two SPC control charts for applications when the process data are not normal, and compare them with the traditional CUSUM chart and two recent distribution-free control charts. Some empirical guidelines are provided for practitioners to choose a proper control chart for a specific application with non-normal data.