Various linear system solvers with multi-physics analysis schemes are compared focusing on the near-field region considering thermal-hydraulic-chemical (THC) coupled multi-physics phenomena. APro, developed at KAERI for total system performance assessment (TSPA), performs a finite element analysis with COMSOL, for which the various combinations of linear system solvers and multi-physics analysis schemes should to be compared. The KBS-3 type disposal system proposed by Sweden is set as the target system and the near-field region, which accounts for most of the computational burden is considered. For comparison of numerical analysis methods, the computing time and memory requirement are the main concerns and thus the simulation time is set up to one year. With a single deposition hole problem, PARDISO and GMRESSSOR are selected as representative direct and iterative solvers respectively. The performance of representative linear system solvers is then examined through a problem with an increasing number of deposition holes and the GMRES-SSOR solver with a segregated scheme shows the best performance with respect to the computing time and memory requirement. The results of the comparative analysis are expected to provide a good guideline to choose better numerical analysis methods for TSPA.

This study examined the subacute oral toxicity of Dendropanax morbiferus H.Lév leaves hot-water extracts (DMWE) using male and female Spargue-Dawley rats. Rats were orally administered the DMWE at dose levels of 0, 250, 500, 1,000, and 2,000 mg/kg body weight (BW) for four weeks. For experimental period, clinical signs and the number of deaths were examined, and feed intake and BW of all experimental animals were measured once a week for four weeks. At the end of the experiment, blood samples were collected from all rats, and all animals were euthanized and autopsies were performed to collect major organs. No dead animals were found during the experimental period. In addition, no differences were found between control and DMWE-treated groups in feed intakes, BW changes, organ weights, clinical signs, hematological parameters, and serum biochemical parameters. The results of this study provided evidence that oral administration of DMWE at the dose of 2,000 mg/kg BW is safe in rats and may not exert severe toxic effects.

In this study, the acute toxicity of Dendropanax morbiferus H.Lév leaf hot-water extracts (DMWE) was examined in male and female ICR mice. Mice were orally administered the DMWE at dose levels of 0, 250, 500, 1,000 and 2,000 mg/kg body weight (BW) for single-dose toxicity test. There were no significant differences in change of BW between control and all DMWE treated-groups. In hematological and blood biochemical analysis, none of the parameters were affected by the DMWE. Similarly, there were no significant effects on markers for liver and kidney functions in all DMWE treated-groups. Since there were no adverse effects of the DMWE in single oral toxicity tests, even at the highest doses, it was concluded that the lethal dose 50 (LD50) of DMWE is estimated at > 2,000 mg/kg BW.

Recently, many studies have been conducted to improve quality by applying machine learning models to semiconductor manufacturing process data. However, in the semiconductor manufacturing process, the ratio of good products is much higher than that of defective products, so the problem of data imbalance is serious in terms of machine learning. In addition, since the number of features of data used in machine learning is very large, it is very important to perform machine learning by extracting only important features from among them to increase accuracy and utilization. This study proposes an anomaly detection methodology that can learn excellently despite data imbalance and high-dimensional characteristics of semiconductor process data. The anomaly detection methodology applies the LIME algorithm after applying the SMOTE method and the RFECV method. The proposed methodology analyzes the classification result of the anomaly classification model, detects the cause of the anomaly, and derives a semiconductor process requiring action. The proposed methodology confirmed applicability and feasibility through application of cases.