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In this study, a numerical analysis was performed as part of an international joint research project to reproduce a real cable tray fire that occurred in the heater bay area of the turbine building of a nuclear power plant. A sensitivity analysis was performed on various input parameters to derive results consistent with the sprinkler activation time obtained from the fire event analysis. For all sensitive parameters, the normalized sprinkler activation time correlated well with the power function of the normalized sprinkler height. A correlation equation was developed to identify the sprinkler activation time at any location when determining the slope or fire growth rate under the conditions assuming a linear or t-squared heat release rate (HRR) time curve. Various cable fire growth assumptions were used to determine which assumption was better to provide the prediction coincident with the information given from the fire event analysis in terms of the sprinkler activation time and total energy generated from cables damaged by fire. In the comprehensive analysis of all the sensitive parameters, the standard deviation of the input parameters increased as the sprinkler height decreased. Within the range of the sensitivity parameter values given in this study, when considering all sprinkler heights, the standard deviation of the cable model change was the largest and that of the overhang position change was the smallest.

This paper introduces a reinforcement learning method that leverages task decomposition and a task-specific reward system to address complex high-level tasks, such as door opening, block stacking, and nut assembly. These tasks are decomposed into various subtasks, with the grasping and putting tasks executed through single joint and gripper actions, while other tasks are trained using the SAC algorithm alongside the task-specific reward system. The task-specific reward system aims to increase the learning speed, enhance the success rate, and enable more efficient task execution. The experimental results demonstrate the efficacy of the proposed method, achieving success rates of 99.9% for door opening, 95.25% for block stacking, 80.8% for square-nut assembly, and 90.9% for round-nut assembly. Overall, this method presents a promising solution to address the challenges associated with complex tasks, offering improvements over the traditional end-to-end approach.

In this study, operator habitability was numerically evaluated in the event of a fire at the main control bench board (MCB) in a reference main control room (MCR). It was investigated if evacuation variables including hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD) at 1.8 m from the MCR floor exceed the reference evacuation criteria provided in NUREG/CR-6850. For a fire model validation, the simulation results of the reference MCR were compared with existing experimental results on the same reference MCR. In the simulation, various input parameters were applied to the MCB panel fire scenario: MCR height, peak heat release rate (HRR) of a panel, number of panels where fire propagation occurs, fire propagation time, door open/close conditions, and mechanical ventilation operation. A specialized-average HRR (SAHRR) concept was newly devised to comprehensively investigate how the various input parameters affect the operator’s habitability. Peak values of the evacuation variables normalized by evacuation criteria of NUREG/CR-6850 were well-correlated as the power function of the SAHRR for the various input parameters. In addition, the evacuation time map was newly utilized to investigate how the evacuation time for different SAHRR was affected by changing the various input parameters. In the previous studies, it was found that the OD is the most dominant variable to determine the MCR evacuation time. In this study, however, the evacuation time map showed that the HF is the most dominant factor at the condition of without-mechanical ventilation for the MCR with a partially-open false ceiling, but the OD is the most dominant factor for all the other conditions. Therefore, the method using the SAHRR and the evacuation time map was very useful to effectively and comprehensively evaluate the operator habitability for the various input parameters in the event of MCB fires for the reference MCR.

Globalization has increased international trade and caused an annual increase in the number of non-native insect pest species found in quarantine sites in Korea. Since over 80% of Korean farms use greenhouses with internal conditions conducive to growing crops and hospitable to exotic pests, efficient pest control is crucial. This study evaluated the efficacy of ethyl formate (EF) against three major exotic insect pests (Aphis gossypii, Frankliniella occidentalis, and Tetranychus urticae) and beneficial organisms (earthworms, honeybees, and silkworms) via EF fumigation experiments at two concentrations. The lethal concentration–time (LCt)99 values of A. gossypii, F. occidentalis, and T. urticae were 8.96, 14.00, and 19.07 g h/m3, respectively. Four hours of fumigation of EF at 15 g/m3 left no residue on the crops or soil after a maximum of 3 h. The beneficial organisms exhibited higher tolerance levels than A. gossypii with regard to LCt99 value, but the higher EF treatment dosage needed to control F. occidentalis and T. urticae could be highly lethal to honeybees. The lower EF dose (4 g/m3) effectively controlled A. gossypii, but 15 g/m3 was needed for F. occidentalis and T. urticae. Phytotoxicity varied in severity with EF concentration. These insights can help in developing a refined disinfestation strategy for greenhouses.

In this study, demagnetization heat treatment at 100 ∼400 °C is studied by using computer simulation to secure the optimal demagnetization heat treatment conditions for waste neodymium iron boron (NdFeB) permanent magnets. From the computer simulation, the temperature of the magnet during heat treatment is higher than the set temperature by up to 6 °C. Delay time occurs when the furnace internal temperature and magnet temperature reached the set temperature. A delay time of 15 minutes in an air atmosphere and 10 minutes in a nitrogen atmosphere occurs. The Nd magnet was completely demagnetized at 300 °C as the magnetic flux decreased when the heat treatment temperature increased up to 250 °C. The fully demagnetized magnet could be magnetized to the level of a new magnet. It was confirmed that NdFeB magnets heat treated up to 350 °C in a nitrogen atmosphere can be reusable due to stable demagnetization being possible without surface change.

In the worst case, a temporary ignition source (also known as transient combustibles) between two electrical panels can damage both panels. Mitigation strategies for electrical panel fires were previously developed using fire modeling and risk analysis. However, since they do not comply with deterministic fire protection requirements, it is necessary to analyze the boundary values at which combustibles may damage targets depending on various factors. In the present study, a sensitivity analysis of input variables related to the damage threshold of two electrical panels was performed for dimensionless geometry using a Fire Dynamics Simulator (FDS). A new methodology using a damage evaluation map was developed to assess the damage of the electrical panel. The input variables were the distance between the electrical panels, the vertical height of the fuel, the size of the fire, the wind speed and the wind direction. The heat flux was determined to increase as the vertical distance between the fuel and the panel decreased, and the largest heat flux was predicted when the vertical separation distance divided by one half flame length was 0.3–0.5. As the distance between the panels increases, the heat flux decreases according to the power law, and damage can be avoided when the distance between the fuel and the panel is twice the length of the panel. When the wind direction is east and south, to avoid damage to the electrical panel the distance must be increased by 1.5 times compared to no wind. The present scale model can be applied to any configuration where combustibles are located between two electrical panels, and can provide useful guidance for the design of redundant electrical panels.

This paper proposes a task decomposition and dedicated reward-system-based reinforcement learning algorithm for the Pick-and-Place task, which is one of the high-level tasks of robot manipulators. The proposed method decomposes the Pick-and-Place task into three subtasks: two reaching tasks and one grasping task. One of the two reaching tasks is approaching the object, and the other is reaching the place position. These two reaching tasks are carried out using each optimal policy of the agents which are trained using Soft Actor-Critic (SAC). Different from the two reaching tasks, the grasping is implemented via simple logic which is easily designable but may result in improper gripping. To assist the grasping task properly, a dedicated reward system for approaching the object is designed through using individual axis-based weights. To verify the validity of the proposed method, wecarry out various experiments in the MuJoCo physics engine with the Robosuite framework. According to the simulation results of four trials, the robot manipulator picked up and released the object in the goal position with an average success rate of 93.2%.