The production process of ultra-pure water (UPW) involves dozens of unit processes such as reverse osmosis (RO), pretreatments, membrane degasifier, and several ion exchange processes. Recently, continuous electrodeionization (CEDI) has replaced the 2-bed and 3-tower (2B3T) ion exchange process. As a result, the majority of wastewater in UPW production now comes from the RO concentrate. The important of RO in UPW production is to produce high-quality water with a low ion concentration (around 1 mg/L) for CEDI feed water. Minimizing RO concentrate is essential to reduce the wastewater produced in the UPW production process. This can be achieved by maximizing the recovery of the RO system. However, increasing the recovery is limited by the water quality of the RO permeate. To ensure high-quality permeate water, the RO system is designed with a two-pass configuration. The recovery of each pass in the RO system is limited (e.g., < 85%) due to the expected increase in permeate water concentration at higher RO feed water concentrations. Interestingly, tests using 4-inch RO modules with low concentration feed water (≤ 35 mg/L as NaCl) revealed that the permeate concentration remains almost constant regardless of the feed water concentration. This implies that the recovery of the first RO pass can be increased as long as the average feed/concentrate concentration of the second RO pass is less than 35 mg/L. According to this design criterion for the RO system, the recovery of the first and second RO pass, with a feed water concentration of 250 mg/L as NaCl, can be increased up to 94.8% and 96.0%, respectively. Compared to the conventional RO system design (e.g., 70% and 80% for the first and second RO pass) for UPW production, this maximum recovery design reduces the volume of RO feed and concentrate by up to 38.4% and 89.2%, respectively.

Construction industry is considered as one of the most high-risk industries for work-related injuries and fatalities, accounting for more than half of fatalities in Korea. Advanced countries have recognized the critical role of designers in preventing construction accidents and have established regulations on design for safety. In line with this, the Korean government have also implemented regulations that require owners and designers to review the safety of design outcomes. However, it has been observed that designers face challenges in identifying hazards and integrating design solutions at the design stage mainly due to their shortage of required knowledge and skills. This study aimed to examine design solutions that can be applied to prevent fall accidents in the construction industry, and to establish a relationship between these solutions and fatal fall accidents occurred over the past three years in Korea. This study also analyzed the relationships of four variables (construction type, cost, work type, and fall location) with design solutions. The results indicated that all four variables have significant relationships with design solutions, with fall location showing the strongest relationship. The design solutions and their relationships with fatal fall accidents identified in this study can be utilized in identifying hazard and integrating design solutions to ensure design for safety.

본 연구는 고속도로용 RC 교각 기둥구조에 대하여 축방향 기존 철근을 중공철근으로 대체하는 설계방안을 제시하였 다. 동일직경 기준으로 기존 이형철근을 중공철근으로 대체할 수 있는 합리적인 설계방안을 제시하였으며, 기존 축방향 배근량 을 감소하는 방안을 제안하였다. 본 연구에서 제안한 설계방안을 검증하기 위하여 3차원 유한요소 구조해석을 수행하였으며, 압 축하중에 의한 변수 수치해석을 통하여 본 연구에서 제안한 방안의 타당성을 제시하였다. 향후 다양한 변수 수치해석 및 실물 시험을 통하여 본 연구에서 제시한 설계방안에 대한 추가 검증이 필요하다.

Reinforcement learning (RL) is widely applied to various engineering fields. Especially, RL has shown successful performance for control problems, such as vehicles, robotics, and active structural control system. However, little research on application of RL to optimal structural design has conducted to date. In this study, the possibility of application of RL to structural design of reinforced concrete (RC) beam was investigated. The example of RC beam structural design problem introduced in previous study was used for comparative study. Deep q-network (DQN) is a famous RL algorithm presenting good performance in the discrete action space and thus it was used in this study. The action of DQN agent is required to represent design variables of RC beam. However, the number of design variables of RC beam is too many to represent by the action of conventional DQN. To solve this problem, multi-agent DQN was used in this study. For more effective reinforcement learning process, DDQN (Double Q-Learning) that is an advanced version of a conventional DQN was employed. The multi-agent of DDQN was trained for optimal structural design of RC beam to satisfy American Concrete Institute (318) without any hand-labeled dataset. Five agents of DDQN provides actions for beam with, beam depth, main rebar size, number of main rebar, and shear stirrup size, respectively. Five agents of DDQN were trained for 10,000 episodes and the performance of the multi-agent of DDQN was evaluated with 100 test design cases. This study shows that the multi-agent DDQN algorithm can provide successfully structural design results of RC beam.

Thin-film shape technology is recognized for its core technology to enhance the technology of LCD, PDP, semiconductor manufacturing processes, hard disks and optical disks, and is widely used to form coated thin films of products. In addition, resistance (electron beam filament) technology for heating is used to manufacture filament for ion implants used in semiconductor manufacturing processes. By establishing an electronic beam filament production system and developing seven specifications of electronic beam filament, it is contributing to improving trade dynamics and increasing exports to Japan through localized media of theoretical imports to domestic companies. In this study, CAE analysis was performed after setting electron beam filament specification and development objectives, facilities and fabrication for electron beam filament production, electron beam filament JIG & fixture design and fabrication followed by electron beam filament prototype. Then, the automation and complete inspection equipment of the previously developed electronic beam filament manufacturing facilities was developed and researched to mass-produce them, to analyze and modify prototypes, design and manufacture automation facilities, and finally, to design and manufacture the complete inspection equipment. In this paper, design and manufacture of electronic beam filament total inspection equipment for mass production were dealted with.

대다수의 부유식 해양플랜트는 위치 유지의 방법으로서 체인 계류 시스템을 사용하나, 그 설계 변경 과정은 논문으로 찾아보 기 힘들다. 본 연구는 FLBT를 대상 해양플랜트로 선정하여 계류 초기설계안과 모형시험을 수치해석으로 분석하고, 변경된 설계조건에 따 라 새로운 계류 설계안을 제시하였다. 주된 환경 방향에 따라 계류선 묶음(bundle)의 주 방향을 조절하는 것이 계류 설계하중 감소에 크게 유효했다. 터렛 계류된 해양플랜트라도 횡파에 노출되며, 횡파 중 운동 때문에 높은 계류 인장력이 발생했다. 일치된 환경 방향 조건은 설 계조건이 될 수 없으며, 바람, 파도, 조류의 각 환경 방향이 복잡한 조건에서 설계 계류 하중이 발생했다. 횡요 운동이 계류 인장력에 미치 는 영향이 큼으로 적절한 횡요 감쇠 계수를 계류해석에 적용하는 것이 중요하다.

Path planning is necessary for mobile robots to perform precise and rapid tasks. A collision avoidance function must be included so that the robot can move safely during work, and it must be able to create an optimal path to reduce work execution time and save energy. In this paper, we propose a smart route generation algorithm that searches for global route with an algorithm that can speed up route search and integrates the TEB algorithm that can search for regional optimum routes in real time according to the situation. The performance of the proposed algorithm was verified through actual driving experiments of mobile robots.