This study investigates the risk reduction effect and identifies the optimal capacity of Multi-barrier Accident Coping Strategy (MACST) facilities for nuclear power plants (NPPs) under seismic hazard. The efficacy of MACST facilities in OPR1000 and APR1400 NPP systems is evaluated by utilizing the Improved Direct Quantification of Fault Tree with Monte Carlo Simulation (I-DQFM) method. The analysis encompasses a parametric study of the seismic capacity of two MACST facilities: the 1.0 MW large-capacity mobile generator and the mobile low-pressure pump. The results demonstrate that the optimal seismic capacity of MACST facilities for both NPP systems is 1.5g, which markedly reduces the probability of core damage. In particular, the core damage risk is reduced by approximately 23% for the OPR1000 system, with the core damage fragility reduced by approximately 72% at 1.0g seismic intensity. For the APR1400 system, the implementation of MACST is observed to reduce the core damage risk by approximately 17% and the core damage fragility by approximately 44% under the same conditions. These results emphasize the significance of integrating MACST facilities to enhance the resilience and safety of NPPs against seismic hazard scenarios, highlighting the necessity for continuous adaptation of safety strategies to address evolving natural threats.

Analyzing and diagnosing the causes of abnormal conditions through control logic processes at the plant site is critically important. When a process is halted, the steps for cause analysis and corrective action vary depending on the operator's experience and the specific characteristics of the process. Since it's often not feasible to keep the process stopped for an extended period, issues are sometimes resolved by forcibly restarting the PLC(Programmable Logic Controller). However, this can lead to the recurrence of the same error, which may negatively impact process operations. In particular, oil sands development is an uncharted area with anticipated environmental challenges. In this regard, an integrated system between control systems in the oil sands production plant was established to implement control logic, develop the HMI(Human-Machine Interface), and verify the user interface. This allowed for a better understanding of the equipment's operability.

This study explores the use of a Deep Autoencoder model to predict depression among plant and machine operators, utilizing data from the Korean National Health and Nutrition Examination Survey (KNHANES, n=3,852). The Deep Autoencoder model outperformed the Logistic Regression, Naive Bayes, XGBoost, and LightGBM models, achieving an accuracy of 86.5%. Key factors influencing depression included work stress, exposure to hazardous substances, and ergonomic conditions. The findings highlight the potential of the Deep Autoencoder model as a robust tool for early identification and intervention in workplace mental health.

This study examines factors influencing occupational injuries among plant and machine operators using the Semi-supervised MarginBoost algorithm. Data from the 2007-2009 Korean National Health and Nutrition Examination Survey (KNHANES) were analyzed, covering 4,062 employed participants. The MarginBoost model achieved 84.3% accuracy, outperforming other models. Key factors identified included exposure to hazardous substances, ergonomic conditions, and psychosocial stress. The findings emphasize the need for targeted interventions to enhance workplace safety and offer a robust predictive tool for the effective management of occupational health.

본 연구는 어린이집 급식설비 손잡이의 식중독 세균 오 염도를 측정하고, 분리 균주의 독소 유전자와 항생제 내 성을 분석하여 급식설비 손잡이에 의한 집단식중독을 예 방을 위한 과학적 기반을 마련하고자 하였다. 실험 대상 은 전라남도 일부 지역 어린이집 101곳의 냉장고, 냉동고, 자외선 살균기 손잡이, 총 303개를 대상으로 하였다. 어린 이집 냉장고, 냉동고 손잡이에서 B. cereus 4 균주(1.3%) 가 검출되었고 어린이집 냉장고 손잡이에서 S. aureus 2 균주(0.7%)가 검출되었다. B. cereus와 S. aureus의 독소유 전자를 분석한 결과 B. cereus 4개 균주 모두에서 nheA, nheB, nheC, entFM, cytK가 검출되었으나, S. aureus의 2 개 균주의 경우 모두 sea, seb, sec, sed, see, seg, seh, sei, sej 독소유전자가 불검출되었다. B. cereus에서 설사를 유 발하는 장독소가 검출되어 B. cereus에 의한 식중독 발생 가능성이 상존하는 것으로 판단되었다. B. cereus와 S. aureus의 항생제 감수성을 실험한 결과 B. cereus 4 균주 에서 AM, FEP 등 β-lactam계 항생제에 내성을 나타내었 고 S. aureus 균주 모두 AM, P 항생제에 내성을 나타내 었다. S. aureus 균주는 OX 항생제에 각각 중간 내성 1 균주와 감수성 1 균주를 나타내었으나 MRSA는 검출되지 않았다. 이러한 결과를 종합하여 볼 때 어린이집 급식설 비 손잡이의 교차오염으로 인한 식중독 발생을 예방하기 위해 급식설비 손잡이에 대한 주기적인 살균 등 위생관리 방안을 강화해야할 것으로 판단되었다.

We examine a single machine scheduling problem with step-improving jobs in which job processing times decrease step-wisely over time according to their starting times. The objective is to minimize total completion time which is defined as the sum of completion times of jobs. The total completion time is frequently considered as an objective because it is highly related to the total time spent by jobs in the system as well as work-in-progress. Many applications of this problem can be observed in the real world such as data gathering networks, system upgrades or technological shock, and production lines operated with part-time workers in each shift. Our goal is to develop a scheduling algorithm that can provide an optimal solution. For this, we present an efficient branch and bound algorithm with an assignment-based node design and tight lower bounds that can prune branch and bound nodes at early stages and accordingly reduce the computation time. In numerical experiments well designed to consider various scenarios, it is shown that the proposed algorithm outperforms the existing method and can solve practical problems within reasonable computation time.

부유식 해상태양광 설비는 패널 지지를 위한 프레임 구조물, 구조체의 부력 제공을 위한 부유체와 전체 시스템의 거동을 제한하는 계류시설로 구성되어 있다. 계류시설은 구조물의 지지조건으로서의 역 할을 통해 안정적인 발전량 수급에 기여한다. 하지만 해당 시스템은 설치된 해상환경 특성상 계류선의 파단 및 손상 시 직접적인 탐지가 불가능해 유지관리에 어려움이 있다. 따라서 본 연구에서는 패널지 지 프레임 구조체에 가속도 센서 부착을 가정하여, 해당 센서 계측값을 토대로 계류설비에서 발생한 파단 및 손상이 발생한 위치를 추정하는 알고리즘을 개발하였다. 알고리즘은 비지도학습 인공지능의 일종인 오토인코더를 활용하여 가속도 계측값의 재현 과정을 통해 정상상태의 구조 응답을 학습한 모 델이 비정상상태의 계측값을 재현 시 발생한 오차를 통해 손상 발생 여부와 위치를 실시간 탐지하도 록 구성하였다. 정상상태 구조응답을 기반으로 한 모델의 학습을 위해 패널지지 구조체를 10x10 격자 형으로 결합한 다중 결합 시스템에 불규칙파랑을 환경하중으로 적용함을 통해 발생한 6자유도 가속도 데이터를 확보하였다. 계류시설의 손상 발생 시 주된 변화 인자 탐지를 위해 상관성 분석과 민감도 분 석을 실시하여 손상 위치 추정 알고리즘에 적용할 주요 인자를 선별하여 학습 및 추정 성능에 대한 비교 분석을 수행하였다. 구축된 알고리즘의 테스트를 위해 총 5개 종 손상 케이스 데이터셋을 구축하 여 손상 위치 추정 성능을 비교하였다. 본 연구를 통해 계류 시설에 발생한 손상 여부 및 위치를 추정 하여 부유식 해상태양광 설비의 선제적 유지관리에 기여할 수 있을 것으로 기대된다.

Considering the difficulties of the manufacturing industry by improving production efficiency in the era of high wages and aging in domestic automation facilities, automation facilities are considered an irreversible trend, but many serious related disasters are occurring due to the problems of increasing automation facilities due to the enlargement of manufacturing processes, line-up, and automation. The purpose of this study is to review the usage conditions and safety measures for industrial robots that are experiencing serious industrial accidents and are expected to continue to increase in facilities among automation facilities at the automation industrial site and propose ways to ensure the fundamental safety of the facilities at all times The suggestions are as follows. The purpose is to prevent safety accidents in advance by applying safety door aids to industrial sites and installing additional safety devices in safety slide door lock systems applied to safety fence doors of new and already installed facilities to detach safety keys and ensure that workers carry them at all times.

PURPOSES : Carbon dioxide (CO2) is a cheaper and easier to installer fire suppressant than other extinguishing gases and is easy to install, but extinguishes fires by is suffocation. As a result, suffocation accidents continue to occur in facilities equipped with CO2 fire-extinguishing facilities, Emission standards have yet to be established. This study aims to address the issue. METHODS : To effectively remove CO2 emitted from installed systems, we reviewed and analyzed previous related research and existing international standards. RESULTS : In protected areas where CO2 fire-extinguishing systems are installed, emission facilities should discharge the emitted CO2 before it enters the protected spaces. CO2 sensors can determine whether safe entry is possible or whether respirators are required. CONCLUSIONS : This study presented a specific installation method for emission facilities capable of actively discharging CO2. Applying this method is expected to contribute to improving safety in facilities equipped with CO2 fire-extinguishing facilities.

PURPOSES : This study aimed to secure the work space in alarm valve rooms to ensure stable working conditions for the engineers. METHODS : We analyzed situations where alarm valve room work spaces were inadequately secured posing a problem. Using the Ovako working posture analysis system (OWAS) method, we measured the body size of adult male technicians and their tools to analyze the actual space needed for them to maintain a healthy posture while working. On this basis, we proposed regulations governing workspace size and acceptable durations for unstable body postures. RESULTS : By measuring valve room work space and technician body size, we found that the workspace was inadequate for technicians. Applying OWAS showed that securing more space in the valve room improved the construction stability. CONCLUSIONS : Regulations on valve room size and appropriate work space for technicians will improve construction and inspection stability. This reduces the probability of poor construction and inadequate inspection, increasing the reliability of the firefighting facility system.

By developing molds and facilities to horizontally mold the functional part of the dry-cast concrete block, We intend to develop molds and a series of facilities to horizontally mold the functional part of the dry-cast concrete block to increase production per cycle while maintaining existing production methods and major facilities. In order to do so, CAE analysis is first required to develop molds and facilities for horizontally molding the functional part of the drycast concrete block in the horizontal direction. The procedure will be carried out by reviewing the validity of boundary conditions and physical properties, 3D modeling, grid generation, construction of analysis models, model validity, analysis according to frequency changes, and analysis according to physical properties. First, through the comparison of two-point support, three-point support, and two-point and three-point support in the constraint conditions, We would like to compare it with the actual molded product in the horizontal direction. But first of all, it is considered two-point support in the constraint conditions in this paper.

MCCI, one of the ex-vessel phenomena during a severe accident, is generally caused by mutual reactions between molten core and reactor building basemat concrete, but occurs between sacrificial materials made by concrete and corium in APR nuclear power plant with PECS applied. In this paper, MCCI analysis was performed to design and apply a device to block the core melt at the junction connected to the ICI cavity sump from the core catcher installed in the reactor cavity of the APR. Unlike the sacrificial material, which has a cooling effect by inducing erosion of the ex-vessel core melt, the device is composed of concrete applied as a barrier to protect the ICI cavity sump. The decent thickness of the barrier wall of the device was calculated.

This paper proposes an algorithm for the Unrelated Parallel Machine Scheduling Problem(UPMSP) without setup times, aiming to minimize total tardiness. As an NP-hard problem, the UPMSP is hard to get an optimal solution. Consequently, practical scenarios are solved by relying on operator's experiences or simple heuristic approaches. The proposed algorithm has adapted two methods: a policy network method, based on Transformer to compute the correlation between individual jobs and machines, and another method to train the network with a reinforcement learning algorithm based on the REINFORCE with Baseline algorithm. The proposed algorithm was evaluated on randomly generated problems and the results were compared with those obtained using CPLEX, as well as three scheduling algorithms. This paper confirms that the proposed algorithm outperforms the comparison algorithms, as evidenced by the test results.

Non-structural elements, such as equipment, are typically affixed to a building’s floor or ceiling and move in tandem with the structure during an earthquake. Seismic forces acting upon non-structural elements traverse the ground and the building’s structure. Considering this seismic load transmission mechanism, it becomes imperative to account for the interactions between soil, structure, and equipment, establishing seismic design procedures accordingly. In this study, a Soil-Structure-Equipment Interaction (SSEI) model is developed. Through seismic response analysis using this model, how the presence or absence of SSEI impacts equipment behavior is examined. Neglecting the SSEI aspect when assessing equipment responses results in an overly conservative evaluation of its seismic response. This emphasizes the necessity of proposing an analytical model and design methodology that adequately incorporate the interaction effect. Doing so enables the calculation of rational seismic forces and facilitates the seismic design of non-structural elements.

본 연구에서는 소형선박용 중·고속 디젤엔진에 적용하여 연구 중인 SCR+DPF 기술을 저속엔진이 설치된 선박에 탑재하여 해상 실증 시험을 수행하였다. 대상 선박(총 톤수 2,881 톤, 정격출력 1,470kW@240rpm ×1)은 국내 연해를 운항하는 일반화물선으로 배출저감설 비의 선박 탑재를 위해 도면 개발, 승인 및 선박 임시검사를 수행하였다. 저감성능 확인을 위해서 가스상물질 측정장비는 NOx technical code 및 ISO-8178의 분석방법을 준용하는 장비를 사용하였으며, 입자상물질 측정장비는 국제해사기구(IMO)에서 논의하고 있는 블랙카본 측정 방법 중 하나인 스모크미터를 사용하였다. 시험은 황 함유량 따라 MGO(0.043%), LSFO(0.42%) 2종의 연료를 사용하였으며 실제 운항 하는 엔진회전수(130, 160 및 180 rpm)를 고려하여 시험 조건을 설정하였다. 시험 조건에 따라 배출저감설비의 전·후단에서 가스상 및 입 자상(매연) 물질을 측정하여 배출저감설비의 저감효율을 확인하였으며 모든 시험 조건에서 NOx의 경우 90% 이상, 입자상물질(매연)의 경우 95% 이상의 저감효율을 확인하였고 엔진 성능의 영향을 줄 수 있는 배기가스 압력은 허용배압 기준인 50mbar 이하를 만족하였다. 본 연구를 통해 해상실증 연구의 중요성과 중소형 저속엔진 선박의 질소산화물 및 입자상물질의 동시 저감을 위한 대응 기술로 SCR+DPF 설비 적용 가능성을 확인할 수 있었다.

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as “makespan”. This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator’s experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.