This paper presents a novel methodology for assessing the vulnerabilities of autonomous vehicles (AVs) across diverse operational design domains (ODDs) related to road transportation infrastructure, categorized by the level of service (LOS). Unlike previous studies that primarily focused on the technical performance of AVs, this study addressed the gap in understanding the impact of dynamic ODDs on driving safety under real-world traffic conditions. To overcome these limitations, we conducted a microscopic traffic simulation experiment on the Sangam autonomous mobility testbed in Seoul. This study systematically evaluated the driving vulnerability of AVs under various traffic conditions (LOSs A–E) across multiple ODD types, including signalized intersections, unsignalized intersections, roundabouts, and pedestrian crossings. A multivariate analysis of variance (MANOVA) was employed to quantify the discriminatory power of the evaluation indicators as the traffic volume was changed by ODD. Furthermore, an autonomous driving vulnerability score (ADVS) was proposed to conduct sensitivity analyses of the vulnerability of each ODD to autonomous driving. The findings indicate that different ODDs exhibit varying levels of sensitivity to autonomous driving vulnerabilities owing to changes in traffic volume. As the LOS deteriorates, driving vulnerability significantly increases for AV–bicycle interactions and AV right turns at both signalized and unsignalized intersections. These results are expected to be valuable for developing scenarios and evaluation systems to assess the driving capabilities of AVs.

This study develops a comprehensive road operation evaluation model that integrates the perspectives of three principal stakeholders: road users prioritizing congestion mitigation, operators emphasizing investment efficiency, and policymakers advocating broader societal goals such as carbon reduction. The analysis database was constructed using traffic data obtained from reliable sources, including the Korea Transport Institute's Big Data Center and Suwon City's Urban Safety Integration Center. Binary logistic regression was employed to identify the factors influencing traffic congestion from the users’ perspective, whereas multiple linear regression models were used to analyze road investment efficiency from the operators’ viewpoint and carbon dioxide emissions from the policymakers’ standpoint. Statistical analyses were conducted on 4,322 road segments in Suwon City, with each evaluation criterion assigned an equal weight of 33.3 points in a unified 100-point scoring system. The analysis identified 15 statistically significant indicators affecting the three evaluation criteria, with the resulting models demonstrating strong explanatory power, evidenced by adjusted R² values of 0.197, 0.593, and 0.544 for traffic congestion, road investment efficiency, and carbon dioxide emission models, respectively. A volume-to-capacity (V/C) ratio of 0.64 was determined to represent the optimal balance point at which the requirements of all stakeholder groups align. When applied to Suwon City's arterial road network, the model identified 248 high-congestion segments (53.13 km), 203 segments with low investment efficiency (26.8 km), and 357 segments with high carbon emissions (156.33 km), each requiring targeted operational improvements. The proposed model addresses the limitations of existing single-stakeholder evaluation frameworks by offering transportation authorities a systematic and multi-dimensional approach to road operation assessment.

원전에서 발생 가능한 중대사고 중 하나인 용융 노심-콘크리트 상호작용(Molten Core Concrete Interaction, MCCI)은 노심의 용융물이 격납용기 하부의 콘크리트를 침투하면서 콘크리트의 물리적 및 화학적 분해를 유도하고, 이로 인해 구조적 손상이 발생하게 된다. 더불어, 분해 과정에서 발생하는 비응축성 가스와 수증기로 인해 내부압력이 급격히 상승할 수 있다. 본 연구는 MCCI 가 발생하는 상황에서 원전 프리스트레스트 콘크리트 격납용기(Prestressed Concrete Containment Vessel, PCCV)의 내부압력 저 항능력을 평가하는 것을 목적으로 한다. 이를 위해 APR1400을 대상으로 MELCOR 코드 기반의 사고 시나리오를 통해 압력 및 온도 상승을 모사하였으며, 검증된 유한요소 해석모델을 이용해 구조응답을 분석하였다. 내부압력 저항능력은 글로벌 후프 변형률(global hoop strain)과 등가소성변형률(equivalent plastic strain) 두 가지 한계상태 기준에 따라 비교 분석하였다.

This study examined the offshore eel trap fishing process using one year of fishing logs and fishermen’s insights to identify key operational challenges and propose equipment improvement for greater efficiency and safety. Conger eel catches varied significantly by season, depth, and temperature, peaking in winter at 85–90 m and 23°C. The western waters of Jeju Island were identified as a major fishing ground, with the highest catch recorded in November and the lowest in July, reflecting seasonal trends. Each fishing operation deployed about 10,000 traps, with an average loss of 38 traps, posing economic concerns. The process involved intensive manual labor in bait preparation, trap retrieval, catch separation, line loading, and unloading, leading to high physical demands and safety risks. To address these issues, the study proposed automation through the development of a line loading device, trap cleaning device, bait processing machine, and automatic catch separator. These innovations could reduce the labor force required by one to two workers per process, alleviate workloads, and enhance resource management. By integrating quantitative logbook analysis with field-based knowledge, this study offers practical value. Further research is recommended on automation development, cost-effectiveness, and field validation to support safer and more sustainable eel trap fisheries.

This study explores the seismic performance of steel diaphragm walls in underground structures, a critical aspect of structural engineering. The study focuses on the effects of slab diaphragm flexibility, an often overlooked factor in seismic design. Traditional seismic designs often assume the slab acts as a rigid diaphragm, leading to inaccuracies in predicting how forces are distributed between the slab and walls during an earthquake. To address this, the authors model steel diaphragm walls using equivalent cross-sections and analyze shear forces in both rigid and semi-rigid diaphragm scenarios. Results show that semi-rigid diaphragms reduce the shear forces on the exterior walls while increasing them on the internal core, thereby affecting the overall stiffness of the structure. The study emphasizes the importance of considering diaphragm flexibility in seismic design to achieve more accurate predictions of structural behavior and improve construction efficiency.