Combat-armored vehicles were equipped with an automatic-fire-extinguishing system to ensure the safety of the crew and vehicle from fires on the vehicle. When a fire was occurred, the automatic-fire-extinguishing system automatically detects the fire through sensors and detection lines, sprays a fire extinguisher, and notifies the crew visually and audibly. Recently, there had been cases of automatic-fire-extinguishing systems malfunction on combat-armored vehicles. In this study, in order to resolve the automatic-fire-extinguisher's malfunction phenomenon, ground noise and inter-circuit noise generated from the fire detection line were identified, and the resistance connected on the circuit was revised to remove noise. As a result of resistance revision, the noises was eliminated and the electromotive force difference between input circuits was made constant, thereby improving the malfunction of the automatic-fire-extinguishing system. By applying the result, it was confirmed that the control device sensed a temperature similar to the actual temperature on actual vehicles, and it was confirmed that the automatic-fire-extinguishing system's malfunction phenomenon was not founded in the field vehicles after then.

The objective of this study is to analyze the difference between the theoretically calculated torque values of lead screws used in vehicle seat rails and the required torque values due to various disturbances that occur in actual systems. Lead screws were classified into square and trapezoidal threads and modeled by two lead type. Dynamic analysis models were constructed by applying contact conditions and rotational joints between the lead screw and nut. The validity of the dynamic model was verified by comparing the torque values obtained from rigid body dynamic analysis with the theoretically calculated torque values. Then, the lead screw was modeled as a flexible body to investigate the torque variation required for the lead screw when dynamic loads are considered. This study will help predict the actual torque values of lead screws for seat rails.

This study uses FMECA (Failure Modes, Effects, and Criticality Analysis) and HAZOP (Hazard and Operability), which are widely applied in industrial areas, among risk assessment methods, and applies them to the same system. While FMECA evaluates system failure conditions and analyzes risks, HAZOP evaluates the system comprehensively by evaluating operational risks that may occur based on system parameters. According to data released by the Ministry of Land, Infrastructure and Transport, as of December 2021, the length of roads in Korea is 113,405 km, and the repair of guardrails that have expired must be fixed urgently in terms of traffic safety. Replacing all of these guardrails with new ones requires a very large cost, but if the guardrails are repaired with a vehicle equipped with the G-Save method, carbon emissions are reduced, the repair period is shortened, and great economic benefits can be obtained. However, risk assessment for guardrail coating vehicles has not been done so far. Focusing on this point, this study aims to evaluate the risk of these coating vehicles and describe the results. Finally, we found that the Risk Priority Numbers(RPN) in the FMECA risk assessment were greatly reduced, and 6 risk factors from HAZOP risk assessment and actions were taken.

A spiral flow path was applied to solve the problem of the existing straight flow path in the leveling shaft, a key component of the self-levelizer that can maintain the height according to the change in payload in EV, SUV. In this study, flow analysis was performed to check the velocity, pressure drop, and flow direction of oil according to the main operating conditions of the leveling shaft with a spiral flow path. As a result of the study, a leveling shaft with a spiral flow path is likely to improve fluid properties around the orifice and inlet valve under compression conditions, and it is judged to have a development application effect.

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

This study aims to understand the current status of exemptions for traffic accidents during the return of emergency vehicles and to provide suggestions for improvement. A survey was conducted on 3,500 firefighters to investigate the perception of traffic accidents during the return of emergency vehicles, and responses from 505 participants were analyzed. Based On the demographic characteristics and perception of the participants, frequency analysis and variance analysis were used as research methods to analyze basic statistics and the current situation. The results showed that firefighters have concerns and anxieties about traffic accidents during the return of emergency vehicles, and the need for applying exemptions and enacting explicit legal provisions was statistically confirmed. Based on these results, we suggest a policy for exemptions to improve the preparation for re-deployment and to alleviate the concerns and anxieties of firefighters.

본 연구에서는 무인항공기인 드론을 활용한 VDMS(Vision-based Displacement Measurement System)를 통해 동적변위계측 정 확도와 동특성 추정 신뢰성 검증을 위한 동적실험을 실시하였다. 비행하는 드론의 이동 및 회전진동을 보정하기 위해 영상 내부의 변 위가 발생하지 않는 고정점을 활용한 보정밥법을 사용하였으며, 검증을 위해 설치한 범용 센서인 LVDT와 LDS의 변위계측 결과와 비 교하여 그 오차를 시간영역과 진동수영역에서 분석하였다. 3가지 타입의 장비 모두 최대 변위 도달 및 주기 운동 계측에 있어서 대체 적으로 유사한 결과를 나타내었다. LDS 기준의 오차 분석 결과, 드론과 LVDT는 가진 진동수 변화에 의한 오차 값은 미비하나, 최대 발생 변위가 작을수록 오차 값은 증가하였다.

Airborne surveys are an essential analysis method for rapid response and contamination identification in the early event of a radiation emergency. On the other hand, airborne surveys are far from the ground, so it is necessary to convert the dose rate at a height of 1 m above the ground. In order to improve the accuracy of the analysis value, a lot of analysis of the measurement data is required. In our previous research, we developed MARK-A1, an instrument for rapid radiation aerial survey in high radiation environment, and MARK-M1, a multipurpose instrument for radiation detection. In this study, a large unmanned aerial vehicle (UAV) was used to conduct airborne surveys using three types of detectors in the Jeju Island environment. The NaI(Tl) detector uses one 3-inch scintillator (38 mm φ × 38 mm H), and the LaBr3 detector uses two 2-inch scintillators (25 mm φ × 25 mm H). The CZT detector uses a detector with dimensions of (15 mm × 15 mm × 7.5 mm). The UAV has a payload of 15 kg (J10, JCH systems Inc. Seoul, Korea). Three different detectors were operated at a constant height of 20 m, 30 m, and 50 m. The flight experiments were performed in the west near Jeju City. Dose rate conversion factors were used to convert the dose rate from the measured spectra, and hovering flights were conducted between 1 and 50 meters to derive altitude correction factors. In this paper, the data measured with each detector in the same area were compared and the differences were derived.

In this study, the safety aspects were studied by comparing the charge control characteristics of the two vehicles when a failure occurs between the OBC including the charging port or the charging door module (CDM) during slow charging using the In Cable Control Box (ICCB) for a long time.When the AC terminal was momentarily disconnected during charging, the Model-3 vehicle was charged normally if the AC circuit was disconnected up to three times, and the charging control was stopped when the number of disconnects reached four times. However, in the Ioniq-5 vehicle, charging control was normally performed when the disconnected AC circuit was normally connected regardless of the number of disconnection.

본 논문에서는 LS-DYNA를 활용한 원자력발전소 설치 로드블록 차량 시뮬레이션 방법을 소개한다. 차량 강습 위협이 원자력 발전 소의 설계기준위협으로 포함된 이후로 차량 강습을 대비하기 위한 차량 방벽(Anti-ram barrier)의 성능 평가 소요가 커지고 있다. 차량 방벽은 일반적으로 충돌 실험을 통하여 성능을 인증 받는다. 하지만 국내에서는 차량 방벽에 대한 성능 시험 시설이 마련되어 있지 않 아, 시뮬레이션을 통한 차량 방벽 성능 검증이 필요하다. LS-DYNA는 충돌 시뮬레이션에 특화되어 있으며, NCAC를 비롯한 여러 기 관에서 충돌 시험과의 타당성 검증을 완료한 수치 모델을 배포하고 있다. 본 논문에서는 로드블록의 가장 핵심적인 차량 차단막 모듈 의 FE 모델을 구축하여 충돌 시뮬레이션을 수행하였다. 계산된 결과는 NCHRP 179의 차량 안전 시설 충돌 시뮬레이션 검증 기준을 준용하여 검증하였다. 그 결과 모래시계 에너지(hourglass energy)가 총 에너지의 5%를 넘지 않고 내부 에너지의 10%를 넘지 않는 것 을 확인하였으며, added mass가 1% 미만으로 기준인 10%를 넘지 않는 것을 확인하였다. 향후 FE 모델을 활용하여 물리적 방벽의 성 능을 평가하여 데이터 베이스를 구축할 예정이다.