The purpose of this paper is to investigate the vibration phenomenon occurring in the structure such as a ship with the hemispherical substructure and operating at fixed frequency, and to suggest the active vibration control method using the Fx-LMS algorithm to reduce vibration amplification. In order to study the possibility of reducing vibration in the hemispherical structure, the active vibration control model was developed and a vibration control experimental device for the hemispherical structure was constructed. The narrowband Fx-LMS algorithm was developed to enable precise real-time control at a specific frequency, and the secondary path for dynamic control was modeled with two coefficients per frequency. The experimental device is equipped with three exciters, six 3-axis actuators, and six 3-axis error sensors, which can acquire 18 error sensor signals. Real-time secondary path tracking was possible with the secondary path consisting of two coefficients and the control algorithm, and effective vibration control performance was confirmed through this. And the experimental results of active vibration control of the exciter for three frequencies showed that the exciter vibration was reduced by a minimum of 63.7% and a maximum of 97.7%, which shows the possibility of reducing the vibration of the structure in real time using the proposed method.

The purpose of this study is to investigate the dynamic behavior of the internal cabinet of a nuclear power plant due to an earthquake and the characteristics of cabinet vibration reduction by TMD(tuned mass damper). For this purpose, the experimental device was constructed and numerical analysis was performed. The experimental device for the dynamic behavior of the cabinet consists of a cabinet, sliding base, mount, actuator, exciter, and measuring system, and the frequency response function of the cabinet was obtained. In addition, the time history of the cabinet was analyzed for acceleration and displacement through TMD design and cabinet 3D modeling. The natural frequency and response of the cabinet were lowered by approximately 26% due to the structural rigidity of the cabinet under the conditions of door opening and sliding base strong excitation. The acceleration and displacement characteristics of the cabinet varied depending on the TMD mass, and the cabinet vibration reduction effect was the best when the TMD mass was 60kg. The reduction in acceleration and displacement of the cabinet was approximately 12.1–16.2% and 10.1–19.1%, respectively.

This study investigates the effects of various Throttle Position Sensor (TPS) signal anomalies and throttle body defects on automotive acceleration and safety by experimentally reproducing and analyzing eight distinct fault scenarios. The results demonstrate that the Electronic Control Unit (ECU) consistently detects signal anomalies and activates fail-safe modes, limiting throttle response and engine output to maintain automotive control. In all fault conditions, sudden unintended acceleration was effectively prevented, and braking performance remained unaffected. These findings underscore the robustness of the throttle control system against electrical and mechanical defects and offer valuable insights for the design of safer drive-by-wire systems.

This study investigates the impact of both direct and indirect moisture ingress into an automotive engine control unit(ECU) on vehicle behavior and operational safety. Two experimental conditions were examined: exposure to an environment with 100% relative humidity(indirect ingress) and direct injection of 1.0~2.0 cc of water onto the ECU(direct ingress). The results showed no abnormal behavior under indirect moisture conditions. However, direct moisture ingress caused engine malfunctions, warning light activations, and irregular vehicle behavior. Notably, the vehicle's safety logic functioned as intended, resulting in engine shutdown without leading to unintended acceleration. These findings provide quantitative data valuable for future reliability assessments of ECUs and investigations into sudden unintended acceleration phenomena.

Early warnings have been developed to provide rapid earthquake information, allowing people to prepare as much time as possible. However, since it takes several seconds for an earthquake warning to be issued, the blind zone is inevitable. To reduce the blind zone, information from a single observatory is used to operate an on-site earthquake warning. However, false and missed alarms are still high, requiring continued research and validation. This study predicted Peak Ground Acceleration (PGA) using the characteristic data to reduce false and missed alarms in on-site earthquake warnings. A machine learning prediction model was created using the initial P-wave parameters developed from the characteristic data to achieve this. Then, the model was used to predict the maximum ground acceleration in the southeastern region of the Korean Peninsula. The expected results for six target earthquakes were confirmed to have a standard deviation within 0.3 compared to the observed PGA and the values within ±2 sigma. This method is expected to help develop an on-site early warning system for earthquakes.

Recently, there has been growing anxiety about automotive due to accidents suspected to be caused by sudden unintended acceleration. A study was conducted on the effect of automotive defects on Sudden Unintended Acceleration. Experimental results were derived and analyzed by simulating the situation of sudden unintended acceleration while driving a automotive. It was experimentally confirmed that the defect in the TPS sensor had no direct effect on the rapid increase in RPM. It has been confirmed that the vehicle brakes normally when the brakes are applied even if there is a TPS sensor defect. In the future, it is necessary to investigate the correlation between automotive defects and sudden unintended acceleration through various experiments.

Recently, the number of elderly driver accidents has been steadily increasing. EDR(Event Data Recorder) helps a lot in understanding traffic accidents. In particular, as anxiety about SUA(Sudden Unintended Acceleration) increases, EDR data is playing an important role in accident analysis. In this study, EDR data of an accident vehicle suspected of SUA was analyzed to identify traffic accident circumstances and detailed accidents. Experimental results were derived and analyzed by simulating the situation of SUA while driving a car. As a result, it was found that normal braking is performed when the brake pedal is operated even in dangerous situations such as mechanical defects and driver malfunctions. Rather than finding the cause of an accident after a traffic accident, countermeasures are needed to prevent mechanical defects and driving malfunctions before a traffic accident.

We examine whether the radial acceleration relation (RAR) of dwarf galaxies can be explained by Verlinde’s emergent gravity. This is the extension of Yoon et al. (2023), which examine the RAR of typical spiral galaxies, to less massive systems. To do this, we compile the line-of-sight velocity dispersion profiles of 30 dwarf galaxies in the Local Group from the literature. We then calculate the expected gravitational acceleration from the stellar component in the framework of the emergent gravity, and compare it with that from observations. The calculated acceleration with the emergent gravity under the assumption of a quasi-de Sitter universe agrees with the observed one within the uncertainty. Our results suggest that the emergent gravity can explain the kinematics of galaxies without introducing dark matter, even for less massive galaxies where dark matter is expected to dominate. This sharply contrasts with MOND, where a new interpolating function has to be introduced for dwarf galaxies to explain their kinematics without dark matter.

During the formation of large-scale structures in the universe, weak internal shocks are induced within the hot intracluster medium (ICM), while strong accretion shocks arise in the warm-hot intergalactic medium (WHIM) within filaments, and the warm-cold gas in voids surrounding galaxy clusters. These cosmological shocks are thought to accelerate cosmic ray (CR) protons and electrons via diffusive shock acceleration (DSA). Recent advances in particle-in-cell and hybrid simulations have provided deeper insights into the kinetic plasma processes that govern microinstabilities and particle acceleration in collisionless shocks in weakly magnetized astrophysical plasma. In this study, we adopt a thermal-leakage type injection model and DSA power-law distribution functions in the test-particle regime. The CR proton spectrum directly connects to the Maxwellian distribution of protons at the injection momentum pinj = Qppth,p. On the other hand, the CR electron spectrum extends down to pmin = Qepth,e and is linked to the Maxwellian distribution of electrons. Here, pth,p and pth,e, are the proton and electron thermal momenta, respectively. Moreover, we propose that the postshock gas temperature and the injection parameters, Qp and Qe are self-regulated to maintain the test-particle condition, as the thermal energy is gradually transferred to the CR energy. Under these constraints, we estimate the self-regulated values of the temperature reduction factor, RT , and the proton injection parameter, Qp, along with the resulting CR efficiencies, ηp and ηe. We then provide analytical fitting functions for these parameters as functions of the shock Mach number, Ms. These fitting formulas may serve as valuable tools for quantitatively assessing the impact of CR protons and electrons, as well as the resulting nonthermal emissions in galaxy clusters and cosmic filaments.

It is very important to measure and analyze various driving performance in the vehicle development stage. Particularly in racing vehicles, analysis of driving characteristics on various courses is very important, and data measurement and analysis technology using actual measurement equipment are widely used in racing strategies. In this paper, we present an analytical approach using vehicle acceleration, which is relatively easy to measure among various factors. Measured acceleration data is used to analyze optimal driving performance.

Structures of high-rise buildings are less prone to earthquake damage. This is because the response acceleration of high-rise buildings appears to be small by generally occurring short-period ground motions. However, due to the increased construction volume of high-rise buildings and concerns about large earthquakes, long-period ground motions have begun to be recognized as a risk factor for high-rise buildings. Ground motion observed on each floor of the building is affected by the eigenmode of the building because the ground motion input to the building is amplified in the frequency range corresponding to the building's natural frequency. In addition, long-period components of ground motion are more easily transmitted to the floor or attached components of the building than short-period components. As such, high-rise buildings and non-structural components pose concerns about long-period ground motion. However, the criteria (ASCE 7-22) underestimate the acceleration response of buildings and non-structural components caused by long-period ground motion. Therefore, the characteristics of buildings’ acceleration response amplification ratio and non-structural components were reviewed in this study through shake table tests considering long-period ground motions.

병렬영상기법인 SENSE 기법은 슬관절 자기공명영상의 검사 시간을 획기적으로 단축할 수 있다. 그러나 기법 적용 시 SENSE factor를 증가시키면 영상에 인공물의 발생이 증가하는 문제점이 있어 개선을 위해 본 연구에서는 최소의 시간이 소요되면서 인공물이 발생하지 않는 최적의 SENSE factor를 제시하고자 하였다. 연구 방법은 SENSE factor 1.0을 기준 으로 0.5 간격씩 5.0까지 변화시켜 팬텀 실험과 임상실험을 시행하였다. 3.0T 초전도 자기공명영상장치와 dS Knee 코일 을 사용하여 T1, T2 강조영상을 획득하였으며, 영상의 비교평가는 임상 경력 10년 이상의 방사선사 10명이 5점 척도로 평가한 후, 일원배치 분산분석과 사후분석을 통해 유의한 차이가 있는지 판단하였다. 연구 결과 팬텀 실험은 T1, T2 강조 영상 모두 SENSE factor를 1.5 이하로 하였을 때 기준 영상과 차이가 없었으며, 임상실험은 SENSE factor를 2.0 이하로 하였을 때 기준 영상과 차이가 없었다. 결론적으로 슬관절 자기공명영상 시 검사 시간을 단축하면서 인공물이 발생하지 않는 최적의 SENSE factor는 팬텀 실험의 경우 1.5, 임상실험의 경우 2.0이 적정하리라 사료된다.

요통을 호소하는 환자에서의 자기공명영상 검사는 다른 영상 진단법에 비해 요추와 주변 조직에 대한 높은 대조도와 해상력, 다양한 영상면의 획득으로 해부학적 구조 파악과 다양한 척추 질환의 진단에 널리 활용되고 있다. 그러나 자기공명 영상 검사는 검사 시간이 길기 때문에 통증으로 협조가 되지 않는 환자들에게서 움직임에 의한 인공물을 유발하는 경우가 많아 검사 시간을 최소화하는 것이 중요하다. 이에 자기공명영상 검사 시간 단축을 위한 다양한 기법들이 개발되어 왔으며, 최근 높은 영상의 질을 유지하면서 검사 시간은 크게 줄이는 K-공간 기반 딥 러닝(K-space based Deep Learning, DL) 기법이 주목받고 있다. 본 연구는 요추 자기공명영상 검사에서 DL 기법의 유용성을 알아보기 위해 본원을 내원하여 척추 질환이 의심되는 환자를 대상으로 DL 기법 적용 전후 시상면 T2 강조 영상과 축상면 T2 강조 영상을 각각 획득하였으며, 신호대잡음비와 대조대잡음비, 영상 획득 시간, 전체적인 영상의 질 및 병변 진단 일치도를 비교 분석하였다. 연구 결과 영상의 질 향상과 검사 시간의 단축뿐만 아니라 빠른 영상 획득으로 움직임이나 호흡에 의한 인공물 또한 감소하는 것을 볼 수 있었다. 따라서 자기공명영상 검사에서 DL 기법 사용 시 진단적 가치가 보다 높은 영상을 제공하는 동시에 환자의 만족도를 높여 임상에서도 유용한 방법이 될 것으로 사료된다.