• Title/Summary/Keyword: Acceleration Response

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Evaluation of Structural Robustness of External Fuel Tank and Pylon for Military Aircraft under Random Vibration (랜덤진동에서 군용 항공기 외부연료탱크 및 파일런 구조 강건성 평가)

  • Kim, Hyun-Gi;Kim, Sungchan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.777-783
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    • 2021
  • Aircraft are affected by various vibrations during maneuvering. These vibrations may have a fatal effect on the survival of aircraft in some cases, so the safety of components applied to the aircraft should be proven against various vibrations through random vibration analysis. In this study, the structural robustness of an external fuel tank and pylon for military aircraft was evaluated under random vibration conditions using commercial software, MSC Random. In the random vibration analysis, a frequency response analysis was performed by imposing a unit load on the boundary condition point, and then excitation was performed with a PSD profile. In this process, the required mode data was extracted through a modal analysis method. In addition, the random vibration profile specified in the US Defense Environment Standard was applied as random vibration conditions, and the PSD profile given in units of G's was converted into units of gravitational acceleration. As a result of the numerical analysis, we evaluated the structural robustness of the external fuel tank and pylon by identifying the safety margins of beam elements, shell elements, and solid elements in a numerical model for random vibration in the x, y, and z directions.

Elastic Wave Propagation in Nuclear Power Plant Containment Building Walls Considering Liner Plate and Concrete Cavity (라이너 플레이트 및 콘크리트 공동을 고려한 원전 격납건물 벽체의 탄성파 전파 해석)

  • Kim, Eunyoung;Kim, Boyoung;Kang, Jun Won;Lee, Hongpyo
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.3
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    • pp.167-174
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    • 2021
  • Recent investigation into the integrity of nuclear containment buildings has highlighted the importance of developing an elaborate diagnostic method to evaluate the distribution and size of cavities inside concrete walls. As part of developing such a method, this paper presents a finite element approach to modeling elastic waves propagating in the containment building walls of a nuclear power plant. We introduce a perfectly matched layer (PML) wave-absorbing boundary to limit the large-scale nuclear containment wall to the region of interest. The formulation results in a semi-discrete form with symmetric damping and stiffness matrices. The transient elastic wave equations for a mixed unsplit-field PML were solved for displacement and stresses in the time domain. Numerical results show that the sensitivity of displacement, velocity, acceleration, and stresses is large depending on the size and location of the cavity. The dynamic response of the wall slightly differs depending on the existence of the containment liner plate. The results of this study can be applied to a full-waveform inversion approach for characterizing cavities inside a containment wall.

Performance Assessment of Navigation Seakeeping for Coastal Liquified-Natural-Gas Bunkering Ship (연안선박용 LNG 벙커링 전용선박의 내항성능 평가에 대한 연구)

  • Yi, Minah;Park, Jun-Bum;Lee, Chang-Hee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.26 no.7
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    • pp.904-914
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    • 2020
  • Through the Ministry of Trade, Industry, and Energy, South Korea is trying to support the "Building Project for Liquified Natural Gas (LNG) Bunkering Ship," centered on the Korea Gas Corporation, while the Ministry of Maritime Af airs and Fisheries is pushing to construct an LNG bunkering terminal at Busan New Port. LNG bunkering ships are essential for supplying LNG fuel from the terminal to the ships, resulting in the need for safety operation procedures. Therefore, in this study, the stability of a coastal LNG bunkering ship operating from Busan New Port to the anchorage in Busan Port was assessed to investigate the need for operational procedures for coastal LNG bunkering ships. Seakeeping analysis of the LNG bunkering ship was performed for each significant wave height by combining the response amplitude operator from the ship motion analysis under the potential flow theory with the actual observed sea data for five years and Texel, Marsen, and Arsloe (TMA) spectrum suitable for the Busan coast. The results showed that the roll and horizontal acceleration were the main risks that affected the navigation seakeeping performance above a significance wave height of 2 m. The operational periods of the LNG bunkering ship ranged from 83.3% to 99.9% of the total observation period.

Impact Evaluation of Rubber Type, Hardness and Induced Prestress Force on the Dynamic Properties of a Damper (감쇠장치의 동적특성에 대한 고무의 종류, 경도 및 프리스트레스력의 영향 평가)

  • Im, Chae-Rim;Yang, Keun-Hyeok;Mun, Ju-Hyun;Won, Eun-Bee
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.6
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    • pp.167-174
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    • 2022
  • The objective of this study is to evaluate the dynamic properties of DUS (damping-up system) composed of the materials with excellent damping capacity, and to compare with those of the conventional hangar bolt. The main parameters are the type and hardness (𝜂H), of rubber and the prestress force (value converted from the compression strain (𝜂R) in the stress-strain relationship of rubber). The dynamic properties were examined from the natural frequency (𝜔n), maximum response acceleration (Am), amplification coefficient (𝛼p), maximum relative displacement (𝚫m), and damping ratio (𝜉D). The test results showed that the Am, 𝛼p, and 𝚫m values of DUS were 46.3%, 46.6% and 62.9% lower, respectively, and the 𝜉D value was 3.89 times higher, when compared to those of the conventional hangar bolt. In particular, the 𝛼p value was 1.3 for DUS, and 2.45 for the conventional hanger bolt, which were similar to those of rigid and flexible components specified in KDS 41 17 00, respectively. Consequently, in the optimal details of DUS, the 𝜂H values of 50 and 45 were required for the NR (natural rubber) and EPDM (ethylene propylene diene monomer), and the 𝜂R value of 5% was also recommended.

A Study to Evaluate the Impact of In-Vehicle Warning Information on Driving Behavior Using C-ITS Based PVD (C-ITS 기반 PVD를 활용한 차량 내 경고정보의 운전자 주행행태 영향 분석)

  • Kim, Tagyoung;Kim, Ho Seon;Kang, Kyeong-Pyo;Kim, Seoung Bum
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.28-41
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    • 2022
  • A road system with CV(Connected Vehicle)s, which is often referred to as a cooperative intelligent transportation system (C-ITS), provides various road information to drivers using an in-vehicle warning system. Road environments with CVs induce drivers to reduce their speed or change lanes to avoid potential risks downstream. Such avoidance maneuvers can be considered to improve driving behaviors from a traffic safety point of view. Thus, empirically evaluating how a given in-vehicle warning information affects driving behaviors, and monitoring of the correlation between them are essential tasks for traffic operators. To quantitatively evaluate the effect of in-vehicle warning information, this study develops a method to calculate compliance rate of drivers where two groups of speed profile before and after road information is provided are compared. In addition, conventional indexes (e.g., jerk and acceleration noise) to measure comfort of passengers are examined. Empirical tests are conducted by using PVD (Probe Vehicle Data) and DTG (Digital Tacho Graph) data to verify the individual effects of warning information based on C-ITS constructed in Seoul metropolitan area in South Korea. The results in this study shows that drivers tend to decelerate their speed as a response to the in-vehicle warning information. Meanwhile, the in-vehicle warning information helps drivers to improve the safety and comport of passengers.

Running Safety and Ride Comfort Prediction for a Highspeed Railway Bridge Using Deep Learning (딥러닝 기반 고속철도교량의 주행안전성 및 승차감 예측)

  • Minsu, Kim;Sanghyun, Choi
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.35 no.6
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    • pp.375-380
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    • 2022
  • High-speed railway bridges carry a risk of dynamic response amplification due to resonance caused by train loads, and running safety and riding comfort must therefore be reviewed through dynamic analysis in accordance with design codes. The running safety and ride comfort calculation procedure, however, is time consuming and expensive because dynamic analyses must be performed for every 10 km/h interval up to 110% of the design speed, including the critical speed for each train type. In this paper, a deep-learning-based prediction system that can predict the running safety and ride comfort in advance is proposed. The system does not use dynamic analysis but employs a deep learning algorithm. The proposed system is based on a neural network trained on the dynamic analysis results of each train and speed of the railway bridge and can predict the running safety and ride comfort according to input parameters such as train speed and bridge characteristics. To confirm the performance of the proposed system, running safety and riding comfort are predicted for a single span, straight simple beam bridge. Our results confirm that the deck vertical displacement and deck vertical acceleration for calculating running safety and riding comfort can be predicted with high accuracy.

Dynamic Performance Estimation of the Incrementally PSC Girder Railway Bridge by Modal Tests and Moving Load Analysis (다단계 긴장 PSC 거더 철도교량의 동특성 실험 및 주행열차하중 해석에 의한 동적성능 평가)

  • Kim, Sung Il;Kim, Nam Sik;Lee, Hee Up
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4A
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    • pp.707-717
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    • 2006
  • As an alternative to conventional prestressed concrete (PSC) girders, various types of PSC girders are either under development or have already been applied in bridge structures. Incrementally prestressed concrete girder is one of these newly developed girders. According to the design concept, these new types of PSC girders have the advantages of requiring less self-weight while having the capability of longer spans. However, the dynamic interaction between bridge superstructures and passing trains is one of the critical issues concerning these railway bridges designed with more flexibility. Therefore, it is very important to evaluate modal parameters of newly designed bridges before doing dynamic analyses. In the present paper, a 25 meters long full scale PSC girder was fabricated as a test specimen and modal testing was carried out to evaluate modal parameters including natural frequencies and modal damping ratios at every prestressing stage. During the modal testing, a digitally controlled vibration exciter as well as an impact hammer is applied, in order to obtain precise frequency response functions and the modal parameters are evaluated varying with construction stages. Prestressed force effects on changes of modal parameters are analyzed at every incremental prestressing stage. With the application of reliable properties from modal experiments, estimation of dynamic performances of PSC girder railway bridges can be obtained from various parametric studies on dynamic behavior under the passage of moving train. Dynamic displacements, impact factor, acceleration of the slab, end rotation of the girder, and other important dynamic performance parameters are checked with various speeds of the train.

Analysis of Driving and Environmental Impacts by Providing Warning Information in C-ITS Vehicles Using PVD (PVD를 활용한 C-ITS 차량 내 경고정보 제공에 따른 주행 및 환경영향 분석)

  • Yoonmi Kim;Ho Seon Kim;Kyeong-Pyo Kang;Seoung Bum Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.224-239
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    • 2023
  • C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

Immunological Characteristics of Hyperprogressive Disease in Patients with Non-small Cell Lung Cancer Treated with Anti-PD-1/PD-L1 Abs

  • Kyung Hwan Kim;Joon Young Hur;Jiae Koh;Jinhyun Cho;Bo Mi Ku;June Young Koh;Jong-Mu Sun;Se-Hoon Lee;Jin Seok Ahn;Keunchil Park;Myung-Ju Ahn;Eui-Cheol Shin
    • IMMUNE NETWORK
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    • v.20 no.6
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    • pp.48.1-48.11
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    • 2020
  • Hyperprogressive disease (HPD) is a distinct pattern of progression characterized by acceleration of tumor growth after treatment with anti-PD-1/PD-L1 Abs. However, the immunological characteristics have not been fully elucidated in patients with HPD. We prospectively recruited patients with metastatic non-small cell lung cancer treated with anti-PD-1/PD-L1 Abs between April 2015 and April 2018, and collected peripheral blood before treatment and 7-days post-treatment. HPD was defined as ≥2-fold increase in both tumor growth kinetics and tumor growth rate between pre-treatment and post-treatment. Peripheral blood mononuclear cells were analyzed by multi-color flow cytometry to phenotype the immune cells. Of 115 patients, 19 (16.5%) developed HPD, 52 experienced durable clinical benefit (DCB; partial response or stable disease ≥6 months), and 44 experienced non-hyperprogressive progression (NHPD). Patients with HPD had significantly lower progression-free survival (p<0.001) and overall survival (p<0.001). When peripheral blood immune cells were examined, the pre-treatment frequency of CD39+ cells among CD8+ T cells was significantly higher in patients with HPD compared to those with NHPD, although it showed borderline significance to predict HPD. Other parameters regarding regulatory T cells or myeloid derived suppressor cells did not significantly differ among patient groups. Our findings suggest high pre-treatment frequency of CD39+CD8+ T cells might be a characteristic of HPD. Further investigations in a larger cohort are needed to confirm our results and better delineate the immune landscape of HPD.

Enhancing Throughput and Reducing Network Load in Central Bank Digital Currency Systems using Reinforcement Learning (강화학습 기반의 CBDC 처리량 및 네트워크 부하 문제 해결 기술)

  • Yeon Joo Lee;Hobin Jang;Sujung Jo;GyeHyun Jang;Geontae Noh;Ik Rae Jeong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.34 no.1
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    • pp.129-141
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    • 2024
  • Amidst the acceleration of digital transformation across various sectors, the financial market is increasingly focusing on the development of digital and electronic payment methods, including currency. Among these, Central Bank Digital Currencies (CBDC) are emerging as future digital currencies that could replace physical cash. They are stable, not subject to value fluctuation, and can be exchanged one-to-one with existing physical currencies. Recently, both domestic and international efforts are underway in researching and developing CBDCs. However, current CBDC systems face scalability issues such as delays in processing large transactions, response times, and network congestion. To build a universal CBDC system, it is crucial to resolve these scalability issues, including the low throughput and network overload problems inherent in existing blockchain technologies. Therefore, this study proposes a solution based on reinforcement learning for handling large-scale data in a CBDC environment, aiming to improve throughput and reduce network congestion. The proposed technology can increase throughput by more than 64 times and reduce network congestion by over 20% compared to existing systems.