• Title/Summary/Keyword: 예측 모델링

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Study of the Incremental Dynamic Inversion Control to Prevent the Over-G in the Transonic Flight Region (천음속 비행영역에서 하중제한 초과 방지를 위한 증분형 동적 모델역변환 제어 연구)

  • Jin, Tae-beom;Kim, Chong-sup;Koh, Gi-Oak;Kim, Byoung-Soo
    • Journal of Aerospace System Engineering
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    • v.15 no.5
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    • pp.33-42
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    • 2021
  • Modern aircraft fighters improve the maneuverability and performance with the RSS (Relaxed Static Stability) concept and therefore these aircrafts are susceptible to abrupt pitch-up in the transonic and moderate Angle-of-Attack (AoA) flight region where the shock wave is formed and the mean aerodynamic center is moved forward during deceleration. Also, the modeling of the aircraft flying in this flight region is very difficult due to complex flow filed and unpredictable dynamic characteristics and the model-based control design technique does not fully cover this problem. In this paper, we analyzed the performance of the TPMC (Transonic Pitching Moment Compensation) control based on the model-based IDI (Incremental Dynamic Inversion) and the Hybrid IDI based on the model and sensor based IDI during the SDT (Slow Down Turn) in transonic region. As the result, the Hybrid IDI had quicker response and the same maximum g suppression performance and provided the predictable flying qualities compared to the TPMC control. The Hybrid IDI improved the performance of the Over-G protection controller in the transonic and moderate AoA region

U-Net Cloud Detection for the SPARCS Cloud Dataset from Landsat 8 Images (Landsat 8 기반 SPARCS 데이터셋을 이용한 U-Net 구름탐지)

  • Kang, Jonggu;Kim, Geunah;Jeong, Yemin;Kim, Seoyeon;Youn, Youjeong;Cho, Soobin;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1149-1161
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    • 2021
  • With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

Numerical Experiment of Driftwood Generation and Deposition Patterns by Tsunami (쓰나미에 의한 유목의 생성과 퇴적패턴의 수치모의실험)

  • Kang, Tae Un;Jang, Chang-Lae;Lee, Nam Joo;Lee, Won Ho
    • Ecology and Resilient Infrastructure
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    • v.8 no.4
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    • pp.165-178
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    • 2021
  • We studied driftwood behaviors including generation and deposition in a tsunami using a numerical simulation. We used an integrated two-dimensional numerical model, which included a driftwood dynamics model. The study area was Sendai, Japan. Observation data collected by Inagaki et al. (2012) were used to verify the simulation results by comparing them with driftwood deposition patterns. A simplified model was developed to consider the threshold of driftwood generation by the drag force of water flows. To consider the volume of driftwood generated, we estimated the total wood number in the study area using Google Earth. Therefore, we simulated more than 13,000 pieces of driftwood that were generated and transported inland from approximately 300,000 trees that were growing in the forest. The final distribution of the driftwood was similar to the observation data. The reproducibility of the generation and deposition patterns of driftwood showed good agreement in terms of longitudinal deposition pattern. In the future, a sensitivity analysis on driftwood parameters, such as the size of the wood, boundary conditions, and grid size, will be implemented to predict the travel patterns of driftwood. Such modeling will be a useful methodology for disaster prediction based on water flow and driftwood.

Optimal Operation Methods of the Seasonal Solar Borehole Thermal Energy Storage System for Heating of a Greenhouse (온실난방을 위한 태양열 지중 계간축열시스템의 최적 운전 방안)

  • Kim, Wonuk;Kim, Yong-Ki
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.1
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    • pp.28-34
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    • 2019
  • Solar energy is one of the most abundant renewable energy sources on Earth but there are restrictions on the use of solar thermal energy due to the time-discrepancy between the solar-rich season and heating demand. In Europe and Canada, a seasonal solar thermal energy storage (SSTES), which stores the abundant solar heat in the summer and uses the heat for the winter heating load, is used. Recently, SSTES has been introduced in Korea and empirical studies are actively underway. In this study, a $2,000m^2$ flat plate type solar collector and $20,000m^2$ of borehole thermal energy storage (BTES) were studied for a greenhouse in Hwaseong City, which has a heating load of 2,164 GJ/year. To predict the dynamic performance of the system over time, it was simulated using the TRNSYS 18 program, and the solar fraction of the system with the control conditions was investigated. As a result, the solar BTES system proposed in this study showed an average solar fraction of approximately 60% for 5 years when differential temperature control was applied to both collecting solar thermal energy and discharging BTES. The proposed system simplified the configuration and control method of the solar BTES system and secured its performance.

The Estimation of Arctic Air Temperature in Summer Based on Machine Learning Approaches Using IABP Buoy and AMSR2 Satellite Data (기계학습 기반의 IABP 부이 자료와 AMSR2 위성영상을 이용한 여름철 북극 대기 온도 추정)

  • Han, Daehyeon;Kim, Young Jun;Im, Jungho;Lee, Sanggyun;Lee, Yeonsu;Kim, Hyun-cheol
    • Korean Journal of Remote Sensing
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    • v.34 no.6_2
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    • pp.1261-1272
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    • 2018
  • It is important to measure the Arctic surface air temperature because it plays a key-role in the exchange of energy between the ocean, sea ice, and the atmosphere. Although in-situ observations provide accurate measurements of air temperature, they are spatially limited to show the distribution of Arctic surface air temperature. In this study, we proposed machine learning-based models to estimate the Arctic surface air temperature in summer based on buoy data and Advanced Microwave Scanning Radiometer 2 (AMSR2)satellite data. Two machine learning approaches-random forest (RF) and support vector machine (SVM)-were used to estimate the air temperature twice a day according to AMSR2 observation time. Both RF and SVM showed $R^2$ of 0.84-0.88 and RMSE of $1.31-1.53^{\circ}C$. The results were compared to the surface air temperature and spatial distribution of the ERA-Interim reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). They tended to underestimate the Barents Sea, the Kara Sea, and the Baffin Bay region where no IABP buoy observations exist. This study showed both possibility and limitations of the empirical estimation of Arctic surface temperature using AMSR2 data.

Construction of Logic Trees and Hazard Curves for Probabilistic Tsunami Hazard Analysis (확률론적 지진해일 재해도평가를 위한 로직트리 작성 및 재해곡선 산출 방법)

  • Jho, Myeong Hwan;Kim, Gun Hyeong;Yoon, Sung Bum
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.31 no.2
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    • pp.62-72
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    • 2019
  • Due to the difficulties in forecasting the intensity and the source location of tsunami the countermeasures prepared based on the deterministic approach fail to work properly. Thus, there is an increasing demand of the tsunami hazard analyses that consider the uncertainties of tsunami behavior in probabilistic approach. In this paper a fundamental study is conducted to perform the probabilistic tsunami hazard analysis (PTHA) for the tsunamis that caused the disaster to the east coast of Korea. A logic tree approach is employed to consider the uncertainties of the initial free surface displacement and the tsunami height distribution along the coast. The branches of the logic tree are constructed by reflecting characteristics of tsunamis that have attacked the east coast of Korea. The computational time is nonlinearly increasing if the number of branches increases in the process of extracting the fractile curves. Thus, an improved method valid even for the case of a huge number of branches is proposed to save the computational time. The performance of the discrete weight distribution method proposed first in this study is compared with those of the conventional sorting method and the Monte Carlo method. The present method is comparable to the conventional methods in its accuracy, and is efficient in the sense of computational time when compared with the conventional sorting method. The Monte Carlo method, however, is more efficient than the other two methods if the number of branches and the number of fault segments increase significantly.

Field Observation of Morphological Response to Storm Waves and Sensitivity Analysis of XBeach Model at Beach and Crescentic Bar (폭풍파랑에 따른 해빈과 호형 사주 지형변화 현장 관측 및 XBeach 모델 민감도 분석)

  • Jin, Hyeok;Do, Kideok;Chang, Sungyeol;Kim, In Ho
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.6
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    • pp.446-457
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    • 2020
  • Crescentic sand bar in the coastal zone of eastern Korea is a common morphological feature and the rhythmic patterns exist constantly except for high wave energy events. However, four consecutive typhoons that directly and indirectly affected the East Sea of Korea from September to October in 2019 impacted the formation of longshore uniform sand bar and overall shoreline retreats (approx. 2 m) although repetitive erosion and accretion patterns exist near the shoreline. Widely used XBeach to predict storm erosions in the beach is utilized to investigate the morphological response to a series of storms and each storm impact (NE-E wave incidence). Several calibration processes for improved XBeach modeling are conducted by recently reported calibration methods and the optimal calibration set obtained is applied to the numerical simulation. Using observed wave, tide, and pre & post-storm bathymetries data with optimal calibration set for XBeach input, XBeach successfully reproduces erosion and accretion patterns near MSL (BSS = 0.77 (Erosion profile), 0.87 (Accretion profile)) and observed the formation of the longshore uniform sandbar. As a result of analysis of simulated total sediment transport vectors and bed level changes at each storm peak Hs, the incident wave direction contributes considerable impact to the behavior of crescentic sandbar. Moreover, not only the wave height but also storm duration affects the magnitude of the sediment transport. However, model results suggest that additional calibration processes are needed to predict the exact crest position of bar and bed level changes across the inner surfzone.

A Study on Structural Characteristics of Axial Fans Operating Speed Using Finite Element Analysis (유한요소해석을 이용한 축류팬 운전속도별 구조특성에 대한 연구)

  • Kook, Jeong-Keun;Cho, Byung-Kwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.593-601
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    • 2021
  • The axial fan is an element of a blower used for ventilation in various industrial fields. Many studies on aerodynamic performance have been conducted to assess axial fans using fluid dynamics. The subject was a large axial fan size, 1800 mm in diameter with 100 horsepower. The blower's axial fan consisted of blades, hubs, hub caps, and bosses are important components. The blade design has a great influence on the aerodynamic performance. 3D point data is extracted using an aerodynamic performance prediction program, and a 3D modeling shape is generated. The blades and hubs, which are important components, can be easily modified if processed by cutting owing to the environment in which blades and hubs are manufactured through die casting or gravity casting. In this study, the structural safety of components and the analysis results of weak areas at the rated operating speed of the axial fan were verified using the maximum stress and safety factor. The tip clearance reflected in the design was the rotation of the blade. To check whether there is interference with other components, the displacement result was derived to verify the structural safety of the axial fan.

Multi-fidelity Data-fusion for Improving Strain accuracy using Optical Fiber Sensors (이종 광섬유 센서 데이터 융합을 통한 변형률 정확도 향상 기법)

  • Park, Young-Soo;Jin, Seung-Seop;Yoo, Chul-Hwan;Kim, Sungtae;Park, Young-Hwan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.547-553
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    • 2020
  • As aging infrastructures increase along with time, the efficient maintenance becomes more significant and accurate responses from the sensors are pre-requisite. Among various responses, strain is commonly used to detect damage such as crack and fatigue. Optical fiber sensor is one of the promising sensing techniques to measure strains with high-durability, immunity for electrical noise, long transmission distance. Fiber Bragg Grating (FBG) is a point sensor to measure the strain based on reflected signals from the grating, while Brillouin Optic Correlation Domain Analysis (BOCDA) is a distributed sensor to measure the strain along with the optical fiber based on scattering signals. Although the FBG provides the signal with high accuracy and reproducibility, the number of sensing points is limited. On the other hand, the BOCDA can measure a quasi-continuous strain along with the optical fiber. However, the measured signals from BOCDA have low accuracy and reproducibility. This paper proposed a multi-fidelity data-fusion method based on Gaussian Process Regression to improve the fidelity of the strain distribution by fusing the advantages of both systems. The proposed method was evaluated by laboratory test. The result shows that the proposed method is promising to improve the fidelity of the strain.

A Study on Supporting Design Decision Making in Office Building Remodeling Projects by Introducing Mixed Reality (혼합현실 도입 오피스 건물 리모델링 프로젝트 설계 의사결정 지원)

  • Han, Mooyeul;Baek, Kwanyup;Lee, Kyung-Tae;Ko, Seonju;Kim, Ju-Hyung
    • Korean Journal of Construction Engineering and Management
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    • v.22 no.1
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    • pp.3-12
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    • 2021
  • In the remodeling projects, clients without architectural expertise have limitations in presenting requirements accurately. In some cases, designers and contractors may not recognize their demands exactly, and deliver final products that are different from the clients' intentions. 3D modeling visualizing final products in previous has been regarded as a solution to enhance understanding and communication. However, this approach has the limitation that the final results are presented as a virtual outputs. In the remodeling project, an alternative, mixed-reality, is likely to reinforce the reality as it enables to present remain structure and the parts to be built together. This paper examines the mixed reality as a solution to support decision making of clients and practitioners in remodeling projects. The examinations is conducted in high-rise office remodeling projects by means of action-research. Clients and practitioners, overview product models presented in the format of 2D drawings, BIM and mixed reality asked to evaluate the effectiveness of each methods in 12 standards. The results have shown that mixed reality has improved the sense of reality, making it easier to predict results, but recognizing patterns is difficult in some areas such as the floor, and it caused dizziness.