• Advances in aircraft and spacecraft science
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• 제6권6호
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• pp.515-528
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• 2019

The structural vibrations of a flat plate induced by fluctuating wall pressures within wall-bounded transonic jet flow downstream of a high-aspect ratio rectangular nozzle are simulated. The wall pressures are calculated using Hybrid RANS/LES CFD, where LES models the large-scale turbulence in the shear layers downstream of the nozzle. The structural vibrations are computed using modes from a finite element model and a time-domain forced response calculation methodology. At low flow speeds, the convecting turbulence in the shear layers loads the plate in a manner similar to that of turbulent boundary layer flow. However, at high nozzle pressure ratio discharge conditions the flow over the panel becomes transonic, and the shear layer turbulence scatters from shock cells just downstream of the nozzle, generating backward traveling low frequency surface pressure loads that also drive the plate. The structural mode shapes and subsonic and transonic surface pressure fields are transformed to wavenumber space to better understand the nature of the loading distributions and individual modal responses. Modes with wavenumber distributions which align well with those of the pressure field respond strongly. Negative wavenumber loading components are clearly visible in the transforms of the supersonic flow wall pressures near the nozzle, indicating backward propagating pressure fields. In those cases the modal joint acceptances include significant contributions from negative wavenumber terms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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• pp.1951-1972
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• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2005년도 추계 학술대회 논문집
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• pp.134-142
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• 2005

지하매질에서 핵종이동현상을 가시적으로 관찰할 수 있는 실험실규모 실험장치를 개발하여 이동실험을 수행하였다. 이 실험장치는 $50{\times}50cm$ 규모 화강암과 아크릴상층부로 구성되어있다. 실험에는 삼중수소, 음이온, 수착성양이온 뿐만 아니라 이동경로를 관찰할 수 있는 유기염료도 포함하였다. 시간에 따른 물질이동양태를 사진을 찍어 컴퓨터에 저장하였다. 또. 이동과정을 모사하고 단위공정별로 분석해 볼 수 잇는 이동모델도 개발하였다. 컴퓨터모사를 통해 균열내 흐름장에서 압력과 유속분포를 계산하고, 균열내 이동양태와 유출곡선을 계산해 실험결과와 비교 평가하였다.

• 한국수소및신에너지학회논문집
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• 제33권1호
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• pp.47-54
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• 2022

In this study, we performed numerical analysis for 1 kWe SOFC stack of internal manifold types according to the different manifold sizes to verify the influence of the flow uniformity into each cell. To simulate the flow phenomena in the stack, the continuity and momentum conservation equations including the standard k-𝜺 turbulent model for the steady-state conditions were applied. From the calculation results, we verified that the pressure drop from inlet pipes to outlet pipes decreased to a log scale as the manifold size increased in the internal manifold types. Also, we found that the flow uniformity increased on an exponential scale as the manifold size increased. In addition, the calculation results showed that the flow uniformity gradually improved as the fuel and oxygen utilization increased.

• 우울조울병
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• 제9권2호
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• pp.78-86
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• 2011

Objectives : The aim of this study was to investigate relationship between perceived stress level, cognitive emotion regulation (CER) strategy and hope in group with high depressive symptom and higher-level perceived stress (H-H) and group with high depressive symptom and lower-level perceived stress (H-L) in patients with depression. Method : A total of 85 patients (over score of 16 by Beck depression Inventory; BDI) were surveyed with Cognitive emotion regulation questionnaire (CERQ), Perceived stress scale (PSS), and The state hope scale (SHS). Mean scores of CERQ and SHS were compared between relatively higher perceived stress and lower perceived stress groups. Correlation analysis and multiple linear regression analyses were performed to identify the effect of BDI, PSS and CER strategy on SHS in two groups. Results : In ANOVA, the level of hope and maladaptive CERQ score proved to be significantly lower among the H-H group than among the H-L group, while adaptive CERQ scores were not. In Regression analysis, the effective CER strategy in SHS were 'Refocus on planning' in H-H group, while it was 'Acceptance' CER strategy in H-L group. The final regression model explained 36% of the variance of SHS in H-H group and explained 21% of SHS in H-L group. Conclusion : These findings suggest that 'Refocus on planning' and 'Acceptance' cognitive emotion strategy are helpful in promotion of state hope on depression. Especially, 'Refocus on planning' strategy is more effective in high depressive symptom and high-perceived stress level, while 'Acceptance' strategy help to promote hope in high depressive symptom and low-perceived stress level in patients with depression.

• 대한조선학회논문집
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• 제60권4호
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• pp.222-230
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• 2023

In the present work, the scale effect on the Boil-Off Rate (BOR) was investigated based on an analytical method to systematically evaluate the thermal performance of a Liquefied Natural Gas (LNG) Cargo Containment System (CCS). A two-dimensional thermal resistance network model was developed to accurately estimate the heat ingress into the CCS from the outside. The analysis was performed for the KC-1 LNG membrane tank under the IGC and USCG design conditions. The ballast compartment of both the LNG tank and cofferdam was divided into six sections and a thermal resistance network model was made for each section. To check the validity of the developed model, the analysis results were compared with those from existing literature. It was shown that the BOR values under the IGC and USCG design conditions were agreed well with previous numerical results with a maximum error of 1.03% and 0.60%, respectively. A SDR, the scale factor of the LNG CCS was introduced and the BOR, air temperature of the ballast compartment, and the surface temperature of the inner hull were obtained to examine the influence of the SDR on the thermal performance. Finally, a correlation for the BOR was proposed, which could be expressed as a simple formula inversely proportional to the SDR. The proposed correlation could be utilized for predicting the BOR of a full-scale LNG tank based on the BOR measurement data of lab-scale model tanks.

• 대기
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• 제16권3호
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• pp.215-223
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• 2006

Among observational, local-environmental, and large-scale factors causing significant changes in climate records, the site relocations and the replacement of the instruments are well-known nonclimatic factors for the analysis of climatic trends, climatic variability, and for the detection of anthropogenic climate change such as heat-island effect and global warming. Using dataset that were contaminated by these nonclimatic factors can affect seriously the assessment of climatic trends and variability, and the detection of the climatic change signal. In this paper, the inhomogeneities, which have been caused by relocation of the observation site, in the climate data of Korea Meteorological Administration (KMA) were examined using two-phase regression model. The observations of pan evaporation and wind speed are more sensitive to site relocations than those of other meteorological elements, such as daily mean, maximum and minimum temperatures, with regardless to region.

• Journal of Information Processing Systems
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• 제19권6호
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• Wind and Structures
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• 제35권1호
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• pp.21-34
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• 2022

Gust factor is an important parameter for the conversion between peak gust wind and mean wind speed used for the structural design and wind-related hazard mitigation. The gust factor of typhoon wind is observed to show a significant dispersion and some differences with large-scale weather systems, e.g., monsoons and extratropical cyclones. In this study, insitu measurement data captured by 13 meteorological towers during a strong typhoon Morakot are collected to investigate the statistical characteristics, height and wind speed dependency of the gust factor. Onshore off-sea and off-land winds are comparatively studied, respectively to characterize the underlying terrain effects on the gust factor. The theoretical method of peak factor based on Gaussian assumption is then introduced to compare the gust factor profiles observed in this study and given in some building codes and standards. The results show that the probability distributions of gust factor for both off-sea winds and off-land winds can be well described using the generalized extreme value (GEV) distribution model. Compared with the off-land winds, the off-sea gust factors are relatively smaller, and the probability distribution is more leptokurtic with longer tails. With the increase of height, especially for off-sea winds, the probability distributions of gust factor are more peaked and right-tailed. The scatters of gust factor decrease with the mean wind speed and height. AS/NZ's suggestions are nearly parallel with the measured gust factor profiles below 80m, while the fitting curve of off-sea data below 120m is more similar to AIJ, ASCE and EU.

• Smart Structures and Systems
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• 제31권3호
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.