• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2007년도 제29회 추계학술대회논문집
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• pp.27-30
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• 2007

In recent years, scientific community has found renewed interest in hypersonic flight research. These hypersonic vehicles undergo severe aero-thermal environments during their flight regimes. One of the most important topics of research in hypersonic aerodynamics is to find a reasonable way of calculating either the surface temperature or the heat flux to surface when its temperature is held fixed. This requires modeling of physical and chemical processes. Hyperbolic system of equations with stiff relaxation method are being identified in recent literature as a novel method of predicting long time behavior of systems such as gas at high temperatures. In present work, Energy Relaxation Method (ERM) has been considered to simulate the real gas flow over a 2-D cylinder. Present heat flux results over the cylinder compared well with the experiment. Thus, real gas effects in hypersonic flows can be modeled through energy relaxation method.

• Korean Chemical Engineering Research
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• 제59권2호
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• pp.209-218
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• 2021

ORV의 열교환 효율 향상 및 운전 최적화를 위한, first principle 기반 모델링 연구들이 수행되어왔지만, ORV의 열 전달 계수는 시간, 위치에 따라 불규칙한 시스템으로, 복잡한 모델링 과정을 거친다. 본 연구는 복잡한 시스템에 대한 데이터 기반 모델링의 실효성을 확인하고자, LNG 재기화 공정의 실제 운전데이터를 이용해, ORV의 해수 유량, 해수온도, LNG 유량 변화에 따른 토출 NG 온도 및 토출 해수 온도의 동적 변화 예측이 가능한, FNN, LSTM 및 AutoML 기반 모델링을 진행하였다. 예측 정확도는 MSE 기준 LSTM > AutoML > FNN 순으로 좋은 성능을 보였다. 기계학습 모델의 자동설계 방법인 AutoML의 성능은 개발된 FNN보다 뛰어났으며, 모델 개발 전체소요시간은 복잡한 모델인 LSTM 대비 1/15로 크게 차이를 보여 AutoML의 활용 가능성을 보였다. LSTM과 AutoML을 이용한 토출 NG 및 토출 해수 온도의 예측은 0.5 K 미만의 오차를 보였다. 예측모델을 활용해, 겨울철 ORV를 이용해 처리 가능한 LNG 기화량의 실시간 최적화를 수행하여, 기존 대비 최대 23.5%의 LNG를 추가 처리 가능함을 확인하였고, 개발된 동적 예측모델 기반의 ORV 최적 운전 가이드라인을 제시하였다.

• 정보과학회 논문지
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• 제44권10호
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• pp.1026-1033
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• 2017

본 논문은 계층적 디리슐레 과정(HDP)과 은닉 마르코프 모형(HMM)이 결합된 베이스 통계학적 방법과 HMM의 상태 지속 정보를 이용한 건강 상태 예측 방법을 제안한다. HDP-HMM은 베이스 방법의 HMM 확장 모형으로서 건강의 동적 특성을 고려하여 불확실하고 가늠하기조차도 어려운 건강 상태의 수를 추정할 수 있게 해준다. 모의 데이터와 실제 건건 검진 데이터를 이용한 시험을 통하여 흥미 있는 행동 특성을 볼 수 있었으며 최대 5년까지로 제한한 미래 예측도 충분한 가능함을 확인하였다. 미래는 불확실하며 예측 문제는 본질적으로 어렵다. 그러나 본 연구의 실험 결과로 동적인 문맥 하에서 다중 후보 가설을 제시함으로서 실용 가능한 건강상태의 장기 예측이 가능하다는 것을 읽을 수 있었다.

• 대한인간공학회지
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• 제31권6호
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• pp.705-713
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• 2012

Objective: The aim of this study is to predict human visual target search using ACT-R cognitive architecture in real scene images. Background: Human uses both the method of bottom-up and top-down process at the same time using characteristics of image itself and knowledge about images. Modeling of human visual search also needs to include both processes. Method: In this study, visual target object search performance in real scene images was analyzed comparing experimental data and result of ACT-R model. 10 students participated in this experiment and the model was simulated ten times. This experiment was conducted in two conditions, indoor images and outdoor images. The ACT-R model considering the first saccade region through calculating the saliency map and spatial layout was established. Proposed model in this study used the guide of visual search and adopted visual search strategies according to the guide. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed ACT-R model is able to predict the human visual search process in real scene images using salience map and spatial layout. Application: This study is useful in conducting model-based evaluation in visual search, particularly in real images. Also, this study is able to adopt in diverse image processing program such as helper of the visually impaired.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1571-1584
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• 2023

In this study, a numerical analysis was performed as part of an international joint research project to reproduce a real cable tray fire that occurred in the heater bay area of the turbine building of a nuclear power plant. A sensitivity analysis was performed on various input parameters to derive results consistent with the sprinkler activation time obtained from the fire event analysis. For all sensitive parameters, the normalized sprinkler activation time correlated well with the power function of the normalized sprinkler height. A correlation equation was developed to identify the sprinkler activation time at any location when determining the slope or fire growth rate under the conditions assuming a linear or t-squared heat release rate (HRR) time curve. Various cable fire growth assumptions were used to determine which assumption was better to provide the prediction coincident with the information given from the fire event analysis in terms of the sprinkler activation time and total energy generated from cables damaged by fire. In the comprehensive analysis of all the sensitive parameters, the standard deviation of the input parameters increased as the sprinkler height decreased. Within the range of the sensitivity parameter values given in this study, when considering all sprinkler heights, the standard deviation of the cable model change was the largest and that of the overhang position change was the smallest.

• 한국환경과학회지
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• 제25권7호
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• pp.1029-1042
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• 2016

The initial and boundary conditions are important factors in regional chemical transport modeling systems. The method of generating the chemical boundary conditions for regional air quality models tends to be different from the dynamically varying boundary conditions in global chemical transport models. In this study, the impact of real time Copernicus atmosphere monitoring service (CAMS) re-analysis data from the modeling atmospheric composition and climate project interim implementation (MACC) on the regional air quality in the Korean Peninsula was carried out using the community multi-scale air quality modeling system (CMAQ). A comparison between conventional global data and CAMS for numerical assessments was also conducted. Although the horizontal resolution of the CAMS re-analysis data is not higher than the conventionally provided data, the simulated particulate matter (PM) concentrations with boundary conditions for CAMS re-analysis is more reasonable than any other data, and the estimation accuracy over the entire Korean peninsula, including the Seoul and Daegu metropolitan areas, was improved. Although an inland area such as the Daegu metropolitan area often has large uncertainty in PM prediction, the level of improvement in the prediction for the Daegu metropolitan area is higher than in the coastal area of the western part of the Korean peninsula.

• International Journal of Computer Science & Network Security
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• 제24권7호
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• pp.24-30
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• 2024

This paper investigates the identification and modeling of a climate greenhouse. Given real climate data from greenhouse installed in the LAPER laboratory in Tunisia, the objective of this paper is to propose a solution of the problem of nonlinear time variant inputs and outputs of greenhouse internal climate. Based on fuzzy logic technique combined with least mean squares (lms) a robust greenhouse climate model for internal temperature prediction is proposed. The simulation results are presented to demonstrate the effectiveness of the identification approach and the power of the implemented Takagi-Sugeno Fuzzy model based Algorithm.

• Coupled systems mechanics
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• 제4권1호
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• pp.37-65
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• 2015

Modeling and simulation of mechanical response of infrastructure object, solids and structures, relies on the use of computational models to foretell the state of a physical system under conditions for which such computational model has not been validated. Verification and Validation (V&V) procedures are the primary means of assessing accuracy, building confidence and credibility in modeling and computational simulations of behavior of those infrastructure objects. Validation is the process of determining a degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. It is mainly a physics issue and provides evidence that the correct model is solved (Oberkampf et al. 2002). Our primary interest is in modeling and simulating behavior of porous particulate media that is fully saturated with pore fluid, including cyclic mobility and liquefaction. Fully saturated soils undergoing dynamic shaking fall in this category. Verification modeling and simulation of fully saturated porous soils is addressed in more detail by (Tasiopoulou et al. 2014), and in this paper we address validation. A set of centrifuge experiments is used for this purpose. Discussion is provided assessing the effects of scaling laws on centrifuge experiments and their influence on the validation. Available validation test are reviewed in view of first and second order phenomena and their importance to validation. For example, dynamics behavior of the system, following the dynamic time, and dissipation of the pore fluid pressures, following diffusion time, are not happening in the same time scale and those discrepancies are discussed. Laboratory tests, performed on soil that is used in centrifuge experiments, were used to calibrate material models that are then used in a validation process. Number of physical and numerical examples are used for validation and to illustrate presented discussion. In particular, it is shown that for the most part, numerical prediction of behavior, using laboratory test data to calibrate soil material model, prior to centrifuge experiments, can be validated using scaled tests. There are, of course, discrepancies, sources of which are analyzed and discussed.

• 응용통계연구
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• 제23권2호
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• pp.249-261
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• 2010

Long-term forecasting of seasonal time series is critical in many applications such as planning business strategies and resolving possible problems of a business company. Unlike the traditional approach that depends solely on dynamic models, Li and Hinich (2002) introduced a combination of stochastic dynamic modeling with filter bank approach for forecasting seasonal patterns using highly coherent(High-C) waveforms. We modify the filter selection and forecasting procedure on wavelet domain to be more feasible and compare the resulting predictor with one that obtained from the wavelet variance estimation method. An improvement over other seasonal pattern extraction and forecasting methods based on such as wavelet scalogram, Holt-Winters, and seasonal autoregressive integrated moving average(SARIMA) is shown in terms of the prediction error. The performance of the proposed method is illustrated by a simulation study and an application to the real stock price data.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.21-26
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• 2006

This paper focuses on modeling and predicting differential GPS corrections transmitted by marine radio-beacon systems using artificial neural networks. Various neural network structures with various training algorithms were examined, including Linear, Radial Biases, and Feedforward. Matlab Neural Network toolbox is used for this purpose. Data sets used in building the model are the transmitted pseudorange corrections and broadcast navigation message. Model design is passed through several stages, namely data collection, preprocessing, model building, and finally model validation. It is found that feedforward neural network with automated regularization is the most suitable for our data. In training the neural network, different approaches are used to take advantage of the pseudorange corrections history while taking into account the required time for prediction and storage limitations. Three data structures are considered in training the neural network, namely all round, compound, and average. Of the various data structures examined, it is found that the average data structure is the most suitable. It is shown that the developed model is capable of predicting the differential correction with an accuracy level comparable to that of beacon-transmitted real-time DGPS correction.