• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.6 no.3
• /
• pp.245-259
• /
• 1994

This paper is concerned with the development of a three-dimensional numerical model for coastal circulation and heat transport with improved prediction ability. The model uses fully nonlinear, time-dependent three-dimensional, $\sigma$-transformed equations of motion and equation of heat transport The model was verified with experimental data for wind-driven current in a one-dimensional channel and thermal jets flowing into stagnant waters and applied for unsteady flow induced by tide and thermal jets in coastal waters around Kori nuclear power plant. The model results were in good agreements with experimental data sets for wind-driven current and thermal jet, and field observed data sets in coastal waters. This study has shown that the $\kappa$-$\varepsilon$ turbulence model is applicable to various coastal conditions without any modification of turbulence constants.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2012.05a
• /
• pp.116-116
• /
• 2012

하천유역 내의 인자를 이용하여 댐의 하천유량(stream flow)을 예측하는 일은 수문특성의 연구와 자연재해에 대한 대비 및 수공구조물과 방재시설의 설계 시 중요한 역할을 한다. 이러한 연구는 과거부터 활발히 이루어졌으며, 아직도 보다 높은 정확도의 결과를 얻기 위해 많은 연구들이 이루어지고 있다. 특히 기존의 유역 내 자료를 통해 비선형적 모델인 인공신경망(artificial neural network)을 이용한 하천유량을 예측하는 연구 역시 활발히 이루어지고 있다. 본 연구의 목적은 여러 유역인자들 중 하천유량에 가장 영향을 미치는 변수를 추출하고 보다 정확한 예측모델을 구축하는 것이다. 기존의 입력자료 선정기법중의 하나인 상호정보량(mutual information)과 수문기상자료의 비선형 동역학적 성분을 추출하는 웨이블렛 변환(wavelet transform)을 사용하여 인공신경망에 적용시켰다. 인공신경망을 적용하는 경우, 수문자료에 있어서 변수의 선택과 자료의 상태가 강우예측의 결과에 큰 영향을 미친다. 이러한 변수의 선택에 있어서 상호정보량을 바탕으로 한 인공신경망 입력변수 선택기법이 많이 사용되고 있다. 일반적으로 시계열자료는 경향성(trend), 주기성(periodicity) 및 추계학적 성분(stochastic component)의 선형조합으로 가정될 수 있으며, 특히 경향성과 주기성은 시계열 모형을 위해 제거되어야 할 결정론적 성분으로 취급한다. 즉. 수문 기상자료에 포함되어 있는 경향성과 주기성과 같은 비선형 동역학적 잡음(nonlinear dynamical noise)을 제거하고 입력자료의 카오스적 거동을 보이는 성분을 분리하기 위해 웨이블렛 변환을 사용하였다. 대상유역은 한강 유역에 포함되어 있는 충주댐으로 선택하였다. 유역 내 다양한 인자들과 하천유량사이의 상호정보량을 구해 영향력이 가장 큰 변수를 추출하고, 그 자료를 웨이블렛 변환을 적용하여 인공신경망의 입력자료로 사용하였다. 본 논문에서는 위와 같은 과정을 이용해 추정한 하천유량 결과와 기존의 방법인 상호정보량을 이용해 인공신경망을 적용한 결과를 실제자료와 비교하였다.

• Transactions of Materials Processing
• /
• v.23 no.5
• /
• pp.289-296
• /
• 2014

Uniaxial tensile tests were conducted to accurately evaluate the in-plane mechanical properties of fiber metal laminates (FMLs). The FMLs in the current study are comprised of a layer of self-reinforced polypropylene (SRPP) sandwiched between two layers of aluminum alloy 5052-H34. The nonlinear tensile behavior of the FMLs under in-plane loading conditions was investigated using both numerical simulations and a theoretical analysis. The numerical simulation was based on finite element modeling using the ABAQUS/Explicit code and the theoretical constitutive model was based on the volume fraction approach using the rule of mixture and a modification of the classical lamination theory, which incorporates the elastic-plastic behavior of the aluminum alloy and the SRPP. The simulations and the model are used to predict the inplane mechanical properties such as stress-strain response and deformation behavior of the FMLs. In addition, a post-stretching process is used to reduce the thermal residual stresses before uniaxial tensile testing of the FMLs. Through comparison of both the numerical simulations and the theoretical analysis with the experimental results, it is concluded that the numerical simulation model and the theoretical approach can describe with sufficient accuracy the actual tensile stress-strain behavior of the FMLs.

• Journal of health informatics and statistics
• /
• v.41 no.3
• /
• pp.318-323
• /
• 2016

Objectives: Except the known risk factors for stroke, few studies have identified novel metabolic markers that could effectively detect stroke at an early stage. In this study, we explored the dose-response relationship between serum metabolites and the incidence of stroke. Methods: We studied 213 adults in the Korean Cancer Prevention Study-II (KCPS-II) biobank and estimated dose-response relationship between serum metabolites and stroke (42 cases and 171 controls). Three serum metabolites (Acetylcholine, HexadecylAcetylGlycerol, and 1-acetyl-2-formyl-sn-glycero-3-phosphocholine) were used in this study. The analysis included (1) exploratory nonlinear analysis, (2) estimation of flexion points and slopes at below and above the points. In the model to estimate risk of incidence of stroke, we controlled for conventional risk factors such as age, sex, systolic blood pressure, type 2 diabetes, triglyceride, and smoking status. Results: The relationship between incidence of stroke and log-transformed 1-acetyl-2-formyl-sn-glycero-3-phosphocholine was non-linear with flexion point around intensity score of 8.8, whereas other metabolites, log-transformed Acetylcholine and HexadecylAcetylGlycerol, showed negative linear patterns. Conclusions: The study suggests that metabolic markers are associated with incidence of stroke, particularly, at or above the flexion point. The study result may contribute to developing a novel system for precise stroke prediction.

• Steel and Composite Structures
• /
• v.33 no.1
• /
• pp.67-79
• /
• 2019

Composite columns made of high strength materials have been used in high-rise construction owing to its excellent structural performance resulting in smaller cross-sectional sizes. However, due to the limited understanding of its structural response, current design codes do not allow the use of high strength materials beyond a certain strength limit. This paper reports additional test data, analytical and numerical studies leading to a new design method to predict the ultimate resistance of composite columns made of high strength steel and high strength concrete. Based on previous study on high strength concrete filled steel tubular members and ongoing work on high strength concrete encased steel columns, this paper provides new findings and presents the feasibility of using high strength steel and high strength concrete for general double symmetric composite columns. A nonlinear finite element model has been developed to capture the composite beam-column behavior. The Eurocode 4 approach of designing composite columns is examined by comparing the test data with results obtained from code's predictions and finite element analysis, from which the validities of the concrete confinement effect and plastic design method are discussed. Eurocode 4 method is found to overestimate the resistance of concrete encased composite columns when ultra-high strength steel is used. Finally, a strain compatibility method is proposed as a modification of existing Eurocode 4 method to give reasonable prediction of the ultimate strength of concrete encased beam-columns with steel strength up to 900 MPa and concrete strength up to 100 MPa.

• Nuclear Engineering and Technology
• /
• v.53 no.10
• /
• pp.3275-3285
• /
• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Journal of the Korea Society for Simulation
• /
• v.28 no.2
• /
• pp.131-137
• /
• 2019

The operation of the precision-guided missiles with seekers is becoming more and more dominant since the modern wars became geographically localized like anti-terror campaigns and civil wars. Imaging seekers are relatively low-price and applicable to various operational conditions. The image tracker, however, requires highly advanced method for the target tracking under harsh missile flight condition. Missile roll can reduce the tracking performance since it introduces big differences in imagery. The missile roll is inevitable because of the disturbance and flight control error. Consequently, the errors of the subsystems should be under control for the stable performance of the tracker and the whole system. But the performance prediction by some simple metric is almost impossible since the target signature and the tracker are highly nonlinear. We established M&S tool for a precision-guided missile with imaging seeker and analyzed the roll effects to tracking and system performance. Furthermore, we defined the specification of missile subsystems through error analysis to guarantee system performance.

• Journal of Convergence for Information Technology
• /
• v.9 no.8
• /
• pp.20-26
• /
• 2019

In this study, the optimal shape parameter condition is presented after analyzing the attributes of the software reliability model according to the change of the shape parameter of Loma life distribution with infinite fault NHPP. In order to analyze the software failure phenomena, the parametric estimation method was applied to the Maximum Likelihood Estimation method, and the nonlinear equation was applied to the bisection method. As a result, it was found that when the attributes according to the change of the shape parameter are compared, the smaller the shape parameter is, the better the prediction ability of the true value, and reliability attributes are efficient. Through this study, it is expected that software developers can increase reliability by preliminarily grasping the type of software failure based on shape parameter, and can be used as basic information to improve the software reliability attributes.

• Journal of the Society of Naval Architects of Korea
• /
• v.56 no.4
• /
• pp.343-351
• /
• 2019

Green water impact may sometimes cause some structure damages on ship's bow deck. Prediction of proper design pressure against the green water impact is an essential task to prevent the possible damages on bow deck. This paper presents a computational method of the bow deck's design pressure against the green water impact. Large heave and pitch motions of ship are calculated by the time domain nonlinear strip method. Green water flow and pressure on bow deck are simulated by the predictor-corrector second kind upstream finite difference method. This green water simulation method is based on the shallow water wave equations expanded for moving bottom conditions. For various kind of ships such as container ship, VLCC, oil tanker and bulk carrier, the green water design pressures on bow deck are computed and discussed. Also, the obtained results of design pressure on bow deck are compared with those of the classification society rules and discussed.

• Structural Engineering and Mechanics
• /
• v.70 no.1
• /
• pp.13-31
• /
• 2019

A nonlinear finite element model (FEM) using ATENA-3D software to simulate the axially compressive behavior of circular steel tube confined concrete (CSTCC) columns infilled with ultra high performance concrete (UHPC) was presented in this paper. Some modifications to the material type "CC3DNonlinCementitious2User" of UHPC without and with the incorporation of steel fibers (UHPFRC) in compression and tension were adopted in FEM. The predictions of utimate strength and axial load versus axial strain curves obtained from FEM were in a good agreement with the test results of eighteen tested columns. Based on the results of FEM, the load distribution on the steel tube and the concrete core was derived for each modeled column. Furthermore, the effect of bonding between the steel tube and the concrete core was clarified by the change of friction coefficient in the material type "CC3DInterface" in FEM. The numerical results revealed that the increase in the friction coefficient leads to a greater contribution from the steel tube, a decrease in the ultimate load and an increase in the magnitude of the loss of load capacity. By comparing the results of FEM with experimental results, the appropriate friction coefficient between the steel tube and the concrete core was defined as 0.3 to 0.6. In addition to the numerical evaluation, eighteen analytical models for confined concrete in the literature were used to predict the peak confined strength to assess their suitability. To cope with CSTCC stub and intermediate columns, the equations for estimating the lateral confining stress and the equations for considering the slenderness in the selected models were proposed. It was found that all selected models except for EC2 (2004) gave a very good prediction. Among them, the model of Bing et al. (2001) was the best predictor.