• 대한조선학회논문집
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• 제48권3호
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• pp.275-280
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• 2011

In the present study, a unified viscoplastic-damage model has been applied in order to describe the mechanical characteristics of fresh water ice such as nonlinear material behavior and volume fraction. The strain softening phenomenon of fresh water ice under quasi-static compressive loading has been evaluated based on unified viscoplastic model. The material degradation such as growth of slip/fraction has quite close relation with material inside damage. The volume fraction phenomenon of fresh water ice has been identified based on volume fraction (nucleation and growth of damage) model. The viscoplastic-damage model has been transformed to the fully implicit formulation and the discretized formulation has been implemented to ABAQUS user defined subroutine (User MATerial: UMAT) for the benefit of application of commercial finite element program. The proposed computational analysis method has been compared to uni-axial compression test of fresh water ice in order to validate the compatibilities, clarities and usefulness.

• Korea-Australia Rheology Journal
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• 제17권2호
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• pp.63-69
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• 2005

The stability of low-speed spinning process exhibiting spinline flow-induced crystallization (FIC) with no neck-like spinline deformation has been investigated using the method of linear stability analysis. Effects of various process conditions such as fluid viscoelasticity and the spinline cooling on the spinning stability have been found closely related to the development of the spinline crystallinity. It also has been found that the FIC makes the system less stable or more unstable than no FIC cases when the spinline crystallinity reaches its maximum possible value, whereas the FIC generally stabilizes the system if the crystallinity doesn't reach its maximum value on the spinline. It is believed that the destabilizing effect of the FIC on low-speed spinning when the crystallinity is fully developed on the spinline is due to the reduction of the real spinning length available for deformation on the spinline. On the other hand, the increased spinline tension caused by the FIC when the maximum crystallinity is not reached on the spinline and thus no reduction in the spinning length occurs, makes the sensitivity of spinline variables to external disturbances smaller and hence stabilizes the system. These linear stability results are consistent with the findings by nonlinear transient simulation, as first reported by Lee et al. (2005b).

• International Journal of Automotive Technology
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• 제5권1호
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• pp.33-46
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• 2004

A finite element model development of a 50th percentile male cervical spine is presented in this paper. The model consists of rigid, geometrically accurate vertebrae held together with deformable intervertibral disks, facet joints, and ligaments modeled as a series of nonlinear springs. These deformable structures were rigorously tuned, through failure, to mimic existing experimental data; first as functional unit characterizations at three cervical levels and then as a fully assembled c-spine using the experimental data from Duke University and other data in the NHTSA database. After obtaining satisfactory validation of the performance of the assembled ligamentous cervical spine against available experimental data, 22 cervical muscle pairs, representing the majority of the neck's musculature, were added to the model. Hill's muscle model was utilized to generate muscle forces within the assembled cervical model. The muscle activation level was assumed to be the same for all modeled muscles and the degree of activation was set to correctly predict available human volunteer experimental data from NBDL. The validated model is intended for use as a post processor of dummy measurement within the simulated injury monitor (SIMon) concept being developed by NHTSA where measured kinematics and kinetic data obtained from a dummy during a crash test will serve as the boundary conditions to "drive" the finite element model of the neck. The post-processor will then interrogate the model to determine whether any ligament have exceeded its known failure limit. The model will allow a direct assessment of potential injury, its degree and location thus eliminating the need for global correlates such as Nij.

• 한국해안해양공학회지
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• 제17권4호
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• pp.243-258
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• 2005

경도상 $1/12^{\circ}$, 위도상 $l/15^{\circ}$의 해상도를 갖는 최병호(1990)의 2차원 황해 및 동중국해의 조석모형을 근간으로 하여 한반도 주변해역의 정밀수심 DB(최병호 등, 2002)를 기초입력으로 하여 격자세분화 기법과 서로 다른 격자체계하에서의 다른 계간시간간격을 사용하는 해안 및 하구역 모형으로의 개선을 통하여 모형의 효율성, 사용성 및 모형영역내의 세격자 영역의 위치적 이식성을 향상시킨 둥지형 동적결합 조식모형체계를 수립하였다. 수립된 모형체계의 타당성과 적용성을 입증하기 위하여 새만금 해역을 세밀격자로서 해상시킨 수치모형 실험을 실시하였으며, 모형의 계산치와 관측치의 비교를 통하여 만족할 만한 결과를 얻을 수 있었다. 수립된 체계는 황해와 동중국해 대륙붕해영역내에서 위치적 이식성이 용이한 조석예보체계로서 발전될 수 있다.

• 전기학회논문지
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• 제59권2호
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• pp.436-444
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• 2010

In this study, we introduce and discuss a concept of a granular-oriented radial basis function neural networks (GRBF NNs). In contrast to the typical architectures encountered in radial basis function neural networks(RBF NNs), our main objective is to develop a design strategy of GRBF NNs as follows : (a) The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of K-Means clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space, (b) The innovative development facet of the network involves a dynamic reduction of dimensionality of the input space in which the information granules are formed in the subspace of the overall input space which is formed by selecting a suitable subset of input variables so that the this subspace retains the structure of the entire space. As this search is of combinatorial character, we use the technique of genetic optimization to determine the optimal input subspaces. A series of numeric studies exploiting some nonlinear process data and a dataset coming from the machine learning repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.

• 대한조선학회논문집
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• 제44권5호
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• pp.542-550
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• 2007

A geometry modification is one of main keys in achieving a successful optimization. The optimized hull form generated from the geometry modification should be a realistic, faired form from the ship manufacturing point of view. This paper presents a practical hull optimization procedure using a parametric modification function. In the parametric modification function method, the initial ship geometry was easily deformed according to the variations of design parameters. For example, bulbous bow can be modified with several parameters such as bulb area, bulb length, bulb height etc. Design parameters are considered as design variables to modify hull form, which can reduce the number of design variables in optimization process and hence reduce its time cost. To verify the use of the parametric modification function, optimization for KCS was performed at its design speed (FN=0.26) and the wave making resistance is calculated using a well proven potential code with fully nonlinear free surface conditions. The design variables used are key design parameters such as Cp curve, section shape and bulb shape. This study shows that the hull form optimized by the parametric modification function brings 7.6% reduction in wave making resistance. In addition, for verification and comparison purpose, a direct geometry variation method using a bell-shape modification function is used. It is shown that the optimal hull form generated by the bell-shaped modification function is very similar to that produced by the parametric modification function. However, the total running time of the parametric optimization is six times shorter than that of the bell shape modification method, showing the effectiveness and practicalness from a designer point of view in ship yards.

• 한국해안해양공학회지
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• 제6권3호
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• pp.245-259
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• 1994

연직 확산계수의 산정에 k-I 난류방정식을 도입하여 예측성을 향상시킨 치안 해수유동 및 온배수 확산에 관한 3차원 수치모형을 개발하였다. 모형은 1차원 수로에서 취송류의 연직분포, 정지수역으로의 온배수 젯트에 대하여 수리실험자료와의 비교검증을 실시하고 고리해역에서 조류 및 온배수 확산을 해석하여 현장 적용성을 검토하였다. 계산결과는 검증에 사용된 자료와 대체로 일치하는 양호한 결과를 보였으며, 취송류, 밀도류, 조류에 대하여 동일한 모형상수를 사용하여 연직 확산계수를 계산할 수 있어 난류모형의 상수가 보편성이 있음을 확인하였다. 따라서, 본 연구에서 $textsc{k}$-ι 난류방정식을 도입하여 개발된 수치모형은 연안 해수유동을 대표하는 취송류, 밀도류, 조류에 대하여 난류상수의 보편성과 모형의 예측성을 갖고 있어 연안 해수유동 및 확산을 연구하는 데 효율적으로 활용될 수 있을 것으로 사료된다.

• 전기학회논문지
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• 제60권4호
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• pp.862-870
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• 2011

In this paper, we introduce a new topology of Radial Basis Function-based Polynomial Neural Networks (RPNN) that is based on a genetically optimized multi-layer perceptron with Radial Polynomial Neurons (RPNs). This study offers a comprehensive design methodology involving mechanisms of optimization algorithms, especially Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization (PSO) algorithms. In contrast to the typical architectures encountered in Polynomial Neural Networks (PNNs), our main objective is to develop a design strategy of RPNNs as follows : (a) The architecture of the proposed network consists of Radial Polynomial Neurons (RPNs). In here, the RPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Fuzzy C-Means (FCM) clustering method. The RPN dwells on the concepts of a collection of radial basis function and the function-based nonlinear (polynomial) processing. (b) The PSO-based design procedure being applied at each layer of RPNN leads to the selection of preferred nodes of the network (RPNs) whose local characteristics (such as the number of input variables, a collection of the specific subset of input variables, the order of the polynomial, and the number of clusters as well as a fuzzification coefficient in the FCM clustering) can be easily adjusted. The performance of the RPNN is quantified through the experimentation where we use a number of modeling benchmarks - NOx emission process data of gas turbine power plant and learning machine data(Automobile Miles Per Gallon Data) already experimented with in fuzzy or neurofuzzy modeling. A comparative analysis reveals that the proposed RPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3275-3285
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• 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.

• Ocean Systems Engineering
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• 제8권4호
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• pp.381-407
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• 2018

This paper presents a hybrid numerical approach, which combines a two-phase Navier-Stokes model (NS) and the fully nonlinear potential theory (FNPT), for modelling wave-structure interaction. The former governs the computational domain near the structure, where the viscous and turbulent effects are significant, and is solved by OpenFOAM/InterDyMFoam which utilising the finite volume method (FVM) with a Volume of Fluid (VOF) for the phase identification. The latter covers the rest of the domain, where the fluid may be considered as incompressible, inviscid and irrotational, and solved by using the Quasi Arbitrary Lagrangian-Eulerian finite element method (QALE-FEM). These two models are weakly coupled using a zonal (spatially hierarchical) approach. Considering the inconsistence of the solutions at the boundaries between two different sub-domains governed by two fundamentally different models, a relaxation (transitional) zone is introduced, where the velocity, pressure and surface elevations are taken as the weighted summation of the solutions by two models. In order to tackle the challenges associated and maximise the computational efficiency, further developments of the QALE-FEM have been made. These include the derivation of an arbitrary Lagrangian-Eulerian FNPT and application of a robust gradient calculation scheme for estimating the velocity. The present hybrid model is applied to the numerical simulation of a fixed horizontal cylinder subjected to a unidirectional wave with or without following current. The convergence property, the optimisation of the relaxation zone, the accuracy and the computational efficiency are discussed. Although the idea of the weakly coupling using the zonal approach is not new, the present hybrid model is the first one to couple the QALE-FEM with OpenFOAM solver and/or to be applied to numerical simulate the wave-structure interaction with presence of current.