• Journal of the Korean Society of Systems Engineering
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• v.13 no.1
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• pp.15-23
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• 2017

This paper describes verification of APR1400 reactor vessel by applying the system engineering approach, in which the design re-engineering method is used to check the design parameters of APR1400 RV (reactor vessel). The RV is classified as safety class 1 and therefore must adhere strictly to the rules of ASME BPVC section III, subsection NB and seismic category I. This study explores designing the RV by following the ASME guidelines and making a comparative study with the current design. To meet this objective we apply system engineering methodologies to structure the process and allow for verification and validation of the major RV design parameters such as thickness of RV. The structural thicknesses of various part of RV are determined as well as reinforcements on the RV major nozzles. A 3D virtual reality model was created based on the design parameters using CATIA V5 and animation using Dassault Composer V2016. A comparison of re-engineered ARP1400 RV and standard APR1400 RV was done to show which design parameters were taken more conservative approach.

• Journal of the Korean Institute of Gas
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• v.18 no.6
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• pp.14-20
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• 2014

In this study, the stress analysis for the piping support design is performed as per the rules of the ASME Code, Section III, subsection NF-Component Support which provides a simplified method of design analysis for piping support. This method makes use of simple equations and conservative allowable stress limits for design and service loadings. For the base plate, code equation is satisfied within the allowable limits. Both anchor bolts and pipe strap are governed by the their interaction equations. The stresses resulting from various loadings and their combinations are within the allowable limits specified in the above mentioned ASME Code. Thus, it was proved that the structural integrity of the pump assembly was satisfactory.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.101-107
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• 2008

We introduce an optimization of fuzzy set-fuzzy systems based on IG (Information Granules). The proposed fuzzy model implements system structure and parameter identification by means of IG and GAs. The concept of information granulation was coped with to enhance the abilities of structural optimization of the fuzzy model. Granulation of information realized with C-Means clustering helps determine the initial parameters of the fuzzy model such as the initial apexes of the membership functions in the premise part and the initial values of polynomial functions in the consequence part of the fuzzy rules. The initial parameters are adjusted effectively with the help of the GAs and the standard least square method. To optimally identify the structure and the parameters of the fuzzy model we exploit GAs with successive tuning method to simultaneously search the structure and the parameters within one individual. We also consider the variant generation-based evolution to adjust the rate of identification of the structure and the parameters in successive tuning method. The proposed model is evaluated with the performance of the conventional fuzzy model.

• Computers and Concrete
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• v.9 no.5
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• pp.327-340
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• 2012

The search for a design that meets both performance and safety, with minimal cost and lesser environmental impact was always the goal of structural engineers. In general, the design of conventional reinforced concrete structures is an iterative process based on rules of thumb established from the personal experience and intuition of the designer. However, such procedure makes the design process exhaustive and only occasionally leads to the best solution. In such context, this work presents the development and implementation of a mathematical formulation for obtaining optimal sections of reinforced concrete columns subjected to uniaxial flexural compression, based on the verification of strength proposed by the Brazilian standard NBR 6118 (ABNT 2007). To minimize the cost of the reinforced concrete columns, the Simulated Annealing optimization method was used, in which the amount and diameters of the reinforcement bars and the dimensions of the columns cross sections were considered as discrete variables. The results obtained were compared to those obtained from the conventional design procedure and other optimization methods, in an attempt to verify the influence of resistance class, variations in the magnitudes of bending moment and axial force, and material costs on the optimal design of reinforced concrete columns subjected to uniaxial flexural compression.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.12-14
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• 2005

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks(SOFPNN) by means of genetically optimized fuzzy polynomial neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms(GAs). The conventional SOFPNNs hinges on an extended Group Method of Data Handling(GMDH) and exploits a fixed fuzzy inference type in each FPN of the SOFPNN as well as considers a fixed number of input nodes located in each layer. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, a collection of the specific subset of input variables, and the number of membership function) and addresses specific aspects of parametric optimization. Therefore, the proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series).

• Special Issue of the Society of Naval Architects of Korea
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• 2017.10a
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• pp.93-104
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• 2017

IMO type C independent tank is one of the cargo containment system specified on IGC code. It is normally adopted for small and medium size liquefied gas carrier's cargo containment system and it can be applied to fuel tank of LNG fueled vessel. This study focuses on rule scantling process and evaluation methods in early design stage of type C independent tank. Actual design results of 22K LPG/Ammonia/VCM carrier's No.2 cargo tank are demonstrated. This paper presents the calculation methods of design acceleration and liquid height for internal design pressure as defined on IGC code. And this paper shows the applied results of classification rules about shell thickness requirement and buckling strength. Additionally this paper deals with evaluation methods of structural strength and cumulative fatigue damage using FE analysis.

• Journal of Welding and Joining
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• v.24 no.2
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• pp.48-56
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• 2006

The fatigue strength of the welds is affected by such factors as the weld geometry, microstructures, tensile properties and residual stresses caused by fabrication. It is very important to evaluate the structural integrity of the welds in nuclear power plant because the weldment undergoes the most of damage and failure mechanisms. In this study, the fatigue assessments for a reactor vessel outlet nozzle with the weldment to the piping system are performed considering the welding residual stresses as well as the effect of local brittle zone in the vicinity of the weld fusion line. The analytical approaches employed are the microstructure and mechanical properties prediction by semi-analytical method, the thermal and stress analysis including the welding residual stress analysis by finite element method, the fatigue life assessment by following the ASME Code rules. The calculated results of cumulative usage factors(CUF) are compared for cases of the elastic and elasto-plastic analysis, and with or without residual stress and local brittle zone effects, respectively. Finally, the fatigue life of reactor vessel outlet nozzle weld is slightly affected by the local brittle zone and welding residual stresses.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1439-1461
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• 2015

Design criteria, modeling rules, and analysis principles of seismic isolation systems have already found place in important building codes and standards such as the Uniform Building Code and ASCE/SEI 7-05. Although real behaviors of isolation systems composed of high damping or lead rubber bearings are nonlinear, equivalent linear models can be obtained using effective stiffness and damping which makes use of linear seismic analysis methods for seismic-isolated buildings possible. However, equivalent linear modeling and analysis may lead to errors in seismic response terms of multi-story buildings and thus need to be assessed comprehensively. This study investigates the accuracy of equivalent linear modeling via numerical experiments conducted on generic five-story three dimensional seismic-isolated buildings. A wide range of nonlinear isolation systems with different characteristics and their equivalent linear counterparts are subjected to historical earthquakes and isolation system displacements, top floor accelerations, story drifts, base shears, and torsional base moments are compared. Relations between the accuracy of the estimates of peak structural responses from equivalent linear models and typical characteristics of nonlinear isolation systems including effective period, rigid-body mode period, effective viscous damping ratio, and post-yield to pre-yield stiffness ratio are established. Influence of biaxial interaction and plan eccentricity are also examined.

• Genomics & Informatics
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• v.1 no.2
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• pp.65-74
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• 2003

Data mining differs primarily from traditional data analysis on an important dimension, namely the scale of the data. That is the reason why not only statistical but also computer science principles are needed to extract information from large data sets. In this paper we briefly review data mining, its characteristics, typical data mining algorithms, and potential and ongoing applications of data mining at biopharmaceutical industries. The distinguishing characteristics of data mining lie in its understandability, scalability, its problem driven nature, and its analysis of retrospective or observational data in contrast to experimentally designed data. At a high level one can identify three types of problems for which data mining is useful: description, prediction and search. Brief review of data mining algorithms include decision trees and rules, nonlinear classification methods, memory-based methods, model-based clustering, and graphical dependency models. Application areas covered are discovery compound libraries, clinical trial and disease management data, genomics and proteomics, structural databases for candidate drug compounds, and other applications of pharmaceutical relevance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1337-1346
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• 2015

In this paper, pattern classifier is designed to classify precipitation and non-precipitation events from weather radar data. The proposed classifier is based on Fuzzy Neural Network(FNN) and consists of three FNNs which operate in parallel. In the proposed network, the connection weights of the consequent part of fuzzy rules are expressed as two polynomial types such as constant or linear polynomial function, and their coefficients are learned by using Least Square Estimation(LSE). In addition, parametric as well as structural factors of the proposed classifier are optimized through Differential Evolution(DE) algorithm. After event classification between precipitation and non-precipitation echo, non-precipitation event is to get rid of all echo, while precipitation event including non-precipitation echo is to get rid of non-precipitation echo by classifier that is also based on Fuzzy Neural Network. Weather radar data obtained from meteorological office is to analysis and discuss performance of the proposed event and echo patter classifier, result of echo pattern classifier compare to QC(Quality Control) data obtained from meteorological office.