• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.131-140
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• 2004

The main objective of the research is to develop an algorithm for the optimum design of two dimensional steel frames using refined plastic hinge analysis which considers material and geometrical nonlinearities. Using developed algorithm, an optimum design was perform without calculating an effective length factor of the column (K-factor). A multi-level discrete optimization technique with two parameters has been developed and employed in the optimum design algorithm. The optimization algorithm is applied to structural design with the objective of minimizing the weight of a structure and with constraints on load limit, frame drift, ductility. Various application example is provided to demonstrate the feasibility, validity and efficiency of the developed program.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.327-332
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• 2005

We investigatea new fuzzy-neural networks-Hybrid Fuzzy set based polynomial Neural Networks (HFSPNN). These networks consist of genetically optimized multi-layer with two kinds of heterogeneous neurons thatare fuzzy set based polynomial neurons (FSPNs) and polynomial neurons (PNs). We have developed a comprehensive design methodology to determine the optimal structure of networks dynamically. The augmented genetically optimized HFSPNN (namely gHFSPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of gHFSPNN leads to the selection leads to the selection of preferred nodes (FSPNs or PNs) available within the HFSPNN. In the sequel, the structural optimization is realized via GAs, whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFSPNN is quantified through experimentation where we use a number of modeling benchmarks synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.352-359
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• 2010

In recent years, the market has shown increasing interest in pump-turbines. The prompt availability of pumped storage plants and the benefits to the power system achieved by peak lopping, providing reserve capacity, and rapid response in frequency control are providing a growing advantage. In this context, there is a need to develop pumpturbines that can reliably withstand dynamic operation modes, fast changes of discharge rate by adjusting the variable diffuser vanes, as well as fast changes from pumping to turbine operation. In the first part of the present study, various flow patterns linked to operation of a pump-turbine system are discussed. In this context, pump and turbine modes are presented separately and different load cases are shown in each operating mode. In order to create modern, competitive pump-turbine designs, this study further explains what design challenges should be considered in defining the geometry of a pump-turbine impeller. The second part of the paper describes an innovative, staggered approach to impeller development, applied to a low head pump-turbine project. The first level of the process consists of optimization strategies based on evolutionary algorithms together with 3D in-viscid flow analysis. In the next stage, the hydraulic behavior of both pump mode and turbine mode is evaluated by solving the full 3D Navier-Stokes equations in combination with a robust turbulence model. Finally, the progress in hydraulic design is demonstrated by model test results that show a significant improvement in hydraulic performance compared to an existing reference design.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.420-428
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• 2016

In this paper, we investigate the scheduling and power allocation for coordinated multi-point transmission in downlink long term evolution advanced (LTE-A) systems, where orthogonal frequency division multiple-access is used. The proposed scheme jointly optimizes user selection, power allocation, and modulation and coding scheme (MCS) selection to maximize the weighted sum throughput with fairness consideration. Considering practical constraints in LTE-A systems, the MCSs for the resource blocks assigned to the same user need to be the same. Since the optimization problem is a combinatorial and non-convex one with high complexity, a low-complexity algorithm is proposed by separating the user selection and power allocation into two subproblems. To further simplify the optimization problem for power allocation, the instantaneous signal-to-interference-plus-noise ratio (SINR) and the average SINR are adopted to allocate power in a single cell and multiple coordinated cells, respectively. Simulation results show that the proposed scheme can improve the average system throughput and the cell-edge user throughput significantly compared with the existing schemes with limited feedback.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.494-496
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• 2013

Cost-Benefit Analysis (CBA) is a systematic optimization process that allows users to compare different alternatives and to determine if a project is a solid investment. Many state DOTs have included CBA in their pavement management systems (PMSs) to help allocate state funds for maintenance, rehabilitation, resurfacing, and reconstruction of pavements. In a typical CBA, each pavement type has an assigned weight factor which represents the level of importance of this pavement type. To conduct an accurate CBA, it is essential to select appropriate weight factors. Arbitrarily assigning weights factors to pavements can lead to biased and inaccurate funding allocation decisions. The purpose for this paper is to outline a method to develop an ideal set of weight factors that can be utilized to conduct more accurate CBA. To this end, a matrix of all possible weight factors sets was developed. CBA was conducted for each set of weight factors to obtain a population of possible optimization solutions. Then a regression analysis was performed to establish the relationship between benefit and weight factors. Finally, a multi-objective genetic algorithm was applied to select the optimal set of weight factors. The findings from this study can be used by state DOTs to strategically manage their roadway systems in a cost effective manner.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.1035-1038
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• 2008

Network mobility (NEMO) has been studied extensively due to its potential applications in military and public transportation. NEMO Basic Support Protocol (NBSP) [1], the current NEMO standard based on mobile IPv6, can be readily deployed using the existing mobile IPv6 infrastructure. However, for Nested network mobility, multi-level tunnel and too many Binding Update packets results in substantial performance overhead, generally known as route sub-optimality, especially in the bottleneck root mobile router (root-MR) and Access Router. In this paper, we propose a route optimization mechanism for nested network mobility management to reduce the overhead of root-MR. In this system, Mobile Router (MR) has a cache that stores Mobile Network Nodes' (MNN) information, Correspondent Nodes' (CN) information for every MNN，and the attachments information with its subnet MRs. Home Agent performs Binding Update with CNs responsible for MRs. Through this mechanism, the number of tunnel is limited between CN and MR and the overhead of root-MR is reduced obviously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.

• Structural Engineering and Mechanics
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• v.33 no.4
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• pp.429-446
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• 2009

Three-scale homogenization procedure is proposed in this paper to provide estimates of the effective thermal conductivities of porous carbon-carbon textile composites. On each scale - the level of fiber tow (micro-scale), the level of yarns (meso-scale) and the level of laminate (macro-scale) - a two step homogenization procedure based on the Mori-Tanaka averaging scheme is adopted. This involves evaluation of the effective properties first in the absence of pores. In the next step, an ellipsoidal pore is introduced into a new, generally orthotropic, matrix to make provision for the presence of crimp voids and transverse and delamination cracks resulting from the thermal transformation of a polymeric precursor into the carbon matrix. Other sources of imperfections also attributed to the manufacturing processes, including non-uniform texture of the reinforcements, are taken into consideration through the histograms of inclination angles measured along the fiber tow path together with a particular shape of the equivalent ellipsoidal inclusion proposed already in Sko ek (1998). The analysis shows that a reasonable agreement of the numerical predictions with experimental measurements can be achieved.

• Corrosion Science and Technology
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• v.14 no.3
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• pp.113-119
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• 2015

Alloy 82/182 weld metals had been extensively used in joining the components of the PWR primary system. Unfortunately, there have been a number of incidents of cracking caused by PWSCC in Alloy 82/182 welds during the operation of PWR worldwide. To mitigate PWSCC, optimization of water-chemistry conditions, especially dissolved hydrogen (DH) and Zn contents, is considered as the most promising and effective remedial method. In this study, the PWSCC behaviours of Alloy 182 weld were investigated in simulated PWR environments with various DH content. Both in-situ and ex-situ oxide characterizations as well as PWSCC initiation tests were performed. The results showed that PWSCC crack initiation time was shortest in PWR water (DH: 30cc/kg). Also, high stress reduced crack initiation time. Oxide layer showed multi-layered structures consisted of the outer needle-like Ni-rich oxide layer, Fe-rich crystalline oxide, and inner Cr-rich inner oxide layers, which was not altered by the level of applied stress. To analyse the multi-layer structure of oxides, EIS measurement were fitted into an equivalent circuit model. Further analyses including TEM and EDS are underway to verify appropriateness of the equivalent circuit model.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.669-676
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• 2008

The adaptive resource optimization problem in multi-input multi-output orthogonal frequency division multiple access (MIMO-OFDMA) systems is addressed. This paper, adaptive modulation and coding(AMC) and power control algorithms is proposed with SFC(Space-Frequency Coding), which aims to maximize the system capacity based on the CQI(Channel Quality Information). Firstly, power level is decided to each sub-channels with received feedback signal to noise ratio(SNR). In the second step, sub-carriers are allocated according to modulation type. Simulation results show that the proposed algorithm achieves a better performance than conventional algorithm in terms of capacity.