• Coupled systems mechanics
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• v.9 no.2
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• pp.163-182
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• 2020

Coupled thermo-mechanical analysis of reinforced concrete slab at elevated temperatures from a fire accounting for nonlinear thermal parameters is carried out. The main focus of the paper is put on a one-way continuous reinforced concrete slab exposed to fire from the single (bottom) side as the most typical working condition under fire loading. Although contemporary techniques alongside the fire protection measures are in constant development, in most cases it is not possible to avoid the material deterioration particularly nearby the exposed surface from a fire. Thereby the structural fire resistance of reinforced concrete slabs is mostly influenced by a relative distance between reinforcement and the exposed surface. A parametric study with variable concrete cover ranging from 15 mm to 35 mm is performed. As the first part of a one-way coupled thermo-mechanical analysis, transient nonlinear heat transfer analysis is performed by applying the net heat flux on the exposed surface. The solution of proposed heat analysis is obtained at certain time steps of interest by α-method using the explicit Euler time-integration scheme. Spatial discretization is done by the finite element method using a 1D 2-noded truss element with the temperature nodal values as unknowns. The obtained results in terms of temperature field inside the element are compared with available numerical and experimental results. A high level of agreement can be observed, implying the proposed model capable of describing the temperature field during a fire. Accompanying thermal analysis, mechanical analysis is performed in two ways. Firstly, using the guidelines given in Eurocode 2 - Part 1-2 resulting in the fire resistance rating for the aforementioned concrete cover values. The second way is a fully numerical coupled analysis carried out in general-purpose finite element software DIANA FEA. Both approaches indicate structural fire behavior similar to those observed in large-scale fire tests.

• Journal of Power Electronics
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• v.15 no.3
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• pp.741-752
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• 2015

This study proposes a new solution for the parallel operation of microgrid inverters in terms of circuit topology and control structure. A combined three-phase four-wire inverter composed of three single-phase full-bridge circuits is adopted. Moreover, the control structure is based on adaptive three-order sliding-mode control and wireless load-sharing control. The significant contributions are as follows. 1) Adaptive sliding-mode control performance in inner voltage loop can effectively reject both voltage and load disturbances. 2) Virtual resistive-output-impedance loop is applied in intermediate loop to achieve excellent power-sharing accuracy, and load power can be shared proportionally to the power rating of the inverter when loads are unbalanced or nonlinear. 3) Transient droop terms are added to the conventional power outer loop to improve dynamic response and disturbance rejection performance. Finally, theoretical analysis and test results are presented to validate the effectiveness of the proposed control scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.288-307
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• 2013

This paper formulates resource allocation for decode-and-forward (DF) relay assisted multi-cell orthogonal frequency division multiple (OFDM) networks as an optimization problem taking into account of inter-cell interference and users fairness. To maximize the transmit rate of system we propose a joint interference coordination, subcarrier and power allocation algorithm. To reduce the complexity, this semi-distributed algorithm divides the primal optimization into three sub-optimization problems, which transforms the mixed binary nonlinear programming problem (BNLP) into standard convex optimization problems. The first layer optimization problem is used to get the optimal subcarrier distribution index. The second is to solve the problem that how to allocate power optimally in a certain subcarrier distribution order. Based on the concept of equivalent channel gain (ECG) we transform the max-min function into standard closed expression. Subsequently, with the aid of dual decomposition, water-filling theorem and iterative power allocation algorithm the optimal solution of the original problem can be got with acceptable complexity. The third sub-problem considers dynamic co-channel interference caused by adjacent cells and redistributes resources to achieve the goal of maximizing system throughput. Finally, simulation results are provided to corroborate the proposed algorithm.

• Communications of the Korean Mathematical Society
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• v.30 no.3
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• pp.297-311
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• 2015

We present a robust and accurate boundary condition for pricing financial options that is a hybrid combination of the payoff-consistent extrapolation and the Dirichlet boundary conditions. The payoff-consistent extrapolation is an extrapolation which is based on the payoff profile. We apply the new hybrid boundary condition to the multi-dimensional Black-Scholes equations with a high correlation. Correlation terms in mixed derivatives make it more difficult to get stable numerical solutions. However, the proposed new boundary treatments guarantee the stability of the numerical solution with high correlation. To verify the excellence of the new boundary condition, we have several numerical tests such as higher dimensional problem and exotic option with nonlinear payoff. The numerical results demonstrate the robustness and accuracy of the proposed numerical scheme.

• Structural Engineering and Mechanics
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• v.45 no.1
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• pp.95-110
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• 2013

In the recent decade, practical of wavelet technique is being utilized in various domain of science. Particularly, engineers are interested to the wavelet solution method in the time series analysis. Fundamentally, seismic responses of structures against time history loading such as an earthquake, illustrates optimum capability of systems. In this paper, a procedure using particularly discrete Haar wavelet basis functions is introduced, to solve dynamic equation of motion. In the proposed approach, a straightforward formulation in a fluent manner is derived from the approximation of the displacements. For this purpose, Haar operational matrix is derived and applied in the dynamic analysis. It's free-scaled matrix converts differential equation of motion to the algebraic equations. It is shown that accuracy of dynamic responses relies on, access of load in the first step, before piecewise analysis added to the technique of equation solver in the last step for large scale of wavelet. To demonstrate the effectiveness of this scheme, improved formulations are extended to the linear and nonlinear structural dynamic analysis. The validity and effectiveness of the developed method is verified with three examples. The results were compared with those from the numerical methods such as Duhamel integration, Runge-Kutta and Wilson-${\theta}$ method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2422-2430
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• 2020

In order to improve calculational efficiency of the CAPP code in the analysis of the hexagonal reactor core, we have tried to implement a refined AFEN method with transverse gradient basis functions and interface flux moments in the hexagonal geometry. The numerical scheme for the refined AFEN method adopted here is the response matrix method that uses the interface partial currents as nodal unknowns instead of the interface fluxes used in the original AFEN method. Since the response matrix method is single-node based, it has good properties such as good calculational efficiency and parallel computing affinity. Because a refined AFEN method equivalent nonlinear FDM response matrix method tried first could not provide a numerically stable solution, a direct formulation of the refined AFEN response matrix were developed. To show the numerical performance of this response matrix method against the original AFEN method, the numerical error analyses were performed for several benchmark problems including the VVER-440 LWR benchmark problem and the MHTGR-350 HTGR benchmark problem. The results showed a more than three times speedup in computing time for the LWR and HTGR benchmark problems due to good convergence and excellent calculational efficiency of the refined AFEN response matrix method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.50-56
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• 2003

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a new combined method based on genetic algorithm(GA) and modified Newton-Raphson(mNR) algorithm via two-step approach for the solution of the static EIT inverse problem. In the first step, each mesh is classified into three mesh groups: target, background, and temporary groups. The mNR algorithm can be used to determine the region of group. In the second step, the values of these resistivities are determined using genetic algorithm. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved compared to that of the mNR algorithm at the expense of increased computational burden.

• Journal of computational fluids engineering
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• v.7 no.1
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• pp.10-19
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• 2002

The non-staggered(collocated) grid approach in which all the solution variables are located at the centers of control volumes is very popular for incompressible flow analyses because of its numerical efficiency on the curvilinear or unstructured grids. Rhie and Chow's paper is the first in using non-staggered grid method for SIMPLE algorithm, where pressure weighted interpolation was used to prevent decoupling of pressure and velocity. But it has been known that this non-staggered grid method has stability problems when pressure fields are nonlinear like in natural convection flows. Also Rhie-Chow scheme generates large numerical diffusion near curved walls. The cause of these unwanted problems is too large pressure damping term compared to the magnitude of face velocity. In this study the magnitude of pressure damping term of Rhie-Chow's method is limited to 1∼10% of face velocity to prevent physically unreasonable solutions. The wall pressure extrapolation which is necessary for cell-centered FVM is another source of numerical errors. Some methods are applied in a unstructured FV solver and analyzed in view of numerical accuracy. Here, two natural convection problems are solved to check the effect of the Rhie-Chow's method on numerical stability. And numerical diffusion from Rhie-Chow's method is studied by solving the inviscid flow around a circular cylinder.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.562-567
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• 2006

Model Predictive Control(MPC) system uses the current input which minimizes the difference between the desired output and the estimated output in the receding horizon scheme. In many cases (for example, system with constraints or nonlinear system), however, it is not easy to find the optimal solution to the above problem. In this paper, we show that real number coding genetic algorithm can be used to solve the optimal problem for MPC effectively. Also, we show by simulation that the real coding algorithm is mote natural and advantageous than the digital coding one.