• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.339-350
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• 2016

Based on the resonance integral (RI) tables produced by the NJOY program, the conventional subgroup method usually ignores both the resonance elastic scattering and the resonance interference effects. In this paper, on one hand, to correct the resonance elastic scattering effect, RI tables are regenerated by using the Monte Carlo code, OpenMC, which employs the Doppler broadening rejection correction method for the resonance elastic scattering. On the other hand, a fast resonance interference factor method is proposed to efficiently handle the resonance interference effect. Encouraging conclusions have been indicated by the numerical results. (1) For a hot full power pressurized water reactor fuel pin-cell, an error of about +200 percent mille could be introduced by neglecting the resonance elastic scattering effect. By contrast, the approach employed in this paper can eliminate the error. (2) The fast resonance interference factor method possesses higher precision and higher efficiency than the conventional Bondarenko iteration method. Correspondingly, if the fast resonance interference factor method proposed in this paper is employed, the $k_{inf}$ can be improved by ~100 percent mille with a speedup of about 4.56.

• Steel and Composite Structures
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• v.36 no.1
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• pp.31-45
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• 2020

The purpose of this study is to develop an effective iterative two-stage method (ITSM) for structural damage identification of offshore platform structures. In each iteration, a new damage index, Modal Energy-Based Damage Index (MEBI), is proposed to help effectively locate the potential damage elements in the first stage. Then, in the second stage, the beetle antenna search (BAS) algorithm is used to estimate the damage severity of these elements. Compared with the well-known particle swarm optimization (PSO) algorithm and genetic algorithm (GA), this algorithm has lower computational cost. A modal energy based objective function for the optimization process is proposed. Using numerical and experimental data, the efficiency and accuracy of the ITSM are studied. The effects of measurement noise and spatial incompleteness of mode shape are both considered. All the obtained results show that under these influences, the ITSM can accurately identify the true location and severity of damage. The results also show that the objective function based on modal energy is most suitable for the ITSM compared with that based on flexibility and weighted natural frequency-mode shape.

• Journal of Korean Association for Spatial Structures
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• v.21 no.1
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• pp.79-86
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• 2021

Control performance of a smart tuned mass damper (TMD) mainly depends on control algorithms. A lot of control strategies have been proposed for semi-active control devices. Recently, machine learning begins to be applied to development of vibration control algorithm. In this study, a reinforcement learning among machine learning techniques was employed to develop a semi-active control algorithm for a smart TMD. The smart TMD was composed of magnetorheological damper in this study. For this purpose, an 11-story building structure with a smart TMD was selected to construct a reinforcement learning environment. A time history analysis of the example structure subject to earthquake excitation was conducted in the reinforcement learning procedure. Deep Q-network (DQN) among various reinforcement learning algorithms was used to make a learning agent. The command voltage sent to the MR damper is determined by the action produced by the DQN. Parametric studies on hyper-parameters of DQN were performed by numerical simulations. After appropriate training iteration of the DQN model with proper hyper-parameters, the DQN model for control of seismic responses of the example structure with smart TMD was developed. The developed DQN model can effectively control smart TMD to reduce seismic responses of the example structure.

• Steel and Composite Structures
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• v.42 no.1
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• pp.23-32
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• 2022

In this paper, a nonlinear numerical method to solve the large deflection problem is introduced. And the non-dimensional load-deflection behavior of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) plates is parametrically investigated. The large deflection problem is formulated according to the von Kármán nonlinear theory and the (1,1,0)^* hierarchical model, and it is approximated by 2-D natural element method (NEM). The shear locking phenomenon is suppressed by the selectively reduced integration method. The nonlinear matrix equations are solved by combining the incremental loading scheme and the Newton-Raphson iteration method. The proposed method is validated from the benchmark experiments, where the propose method shows an excellent agreement with the reference methods. The nonlinear behavior of FG-CNTRC plates is evaluated in terms of the non-dimensional load-deflection curve, and it is parametrically investigated with respect to the existence/non-existence and gradient pattern of CNTs, the width-to-thickness and aspect ratios of plates and the type of boundary conditions. The non-dimensional central deflection is significantly reduced when CNTs and added, and it decreases with the volume fraction of CNTs. But, it shows a uniform increase in proportion to the width-to-thickness and aspect ratios. Both the gradient pattern of CNTs and the type of boundary conditions do also show the remarkable effects.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1225-1232
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• 2023

The ¹⁸⁰W is the lightest isotope of Tungsten with small abundance ratio. It is slightly radioactive (α decay), with an extremely long half-life. Its separation is possible by non-conventional single withdrawal cascades. The ¹⁸⁰W is used in radioisotopes production and study of metals through gamma-ray spectroscopy. In this paper, single withdrawal cascade model is developed to evaluate multicomponent separation in non-conventional transient cascades, and available experimental results are used for validation. Numerical studies for separation of ¹⁸⁰W in a transient single withdrawal cascade are performed. Parameters affecting the separation and equilibrium time of cascade such as number of stages, cascade arrangements, feed location and flow rate for a fixed number of gas centrifuges (GC) are investigated. The Salp Swarm Algorithm (SSA) as a bio-inspired optimization algorithm is applied as a novel method to minimize the feed consumption to obtain desired concentration in the collection tank. Examining different cascade arrangements, it is observed in arrangements with more stages, the separation is further efficient. Based on the obtained results, with increasing feed flow rate, for fixed product concentration, the cascade equilibrium time decreases. Also, it is shown while the feed location is the farthest stage from the collection tank, the separation and cascade equilibrium time are well-organized. Finally, using SSA optimal parameters of the cascade is calculated, and optimal arrangement to produce 5 gr of ¹⁸⁰W with 90% concentration in the tank, is proposed.

• Steel and Composite Structures
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• v.44 no.5
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• pp.633-649
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• 2022

This paper is first implemented with the bending behavior of three-dimensional functionally graded (3DFG) plates in the framework of level set-based topology optimization (LS-based TO). Besides, due to the suitable properties of the current design domain, the thin-plate spline (TPS) is recognized as a RBF to construct the LS function. The overall mechanical properties of the 3DFG plate are assessed using a power-law distribution scheme via Mori-Tanaka micromechanical material model. The bending response is obtained using the first-order shear deformation theory (FSDT). The mixed interpolation of four elements of tensorial components (MITC4) is also implemented to overcome a well-known shear locking problem when the thickness becomes thinner. The Hamilton-Jacobi method is utilized in each iteration to enforce the necessary boundary conditions. The mathematical formulas are expressed in great detail for the LS-based TO using 3DFG materials. Several numerical examples are exhibited to verify the efficiency and reliability of the current methodology with the previously reported literature. Finally, the influences of FG materials in the optimized design are explained in detail to illustrate the behaviors of optimized structures.

• Advances in Computational Design
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• v.9 no.2
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• pp.115-136
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• 2024

Stochastic optimization methods have been extensively studied for structural optimization in recent decades. In this study, a novel algorithm named the CA-SA method, is proposed for topology optimization of steel double-layer grid structures. The CA-SA method is a hybridized algorithm combining the Simulated Annealing (SA) algorithm and the Cellular Automata (CA) method. In the CA-SA method, during the initial iterations of the SA algorithm, some of the preliminary designs obtained by SA are placed in the cells of the CA. In each successive iteration, a cell is randomly chosen from the CA. Then, the "local leader" (LL) is determined by selecting the best design from the chosen cell and its neighboring ones. This LL then serves as the leader for modifying the SA algorithm. To evaluate the performance of the proposed CA-SA algorithm, two square-on-square steel double-layer grid structures are considered, with discrete cross-sectional areas. These numerical examples demonstrate the superiority of the CA-SA method over SA, and other meta-heuristic algorithms reported in the literature in the topology optimization of large-scale skeletal structures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.3B
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• pp.175-183
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• 2012

In this study, Galerkin scheme and SU/PG scheme of Petrov-Galerkin family were applied to the shallow water equations and a finite element model for shallow water flow was developed. Numerical simulations were conducted in several flumes with convection-dominated flow condition. Flow simulation of channel with slender structure in the water course revealed that Galerkin and SU/PG schemes showed similar results under very low Fr number and Re number condition. However, when the Fr number increased up to 1.58, Galerkin scheme did not converge while SU/PG scheme produced stable solutions after 5 iterations by Newton-Raphson method. For the transcritical flow simulation in diverging channel, the present model predicted the hydraulic jump accurately in terms of the jump location, the depth slope, and the flow depth after jump, and the numerical results showed good agreements with the hydraulic experiments carried out by Khalifa(1980). In the oblique hydraulic jump simulation, in which convection-dominated supercritical flow (Fr=2.74) evolves, Galerkin scheme blew up just after the first iteration of the initial time step. However, SU/PG scheme captured the boundary of oblique hydraulic jump accurately without numerical oscillation. The maximum errors quantified with exact solutions were less than 0.2% in water depth and velocity calculations, and thereby SU/PG scheme predicted the oblique hydraulic jump phenomena more accurately compared with the previous studies (Levin et al., 2006; Ricchiuto et al., 2007).

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.2
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• pp.89-96
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• 2000

Slug tests are the most widely used field method for quantification of hydraulic conductivity of porous media. Well recovery is affected by well casing, borehole radii, screened length, hydraulic conductivity, and specific storage of porous media. In this study, a new slug tests model was developed through finite element approximation and the validity and usefulness of the model were tested in various ways. Water level fluctuation in a well under slug test and cons-equent groundwater flow in the surrounding porous medium were appropriately coupled through estimation of well-flux using an iteration technique. Numerical accuracy of the model was verified using the Cooper et al. (1967) solution. The model has advantages in simulations for monitored slug tests, partial penetration, and inclusion of storage factor. Volume coverage of slug tests is significantly affected by storage factor. Magnitude and speed of propagation of head changes from a well increases as storage factor becomes low. It will be beneficial to use type curves of monitored head transients in the surrounding porous formation for estimation of specific storage. As the vertical component of groundwater flow is enhanced, the influence of storage factor on well recovery decreases. For a radial-vertical flow around a partially penetrated well, deviations between hydraulic estimates by various methods and data selection of recovery curve are negligible on practical purposes, whereas the deviations are somewhat significant for a radial flow.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.211-216
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• 2013

In general, smoothing filters regularize functions by reducing differences between adjacent values. The smoothing filters, therefore, can regularize inverse solutions and produce more accurate subsurface structure when we apply it to full waveform inversion. If we apply a smoothing filter with a constant coefficient to subsurface image or velocity model, it will make layer interfaces and fault structures vague because it does not consider any information of geologic structures and variations of velocity. In this study, we develop a selective smoothing regularization technique, which adapts smoothing coefficients according to inversion iteration, to solve the weakness of smoothing regularization with a constant coefficient. First, we determine appropriate frequencies and analyze the corresponding wavenumber coverage. Then, we define effective maximum wavenumber as 99 percentile of wavenumber spectrum in order to choose smoothing coefficients which can effectively limit the wavenumber coverage. By adapting the chosen smoothing coefficients according to the iteration, we can implement multi-scale full waveform inversion while inverting multi-frequency components simultaneously. Through the successful inversion example on a salt model with high-contrast velocity structures, we can note that our method effectively regularizes the inverse solution. We also verify that our scheme is applicable to field data through the numerical example to the synthetic data containing random noise.