• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1449-1457
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• 2009

Combustion instability is a major issue in design of co-generation gas turbine combustors for efficient operation with low emissions. Combustion instability is induced by the interaction of the unsteady heat release of the combustion process and the change in the acoustic pressure in the combustion chamber. In an effort to develop a technique to predict self-excited combustion instability of co-generation gas turbine combustors, a new stability analysis method based on the transfer matrix method is developed. The method views the combustion system as a one-dimensional acoustic system with a side branch and describes the heat source as the input to the system. This approach makes it possible to use not only the advantages of the transfer matrix method but also well established classic control theories. The approach is applied to a simple co-generation gas turbine combustion system, which shows the validity and effectiveness of the approach.

• Advances in concrete construction
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• v.1 no.4
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• pp.289-304
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• 2013

A reliable concrete constitutive material model is critical for an accurate numerical analysis simulation of reinforced concrete structures under extreme dynamic loadings including impact or blast. However, the formulation of concrete material model is challenging and entails numerous input parameters that must be obtained through experimentation. This paper presents a damage scale analytical model to characterize concrete material for its pre- and post-peak behavior. To formulate the damage scale model, statistical regression and finite element analysis models were developed leveraging twenty existing experimental data sets on concrete compressive strength. Subsequently, the proposed damage scale analytical model was implemented in the finite element analysis simulation of a reinforced concrete pier subjected to vehicle impact loading and the response were compared to available field test data to validate its accuracy. Field test and FEA results were in good agreement. The proposed analytical model was able to reliably predict the concrete behavior including its post-peak softening in the descending branch of the stress-strain curve. The proposed model also resulted in drastic reduction of number of input parameters required for LS-DYNA concrete material models.

• Ocean and Polar Research
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• v.34 no.1
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• pp.65-71
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• 2012

Gambierdiscus toxicus, Adachi et. Fukuyo, is a benthic ciguatoxin-producing armored dinoflagellate, often attached to macroalgae. This organism is the primary causative agent of ciguatera fish poisoning which occurs in tropical and subtropical regions. However, regardless of the fact that the population of Gambierdiscus spp. has expanded to such temperate areas from sub-trophic and trophic areas, monitoring of G. toxicus has been lacking in the Korean coastal waters of temperate areas. This study was performed at the uninhabited Baekdo Islands off the southern coast of Korea and at Seopsom Island in the vicinity of Seogwipo, Jeju Province during April and May, 2011. Cell densities of Gambierdiscus spp. on macroalgae at Baekdo and Jeju Island ranged from zero to 56.4 cells $g^{-1}$. Maximum density was recorded on the brown alga Cladophora japonica at St. 3 of Jeju Island. In particular, the cell densities of Gambierdiscus spp. were influenced by the substrate characteristics of macroalgae. In the future, the continuous monitoring of toxic benthic dinoflagellate is necessary to predict and prevent ciguatera poisoning in Korean coastal waters.

• Earthquakes and Structures
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• v.14 no.6
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• pp.525-535
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• 2018

This study presents a new beam-column model comprising material nonlinearity and joint flexibility to predict the nonlinear response of reinforced concrete structures. The nonlinear behavior of connections has an outstanding role on the nonlinear response of reinforced concrete structures. In presented research, the joint flexibility is considered applying a rotational spring at each end of the member. To derive the moment-rotation behavior of beam-column connections, the relative rotations produced by the relative slip of flexural reinforcement in the joint and the flexural cracking of the beam end are taken into consideration. Furthermore, the considered spread plasticity model, unlike the previous models that have been developed based on the linear moment distribution subjected to lateral loads includes both lateral and gravity load effects, simultaneously. To confirm the accuracy of the proposed methodology, a simply-supported test beam and three reinforced concrete frames are considered. Pushover and nonlinear dynamic analysis of three numerical examples are performed. In these examples the nonlinear behavior of connections and the material nonlinearity using the proposed methodology and also linear flexibility model with different number of elements for each member and fiber based distributed plasticity model with different number of integration points are simulated. Comparing the results of the proposed methodology with those of the aforementioned models describes that suggested model that only uses one element for each member can appropriately estimate the nonlinear behavior of reinforced concrete structures.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.6
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• pp.77-83
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• 2013

Orthodontics is a branch of dentistry that is concerned with the study and treatment of malocclusion, which may result from tooth irregularities, disproportionate jaw relationships, or both. Orthodontic devices consist of brackets, archwire connected to each bracket, and bends and hooks for auxiliary functions. Basically, orthodontics involves the interaction of brackets and archwire. It should be noted that uncontrolled tipping can occur due to unwanted movement of the teeth. The bending of an archwire can control the angle of an archwire and the rotation of a tooth. In this study, we predict the relationship between the bending angle of an archwire and the rotation of a tooth using the Kriging interpolation method. Also, we calculate the angle of an archwire that occurs at the minimum value of tooth rotation.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.64-71
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• 2016

Void fraction is an important parameter in the oil industry. This quantity is necessary for volume rate measurement in multiphase flows. In this study, the void fraction percentage was estimated precisely, independent of the flow regime in gas-liquid two-phase flows by using ${\gamma}-ray$ attenuation and a multilayer perceptron neural network. In all previous studies that implemented a multibeam ${\gamma}-ray$ attenuation technique to determine void fraction independent of the flow regime in two-phase flows, three or more detectors were used while in this study just two NaI detectors were used. Using fewer detectors is of advantage in industrial nuclear gauges because of reduced expense and improved simplicity. In this work, an artificial neural network is also implemented to predict the void fraction percentage independent of the flow regime. To do this, a multilayer perceptron neural network is used for developing the artificial neural network model in MATLAB. The required data for training and testing the network in three different regimes (annular, stratified, and bubbly) were obtained using an experimental setup. Using the technique developed in this work, void fraction percentages were predicted with mean relative error of <1.4%.

• Structural Engineering and Mechanics
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• v.72 no.4
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• pp.479-489
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• 2019

The corrosion of reinforcement leads to a gradual decay of structural strength and durability. Several models for crack occurrence prediction and crack width propagation are investigated in this paper. Analytical and experimental models were used to predict the bond strength in the period of corrosion propagation. The manner of flexural strength loss is calculated by application of these models for different scenarios. As a new approach, the variation of the concrete beam neutral axis height has been evaluated, which shows a reduction in the neutral axis height for the scenarios without loss of bond. Alternatively, an increase of the neutral axis height was observed for the scenarios including bond and concrete section loss. The statistical properties of the parameters influencing the strength have been deliberated associated with obtaining the time-dependent bending strength during corrosion propagation, using Monte Carlo (MC) random sampling method. Results showed that the ultimate strain in concrete decreases significantly as a consequence of the bond strength reduction during the corrosion process, when the section reaches to its final limit. Therefore, such sections are likely to show brittle behavior.

• Corrosion Science and Technology
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• v.19 no.6
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• pp.302-309
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• 2020

This study aimed to predict the pitting corrosion characteristics of AL-6XN super-austenitic steel using multiple linear regression. The variables used in the model are degree of sensitization, temperature, and pH. Experiments were designed and cyclic polarization curve tests were conducted accordingly. The data obtained from the cyclic polarization curve tests were used as training data for the multiple linear regression model. The significance of each factor in the response (critical pitting potential, repassivation potential) was analyzed. The multiple linear regression model was validated using experimental conditions that were not included in the training data. As a result, the degree of sensitization showed a greater effect than the other variables. Multiple linear regression showed poor performance for prediction of repassivation potential. On the other hand, the model showed a considerable degree of predictive performance for critical pitting potential. The coefficient of determination (R2) was 0.7745. The possibility for pitting potential prediction was confirmed using multiple linear regression.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.259-272
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• 2022

The branch of electronics that uses an organic solar cell or conductive organic polymers in order to yield electricity from sunlight is called photovoltaic. Regarding this crucial issue, an artificial intelligence-based predictor is presented to investigate the vibrational behavior of the organic solar cell. In addition, the generalized differential quadrature method (GDQM) is utilized to extract the results. The validation examination is done to confirm the credibility of the results. Then, the deep neural network with fully connected layers (DNN-FCL) is trained by means of Adam optimization on the dataset whose members are the vibration response of the design-points. By determining the optimum values for the biases along with weights of DNN-FCL, one can predict the vibrational characteristics of any organic solar cell by knowing the properties defined as the inputs of the mentioned DNN. To assess the ability of the proposed artificial intelligence-based model in prediction of the vibrational response of the organic solar cell, the authors monitored the mean squared error in different steps of the training the DNN-FCL and they observed that the convergency of the results is excellent.

• Structural Engineering and Mechanics
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• v.81 no.4
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• pp.523-527
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• 2022

The objective of this study is to simulate the flow in pipes with various boundary conditions. Free-pressure fluid model, is used in the pipe based on Navier-Stokes equation. The models are solved by using the numerical method. A problem called "stability of pipes" is used in order to compare frequency and critical fluid velocity. When the initial conditions of problem satisfied the instability conditions, the free-pressure model could accurately predict discontinuities in the solution field. Employing nonlinear strains-displacements, stress-strain energy method the governing equations were derived using Hamilton's principal. Differential quadrature method (DQM) is used for obtaining the frequency and critical fluid velocity. The results of this paper are analyzed by hyperbolic numerical method. Results show that the level of numerical diffusion in the solution field and the range of well-posedness are two important criteria for selecting the two-fluid models. The solutions for predicting the flow variables is approximately equal to the two-pressure model 2. Therefore, the predicted pressure changes profile in the two-pressure model is more consistent with actual physics. Therefore, in numerical modeling of gas-liquid two-phase flows in the vertical pipe, the present model can be applied.