• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.2
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• pp.67-76
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• 1988

A fully non-linear two-dimensional model for studying basic tidal dynamics within the Arabian Gulf has been formulated. The model extends to the east as far as continental shelf edge and has a mesh resolution of 1/12 degree latitude by 1/10 degree longitude. The developed model was used to investigate the distribution of dominant $M_2$, $S_2$, $K_1$, $O_1$ and $N_2$ tides adopting the open boundary tidal information from Schwiderski's global ocean tidal model. Computed co amplitude and cophase charts were presented independently and comparison between these charts and existing Admiralty tidal charts were made. Maximum bottom stress vector during the semidiurnal period due to $M_2$ and $M_4$ tides are also presented to suggest the possible direction of sediment movement in the region.

• Smart Structures and Systems
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• v.26 no.4
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• pp.495-506
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• 2020

Monitoring of complex processes faces several challenges mainly due to the lack of relevant sensory information or insufficient elaborated decision-making strategies. These challenges motivate researchers to adopt complex data processing and analysis in order to improve the process representation. This paper presents the development and implementation of quality monitoring framework based on a model-driven approach using embedded artificial intelligence strategies. In this work, the strategies are applied to the supervision of a microfabrication process aiming at showing the great performance of the framework in a very complex system in the manufacturing sector. The procedure involves two methods for modelling a representative quality variable, such as surface roughness. Firstly, the hybrid incremental modelling strategy is applied. Secondly, a generalized fuzzy clustering c-means method is developed. Finally, a comparative study of the behavior of the two models for predicting a quality indicator, represented by surface roughness of manufactured components, is presented for specific manufacturing process. The manufactured part used in this study is a critical structural aerospace component. In addition, the validation and testing are performed at laboratory and industrial levels, demonstrating proper real-time operation for non-linear processes with relatively fast dynamics. The results of this study are very promising in terms of computational efficiency and transfer of knowledge to manufacturing industry.

• Korean Journal of Computational Design and Engineering
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• v.20 no.1
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• pp.84-92
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• 2015

In this study, we describe a method to analysis dynamic behavior of an offshore wind turbine in the frequency domain and expected effects of the method. An offshore wind turbine, which is composed of platform, tower, nacelle, hubs, and blades, can be considered as multibody systems. In general, the dynamic analysis of multibody systems are carried out in the time domain, because the equations of motion derived based on the multibody dynamics are generally nonlinear differential equations. However, analyzing the dynamic behavior in time domain takes longer than in frequency domain. In this study, therefore, we describe how to analysis the system multibody systems in the frequency domain. For the frequency domain analysis, the non-linear differential equations are linearized using total derivative and Taylor series expansions, and then the linearized equations are solved in time domain. This method was applied to analysis of double pendulum system for the verification of its effectiveness, and the equations of motion for the offshore wind turbine was derived with assuming that the wind turbine is rigid multibody systems. Using this method, the dynamic behavior analysis of the offshore wind turbine can be expected to take less time.

• Ocean Systems Engineering
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• v.7 no.4
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• pp.435-460
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• 2017

The main objective of this study is to investigate the turning and zig-zag maneuvering performance of the well-known naval surface combatant DTMB (David Taylor Model Basin) 5415 hull with URANS (Unsteady Reynolds-averaged Navier-Stokes) method. Numerical simulations of static drift tests have been performed by a commercial RANS solver based on a finite volume method (FVM) in an unsteady manner. The fluid flow is considered as 3-D, incompressible and fully turbulent. Hydrodynamic analyses have been carried out for a fixed Froude number 0.28. During the analyses, the free surface effects have been taken into account using VOF (Volume of Fluid) method and the hull is considered as fixed. First, the code has been validated with the available experimental data in literature. After validation, static drift, static rudder and drift and rudder tests have been simulated. The forces and moments acting on the hull have been computed with URANS approach. Numerical results have been applied to determine the hydrodynamic maneuvering coefficients, such as, velocity terms and rudder terms. The acceleration, angular velocity and cross-coupled terms have been taken from the available experimental data. A computer program has been developed to apply a fast maneuvering simulation technique. Abkowitz's non-linear mathematical model has been used to calculate the forces and moment acting on the hull during the maneuvering motion. Euler method on the other hand has been applied to solve the simultaneous differential equations. Turning and zig-zag maneuvering simulations have been carried out and the maneuvering characteristics have been determined and the numerical simulation results have been compared with the available data in literature. In addition, viscous effects have been investigated using Eulerian approach for several static drift cases.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Korean Journal of Biological Psychiatry
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• v.4 no.1
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• pp.67-73
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• 1997

The changes of electroencephalogram(EEG) in patients with dementia are most commonly studied by analyzing power or magnitude in certain traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to chaos theory, irregular signals of EEG can also result from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the correlation dimension. The authors have analyzed EEG epochs from three patients with dementia of Alzheimer type and three matched control subjects. The multichannel correlation dimension is calculated from EEG epochs consisting of 15 channels with 16,384 data points per channel. The results showed that patients with dementia of Alzheimer type had significantly lower correlation dimension than non-demented controls on 12 channels. Topographic analysis showed that the correlation dimensions were significantly lower in patients with Alzheimer's disease on frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer type have a decreased complexity of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating correlation dimension can be a promising tool for detecting relative changes in the complexity of brain dynamics.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.4
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• pp.413-420
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• 1994

Dynamics of the river plume is a very complicated non-linear problem with the free boundary changing in time and space. Mixing with the ambient water through the boundary makes the problem more complicated. In this paper we reduced 3-dimensional problem into 1-dimensional one by using the integral analysis method. Basic equations have been integrated over the lateral and vertical variations. For these integrations we adopted the well-established assumption that the flow-axis component of plume velocity and the density difference of the plume with the ambient water have Gaussian distributions in directions which are perpendicular to the flow-axis of the plume. We also used the result of our previous study on the lateral spreading velocity of the plume derived under the same assumption. And entrainment was included as a mixing process. The resultant 1-dimensional equations were solved by Runge-Kutta numerical method. Consequently, comparatively easy method of numerical analysis is presented for the 3-dimensional river plume. The method can also be used for the analysis of the thermal plume of cooling water of power plants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.253-263
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• 2018

This paper examined the U-shape curvilinear relationship between team level conflict management and individual level turnover intention by using exit-voice theory, bandwagon effect, and social loafing theory. In addition to the non-linear relationship between team-level conflict management and individual-level turnover intentions, we also examined how trust in leaders has a moderating effect on this relationship. The samples were collected from a South Korean manufacturing company with 331 team members from 48 teams and items were measured twice to avoid common method biases. The intercepts-as-outcomes model of hierarchical linear modelling was conducted to verify the hypothesis. Results supported the cross-level curvilinear hypothesis which indicated that employees' turnover intention sharply decreased if the activeness of group conflict management was small and increases slightly, but this tendency moderated as activeness increases. After passing the lowest point, their turnover intention increased in the end. However, the moderation effect of trust in leader on this relationship was not statistically significant and hypothesis 2 was rejected. This paper explained the effects of group dynamics of conflict management on individual turnover intention. Such evidence may elucidate the importance of managing the social loafing behavior on conflict management process. This paper examined the sequential, multi-level, and curvilinear relationship between conflict management and turnover intention. Organizations and managers will benefit from avoiding the human resource loss by managing the conflict management process.

• Journal of Korean Neurosurgical Society
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• v.65 no.6
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• pp.834-840
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• 2022

Objective : C-reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), and white blood cell (WBC) count are inflammatory markers used to evaluate postoperative infections. Although these markers are non-specific, understanding their normal kinetics after surgery may be helpful in the early detection of postoperative infections. To compliment the recent trend of reducing the duration of antibiotic use, this retrospective study investigated the inflammatory markers of patients who had received antibiotics within 24 hours after surgery according to the Health Insurance Review & Assessment Service guidelines and compared them with those of patients who had received antibiotics for 5 days, which was proven to be non-infectious. Methods : We enrolled 74 patients, divided into two groups. Patients underwent posterior lumbar interbody fusion (PLIF) at a single institution between 2019 and 2020. Group A included 37 patients who received antibiotics within 24 hours after the PLIF procedure, and group B comprised 37 patients who had used antibiotics for 5 days. A 1 : 1 nearest-neighbor propensity-matched analysis was used. The clinical variables included age, sex, medical history, body mass index, estimated blood loss, and operation time. Laboratory data included CRP, ESR, and WBC, which were measured preoperatively and on postoperative days (POD) 1, 3, 5, and 7. Results : CRP dynamics tended to decrease after peaking on POD 3, with a similar trend in both groups. The average CRP level in group B was slightly higher than that in group A; however, the difference was not statistically significant. Multiple linear regression analysis revealed operation time, number of fused levels, and estimated blood loss as significant predictors of a greater CRP peak value (r²=0.473, p<0.001) in patients. No trend (a tendency to decrease from the peak value) could be determined for ESR and WBC count on POD 7. Conclusion : Although slight differences were observed in numerical values and kinetics, sequential changes in inflammatory markers according to the duration of antibiotic administration showed similar patterns. Knowledge of CRP kinetics allows the assessment of the degree of difference between the clinical and expected values.