• Computational Structural Engineering : An International Journal
• /
• v.1 no.1
• /
• pp.31-38
• /
• 2001

In the case of the non-proportionally damped system such as the soil-structure interaction system, the structural control system and composite structures, the eigenproblem with the damping matrix should be necessarily performed to obtain the exact dynamic response. However, most of the eigenvalue analysis methods such as the subspace iteration method and the Lanczos method may miss some eigenvalues in the required ones. Therefore, the eigenvalue analysis method must include a technique to check the missed eigenvalues to become the practical tools. In the case of the undamped or proportionally damped system the missed eigenvalues can easily be checked by using the well-known Sturm sequence property, while in the case of the non-proportionally damped system a checking technique has not been developed yet. In this paper, a technique of checking the missed eigenvalues for the eigenproblem with the damping matrix is proposed by applying the argument principle. To verify the effectiveness of the proposed method, two numerical examples are considered.

• Journal of Korea Game Society
• /
• v.16 no.1
• /
• pp.119-128
• /
• 2016

In this paper, we consider an improved deformation method of IFS(iterated function system) fractal using codes of fractal points. In the existing deformation methods, the intermediate results of position dependent partial deformation propagate randomly due to the randomly selected maps of iteration. Therefore, in many cases, the obtained results become somewhat monotonous feeling shapes. To improve these limitations, we propose a method in which the selection of maps are controlled by codes of fractal points. Applying this method, we can obtain interesting fractal deformation conforming with its fractal features. Also, we propose a simple method, incorporating state variables, that can be applied to deformation of some fractal features other than position coordinates.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.2 s.257
• /
• pp.211-220
• /
• 2007

This work presents an iterated improved reduced system (IIRS) procedure combined with sub-structuring scheme for large structures. Iterated IRS methods are usually more efficient than others because the dynamic condensation matrix is updated repeatedly until the desired convergent values are obtained. However, using these methods simply for large structures causes expensive computational cost and even makes analyses intractable because of the limited computer storage. Therefore, the application of sub-structuring scheme is necessary. Because the large structures are subdivided into several (or more) sub-domains, the construction of dynamic condensation matrix does not require much computation cost in every iteration. This makes the present method much more efficient to compute the eigenpairs both in lower and intermediate modes. In Part I, iterated IRS method combined with sub-structuring scheme for undamped structures is presented. The validation of the proposed method and the evaluation of computational efficiency are demonstrated through the numerical examples.

• Journal of Korea Society of Industrial Information Systems
• /
• v.8 no.4
• /
• pp.26-30
• /
• 2003

The Lanczos algorithm is the most commonly used in approximating a small number of extreme eigenvalues for symmetric large sparse matrices. Global communications in MP(Message Passing) parallel computer decrease the computation speed. In this paper, we introduce the s-step Lanczos method, and s-step method generates reduction matrices which are similar to reduction matrices generated by the standard Lanczos method. One iteration of the s-step Lanczos algorithm corresponds to s iterations of the standard Lanczos algorithm. The s-step method has the minimized global communication and has the superior parallel properties to the standard method. These algorithms are implemented on Cray T3E and performance results are presented.

• IE interfaces
• /
• v.20 no.2
• /
• pp.112-120
• /
• 2007

As the market rapidly changes, the speed of new product development is highlighted as a critical element which determines the success of firms. While firms endeavor to accelerate the development speed, frequent iterations in a development process hinders the effort of acceleration. For this reason, many previous researches tried to find the optimal structure of the development process which minimizes the number of iterations. However, such researches have a limitation in that they can be applied to only a single-project environment. In a multi-project environment, waiting time induced by lack of resources also delays the process as well as the iterations do. In this paper, we propose dynamic sequencing method focusing on both iterations and waiting time for reducing the durations of development projects in a multi-project environment. This method reduces the waiting time by changing the sequence of development tasks according to the states of resources. While the method incurs additional iterations, they are expected to be offset by the reduced waiting time. The results of simulation show that the dynamic sequencing method dramatically improves the efficiency of a development process. Especially, the improvement is more salient as projects are more crowded and the process is more unbalanced. This method gives a new insight in researches on managing multiple development projects.

• The Journal of Korea Robotics Society
• /
• v.17 no.2
• /
• pp.221-229
• /
• 2022

Sliding mode control (SMC) is a robust control method to control a robot arm with nonlinear properties. A high switching gain of SMC causes chattering problems, although the SMC allows the adequate control performance by giving high switching gain, without the exact robot model containing nonlinear and uncertainty terms. In order to solve this problem, SMC with sliding perturbation observer (SMCSPO) has been researched, where the method can reduce the chattering by compensating the perturbation, which is estimated by the observer, and then choosing a lower switching control gain of SMC. However, optimal gain tuning is necessary to get a better tracking performance and reducing a chattering. This paper proposes a method that the Q-learning automatically tunes the control gains of SMCSPO with an iterative operation. In this tuning method, the rewards of reinforcement learning (RL) are set minus tracking errors of states, and the action of RL is a change of control gain to maximize rewards whenever the iteration number of movements increases. The simple motion test for a 7-DOF robot arm was simulated in MATLAB program to prove this RL tuning algorithm. The simulation showed that this method can automatically tune the control gains for SMCSPO.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.27 no.6
• /
• pp.471-480
• /
• 2022

Inductive power transfer (IPT) is an attractive power transmission solution that is already used in many applications. In the IPT system, optimal coil design is essential to achieve high power efficiency, but the effective design method is yet to be investigated. The inductance formula and finite element method (FEM) are popular means to link the coil geometric parameters and circuit parameters; however, the former lacks generality and accuracy, and the latter consumes much computation time. This study proposes a novel coil design method to achieve speed and generality without much loss of accuracy. By introducing one-turn permeance simulation in each FEM phase combined with curve fitting and optimization by MATLAB in the efficiency calculation phase, the iteration number of FEM can be considerably reduced, and the generality can be retained. The proposed method is verified through a 100 W IPT system experiment.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.40 no.11
• /
• pp.705-715
• /
• 2016

In this study, the cycle performance of an air conditioner with multi-indoor units is analyzed and simulated. The cycle performance could be predicted through the integration of mathematical formulation for these devices. The condenser pressure is obtained by an iteration process to match the mass flow rates of the compressor and the expansion valve and the evaporator pressure is determined by an iteration process, in which the suction super heat is tracing the targeted super heat. The required software was developed by system programming. the software algorithm is extended to predict the cycle performance of an air conditioner system with multi-indoor units, and then the numerical results are compared with experimental results. This mathematical model is validated from the result of experiments conducted on 8.3kW air conditioner. The errors in capacity, electronic power, and COP are found to be within 10% in general.

• Journal of Korean Association for Spatial Structures
• /
• v.20 no.2
• /
• pp.51-58
• /
• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.5
• /
• pp.1-5
• /
• 2010

This paper deals with a method to measure the thickness of scale-layer, iron oxide formed on the surface of the rolling steel, using a dielectric lens antenna. The dielectric lens antenna has an independent characteristic with the frequency in the X-band and changes the spherical wave radiated from a horn antenna into a plane wave at the focusing point. Using this concept, we regard a scale-layer on the rolling steel as a dielectric-PEC(Perfect Electric Conductor) layer and apply a theoretical analysis of the normal-incident plane wave. To reduce the phase error arising from the use of the dielectric lens antenna, this paper utilizes a regression process algorithm. In comparison with the conventional iteration algorithm, the present algorithm led to a unique solution for the thickness of the scale-layer.