• Journal of Advanced Marine Engineering and Technology
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• v.6 no.2
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• pp.69-91
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• 1982

The major factors which affect the crankshaft axial vibration are such items as the axial stiffness and mass of crankshaft, the thrust block stiffness, the propeller's entrained water and the exciting and damping forces of engine, propeller and shafting. Among above mentioned items, the axial stiffness and mass of crankshaft, thrust block stiffness and propeller's entrained water were treated in detail in part I, and so in this paper, the rest of above items will be studied. The exciting forces of crankshaft axial vibration are generated mainly from the gas explosion pressure of cylinder, the thrust fluctuation of propeller, and sometimes the torsional vibration of crankshaft induces the crankshaft axial vibration. As for the propeller thrust fluctuation, its harmonic components can be fairly exactly calculated from the experimental results of propeller in the towing tank, but as the calculation process is rather tedious and laborious, the empirical values are ordinarily used. On the other hand, the table of harmonic components of gas pressure has been already published by major slow speed diesel engine makers, but the axial thrust conversion factor of radial force is not unknown yet, and as its estimated value is unreliable, the axial vibration force of gas pressure is uncertain. As the calculation of damping force is very complicated and it includes some uncertain factors, the thoretically estimated amplitudes of axial vibration are much more incorrect in comparison with those of torsional vibrations. Authors have paid special attentions to deriving the theoretical calculation formula of axial conversion factor of radial force and damping force of crankshaft axial vibration and developed a computer program to calculate resonance amplitudes and additional stresses of crankshaft axial vibrations. Also, to check the reliability of the developed computer program, the axial vibrations of three ships' propulsion shaftings were analyzed and their results were compared with those of measured values and makers' results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.211-217
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• 1998

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would ofter lose its original meaning of optimality. Nevertheless, the human operators usually performs satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation(ATO) system for the magnetically levitated vehicles(MAGLEV). One of the human operator's strategies is to predict the control result in order to find the meaningful solution. In this paper, Takagi-Sugeno fuzzy model is used to simulated the prediction procedure. Another str tegy is to evaluate the multiple objectives with respect to their own standards. To realize this strategy, we propose the concept of a satisfactory solution and a satisfactory control scheme. The MAGLEV train is a typical example of the uncertain, complex and large-scale plants. Moreover, the ATO system has to satisfy multiple objectives, such as seed pattern tracking, stop gap accuracy, safety and riding comfort. In this paper, the speed pattern tracking controller and the automatic stop controller of the ATO system is designed based on the proposed control scheme. The effectiveness of the ATO system based on the proposed scheme is shown by the experiments with a rotary test bed and a real MAGLEV train.

• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.447-454
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• 2004

During the hierarchical formation of large scale structure in the universe, the progressive collapse and merging of dark matter should inevitably drive shocks into the gas, with nonthermal particle acceleration as a natural consequence. Two topics in this regard are discussed, emphasizing what important things nonthermal phenomena may tell us about the structure formation (SF) process itself. 1. Inverse Compton gamma-rays from large scale SF shocks and non-gravitational effects, and the implications for probing the warm-hot intergalactic medium. We utilize a semi-analytic approach based on Monte Carlo merger trees that treats both merger and accretion shocks self-consistently. 2. Production of $^6Li$ by cosmic rays from SF shocks in the early Galaxy, and the implications for probing Galaxy formation and uncertain physics on sub-Galactic scales. Our new observations of metal-poor halo stars with the Subaru High Dispersion Spectrograph are highlighted.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.311-314
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• 2001

Recently, research on Intelligent Information Process has actively been under way JD various areas and gradually extended to be adaptive to uncertain and complex dynamic environments. This paper presents a Multiple Valued Logic Automata(MVL-Automata) Model, utilizing properties of difference in a Multiple Valued Logic function. That is, MVL-Automata is able to be autonomously adapted to dynamic changing since an input stling is mapped to the value of a Multiple Valued Logic function and the property of difference in a Multiple Valued Logic function is applied to state transition. Therefore, Multiple Valued Logic Automata can be widely applied to the modeling dynamically of changing environments.

• Journal of the Korea Institute of Building Construction
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• v.11 no.1
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• pp.91-99
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• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1228-1229
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• 2011

A novel approach has been promoted for FNN ship controllers. An Electro-hydraulic governor has been widely adopted to the ship speed control of propulsion marine diesel engines for a long time, it was very difficult for Electro-hydraulic governor to regulate the speed of high power engine with long stroke at low speed and low load, because of the jiggling phenomena by rough fluctuation of rotating torque and the hunting phenomena by long dead time occurred in fuel combustion process in the engine cylinder. This paper provides an efficient way for improving control performance by FNN controller. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The performance of controller is evaluated by the system simulation using simulink tools.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.146-154
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• 2014

This paper proposes a bandwidth-aware localized-routing algorithm that is capable of sensing the available spectrum bands within a two-hop neighboring for choosing the highly opportunistic routes. A mixed-integer linear programming (MILP) is utilized to formulate the optimization problem. Then, the proposed algorithm is used to determine the maximum bandwidth possible of link pairs via a bandwidth approximation process of relaxed variables. Thereby, the proposed algorithm can allow selected routes corresponding to maximum bandwidth possible between cognitive radio (CR) users through link pairs in cognitive radio networks. By comparing the solution values to previous works, simulation results demonstrate that the proposed algorithm can offer a closed-optimal solution for routing performance in cognitive radio networks. The contribution of this paper is achieved through approximately 50% throughput utilized in the network.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.29-34
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• 2010

This paper presents an intelligent learning controller for repetitive walking motion of biped walking robot. The proposed learning controller consists of an iterative learning controller and a direct learning controller. In the iterative learning controller, the PID feedback controller takes part in stabilizing the learning control system while the feedforward learning controller plays a role in compensating for the nonlinearity of uncertain biped walking robot. In the direct learning controller, the desired learning input for new joint trajectories with different time scales from the learned ones is generated directly based on the previous learned input profiles obtained from the iterative learning process. The effectiveness and tracking performance of the proposed learning controller to biped robotic motion is shown by mathematical analysis and computer simulation with 12 DOF biped walking robot.

• Korean Institute of Interior Design Journal
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• no.14
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• pp.63-73
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• 1998

The aim of this study is to understand and redefine the nature of architectural environment within the paradigm of natural science. The chaos theory non-equilibrium thermodynamics theory self-organization of modern physics offer new insights to explain not only natural phenomena but also to define creative and dynamic architectural environment. First natural laws in modern physics like the arrow of time but is related not only with certainty but also possibility so nature is understood as a constantly changing process of evolution. Second the new architectural environment is defined as a kind of fluid and irreducible organic biosytem that cannot be fully understood by modernist idea of architecture. It is conceived of as a fluid constantly changing self-oraganizing system that consists of different situations events movements and programs in uncertain and irreducible time frame. Third insights and implications of natural science offer new language and strategy for design and the two disciplines can be understood as interdependent and co-evolving

• Journal of the military operations research society of Korea
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• v.31 no.1
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• pp.26-41
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• 2005

The ROK TRANSCOM and Army Logistics Command have established wartime overland transportation plans. They have to mobilize several wartime overland transportation troops in order to meet the wartime transportation requirement. But there are some uncertainties in the process of transportation such as the number of vehicles to mobilize, the vehicle utilization factor, and round trip time. Here, we established two models. One is the simulation model to evaluate the transportation capability considering uncertain factors. The simulation model is executed with two scenarios and then the results are analyzed through a sensitivity analysis. The other model is the regression model to analyze the effects of transportation factors toward capability.