• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.357-364
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• 2000

The three main processes involved in the design of stressed membrane surface are surface form-finding, stress analysis and cutting pattern generation. The last process, cutting pattern generation, is considered as a very important procedure in the aspect of the practical design for the fabric membrane surface. In this paper, The cutting pattern generation technique using the geodesic line algorithms is first introduced. And the numerical examples resulting from this technique are presented. Cable elements are used for the approximating membrane surface and two kinds of model, square line and central line model, are used in pattern generation. Finally, a number of different cutting pattern generation for the same membrane surface is carried out and the numerical results are compared each

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• Journal of Industrial Technology
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• v.31 no.B
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• pp.45-50
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• 2011

Recently, machine olfactory systems that have been proposed as an artificial substitute of the human olfactory system are being studied by many researchers because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. The design method adopted the sequential combination between genetic algorithms and TSK fuzzy logic system. First, the proposed method allowed the designed gas identification system effectively performing the pattern analysis because it was able to avoid the curse of dimensionality caused by use of a large number of sensors. Secondly, the method led the gas identification system to good performance because it was able to deal with drift characteristics of the sensor data by using description ability of the fuzzy system for nonlinear data. In simulation, we demonstrated the effectiveness of the designed gas identification system by using the simulation results of five types of gases.

• Journal of Korean Society of Steel Construction
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• v.16 no.6 s.73
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• pp.819-832
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• 2004

This study describes an efficient and facile method for configuration optimum design of structures. One of the ways to achieve numerical shape representation and the selection of design variables is using the design element concept. Using this technique, the number of design variables could be drastically reduced. Isoparametric mapping was utilized to automatically generate the finite element mesh during the optimization process, and this made it possible to easily calculate the derivatives of the coordinates of generated finite element nodes w.r.t. the design variables. For the structural analysis, finite element analysis was adopted in the optimization procedure, and two different techniques(the deterministic method, a modified method of feasible direction; and the stochastic method, a genetic algorithms) were applied to obtain the minimum volumes and section areas for an efficient configuration optimization procedure. Futhermore, spline interpolation was introduced to present a realistic optimum configuration that meet the manufacturing requirements. According to the results of several numerical examples(steel structures), the two techniques suggested in this study simplified the process of configuration optimum design of structures, and yielded improved objective function values with a robust convergence rate. This study's applicability and capability have therefore been demonstrated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1164-1171
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• 2012

Recently, machine olfactory systems as an artificial substitute of the human olfactory system are being studied actively because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. Even though dimensionality reduction is the very important part, in pattern analysis, We handled effectively the dimensionality reduction by grouping the sensors of which the measured patterns are similar each other, where genetic algorithms were used for combination optimization. To identify the gas type, we constructed the hierarchical rule base with two frames by using rough set theory. The first frame is to accept measurement characteristics of each sensor and the other one is to reflect the identification patterns of each group. Thus, the proposed methods was able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• Journal of the Semiconductor & Display Technology
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• v.5 no.1 s.14
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• pp.5-11
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• 2006

One of the most important is to insure that a new circuit design is qualified far release before it is scheduled for manufacturing, test, assembly and delivery. Due to various causes, there happens to be a low yield in the wafer process. Wafer test is a critical process in analyzing the chip characteristics in the EDS(electric die sorting) using analytic tools -wafer map, wafer summary and datalog. In this paper, we propose new analytic map algorithms for DDI chip test data. Using the proposed analytic map algorithms, we expect to improve the yield, quality and analysis time.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.3
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• pp.190-200
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• 2001

The homogenization method is applied to maximize crash energy absorption for a given volume. To obtain the best combination of optimizing factors by resizing and threshold algorithms for an example problem, the sensitivity analysis has been performed using design of experiments. The results show that very little interaction among optimizing factors is found. Optimization analysis of several combination of factors is conducted; and the orignal design and a new design with holes for an example problem are compared for crash energy absorption.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.221-229
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.76-85
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• 1998

Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.2
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• pp.136-143
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• 2004

This paper presents three algorithms of repetitive controller for compensation of the repeatable runout in hard disk drive. The basic theory of the repetitive controller and the analysis of the disturbance in hard disk drive are introduced. The tracking controller is designed in order to design the "plug-in type" repetitive controller. Design of the repetitive controller is considered as the design of the filter, determination of gain and design of additional compensation for the various types. Specially, trade-off relationship between stability and performance is important for the design. The three kinds of "plug-in type" repetitive controllers are designed, simulated and experimented. Performance and characteristic of them are compared with the analysis of the experimental results.