• Journal of the Korean Institute of Intelligent Systems
• /
• v.9 no.6
• /
• pp.591-597
• /
• 1999

When fuzzy logic controllers which are designed based on plant models and intuitive base are applied to real plants, the control systems may not give satisfactory control results due to the modeling error and the lack of knowledge on the plants. In that case. the controller must be retuned by adjusting the control parameters; this retuning process may require a large number of trial-and-error evaluations and thus much time and cost. In order to resolve these problems, we propose a systematic and efficient procedure for designing a fuzzy logic controller using response surface methodology. First wc select the initial optimal conditions of control parameters using a genetic algorithm, in which a nominal plant model with intrinsic modeling errors is used. And then we determine the tinal optimal conditions of the control parameters using response surface methodology. Computer simulations are performed to verify the capability of the proposed method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.05a
• /
• pp.75-80
• /
• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• Journal of the Korea Society for Simulation
• /
• v.22 no.1
• /
• pp.41-51
• /
• 2013

This tutorial paper presents the design methodology of system-level simulators targeted for code division multiple access (CDMA) cellular standards such as EV-DO (Evolution-Data Only) and broadcast multicast service (BCMCS). The basic structure and simulation flow of system-level simulators are delineated, following the procedure of cell layout, mobile drops, channel modeling, received power calculation, scheduling, packet error prediction, and traffic generation. Packet data transmissions on the forward link of CDMA systems and EV-DO BCMCS systems are considered for modeling simulators. System-level simulators for cellular standards are modeled and developed with high-level languages and utilized to evaluate and predict air interface performance metrics including capacity and coverage.

• Journal of Applied Reliability
• /
• v.17 no.2
• /
• pp.168-180
• /
• 2017

Purpose: In this research, we develop an effectiveness analysis simulation model using Agent Based Modeling with Communication Effects for the development of a new weapon system. Methods: To describe the future battlefield that has more complexity, we develop Agent Based Modeling to describe communication Effects. We use the communication theory (Path-Loss Model) and the real map. Results: We have compared simulation model with real map and simulation model without real map. The Blue Survival Ratio of simulation model with real map is worse than one without real map since the performance of communication gets lower. Conclusion: There are many studies about the effectiveness analysis of a weapon system. Most of previous researches assumed no communication error. In the real world, however, it's not appropriate assumption. Therefore, this study considers the communication error and shows that it is important factor in the effectiveness analysis.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2017.05a
• /
• pp.213-217
• /
• 2017

Since more than 30% of the liquid rocket engine failures occur during the start-up process, and the Space Shuttle Main Engine (SSME) is especially sensitive to small changes in propellant conditions, a 2% error in the valve position or a 0.1sec timing error could lead to significant damage of the engine, simulation modeling of start-up process is important. However, there are many difficulties associated with engine start-up process caused by nonlinear mass flow and heat transfer characteristics associated with filling an unconditioned engine system with cryogenic propellants. In this paper, we modelled a SSME simulation model using partially Computational Fluid Dynamics (CFD) method to solve these problems and checked the performance by comparing with the performance of the simulation model using the lumped method under the state of normal condition.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.9
• /
• pp.4408-4428
• /
• 2019

Due to the rapid advancement in smart phones, numerous new specifications are developed for variety of applications ranging from health monitoring to navigations and tracking. The word indoor navigation means location identification, however, where GPS signals are not available, accurate indoor localization is a challenging task due to variation in the received signals which directly affect distance estimation process. This paper proposes a hybrid approach which integrates fingerprinting based K-Nearest Neighbors (K-NN) and lateration based MinMax position estimation technique. The novel idea behind this hybrid approach is to use Euclidian distance formulation for distance estimates instead of indoor radio channel modeling which is used to convert the received signal to distance estimates. Due to unpredictable behavior of the received signal, modeling indoor environment for distance estimates is a challenging task which ultimately results in distance estimation error and hence affects position estimation process. Our proposed idea is indoor position estimation technique using Bluetooth enabled smart phones which is independent of the radio channels. Experimental results conclude that, our proposed hybrid approach performs better in terms of mean error compared to Trilateration, MinMax, K-NN, and existing Hybrid approach.

• International journal of steel structures
• /
• v.18 no.5
• /
• pp.1541-1559
• /
• 2018

This paper addresses the dynamic loading characteristics of the shock tube onto sandwich steel beams as an efficient and accurate alternative to time consuming and complicated fluid structure interaction using finite element modeling. The corrugated sandwich steel beam consists of top and bottom flat substrates of steel 1018 and corrugated cores of steel 1008. The corrugated core layers are arranged with non-uniform thicknesses thus making sandwich beam graded. This sandwich beam is analogous to a steel beam with web and flanges. Substrates correspond to flanges and cores to web. The stress-strain relations of steel 1018 at high strain rates are measured using the split-Hopkinson pressure. Both carbon steels are assumed to follow bilinear strain hardening and strain rate-dependence. The present finite element modeling procedure with an improved dynamic impulse loading assumption is validated with a set of shock tube experiments, and it provides excellent correlation based on Russell error estimation with the test results. Four corrugated graded steel core arrangements are taken into account for core design parameters in order to maximize mitigation of blast load effects onto the structure. In addition, numerical study of four corrugated steel core placed in a reverse order is done using the validated finite element model. The dynamic behavior of the reversed steel core arrangement is compared with the normal core arrangement for deflections, contact force between support and specimen and plastic energy absorption.

• Journal of Information Processing Systems
• /
• v.18 no.2
• /
• pp.223-234
• /
• 2022

The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

• Nuclear Engineering and Technology
• /
• v.53 no.1
• /
• pp.103-110
• /
• 2021

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.10
• /
• pp.520-529
• /
• 2005

A feature-based 3D modeling algorithm is presented in this paper. Since conventional methods use depth-based techniques, they need much time for the image matching to extract depth information. Even feature-based methods have less computation load than that of depth-based ones, the calculation of modeling error about whole pixels within a triangle is needed in feature-based algorithms. It also increase the computation time. Therefore, the proposed algorithm consists of three phases, which are an initial 3D model generation, model evaluation, and model refinement phases, in order to acquire an efficient 3D model. Intensity gradients and incremental Delaunay triangulation are used in the Initial model generation. In this phase, a morphological edge operator is adopted for a fast edge filtering, and the incremental Delaunay triangulation is modified to decrease the computation time by avoiding the calculation errors of whole pixels and selecting a vertex at the near of the centroid within the previous triangle. After the model generation, sparse vertices are matched, then the faces are evaluated with the size, approximation error, and disparity fluctuation of the face in evaluation stage. Thereafter, the faces which have a large error are selectively refined into smaller faces. Experimental results showed that the proposed algorithm could acquire an adaptive model with less modeling errors for both smooth and abrupt areas and could remarkably reduce the model acquisition time.