• Computers and Concrete
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• v.31 no.2
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• pp.111-121
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• 2023

The influence of material composition such as aggregate types, addition of supplementary cementitious materials as well as exposed temperature levels have significant impacts on concrete residual mechanical strength properties when exposed to elevated temperature. This study is based on data obtained from literature for fly ash blended concrete produced with natural and recycled concrete aggregates to efficiently develop prediction models for estimating its residual compressive strength after exposure to high temperatures. To achieve this, an extensive database that contains different mix proportions of fly ash blended concrete was gathered from published articles. The specific design variables considered were percentage replacement level of Recycled Concrete Aggregate (RCA) in the mix, fly ash content (FA), Water to Binder Ratio (W/B), and exposed Temperature level. Thereafter, a simplified mathematical equation for the prediction of concrete's residual compressive strength using Gene Expression Programming (GEP) was developed. The relative importance of each variable on the model outputs was also determined through global sensitivity analysis. The GEP model performance was validated using different statistical fitness formulas including R², MSE, RMSE, RAE, and MAE in which high R² values above 0.9 are obtained in both the training and validation phase. The low measured errors (e.g., mean square error and mean absolute error are in the range of 0.0160 - 0.0327 and 0.0912 - 0.1281 MPa, respectively) in the developed model also indicate high efficiency and accuracy of the model in predicting the residual compressive strength of fly ash blended concrete exposed to elevated temperatures.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1074-1083
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• 1993

NC simulation has been used to replace the test cutting of NC machining. Although it can reduce the NC part programming effort, it still has a problem. If any error is found during the simulation, then the part has to be reprogrammed and it is time consumming. This paper presents a method for verifying and editing the NC code after the post-processing without going back to the part programming stage. A data structure and an algorithm to verify and edit the NC code interactively with the aid of graphics is introduced. Z-map method is used for the shaded image display and cross-sectional view display of the macined parts. The method was implemented in a IBM/PC-386 with MS-Windows software, and the multi-window function of the of the MS-Windows is used for the simultaneous editing and verification.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1915-1919
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• 1991

The efficiency of automated assembly line is increased by realizing the automation of each assembly cell, monitoring the line information and developing the real-time line control system it. which production flow is controllable. In this paper, the several modules which are important factors when constructing automated real-time control system, such as, line control S/W module, real-time model change module, error handling module and line production management S/W module, are developed. For developing these important programming modules, real-time control and multi-tasking techniques are integrated. In this paper, operating method of real-time line control in PCB automated assembly line is proposed and for effective control of production line by using multi-tasking technique, proper operating method for relating real-time line control with multi-tasking is proposed by defining the levels of signals and tasks. CIM-Oriented modular programming method considering expandability and flexibility will be added for further research in the future.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.567-572
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• 2002

The equipment of industrial robot in manufacturing and assembly lines has rapidly increased. In order to achieve high productivity and flexibility, it becomes very important to develop the visual feedback control system with Off-Line Programming System(OLPS ). We can save much efforts and time in adjusting robots to newly defined workcells by using Off-Line Programming System. A proposed visual calibration scheme is based on position-based visual feedback. The visual calibration system is composed of a personal computer, an image processing board, a video monitor, and one camera. The calibration program firstly generates predicted images of objects in an assumed end-effector position. The process to generate predicted images consists of projection to screen-coordinates, visible range test, and construction of simple silhouette figures. Then, camera images acquired are compared with predicted ones for updating position and orientation data. Computation of error is very simple because the scheme is based on perspective projection, which can be also expanded to experimental results. Computation time can be extremely reduced because the proposed method does not require the precise calculation of tree-dimensional object data and image Jacobian.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.140-145
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• 2001

The equipment of industrial robot in manufacturing and assembly lines has rapidly increased. In order to achieve high productivity and flexibility, it becomes very important to develop the visual feedback control system with Off-Line Programming System(OLPS). We can save much efforts and time in adjusting robots to newly defined workcells by using Off-Line Programming System. A proposed visual calibration scheme is based on position-based visual feedback. The visual calibration system is composed of a personal computer, an image processing board, a video monitor, and one camera. The calibration program firstly generates predicted images of objects in an assumed end-effector position. The process to generate predicted images consists of projection to screen-coordinates, visible range test, and construction of simple silhouette figures. Then, camera images acquired are compared with predicted ones for updating position and orientation data. Computation of error is very simple because the scheme is based on perspective projection, which can be also expanded to experimental results. Computation time can be extremely reduced because the proposed method does not require the precise calculation of tree-dimensional object data and image Jacobian.

• Management Science and Financial Engineering
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• v.11 no.2
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• pp.19-43
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• 2005

This paper considers a variation of the customer order scheduling problem, and the variation is the case where the machine-job assignment is fixed. We examine the parallel machine environment, and the objective is to minimize the sum of the completion times of the batches. While a machine can process only one job at a time, different machines can simultaneously process different jobs in a batch. The recognition version of this problem is known to be NP-complete in the strong sense even if there exist only two parallel machines. When there are an arbitrary number of parallel machines, we establish three lower bounds and develop a dynamic programming (DP) algorithm which runs in exponential time on the number of batches. We present two simple but intuitive heuristics, SB and GR, and find some special cases where SB and GR generate an optimal schedule. We also find worst case upper bounds on the relative error. For the case of the two parallel machines, we show that GR generates an optimal schedule when processing times of all batches are equal. Finally, the heuristics and the lower bounds are empirically evaluated.

• Water for future
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• v.27 no.4
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• pp.59-67
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• 1994

The objective of this study is to develop a method which can design an optimal pipe network system using nonlinear programming(NLP) technique. The method finds the minimum-cost pipe network while satisfying all the design constraints including hydraulic constraints. The method developed in this study was applied to the Goyang distribution area in Goyang, Kyoungi-do. It has been found in the application and the comparison between the original design and the optimal design of this study that the optimal design method developed in this study does not require the trial-and-error procedure while satisfying the discharge and pressure requirements at the demanding nodes. Therefore, the optimal design method using NLP could be effectively utilized in the practical design considering economic aspect of the pipe network system at the same time.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.10
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• pp.831-837
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• 2002

Scaled SONOS transistors have been fabricated by 0.35$\mu\textrm{m}$ CMOS standard logic process. The thickness of stacked ONO(blocking oxide, memory nitride, tunnel oxide) gate insulators measured by TEM are 2.5 nm, 4.0 nm and 2.4 nm, respectively. The SONOS memories have shown low programming voltages of ${\pm}$8.5 V and long-term retention of 10-year Even after 2 ${\times}$ 10$\^$5/ program/erase cycles, the leakage current of unselected transistor in the erased state was low enough that there was no error in read operation and we could distinguish the programmed state from the erased states precisely The tight distribution of the threshold voltages in the programmed and the erased states could remove complex verifying process caused by over-erase in floating gate flash memory, which is one of the main advantages of the charge-trap type devices. A single power supply operation of 3 V and a high endurance of 1${\times}$10$\^$6/ cycles can be realized by the programming method for a flash-erased type EEPROM.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.237-247
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• 1997

A geometrical inverse heat conduction problem is solved for the infrared scanning cavity detection by the boundary element method using minimal energy technique. By minimizing the kinetic energy of temperature field, boundary element equations are converted to the quadratic programming problem. A hypothetical inner boundary is defined such that the actual cavity is located interior to the domain. Temperatures at hypothetical inner boundary are determined to meet the constraints of mea- surement error of surface temperature obtained by infrared scanning, and then boundary element analysis is peformed for the position of an unknown boundary (cavity). Cavity detection algorithm is provided, and the effects of minimal energy technique on the inverse solution method are investigated by means of numerical analysis.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.