• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2384-2389
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• 2007

The 2nd order response surface method (RSM) has been carried out to get optimum thermal design for enhanced heat transfer on square channel with bleed holes. The RSM was used as an optimization technique with Reynolds-averaged navier-stokes equation. Turbulence model for heat transfer analysis used RNG k-epsilon model. The wall function used enhanced wall function. Numerical local heat transfer coefficients were similar to the experimental tendency. Two design variables such as attack angle of rib (${\alpha}$), rib pitch-to-rib height ratio (p/e) were chosen. Operation condition considered bleeding ratio per bleed hole ($BR_{hole}$). A response surface were constructed by the design variables and operation condition. As a result, adjusted $R^2$ was more than 0.9. Optimization results of various objective function were similar to heat transfer in channel with and without bleed flow. But friction factor was lower than channel without bleed flow.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.387-396
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• 2002

Batch processes are a significant class of processes in the process industry and play an important role in the production of high quality speciality materials. Examples include the production of semiconductors, chemicals, pharmaceuticals, and biochemicals. With on-line sensors connected to most batch processes, massive amounts of data are being collected routinely during the batch on easily measured process variables such as temperatures, pressures, and flowrates. In this paper, multivariate SPC charts for on-line monitoring of the progress of new batches are developed which utilize the information in the on-line measurements in real-time. We propose the formation of statistical model which describes the normal operation of a batch at each time interval during the batch operation. An on-line monitoring scheme based on the proposed method can handle both cross-correlation among process variables at any one time and auto-correlation over time. And the control limits for the monitoring charts are established from sound statistical framework unlike previous researches which use the external reference distribution. The proposed charts perform real-time, on-line monitoring to ensure that the batch is progressing in a manner that will lead to a high-quality product or to detect and indicate faults that can be corrected prior to completion of the batch. This approach is capable of tracking the progress of new batch runs, identifying the time periods in which the fault occurred and detecting underlying cause.

• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.1
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• pp.61-70
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• 2012

A construction project is very costly and takes a long time to make investment and yield profit. For this reason, financial institutions are cautious about financing construction projects. Meanwhile, a construction company needs financing from financial institutions to cover a large expense of a construction project. Thus, there is likely to be a close correlation between financing conditions and business operation of a construction company. To examine the relationship, variables were identified that are related to insolvency of a construction company and changes in financing conditions. The analysis period is between the second quarter of 2001 and the fourth quarter of 2010. Data was retrieved from TS2000 established by Korea Listed Companies Association (KLCA), Statistics Office, and Construction Economy Research Institute of Korea (CERIK). In terms of methodology, VECM (Vector Error Correction Model) was used to analyze dynamic relationship between changes in financing conditions and insolvency of a construction company based on the identified variables. The hypothesis was that changes in financing conditions would significantly affect business of a construction company, but, the analysis did not find a close relation between the two factors. However, it was shown that poor business of a construction company affects financing conditions adversely.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2003.11a
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• pp.249-271
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• 2003

The purpose of the present study is to identify the drying cylinder model in paper plants and to analyze characteristics of process responses for changes in input variables. The model developed in this work is based on actual plant operation data and the steam pressure applied to the cylinder behaves as one the main variables. It is found that heat transfer coefficients from the condensate to the canvas could be represented as empirical relations based on heat conductivities and operation date. The effectiveness of the cylinder model is demonstrated by the measured moisture contents and web temperature. Using transfer functions derived from the cylinder model stability of the drying process is analyzed.

• Journal of Korean Society on Water Environment
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• v.32 no.3
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• pp.253-260
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• 2016

To reduce energy consumption in wastewater treatment plants (WWTPs), renewable energy applications such as small hydropower, solar energy, and wind energy are popular. However, it should be noticed that energy originated from operation of wastewater treatment process can be reduced through optimized operation based on analysis of factors affecting energy. In this research, the relationship to the various operational variables and influent factors was explored using correlation analysis and decision tree algorithm. Due to the non-linear characteristics of the process, it was difficult to find clear linear patterns through correlation analysis. However, decision tree algorithm showed its usefulness in uncovering hidden patterns that consume energy. As operational factors, influent flowrate, the amount of aeration, nitrate recycling pumping rate, and sludge wasting pumping rate were selected as important factors. For environmental factors associated with influent compositions and removal rate, BOD and T-N removal rate were selected as significant factors.

• International Journal of Quality Innovation
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• v.1 no.1
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• pp.89-96
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• 2000

Evolutionary operation (EVOP) is a continuous improvement system which explores a region of process operating conditions by deliberately creating some systematic changes to the process variable levels without jeopardizing the product. It is aimed at securing a satisfactory operating condition in full-scale manufacturing processes, which is generally different from that obtained in laboratory or pilot plant experiments. Information on how to improve the process is generated from a simple experimental design. Traditional EVOP procedures are established on the assumption that the variance of the response variable should be small and stable in the region of the process operation. However, it is often the case that process noises have an influence on the stability of the process. This process instability is due to many factors such as raw materials, ambient temperature, and equipment wear. Therefore, process variables should be optimized continuously not only to meet the target value but also to keep the variance of the response variables as low as possible. We propose a scheme to achieve robust process improvement. As a process performance measure, we adopted the mean square error (MSE) of the replicate response values on a specific operating condition, and used the Kruskal-Wallis test to identify significant differences between the process operating conditions.

• Journal of Environmental Science International
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• v.31 no.7
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• pp.555-567
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• 2022

With the introduction of the tele-monitoring system (TMS) in South Korea, monitoring of the concentration of pollutants discharged from nationwide water quality TMS attachments is possible. In addition, the Ministry of Environment is implementing a smart sewage system program that combines ICT technology with wastewater treatment plants. Thus, many institutions are adopting the automatic operation technique which uses process operation factors and TMS data of sewage treatment plants. As a part of the preliminary study, a multilayer perceptron (MLP) analysis method was applied to TMS data to identify predictability degree. TMS data were designated as independent variables, and each pollutant was considered as an independent variables. To verify the validity of the prediction, root mean square error analysis was conducted. TMS data from two public sewage treatment plants in Chungnam were used. The values of RMSE in SS, T-N, and COD predictions (excluding T-P) in treatment plant A showed an error range of 10%, and in the case of treatment plant B, all items showed an error exceeding 20%. If the total amount of data used MLP analysis increases, the predictability of MLP analysis is expected to increase further.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.694-705
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• 2010

The mutation operation is the main operation in the evolutionary programming which has been widely used for the optimization of real valued function. In general, the mutation operation utilizes both a probability distribution and its parameter to change values of variables, and the parameter itself is subject to its own mutation operation which requires other parameters. However, since the optimal values of the parameters entirely depend on a given problem, it is rather hard to find an optimal combination of values of parameters when there are many parameters in a problem. To solve this shortcoming at least partly, if not entirely, in this paper, we propose a new mutation operation in which the parameter for the variable mutation is theoretically estimated from the self-adaptive perspective. Since the proposed algorithm estimates the scale parameter of the Cauchy probability distribution for the mutation operation, it has an advantage in that it does not require another mutation operation for the scale parameter. The proposed algorithm was tested against the benchmarking problems. It turned out that, although the relative superiority of the proposed algorithm from the optimal value perspective depended on benchmarking problems, the proposed algorithm outperformed for all benchmarking problems from the perspective of the computational time.

• Korean Chemical Engineering Research
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• v.46 no.4
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• pp.739-746
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• 2008

The aim of this study is finding the optimal design parameters and the optimal operation variables of a reactive distillation column. Different from steady state optimization, dynamic optimization makes it possible considering operation ability as well as design problems at process design step. For performing dynamic optimization, dynamic simulation should be done first. If dynamic simulation is already finished, dynamic optimization can be performed with less effort than that of dynamic simulation.Reactive distillation systems involving reaction and separation in a single unit have the potential to reduce capital and operating costs, particularly when reaction have conversion constraint or when azeotropes exist making conventional separation difficult and expensive. This study here present work on the continuous distillation process, the homogeneous catalyzed esterification of methanol and acetic acid, the synthesis of methyl acetate. Based on an equilibrium stage model of a reactive distillation column a dynamic optimization problem was formulated and solved. And the results were verified by performing dynamic simulation and showing the variation of conversion and purity as the variation of the operation variables. As the results of dynamic optimization, this study found optimal feed ratio, reflux ratio and reboiler duty of this system. And as this study applied it to dynamic simulations the dynamic characteristics of a reactive distillation column are showed under optimal operating condition.

• International Journal of Highway Engineering
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• v.7 no.4 s.26
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• pp.21-30
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• 2005

Traffic volume data have been used for the plan, the design, and the operation of highway. Since 1955, traffic survey has been nation- widely carried out at national highway and the regular survey in national highway has been conducted at the intersections of highways. However, it is critical issue to select the priority of the regular survey because it is almost impossible to conduct regular survey at all intersections of national highways. In this study, MCDM(Multiple Criteria Decision Making) using AHP(Analytic Hierarchy Process) was applied to decide the priority of the regular survey. The following standard variables for determining the priority was selected the highway plan variables[AADT, VKT, Peak Hourly Volume, Location of highway from Urban], the highway design variables[Volume(pcu), Directional Traffic Volume, Heavy Vehicle Rate], and the highway operation variables[Speed, Density, V/C]. The standard variables were quantified and normalized. Using the Eigen vector method, the weighted values of each hierarchy based on the pair-wise comparison values from the questionnaire survey were calculated. The selection of the priority of regular survey was dependent on the size of the product of the weighted values for each hierarchy and the normalized values for the standard variables. Finally, the priority of regular survey of the intersections of national highways was determined according to the order in the size of the product of two values.