• Journal of Korean Society on Water Environment
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• v.23 no.2
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• pp.206-215
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• 2007

The objective of this study was to establish the optimal system operating strategies for nitrogen and phosphorus removal through model simulation system built for advanced wastewater treatment targeting on simultaneous temporal/special phase isolation BNR process. The simulation system was built with unit process modules using object modules in GPS-X code. The system was well verified by field experiment data. Simulation study was carried out to investigate performance response to design and operation parameters, i.e. hydraulic retention time (HRT), solids retention time (SRT), and cycle time. The process operated at HRTs of 10~15 hours, longer SRTs, and cycle time of 2 hours showed optimal removal of nitrogen. The HRTs of 10~15 hours, SRTs of 20~25 days, and longer cycle time was optimal for phosphorus removal. Both simulation and field studies showed that optimal operating strategies satisfying both the best nitrogen and phosphorus removals include HRTs ranged 10~15 hours, SRTs ranged 20~25 days, and cycle times of 4~8 hours. The simulation system with modularization of generalized components in BNR processes was, therefore, believed to be a powerful tool for establishing optimal strategies of advanced wastewater treatment.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.5 s.170
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• pp.103-112
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• 2005

This paper presents one-axis high precision scanning system and illustrates the design of modified $X-Y-{\theta}$ stage as a tracker using VCM and commercialized air bearings for it. The scanning system for 100nm resolution is composed of the 3-axis stage and one axis long stroke linear motor stage as a follower. In this study a previous proposed and presented structure of VCM for the fine stage is modified. The tracker has 3 DOF($X-Y-{\theta}$ motions by four VCM actuators which are located on the same plane. So 4 actuating forces are suggested and designed to create least pitch and roll motions. This article will show about the design especially about optimal design. The design focus of this fine stage is to have high acceleration to accomplish high throughput. The optimal design of maximizing acceleration is performed in restrained size. The most sensitive constraint of this optimal design is heat dissipation of coil. There are 5 design variables. Because the relationship between design variables and system parameters are quite complicated, it is very difficult to set design variables manually. Due to it, computer based optimal design procedure using MATLAB is used. Then, this paper also describes the procedures of selecting design variables for the optimal design and a mathematical formulation of the optimization problem. Based on the solution of the optimization problem, the final design of the stage is also presented. The results can be verified by MAXWELL. The designed stage has the acceleration of about 5 $m/s^{2}$ with 40kg total mass including wafer chuck and interferometer mirror. And the temperature of coil is increased $50^{\circ}C$. In addition, the tracker is controlled by high precision controller system with HP interferometer for it and linear scaler for the follower. At that time, the scanning system has high precision resolution about 5nm and scanning resolution about 40nm in 25mm/s constant speed

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.4
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• pp.56-62
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• 2013

The system analysis and design program of the liquid rocket engine has been developed for preliminary conceptual design process. The program analyzes the engine system and obtains optimal design variables by optimization methods such as genetic algorithm for the higher specific impulse and thrust to weight ratio using given input parameters and requirements. For the users' convenience, the GUI has been offered. The 3-dimensional model for the visualization of results has been interconnected with the CATIA program. The results are expected to be applied to the design process of the space launch vehicle for the analysis and selection of the propulsion system.

• Applied Chemistry for Engineering
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• v.29 no.6
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• pp.765-771
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• 2018

In this study, the optimization of carbonization conditions in manufacturing processes was performed to improve the absorption performance of sewage sludge based sorbent used for treating $H_2S$ out of all odorous substances generated by various environmental facilities. Adsorbents applied were manufactured from the sewage treatment plant under different carbonization conditions, such as temperature and heating rate, and the correlation between the adsorption performance and physical properties of the adsorbents was verified. As a result, the adsorption performance of sludge at $900^{\circ}C$ with a heating rate of $10^{\circ}C/min$ was the best, and the SEM and BET analysis revealed that specific surface area and characteristics of pore (size, volume) were major parameters for the adsorption. In addition, the effect of K ions used for improving the adsorption performance of the optimum carbonization condition sorbent was insignificant for the sewage sludge based sorbent.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1393-1406
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• 2018

In this study, three parameters (Pressure ($X_1$), Airflow rate ($X_2$), Operation time ($X_3$)) were experimentally designed and the predicted model and optimal conditions were established by using the terminal rise velocity of the microbubbles as the response value. The polynomial regression analysis showed that the optimum value for the terminal rise velocity at the Pressure ($X_1$) of 4.5 bar, Airflow rate ($X_2$) of 3.3 L/min and Operation time ($X_3$) of 2.2 min was 5.14 cm/min ($85.7{\mu}m/sec$). Also, the highest microbubble diameter size distribution in the range of 2 to $5{\mu}m$ and 25 to $50{\mu}m$ was confirmed by using a laser particle counting apparatus.

• Journal of Drive and Control
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• v.16 no.3
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• pp.51-58
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• 2019

The objective of this study was to investigate a simulation technology for the AM field based on ANSYS Inc.. The introduction of metal 3D printing AM process, and the examining of the present status of AM process simulation software, and the AM process simulation processor were done in the previous study (part 1). This present study (part 2) examined the use of the AM process simulation processor, presented in Part 1, through direct execution of Topology Optimization, Ansys Workbench, Additive Print and Additive Science. Topology Optimization can optimize additive geometry to reduce mass while maintaining strength for AM products. This can reduce the amount of material required for additive and significantly reduce additive build time. Ansys Workbench and Additive Print simulate the build process in the AM process and optimize various process variables (printing parameters and supporter composition), which will enable the AM to predict the problems that may occur during the build process, and can also be used to predict and correct deformations in geometry. Additive Science can simulate the material to find the material characteristic before the AM process simulation or build-up. This can be done by combining specimen preparation, measurement, and simulation for material measurements to find the exact material characteristics. This study will enable the understanding of the general process of AM simulation more easily. Furthermore, it will be of great help to a reader who wants to experience and appreciate AM simulation for the first time.

• Earthquakes and Structures
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• v.17 no.2
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• pp.143-162
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• 2019

Motivated by a simpler and more compact hybrid active tuned mass damper (ATMD) system with wide frequency spacing (i.e., high robustness) but not reducing the effectiveness using the least number of ATMD units, the active tuned tandem mass dampers (ATTMD) have been proposed to attenuate undesirable oscillations of structures under the ground acceleration. Likewise, it is expected that the frequency spacing of the ATTMD is comparable to that of the active multiple tuned mass dampers (AMTMD) or the multiple tuned mass dampers (MTMD). In accordance with the mode generalised system in the specific vibration mode being controlled (simply referred herein to as the structure), the closed-form expression of the dimensionless displacement variances has been derived for the structure with the attached ATTMD. The criterion for the optimum searching may then be determined as minimization of the dimensionless displacement variances. Employing the gradient-based optimization technique, the effects of varying key parameters on the performance of the ATTMD have been scrutinized in order to probe into its superiority. Meanwhile, for the purpose of a systematic comparison, the optimum results of two active tuned mass dampers (two ATMDs), two tuned mass dampers (two TMDs) without the linking damper, and the TTMD are included into consideration. Subsequent to work in the frequency domain, a real-time Simulink implementation of dynamic analysis of the structure with the ATTMD under earthquakes is carried out to verify the findings of effectiveness and stroke in the frequency domain. Results clearly show that the findings in the time domain support the ones in the frequency domain. The whole work demonstrates that ATTMD outperforms two ATMDs, two TMDs, and TTMD. Thereinto, a wide frequency spacing feature of the ATTMD is its highlight, thus deeming it a high robustness control device. Furthermore, the ATTMD system only needs the linking dashpot, thus embodying its simplicity.

• Journal of IKEEE
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• v.23 no.2
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• pp.529-533
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• 2019

Combined cycle power plants are often used to produce power. These days prediction of power plant output based on operating parameters is a major concern. This paper presents an approach to using computational intelligence technique to predict the output power of combined cycle power plant. Computational intelligence techniques have been developed and applied to many real world problems. In this paper, tree architectures of fuzzy neural networks are considered to predict the output power. Tree architectures of fuzzy neural networks have an advantage of reducing the number of rules by selecting fuzzy neurons as nodes and relevant inputs as leaves optimally. For the optimization of the networks, two-step optimization method is used. Genetic algorithms optimize the binary structure of the networks by selecting the nodes and leaves as binary, and followed by random signal-based learning further refines the optimized binary connections in the unit interval. To verify the effectiveness of the proposed method, combined cycle power plant dataset obtained from the UCI Machine Learning Repository Database is considered.

• Korean Journal of Chemical Engineering
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• v.35 no.11
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• pp.2241-2255
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• 2018

RSM methodology was applied to present mathematical models for the fabrication of polyvinylidene fluoride (PVDF) dual-layer hollow fibers in membrane distillation process. The design of experiments was used to investigate three main parameters in terms of polymer concentration in both outer and inner layers and the flow rate of dope solutions by the Box-Behnken method. According to obtained results, the optimization was done to present the proper membrane with desirable properties. The characteristics of the optimized membrane (named HF-O) suggested by the Box-Behnken (at the predicted point) showed that the proposed models are strongly valid. Then, a morphology study was done to modify the fiber by a combination of three types of a structure such as macro-void, sponge-like and sharp finger-like. It also improved the hydrophobicity of outer surface from 87 to $113^{\circ}$ and the mean pore size of the inner surface from 108.12 to 560.14 nm. The DCMD flux of modified fiber (named HF-M) enhanced 62% more than HF-O when it was fabricated by considering both of RSM and morphology study results. Finally, HF-M was conducted for long-term desalination process up to 100 hr and showed stable flux and wetting resistance during the test. These stepwise approaches are proposed to easily predict the main properties of PVDF dual-layer hollow fibers by valid models and to effectively modify its structure.

• Korean Journal of Materials Research
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• v.30 no.12
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• pp.650-654
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• 2020

A combination of Polycarbonate (PC) material and Polymethylmethacrylate (PMMA), fabricated using an injection molding machine, has been investigated to determine its advantages, as studied in Ref. 1). This paper aims to investigate the optimization of PMMA/PC blend for both tensile yield strength and impact strength. Furthermore, interaction effects of process conditions on mechanical properties including tensile yield strength and impact strength of PMMA/PC blend by injection molding process are interpreted in this study. Tensile and impact specimens are designed following ASTM, type V, and are fabricated by injection molding process. The processing conditions such as melt temperature, mold temperature, packing pressure, and cooling time are applied; each factor has three levels. As a result, in comparison with optimization of separated responses, mechanical properties of PMMA/PC are found to decrease when optimizing both tensile and impact strengths simultaneously. The melt temperature is found to be the most significant interaction parameter with the mold temperature and packing pressure. In addition, there is more interaction between the mold temperature and cooling time. This investigation provides a useful understanding of the control of injection molding processing of polymer blends in optical application.