• 산업기술연구
• /
• 제16권
• /
• pp.157-168
• /
• 1996

The deposition characteristics of ultrafine $SiO_2$ particles were investigated in a tube furnace reactor theoretically and experimentally controlling tube wall temperature in deposition zone. The model equations such as mass and energy balance equations and aerosol dynamic equations inside reactor and deposition tube were solved to predict the particle growth and deposition. The particle size and deposition efficiencies of $SiO_2$ particles were calculated, changing the process conditions such as tube furnace setting temperature, total gas flow rate inlet $SiCl_4$ concentration and were compared with the experimental results.

• 임산에너지
• /
• 제22권1호
• /
• pp.37-43
• /
• 2003

천연셀룰로오스의 탄화과정에서 탄화수율에 영향을 미치는 인자는 탄화온도, 승온속도 및 탄화로 내의 분위기를 들 수 있다. 일반적으로 탄화수율을 높이기 위해서는 탄화목표온도를 낮추고, 승온속도를 느리게 하면 탄화로의 분위기를 불활성가스의 조건에서 탄화수율이 높아진다고 보고되어 있다. 본 연구에서는 탄화조건 중에서 가장 유동성을 가지고 있는 승온속도를 조절하고, 탈수촉매제로서 황산을 첨가함으로서 탄화수율의 향상과 탄화과정에서 천연셀룰로오스를 재료로 하여 탄화특성에 대하여 조사하였다. 그 결과 황산무처리시료에 대하여는 승온속도가 증가함에 따라 수율이 상당히 감소하였지만 황산처리 시료는 승온속도가 증가하여도 수율 감소 폭이 크지 않았다. 본 연구의 결과에서 탄화과정에 있어서 승온속도의 조절과 적당한 탈수제의 첨가는 탄화재료의 수율 향상과 탄화시간 단축에 유용한 기초자료가 될 것으로 생각된다.

• 한국진공학회:학술대회논문집
• /
• 한국진공학회 2014년도 제46회 동계 정기학술대회 초록집
• /
• pp.430.1-430.1
• /
• 2014

According to advanced nanotechnology in the field of biomedical engineering, many studies of the interaction between topography of surfaces and cellular responses have been focused on nanostructure. In order to investigate this interaction, it is essential to make well-controlled nanostructures. Electron beam lithography (EBL) have been considered the most typical processes to fabricate and control nano-scale patterns. In this work, $TiO_2$ nanowire array was fabricated with hybrid process (top-down and bottom-up processes). Nanodot arrays were patterned on the substrate by EBL process (top-down). In order to control the spacing between nanodots, we optimized the EBL process using Poly(methyl methacrylate) (PMMA) as an electron beam resist. Metal lift-off was used to transfer the spacing-controlled nanodots as a seed pattern of $TiO_2$ nanowire array. Au or Sn nanodots which play an important role for catalyst using Vapor-Liquid-Solid (VLS) method were patterned on the substrate through the lift-off process. Then, the sample was placed in the tube furnace and heated at the synthesis temperature. After heat treatment, $TiO_2$ nanowire array was fabricated from the nanodots through VLS method (bottom-up). These results of spacing-controlled nanowire arrays will be used to study the interaction between nanostructures and cellular responses in our next steps.

• 한국데이타베이스학회:학술대회논문집
• /
• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
• /
• pp.261-270
• /
• 1999

Sintering transforms powdered ore into lumped ore so that the latter can be used in a blast furnace. The powdered ore combined with coke and other materials is loaded into a container and moved along by a pallet while the ignited coke bums. The speed by which the pallet moves determines how much sintering takes place. Since the process is complicated and lacks an accurate mathematical model, human operators manually control the speed by monitoring various factors in the plant. In this paper, we propose a neural network-based pallet speed controller which copies human operator knowledge. Actual process data were collected from a sintering plant fer eight months and preprocessed to remove noisy and inconsistent data. A multilayer perceptron was trained using a back-propagation learning algorithm. In on-line testing at the sinter plant, the proposed model reliably controlled pallet speed during normal operation without the help of human operators. Moreover, the duality and productivity was as good as with human operators.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
• /
• pp.261-270
• /
• 1999

Sintering transforms powdered ore into lumped ore so that the latter can be used in a blast furnace. The powdered or combined with coke and other materials is loaded into a container and moved along by a pallet while the ignited coke burns. The speed by which the pallet moves determines how much sintering takes place. Since the process is complicated and lacks an accurate mathematical model, human operators manually control the speed by monitoring various factors in the plant. In this paper, we propose a neural network-based pallet speed controller which copies human operator knowledge. Actual process data were collected from a sintering plant for eight months and preprocessed to remove noisy and inconsistent data. A multilayer perceptron was trained using a back-propagation learning algorithm. In on-line testing at the sinter plant, the proposed model reliably controlled pallet speed during normal operation without the help of human operators. Moreover, the quality and productivity was as good as with human operators.

• Environmental Engineering Research
• /
• 제25권3호
• /
• pp.335-344
• /
• 2020

This work describes highly efficient recovery and selective leaching of Zn from electric arc furnace dust (EAFD) with different physicochemical properties, induced by acid leaching at ambient conditions. The chemical compositions, mineralogical phases, and particle sizes of the EAFDs were analyzed and compared. The effects of leaching time, liquid/solid ratio, acid type, and acid concentration on the selective leaching of Zn were also studied. The EAFD with high Fe/Zn ratio (> 1, EAFD₃) was richer in ZnFe₂O₄ and exhibited larger particle size than samples with low Fe/Zn ratio (< 1, EAFD_1,2). ANOVA analysis revealed that the Fe/Zn ratios of the EAFDs also have a significant effect on Zn extraction (p < 0.005). Selective leaching of Zn with minimum Fe dissolution was obtained at pH > 4.5, regardless of other parameters or sample properties. The maximum Zn extraction rate obtained by the pH control was over 97% for EAFD₁ and EAFD₂, 76% for EAFD₃, and 80% for EAFD₄. The present results confirm that the Fe/Zn ratio can be used to identify EAFDs that permits facile and high-yield Zn recovery, and pH can be used as a process control factor for selective leaching of Zn regardless of any differences in the properties of the EAFD sample.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
• /
• pp.185-188
• /
• 1996

In this paper, a fuzzy PNN algorithm is proposed to estimate the structure and parameters of fuzzy model, using the PNN based on GMDH algorithm. New algorithm uses PNN algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the leastsquare method in order to identify the optimal consequence parameters. Both time series data for gas furnace and data for wastewater treatment process are used for the purpose of evaluating the performance of the fuzzy PNN. The results show that the proposed technique can produce the fuzzy model with higher accuracy than other works achieved previously.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
• /
• pp.493-495
• /
• 2005

This paper proposes a swarm-based fuzzy system modeling technique for coke oven combustion control diagnosis. The coke plant produces coke for the blast furnace plant in steel making process by charging coal into oven and supplying gas to carbonize it. A conventional mathematical model for coke oven combustion control has been used to control the amount of gas input, but it does not work well because of highly nonlinear feature of coke plant. To solve this problem, swarm-based fuzzy system modeling technique is suggested to construct a diagnosis model of coke oven combustion control. Based on the measured input-output data pairs, the fuzzy rules are generated and the parameters are tuned by the PSO(Particle Swarm Optimizer) to increase the accuracy of the fuzzy system is operated. This system computes the proper amount of gas input taking the operation conditions of coke oven into account, and compares the computed result with the supplied gas input.

• 한국분말재료학회지
• /
• 제21권5호
• /
• pp.371-376
• /
• 2014

In this study, modified catalytic chemical vapor deposition (CCVD) method was applied to control the CNTs (carbon nanotubes) growth. Since titanium (Ti) substrate and iron (Fe) catalysts react one another and form a new phase ($Fe_2TiO_5$) above $700^{\circ}C$, the decrease of CNT yield above $800^{\circ}C$ where methane gas decomposes is inevitable under common CCVD method. Therefore, we synthesized CNTs on the Ti substrate by dividing the tube furnace into two sections (left and right) and heating them to different temperatures each. The reactant gas flew through from the end of the right tube furnace while the Ti substrate was placed in the center of the left tube furnace. When the CNT growth temperature was set $700/950^{\circ}C$ (left/right), CNTs with high yield were observed. Also, by examining the micro-structure of CNTs of $700/950^{\circ}C$, it was confirmed that CNTs show the bamboo-like structure.

• 제어로봇시스템학회논문지
• /
• 제15권6호
• /
• pp.634-640
• /
• 2009

The plate manufacturing processes are composed of the reheating furnace, finishing mill, cooling process and hot leveling. The finishing rolling mill (FM) as a reversing mill has produced the plate steel through multiple pass rolling. The automatic gauge control (AGC) is employed to maintain the thickness tolerance. The high grade products are forming greater parts of the manufacturing and customers are requiring strict thickness margin. For this reason, the advanced AGC method is required instead of the conventional AGC based on the PI control. To overcome the slow response performance of the conventional AGC and the thickness measurement delay, a fuzzy AGC based on the thickness deviation and its trend is proposed in this paper. An embedded controller with the fuzzy AGC has been developed and implemented at the plate mill in POSCO. The fuzzy AGC has dynamically controlled the roll gap in real time with the programmable logic controller (PLC). On line tests have been performed for the general and TMCP products. As the results, the thickness deviation range (maximum - minimum of the inner plate) is averagely from 0.3 to 0.1 mm over the full length. The fuzzy AGC has improved thickness deviation and completely satisfied customer needs.