• Journal of Environmental Health Sciences
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• v.30 no.2
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• pp.84-91
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• 2004

Biological nutrient removal(BNR) from wastewater was performed by adopting various process configurations. The simultaneous biological organics, phosphorus and nitrogen removal of synthetic wastewater was investigated in a sequencing batch biofilm reactor (SBBR). The other reactor was operating as a reference, without biofilm being added. The cycling time in SBR and SBBR was adjusted at 12 hours and then certainly included anaerobic and aerobic conditions. Both systems has been operated with a stable total organic carbon(TOC), nitrogen and phosphorus removal performance for over 90 days. Average removal efficiencies of TOC and total nitrogen were 83% and 95%, respectively. The nitrification rate in SBR was higher than that in SBBR. On the contrary, the denitrification rate in SBBR was higher than that in SBR. The phosphorus release was occurred in SBBR, however, not in SBR because of the inhibition effect of NO$_3$$^{[-10]}$ .

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.299-320
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• 2011

The overhead of processing fine-grain tasks on a grid induces the need for batch processing or task group deployment in order to minimise overall application turnaround time. When deciding the granularity of a batch, the processing requirements of each task should be considered as well as the utilisation constraints of the interconnecting network and the designated resources. However, the dynamic nature of a grid requires the batch size to be adaptable to the latest grid status. In this paper, we describe the policies and the specific techniques involved in the batch resizing process. We explain the nuts and bolts of these techniques in order to maximise the resulting benefits of batch processing. We conduct experiments to determine the nature of the policies and techniques in response to a real grid environment. The techniques are further investigated to highlight the important parameters for obtaining the appropriate task granularity for a grid resource.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.56.6-56
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• 2002

1. Introduction 2. Process description 2.1 Process description 2.2 Assumption 3. Mathematical model 3.1 MILP model for cintinuous part 3.2 LP model for batch part 4. Exapmles and Results 5. Conclusion. Acknowledgement. Reference.

• Biotechnology and Bioprocess Engineering:BBE
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• v.7 no.5
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• pp.275-280
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• 2002

In order to control glucose concentration during fed-batch culture for antibiotic production, we applied so called “software sensor” which estimates unmeasured variable of interest from measured process variables using software. All data for analysis were collected from industrial scale cultures in a pharmaceutical company. First, we constructed an estimation model for glucose feed rate to keep glucose concentration at target value. In actual fed-batch culture, glucose concentration was kept at relatively high and measured once a day, and the glucose feed rate until the next measurement time was determined by an expert worker based on the actual consumption rate. Fuzzy neural network (FNN) was applied to construct the estimation model. From the simulation results using this model, the average error for glucose concentration was 0.88 g/L. The FNN model was also applied for a special culture to keep glucose concentration at low level. Selecting the optimal input variables, it was possible to simulate the culture with a low glucose concentration from the data sets of relatively high glucose concentration. Next, a simulation model to estimate time course of glucose concentration during one day was constructed using the on-line measurable process variables, since glucose concentration was only measured off-line once a day. Here, the recursive fuzzy neural network (RFNN) was applied for the simulation model. As the result of the simulation, average error of RFNN model was 0.91 g/L and this model was found to be useful to supervise the fed-batch culture.

• Elastomers and Composites
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• v.46 no.1
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• pp.60-69
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• 2011

The various types of PBA/PMMA composite latexes were prepared by $2.1\;{\mu}m$ PBA seeded batch and seeded semi-continuous dispersion polymerization. The morphology of the PBA/PMMA composite latexes by seeded batch process was found to be closely dependant on the weight ratios of methanol/water in polymerization medium and of PBA seed/MMA at the second stage. In general, egg, snowman, confetti, peanut-like nonspherical composite latex particles were formed with increasing amount of water and MMA as a result of the occurrence of the phase separation between PBA seed and PMMA. The morphology of the PBA/PMMA composite latexes by seeded semi-continuous process was controlled by the addition time of MMA, especially, spherical shaped core(PBA)/shell(PMMA) composite latex particles were prepared under the monomer-starved condition at the second stage.

• 한국초전도학회:학술대회논문집
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• v.15
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• pp.65-65
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• 2005

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1028-1031
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• 1996

Dynamic scheduling is very important in constructing CIM and improving productivity of chemical processing systems. Computation at the scheduling level requires mostly a long time to generate an optimal schedule, so it is difficult to immediately respond to actual process events in real-time. To solve these problems, we developed dynamic scheduling algorithms such as DSMM(Dynamic Shift Modification Method), PUOM(Parallel Unit Operation Method) and UVVM(Unit Validity Verification Method). Their main functions are to minimize the effects of unexpected disturbances such as process time variations and unit failure, to predict a makespan of the updated dynamic schedule and to modify schedule desirably in real-time responding to process time variations. As a result, the algorithms generate a new pertinent schedule in real-time which is close to the original schedule but provides an efficient way of responding to the variation of process environment. Examples in a shampoo production batch process illustrate the efficiency of the algorithms.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.341-345
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• 2001

New technoloty called microcellular foaming process was developed at MIT in 1980's. Although it has many good things, it could not be used it all sides of manufacturing plastics. Because it takes a long time for making foamed goods. So microcellular foaming injection molding process appeared to solve this problem. The first purpose of this research is to measure the impact strength as foaming magnitude of microcellular foamed plastics. There are two methods such as batch process and microcellular foaming injection molding process in making foamed plastics. According to the experimental data, the impact strength of each specimen was measured to find out the influence of foaming magnitude of microcellular foamed plastics.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.615-619
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• 2004

This paper considers a variation of customer order scheduling problems. The variation is the case where machine-job assignment is fixed, and the objective is to minimize the sum of the completion times of the batches. In customer order scheduling problems, jobs are dispatched in batches. While a machine can process only one job at a time, multiple machines can simultaneously process jobs in a batch. We first establish a couple of lower bounds. Then, we develop a dynamic programming (DP) algorithm that runs in exponential time on the number of batches when there exist two machines. For the same problem with arbitrary number of machines, we present two simple heuristics, which use simple scheduling rules such as shortest batch first and shortest makespan batch first rules. Finally, we empirically evaluate the heuristics.