• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.137-147
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• 2008

Soil Vapor Extraction (SVE) has been extensively used to remove volatile organic compounds (VOCs) from the vadoze zone. In order to investigate the removal mechanism during SVE operation, laboratory modeling experiments were carried out and tailing effect could be observed in later stage of the experiment. Tailing effect means that removal rate of contaminants gets significantly to decrease in later stage of SVE operation. Also, mathematical model simulating the tailing effect was used, which considers rate-limited diffusion in a water film during mass transfer among gas, liquid, and solid phases. Measurement data obtained through the experiment was used as input data of the numerical analyses. Sensitivity analysis was performed to examine the effect of each parameter on required time to reach final target concentration. Finally, it was found that the concentration in the soil phase decreased significantly with a liquid and gas diffusion coefficient larger, actual path length shorter, and water saturation smaller.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.433-437
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• 2006

Recently, mathematical modeling for the activated sludge process is important to design and control of wastewater treatment plant. Nevertheless, there is a lack of information regarding the pathway of substrate utilization between external and internal substrates in biological nutrient removal (BNR). In this research, a new activated sludge model (step growth model) is proposed and compare with ASM No.3. This model structure is consist of five processes; aerobic storage, growth on external substrate and stored intercellular storage compounds (ISCs), endogenous respiration and aerobic respiration of ISCs. The predicted results by the step growth model were more good accordance with the results of oxygen utilization rate (OUR) and TCOD experiment than that of the ASM No.3.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.110-113
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• 2022

Nowadays, breaking through the conventional traffic signal control method based on mathematical optimization, artificial intelligence began to be used in the area. In response to this trend, many studies are ongoing to figure out how to utilize AI technology properly for traffic signal optimization. They just simply focus on which method will work well besides lots of machine learning techniques and abandon the reward function engineering. In many cases, the reward function consists of the average delay of the vehicles in the intersection. However, this may lead to AI's misunderstanding about the traffic signal control: what AI regards as a good situation may not be realistic. Even the reward function itself may not meet the service level. Therefore, this study analyzes the problems of previous reward functions and will suggest how to reward function can be enhanced.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.49-62
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• 2024

In this paper, a sustainable closed-loop supply chain (SCLSC) network model is proposed for domestic mobile phone industry. Economic, environmental and social factors are respectively considered for reinforcing the sustainability of the SCLSC network model. These three factors aim at minimizing total cost, minimizing total amount of CO₂ emission, and maximizing total social influence resulting from the establishment and operation of facilities at each stage of the SCLSC network model. Since they are used as each objective function in modeling, the SCLSC network model can be a multi-objective optimization problem. A mathematical formulation is used for representing the SCLSC network model and a hybrid meta-heuristic approach is proposed for efficiently solving it. In numerical experiment, the performance of the proposed hybrid meta-heuristic approach is compared with those of conventional meta-heuristic approaches using some scales of the SCLSC network model. Experimental results shows that the proposed hybrid meta-heuristic approach outperforms conventional meta-heuristic approaches.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.E
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• pp.1-17
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• 2000

In this study, the concentrations of particulate organic constituents of environmental tobacco smoke(ETS) were determined using an environmental smog chamber, where ETS is the sole source of target compounds. ETS was generated in a 30 ㎥ environmental chamber by a number of different cigarettes, including the Kentucky 1R4F reference cigarette and eight commercial brands. A total of 12 experimental runs was conducted, and target analytes included a group of ETS markers both in vapor and particulate phase and a class of polycylic aromatic hydrocarbos(PAHs) associated with ETS particles. The mass concentrations of PAH in ETS particles were also determined. The average contents of benzo(a) pyrene and benzo(a) anthracene in ETS particles for the commercial brands were 12.8 and 21.5$\mu\textrm{g}$/g, respectively, There values are all somewhat higher than those determined previously by other studies. Results form the chamber study are further used to estimate the average and variability of cigarette yields for target compounds associated with ETS. Finally, ratios of RSP to the surrogate standards of UVPM, FPM and solanesol were calculated for each sample. The average conversion factors factors for the eight commercial brands were 7.3, 38, and 41 for UVPM, EPM, and solanesol, respectively. The UVPM and FPM factors are in good agreement with the recently published values. Whereas there might be a substantial difference in the solanesol content among cigarettes produced in different countries, the variability is somewhat greater than those of UVPM and FPM, Unfortunately, comparison of the PAH yield data from this study with literature values was complicated by a lack of consistency in cigarette smoke generating methodology. Validation of the PAH yields was also difficult due to a lack of information on the ETS related PAH in the literature. From and engineering viewpoint , however, these data on the cigarette yields of ETS components may still provide useful information to studies on the mathematical modeling of indoor air quality management regarding tobacco smoke as a source of interest, or to studies on the assessment of human exposure to ETS.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.574-580
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• 2014

Storage tanks of Carbon dioxide ($CO_2$) carriers utilized for the purpose of carbon capture and storage (CCS) into subsea strata have to undergo a pre-cooling session before beginning to load cryogenic liquid cargos in order to prevent physical and thermal deterioration of tanks which may result from cryogenic $CO_2$ contacting tank walls directly. In this study we propose dynamic model to calculate the tank inflow of $CO_2$ gas injected for precooling process and its dynamic simulation results under proportional-integral control algorithm. We selected two cases in which each of them had one controlled variable (CV) as either the tank pressure or the tank temperature and discussed the results of that decision-making on the pre-cooling process. As a result we demonstrated that the controlling instability arising from nonlinearity and singularity of the mathematical model could be avoided by choosing tank pressure as CV instead of tank temperature.

• Journal of Soil and Groundwater Environment
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• v.13 no.2
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• pp.1-11
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• 2008

Phenanthrene uptake by surfactant sorbed on activated carbon was investigated to recycle of surfactant in washed solution for contaminated soil. The partitioning of phenanthrene to the activated carbon coating with Triton X-100 as a surfactant was also evaluated by a mathematical model. Phenanthrene-contaminated soil (200 mg/kg) was washed in 10 g/L of surfactant solution. Washed phenanthrene in solution was separated by various particle loadings of granular activated carbon through a mode of selective adsorption. Removal of phenanthrene was 99.3%, and surfactant recovery was 88.9% by 2.5 g/L of granular activated carbon, respectively. Phenanthrene uptake by activated carbon was greater than that of phenanthrene calculated by a standard model for a system with one partitioning component. This is accounted for enhanced surface solubilization by hemi-micelles adsorbed onto granular activated carbon. The effectiveness factor is greater than 1 and molar ratio of solubilization to sorbed surfactant is higher than that of liquid surfactant. Results suggest that separation of contaminants and surfactants by activated carbon through washing process in soil is much effective than that of calculated in a theoretical model.

• Korean Chemical Engineering Research
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• v.49 no.5
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• pp.644-651
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• 2011

Storing hydrogen in solid state hydride is one of the best promising methods for the future hydrogen economy. The total performance of such systems depends on the rate at which the amount of mass and heat migration is supplied to solid hydride. Therefore, an accurate modeling of the heat and mass transfer is of prime importance in optimizing the design of such systems. In this work, Hydrogen storage in Pt-CNTs hydrogen reactor has been intensively investigated by solving 2 dimensional mathematical models. Using a CFD computer software, systematic studies have been performed to elucidate the effect of heat and mass transfer during hydrogen charging periods. It was revealed that the optimized design of hydrogen storage vessel can prevent the increase of system temperature and the charging time due to the convective cooling effects inside the vessels at even high charging pressure. Because none has reported the critical issues of heat and mass transfer for CNT based hydrogen storage system, this work can support the first insight of the optimal design for solid state hydrogen storage system based on CNT in the near future.

• Journal of the Korea Concrete Institute
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• v.15 no.1
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• pp.25-34
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• 2003

The degradation of reinforced concrete (RC) structures due to physical and chemical attacks has been a major issue in construction engineering. Deterioration of RC structures by chloride attack followed by reinforcement corrosion is one of the serious problems. An objective of this study is to develop a form of mathematical model of chloride ingress into concrete. In order to overcome some limits of the previous approaches, a chloride ingress model, consisting of chloride solution intrusion through the capillary pore and chloride ion diffusion through the pore water, was proposed. Moreover, the variability of chloride ion diffusivity due to the degree of hydration of cement, relative humidity in pore, exposure condition, and variation of chloride binding, was considered in the model. In order to verify the proposed model, the results predicted by the proposed model were compared with analysis results of Life-365, a computer program for predicting the service life of reinforced concrete structures exposed to chlorides. In conclusion, the proposed model would be promising to predict the chloride ion profile and to estimate the service life of RC structures.