• Transactions of the Korean hydrogen and new energy society
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• v.21 no.5
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• pp.425-434
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• 2010

Integrated gasification combined cycle (IGCC) is an efficient and environment-friendly power generation system which is capable of burning low-ranked coals and other renewable resources such as biofuels, petcokes and residues. In this study some process modeling on a conceptual entrained flow gasifier was conducted using the ASPEN Plus process simulator. This model is composed of three major steps; initial coal pyrolysis, combustion of volatile components, and gasification of char particles. One of the purposes of this study is to develop an effective and versatile simulation model applicable to numerous configurations of coal gasification systems. Our model does not depend on the hypothesis of chemical equilibrium as it can trace the exact reaction kinetics and incorporate the residence time calculation of solid particles in the reactors. Comparisons with previously reported models and experimental results also showed that the predictions by our model were pretty reasonable in estimating the products and the conditions of gasification processes. Verification of the accuracy of our model was mainly based upon how closely it predicts the syngas composition in the gasifier outlet. Lastly the effects of change oxygen are studied by sensitivity analysis using the developed model.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.173-179
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• 2019

Cryogenic air separation unit produces various gases such as $N_2$, $O_2$, and Ar by liquefying air. The process also varies with diverse production conditions. The one for SNG production among them has lower efficiency compared to other air separation unit because it requires ultrapure $O_2$ with purity not lower than 99.5%. Among factors that reduce the efficiency of air separation unit, power consumption due to compress air and heat duty of double column were representatives. In this study, simulation of the air separation unit for SNG production was carry out by using ASEPN PLUS. In the results of the simulation, 18.21 kg/s of at least 99.5% pure $O_2$ was produced and 33.26 MW of power was consumed. To improve the energy efficiency of air separation unit for SNG production, the sensitivity analysis for power consumption, purities and flow rate of $N_2$, $O_2$ production in the air separation unit was performed by change of air boosting ratios. The simulated model has three types of air with different pressure levels and two air boosting ratio. The air boosting ratio means flow rate ratio of air by recompressing in the process. As increasing the first air boosting ratio, $N_2$ flow rate which has purity of 99.9 mol% over increase and $O_2$ flow rate and purity decrease. As increasing the second air boosting ratio, $N_2$ flow rate which has purity of 99.9 mol% over decreases and $O_2$ flow rate increases but the purity of $O_2$ decreases. In addition, power consumption of compressing to increase in the two cases but results of heat duty in double column were different. The heat duty in double column decreases as increasing the first air boosting ratio but increases as increasing the second air boosting ratio. According to the results of the sensitivity analysis, the optimum air boosting ratios were 0.48 and 0.50 respectively and after adjusting the air boosting ratios, power consumption decreased by approximately 7% from $0.51kWh/O_2kg$ to $0.47kWh/O_2kg$.

• Korean Chemical Engineering Research
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• v.54 no.2
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• pp.248-254
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• 2016

Efficacious wastewater treatment is essential for increasing sewage sludge volume and implementing strict environmental regulations. The operation cost of sludge treatment amounts up to 50% of the total costs for wastewater treatment plants, therefore, an economical sludge destruction method is crucially needed. Amid several destruction methods, wet air oxidation (WAO) can efficiently treat wastewater containing organic pollutants. It can be used not only for sludge destruction but also for useful by-product production. Volatile fatty acids (VFAs), one of many byproducts, is considered to be an important precursor of biofuel and chemical materials. Its high reaction condition has instituted the study of gravity pressure reactor (GPR) for an economical process of WAO to reduce operation cost. Simulation of subcritical condition was conducted using Aspen Plus with predictive Soave-Redlich-Kwong (PSRK) equation of state. Conjointly, simulation analysis for GPR depth, oxidizer type, sludge flow rate and oxidizer injection position was carried out. At GPR depth of 1000m and flow rate of 2 ton/h, the conversion and yield of VFAs were 92.02% and 0.17g/g, respectively.

• Journal of the Korean Solar Energy Society
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• v.28 no.2
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• pp.64-69
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• 2008

As the grid-connected photovoltaic power conditioning systems (PVPCS) are installed in many residential areas, these have raised potential problems of network protection on electrical power system. One of the numerous problems is an Islanding phenomenon. There has been an argument that it may be a non-issue in practice because the probability of islanding is extremely low. However, there are three counter-arguments: First, the low probability of islanding is based on the assumption of 100% power matching between the PVPCS and the islanded local loads. In fact, an islanding can be easily formed even without 100% power matching (the power mismatch could be up to 30% if only traditional protections are used, e.g. under/over voltage/frequency). The 30% power-mismatch condition will drastically increase the islanding probability. Second, even with a larger power mismatch, the time for voltage or frequency to deviate sufficiently to cause a trip, plus the time required to execute a trip (particularly if conventional switchgear is required to operate), can easily be greater than the typical re-close time on the distribution circuit. Third, the low-probability argument is based on the study of PVPCS. Especially, if the output power of PVPCS equals to power consumption of local loads, it is very difficult for the PVPCS to sustain the voltage and frequency in an islanding. Unintentional islanding of PVPCS may result in power-quality issues, interference to grid-protection devices, equipment damage, and even personnel safety hazards. Therefore the verification of anti-islanding performance is strongly needed. In this paper, improved RPV method is proposed through considering power quality and anti-islanding capacity of grid-connected single-phase PVPCS in IEEE Std 1547 ("Standard for Interconnecting Distributed Resources to Electric Power Systems"). And the simulation results are verified.

• Journal of Power Electronics
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• v.5 no.2
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• pp.129-141
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• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• KIEAE Journal
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• v.15 no.6
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• pp.101-109
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• 2015

Purpose: Glazing and shading devices influence a lot on the thermal and visual environment in office buildings. Solar heat and daylight are contrary concept, therefore proper arrangement of thermal and optical performance is needed when designing a glazing and shading devices. The purpose of this study is to examine the conditions of the glazing and shading devices available for promoting the reduction of cooling loads + lighting loads and the improvement in thermal comfort and visual comfort for the summer season in an office building installed with venetian blind. Method: This study established 12 simulation cases which have different glazings and the positions of venetian blind for evaluating different thermal and optical performance. And by using EnergyPlus v8.1 and Window v7.2 program, we quantitatively analyzed cooling loads + lighting loads, thermal comfort and visual comfort in an office building installed with the glazing and shading devices. Result: Consequently, Case 9(Double Low-E+Exterior Blind) is the best arrangement of solar heat gain and daylight influx, thereby becomes the most excellent case of reducing cooling+lighting loads(46.8%) and simultaneously becomes the enhancement case in thermal comfort. Also, DGI(Daylight glare index) under clear sky conditions in summer was evaluated to be 19.6, and thereby satisfied the recommendation level of allowing visual comfort.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.550-564
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• 2020

Distillation columns are one of the main equipment used for the separation of chemical components in petrochemical process design. However, in spite of the efficient operation in wide range, and the advantage of data collection for equipment verification, the distillation columns are inherently known for high energy consumption and capital cost. Hence, the trade-off analysis needs to be done between investment cost and operation cost to develop the most economical distillation columns. This study was conducted using Aspen Plus, a popular process simulation program, in the pursuit of broad application by as many process engineers as possible. In this paper, design variables for optimization of distillation columns were defined to improve emphatically the design quality with reducing erratic practice of many engineers. In addition, by eliminating unnecessary reviewing step and establishing systematic and efficient procedures, the amount of time for design and human resources were minimized. Aspen Process Economic Analyzers (APEA) program was introduced in order to calculate the investment cost reliably, and the efficient systematic procedure for utilization of APEA was established.

• Korean Chemical Engineering Research
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• v.43 no.4
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• pp.467-473
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• 2005

Liquid phase nitrous oxide ($N_2O$) contains air, carbon monoxide, water, carbon dioxide and NOx as main impurities. It is known to be very dangerous to obtain a very pure $N_2O$ product by using solidification at low temperature. In this study a new method to obtain a high purity of $N_2O$ product based on a continuous distillation process was introduced. For the modeling of the continuous distillation process to obtain a product having a purity over 99.999％ of $N_2O$ stream, Intalox wire gauze packing- No. SCH-80S gauze packing column was used. Peng-Robinson equation of state was used for the modeling of the continuous distillation process and refrigeration system. Computational results performed in this work showed a good agreement with Aspen Plus simulation results.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.3
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• pp.626-637
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• 2014

On ship, especially on large ship, the flexure deformation between Master (M)/Slave (S) Inertial Navigation System (INS) is a key factor which determines the accuracy of the integrated system of M/S INS. In engineering this flexure deformation will be increased with the added ship size. In the M/S INS integrated system, the attitude error between MINS and SINS cannot really reflect the misalignment angle change of SINS due to the flexure deformation. At the same time, the flexure deformation will bring the change of the lever arm size, which further induces the uncertainty of lever arm velocity, resulting in the velocity matching error. To solve this problem, a $H_{\infty}$ algorithm is proposed, in which the attitude and velocity matching error caused by deformation is considered as measurement noise with limited energy, and measurement noise will be restrained by the robustness of $H_{\infty}$ filter. Based on the classical "attitude plus velocity" matching method, the progress of M/S INS information fusion is simulated and compared by using three kinds of schemes, which are known and unknown flexure deformation with standard Kalman filter, and unknown flexure deformation with $H_{\infty}$ filter, respectively. Simulation results indicate that $H_{\infty}$ filter can effectively improve the accuracy of information fusion when flexure deformation is unknown but non-ignorable.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.