• Korean Chemical Engineering Research
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• v.52 no.6
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• pp.720-726
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• 2014

PEM fuel cell vehicles have been getting much attraction due to a sort of highly clean and effective transportation. The onboard fuel processor, however, is inevitably required to supply the hydrogen by conversion from some fuels since there are not enough available hydrogen stations nearby. A lot of studies have been focused on analyses of ATR reactor under the assumption of thermo-neutral condition and those of the optimized process for the minimization of energy consumption using thermal efficiency as an objective function, which doesn't guarantee the maximum hydrogen production. In this study, the analysis of optimization for 100 kW PEMFC onboard fuel processor was conducted targeting various fuels such as gasoline, LPG, diesel using newly defined hydrogen efficiency and keeping simply synthesized heat exchanger network regardless of external utilities leading to compactness and integration. Optimal result of gasoline case shows 9.43% reduction compared to previous study, which shows the newly defined objective function leads to better performance than thermal efficiency in terms of hydrogen production. The sensitivity analysis was also done for hydrogen efficiency, heat recovery of each heat exchanger, and the cost of each fuel. Finally, LPG was estimated as the most economical fuel in Korean market.

• Korean Chemical Engineering Research
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• v.61 no.3
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• pp.378-387
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• 2023

Petrochemical is an energy consuming industry that consumes about 30% of total industrial energy consumption and is a representative carbon dioxide (CO₂) emission source. Among them, the Naphtha Cracking Center (NCC), which produces ethylene, propylene, propane and mixed C4, consumes large amounts of energy and emits significant amounts of CO₂. For this reason, an integrated techno economic- environmental impact assessment aimed at reducing energy consumption and environmental impact factors is necessary to ensure efficiency in terms of economics and environment. This study aims to analyze the efficiency of the heat exchanger network used in the existing NCC base on the pinch analysis and select an improvement plan that can reduced energy consumption. In order to reduces the utility consumption in the process, an optimal heat exchanger network considering the high-temperature and low-temperature stream was derived, and the economic evaluation was conducted by considering the trade-off between the reduction in utility consumption and the increase in heat exchanger installation cost. In addition, an environmental impact assessment was conducted on the reduced CO₂ emission in consideration of the environmental aspect, and the economic environmental impact assessment used the payback period to recover the invested funds to come up with an energy saving plan that can be applied based on the actual process. As a result of considering the economic-environmental impact assessment, when the environmental impact assessment was not considered, it was 4.29 months, 3.21 months, and 3.39 months for each case, and when considering the environmental impact assessment, it was 4.24 months, 3.17 months, and 3.35 months for each case. These results appeared equally both when the environmental impact assessment was not include and when it was include. In addition, a sensitivity analysis was conducted for each case to determine how important factors affect the payback period. As a result of the sensitivity analysis, the cost of the heat exchanger was identified as a major factor influencing the overall cost.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.