• Advances in Energy Research
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• v.6 no.1
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• pp.75-90
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• 2019

Anthropogenic greenhouse gas emissions are rising rapidly despite efforts to curb release of such gases. One long term potential solution to offset these destructive emissions is the capture and storage of carbon dioxide. Partially depleted hydrocarbon reservoirs are attractive targets for permanent carbon dioxide disposal due to proven storage capacity and seal integrity, existing infrastructure. Optimum well completion design in depleted reservoirs requires understanding of prominent geomechanics issues with regard to rock-fluid interaction effects. Geomechanics plays a crucial role in the selection, design and operation of a storage facility and can improve the engineering performance, maintain safety and minimize environmental impact. In this paper, an integrated geomechanics workflow to evaluate reservoir caprock integrity is presented. This method integrates a reservoir simulation that typically computes variation in the reservoir pressure and temperature with geomechanical simulation which calculates variation in stresses. Coupling between these simulation modules is performed iteratively which in each simulation cycle, time dependent reservoir pressure and temperature obtained from three dimensional compositional reservoir models in ECLIPSE were transferred into finite element reservoir geomechanical models in ABAQUS and new porosity and permeability are obtained using volumetric strains for the next analysis step. Finally, efficiency of this approach is demonstrated through a case study of oil production and subsequent carbon storage in an oil reservoir. The methodology and overall workflow presented in this paper are expected to assist engineers with geomechanical assessments for reservoir optimum production and gas injection design for both natural gas and carbon dioxide storage in depleted reservoirs.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.3
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• pp.42-55
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• 2021

In this study, the effect of nozzle performance according to the selection of the center line equation. Three of S-type nozzles and three of double S-type nozzles were designed using the curve equation and design parameters, and the nozzle shielding performance was evaluated using the shielding ratio definition. In order to analyze the internal flow of the nozzle, the characteristics of the velocity distribution and pressure distribution were studied, and the nozzle performance was evaluated through the total thrust ratio(f) and the nozzle insulation efficiency coefficient(η). On the other hand, the centerline with a sharply change in curvature at the entrance has a low nozzle performance and a high shielding rate. The double S-type nozzle is excellent nozzle performance and shielding rate by using a smooth centerline at the first curvature.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.799-806
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• 2021

In the IoT environment, event data from sensors is continuously reported over time. Event data obtained in this trend is accumulated indefinitely, so a method for efficient analysis and management of data is required. In this study, a data stream segmentation method was proposed to support the effective selection and utilization of event data from sensors that are continuously reported and received. An identifier for identifying the point at which to start the analysis process was selected. By introducing the role of these identifiers, it is possible to clarify what is being analyzed and to reduce data throughput. The identifier for stream segmentation proposed in this study is a semantic-oriented data stream segmentation method based on the event occurrence of each stream. The existence of identifiers in stream processing can be said to be useful in terms of providing efficiency and reducing its costs in a large-volume continuous data inflow environment.

• Animal Bioscience
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• v.34 no.4
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• pp.516-524
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• 2021

Objective: The genetic evaluation of Santa Inês sheep was performed for resistance to gastrointestinal nematode infection (RGNI) and body size using different relationship matrices to assess the efficiency of including genomic information in the analyses. Methods: There were 1,637 animals in the pedigree and 500, 980, and 980 records of RGNI, thoracic depth (TD), and rump height (RH), respectively. The genomic data consisted of 42,748 SNPs and 388 samples genotyped with the OvineSNP50 BeadChip. The (co)variance components were estimated in single- and multi-trait analyses using the numerator relationship matrix (A) and the hybrid matrix H, which blends A with the genomic relationship matrix (G). The BLUP and single-step genomic BLUP methods were used. The accuracies of estimated breeding values and Spearman rank correlation were also used to assess the feasibility of incorporating genomic information in the analyses. Results: The heritability estimates ranged from 0.11±0.07, for TD (in single-trait analysis using the A matrix), to 0.38±0.08, for RH (using the H matrix in multi-trait analysis). The estimates of genetic correlation ranged from -0.65±0.31 to 0.59±0.19, using A, and from -0.42±0.30 to 0.57±0.16 using H. The gains in accuracy of estimated breeding values ranged from 2.22% to 75.00% with the inclusion of genomic information in the analyses. Conclusion: The inclusion of genomic information will benefit the direct selection for the traits in this study, especially RGNI and TD. More information is necessary to improve the understanding on the genetic relationship between resistance to nematode infection and body size in Santa Inês sheep. The genetic evaluation for the evaluated traits was more efficient when genomic information was included in the analyses.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.186-191
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• 2020

In this paper, we proposed an optimization technique for efficiently placing vehicles on decks in a vehicle-carrying ship to efficiently handle loading and unloading. For this purpose, we utilized the transformation method of the XML data representing the ship's spatial information, merging and branching algorithm and genetic algorithm, and implemented the function to visualize the optimized vehicle placement results. The techniques of selection, crossover, mutation, and elite preservation, which are used in the conventional genetic algorithms, are used. In particular, the vehicle placement optimization method is proposed by merging and branching the ship space for the vehicle loading. The experimental results show that the proposed merging and branching method is effective for the optimization process that is difficult to optimize with the existing genetic algorithm alone. In addition, visualization results show vehicle layout results in the form of drawings so that experts can easily determine the efficiency of the layout results.

• Applied Chemistry for Engineering
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• v.22 no.5
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• pp.566-574
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• 2011

Coal gasifier is a key component for achieving high efficiency in integrated gasification combined cycle and indirect coal liquefaction. Although there have been several successful coal gasifiers that were commercially proven, many different design configurations are still possible for a simple and reliable gasifier operation. Four different gasifier design concepts of dry-feeding were compared in terms of residence time, exit syngas temperature and syngas composition. First, cold-flow simulation was applied to pre-select the configuration concepts, and the hot-flow simulation including chemical reactions was performed to compare the concepts at more actual gasifier operating conditions. There are many limitations in applying CFD method in gasifier design, particularly in estimating slag behavior and slag-tap design. However, the CFD analysis proved to be useful in comparing the widely different gasifier design concepts as a pre-selection tool.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.1
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• pp.103-116
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• 2021

Analysis of runoff is substantial for effective water management in the watershed. Runoff occurs by reaction of a watershed to the rainfall and has non-linearity and uncertainty due to the complex relation of weather and watershed factors. ANN (Artificial Neural Network), which learns from the data, is one of the machine learning technique known as a proper model to interpret non-linear data. The performance of ANN is affected by the ANN's structure, the number of hidden layer nodes, learning rate, and activation function. Especially, the activation function has a role to deliver the information entered and decides the way of making output. Therefore, It is important to apply appropriate activation functions according to the problem to solve. In this paper, ANN models were constructed to estimate runoff with different activation functions and each model was compared and evaluated. Sigmoid, Hyperbolic tangent, ReLU (Rectified Linear Unit), ELU (Exponential Linear Unit) functions were applied to the hidden layer, and Identity, ReLU, Softplus functions applied to the output layer. The statistical parameters including coefficient of determination, NSE (Nash and Sutcliffe Efficiency), NSEln (modified NSE), and PBIAS (Percent BIAS) were utilized to evaluate the ANN models. From the result, applications of Hyperbolic tangent function and ELU function to the hidden layer and Identity function to the output layer show competent performance rather than other functions which demonstrated the function selection in the ANN structure can affect the performance of ANN.

• Journal of Drive and Control
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• v.17 no.4
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• pp.125-132
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• 2020

The objective of this study was to analyze the axle load of a rice transplanter when planting rice seedlings at different working load conditions to select a suitable gear stage and a constant planting depth for rice seedlings. In this study, there are four levels of planting distances (26, 35, 43, and 80 cm) and three planting depths (low, medium, and high) with two gear stages (1.3 and 1.7 m/s). Axle loads and required planting pressures were analyzed statistically. It was observed that axle torques were increased with increasing planting depths for both gear stages, meaning that axle torques were directly proportional to planting depths for both gear stages. It was also observed that required planting pressures had a significant difference between planting distances. Planting pressures also showed significant difference according to gear stage and planting depth. These results indicate that planting pressures were directly proportional to both gear stage and planting depth. Results revealed that the automatic depth control system of a rice transplanter could not guarantee a constant planting depth as supplied pressures were variable. This indicates that a control algorithm is needed to ensure a constant planting depth. In the future, a control algorithm will be developed for an automatic depth control system of a rice transplanter to improve its comprehensive performance and efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.515-521
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• 2020

Recently, data traffic has exploded due to development of various industries, which causes problems about losing of efficiency and overloaded existing networks. To solve these problems, network slicing, which uses a virtualization technology and provides a network optimized for various services, has received a lot of attention. In this paper, we propose a resource allocation method using credit value. In the method using the clustering technology, an operation for selecting a cluster is performed whenever an allocation request for various services occurs. On the other hand, in the proposed method, the credit value is set by using the residual capacity and balancing so that the slice request can be processed without performing the operation required for cluster selection. To prove proposed method, we perform processing time and balancing simulation. As a result, the processing time and the error factor of the proposed method are reduced by about 13.72% and about 7.96% compared with the clustering method.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.117-133
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• 2021

This study aimed to identify its research trends using social network analysis(SNA). The results of the analysis showed that, for degree centrality, Busan Port(0.223) was the keyword that had the highest centrality, followed by DEA(0.060), AHP(0.056), and container terminal and port competitiveness(0.049). Busan Port(0.245) also had the highest betweenness centrality, followed by DEA(0.048), container terminal(0.044), AHP(0.039), and Busan New Port(0.032). The trend analysis inferred that efficiency analysis(DEA), strategy selection, and competition analysis(AHP) were the keywords with a high centrality for Busan Port to gain a competitive edge with global ports. However, research on the Fourth Industrial Revolution, which is emerging as a key issue, was insufficient. In the future, research using social data, such as mass media and social networks, is necessary.