• The Journal of Engineering Geology
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• v.29 no.4
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• pp.509-529
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• 2019

This study performs to evaluate the role of filter material at alluvial well for intake of riverbank filtration and the applicability and improvement effect of dual filter well. To achieve this objective, dual filter intake well and single filter intake well were installed with different filter conditions at riverbank free surface aquifer in soil layer then we evaluated filter material condition, permeability, optimum yield and well efficiency according to yield in drawdown test. As a results, we assumed forming dual filter layer minimizes sudden speed changes at boundary between aquifer and filter layer by cushioning of groundwater flow. This suppresses warm current then intake groundwater efficiently, therefore it seems decreasing peripheral groundwater level changes in spite of higher intake water amount than single filter intake well. Furthermore, we confirmed by test, installing dual filter improves permeability, optimum yield and well efficiency. The result will be used by combining with former study to set up standard of design/construction of dual filter intake well at alluvial aquifer layer. Furthermore, we expect this result will be used to prove application effect of dual filter intake well compared to single filter one and radial collector well which are mainly applied on riverbank filtration.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.2
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• pp.9-14
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• 2020

Four developed patents have applied for a new type of Composite Cyclone Scrubber followed by the previous research (Cho and Kim, 2017), including dust reducing fan with filters. Regarding target installation and maintenance cost, 64% reduction for investment costs (6.2 billion won vs. 17 billion won) compared to existing road pollution reduction system, while social benefit costs increase by 43% compared to existing road pollution reduction measures (72.6 billion won vs. 50.8 billion won). The composition of the device is an air blower type spiral guide vane, and an injection pressure collecting dust efficiency. A nozzle varies Injection angle and contact range, spray liquid species (waterworks, salty water). The proposed patent tests are circulation water Time-by-Time Spray and collected 41.4% more increased micro dust since the sprayed water meets contaminated gas due to the 45° degree colliding, which is 141% increased conventional dust collector. (Ratio of collection over 85%). As regards the source of collection liquid, circulated rainwater and well water, we expect a huge amount of energy and economically saved eco-friendly system in our patent. Finally, the guided vane and metal filter reduced over 90% micro-dust, while sprayed water cleans the vane and filters, resultantly minimizing the maintenance budget. The preliminary evaluations of the developed design make it possible to reduce not only cheaper maintenance budget due to the characteristic water spraying but the cost of water comes from mainly rain and underground.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.302-303
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• 2010

Generally, the high energy lithium ion batteries depend intimately on the high capacity of electrode materials. For anode materials, the capacity of commercial graphite is unlike to increase much further due to its lower theoretical capacity of 372 mAhg-1. To improve upon graphite-based negative electrode materials for Li-ion rechargeable batteries, alternative anode materials with higher capacity are needed. Therefore, some metal anodes with high theoretic capacity, such as Si, Sn, Ge, Al, and Sb have been studied extensively. This work focuses on ternary Si-M1-M2 composite system, where M1 is Ge that alloys with Li, which has good cyclability and high specific capacity and M2 is Mo that does not alloy with Li. The Si shows the highest gravimetric capacity (up to 4000mAhg-1 for Li21Si5). Although Si is the most promising of the next generation anodes, it undergoes a large volume change during lithium insertion and extraction. It results in pulverization of the Si and loss of electrical contact between the Si and the current collector during the lithiation and delithiation. Thus, its capacity fades rapidly during cycling. Si thin film is more resistant to fracture than bulk Si because the film is firmly attached to the substrate. Thus, Si film could achieve good cycleability as well as high capacity. To improve the cycle performance of Si, Suzuki et al. prepared two components active (Si)-active(Sn, like Ge) elements film by vacuum deposition, where Sn particles dispersed homogeneously in the Si matrix. This film showed excellent rate capability than pure Si thin film. In this work, second element, Ge shows also high capacity (about 2500mAhg-1 for Li21Ge5) and has good cyclability although it undergoes a large volume change likewise Si. But only Ge does not use the anode due to its costs. Therefore, the electrode should be consisted of moderately Ge contents. Third element, Mo is an element that does not alloys with Li such as Co, Cr, Fe, Mn, Ni, V, Zr. In our previous research work, we have fabricated Si-Mo (active-inactive elements) composite negative electrodes by using RF/DC magnetron sputtering method. The electrodes showed excellent cycle characteristics. The Mo-silicide (inert matrix) dispersed homogeneously in the Si matrix and prevents the active material from aggregating. However, the thicker film than $3\;{\mu}m$ with high Mo contents showed poor cycling performance, which was attributed to the internal stress related to thickness. In order to deal with the large volume expansion of Si anode, great efforts were paid on material design. One of the effective ways is to find suitably three-elements (Si-Ge-Mo) contents. In this study, the Si based composites of 45~65 Si at.% and 23~43 Ge at.%, and 12~32 Mo at.% are evaluated the electrochemical characteristics and cycle performances as an anode. Results from six different compositions of Si-Ge-Mo are presented compared to only the Si and Ge negative electrodes.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.