• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.568-574
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• 2021

According to the Framework Act on Sustainable Infrastructure Management, which has been enforced since 2020, reservoirs should be managed to minimize life cycle costs caused by aging through preemptive management such as systematic maintenance and performance improvement. For maintenance in consideration of the life cycle, it is essential to derive the end of life due to continuous performance degradation as the common period increases. For this purpose, it is necessary to develop a performance-predicting model for reservoirs. In this study, a reservoir was divided into main complex facilities to develop a model for the maintenance of the life cycle. A model was developed for each facility. For model development, maintenance information data were collected under management by the Rural Community Corporation. The data available for model development were selected by analyzing the collected data. The developed model was used to predict the expected life expectancy of the reservoir in the current maintenance system and the expected life expectancy in the case of no action. By using the developed model, it is expected that it will be possible to support decision making in operation management and maintenance while considering the life cycle of the reservoir.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2004.09a
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• pp.233-241
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• 2004

A new alloy definition will be presented concerning increasing demands for the board level reliability of miniaturized interconnections. The damage mechanism for LFBGA components on different board finishes is not quite understood. Further demands from mobile phones are the drop test, characterizing interface performance of different package constructions in relation to decreased pad constructions and therefore interfaces. The paper discusses the characterization of interfaces based on SnPb, SnPbXYZ, SnAgCu and SnAgCuInNd ball materials and SnAgCuInNd as solder paste, the stability after accelerated tests and the description of modified interfaces strictly related to the assembly conditions, dissolution behavior of finishes on board side and the influence of intermetallic formation. The type of intermetallic as well as the quantity of intermetallics are observed, primaliry the hardness, E modules describing the ability of strain/stress compensation. First results of board level reliability are presented after TCT-40/+150. Improvement steps from the ball formulation will be discussed in conjunction to the implementation of lead free materials In order to optimize ball materials for area array devices accelareted aging conditions like TCTs were used to analyze the board level reliability of different ball materials for BGA, LFBGA, CSP, Flip Chip. The paper outlines lead-free ball analysis in comparison to conventional solder balls for BGA and chip size packages. The important points of interest are the description of processability related to existing ball attach procedures, requirements of interconnection properties and the knowledge gained the board level reliability. Both are the primary acceptance criteria for implementation. Knowledge about melting characteristic, surface tension depend on temperature and organic vehicles, wetting behavior, electrical conductivity, thermal conductivity, specific heat, mechanical strength, creep and relaxation properties, interactions to preferred finishes (minor impurities), intermetallic growth, content of IMC, brittleness depend on solved elements/IMC, fatigue resistance, damage mechanism, affinity against oxygen, reduction potential, decontamination efforts, endo-/exothermic reactions, diffusion properties related to finishes or bare materials, isothermal fatigue, thermo-cyclic fatigue, corrosion properties, lifetime prediction based on board level results, compatibility with rework/repair solders, rework temperatures of modified solders (Impurities, change in the melting point or range), compatibility to components and laminates.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2004.09a
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• pp.211-219
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• 2004

A new alloy definition will be presented concerning increasing demands for the board level reliability of miniaturized interconnections. The damage mechanism for LFBGA components on different board finishes is not quite understood. Further demands from mobile phones are the drop test, characterizing interface performance of different package constructions in relation to decreased pad constructions and therefore interfaces. The paper discusses the characterization of interfaces based on SnPb, SnPbXYZ, SnAgCu and SnAgCuInNd ball materials and SnAgCuInNd as solder paste, the stability after accelerated tests and the description of modified interfaces stric시y related to the assembly conditions, dissolution behavior of finishes on board side and the influence of intermetallic formation. The type of intermetallic as well as the quantity of intermetallics are observed, primaliry the hardness, E modules describing the ability of strain/stress compensation. First results of board level reliability are presented after TCT-40/+150. Improvement steps from the ball formulation will be discussed in conjunction to the implementation of lead free materials. In order to optimize ball materials for area array devices accelareted aging conditions like TCTs were used to analyze the board level reliability of different ball materials for BGA, LFBGA, CSP, Flip Chip. The paper outlines lead-free ball analysis in comparison to conventional solder balls for BGA and chip size packages. The important points of interest are the description of processability related to existing ball attach procedures, requirements of interconnection properties and the knowledge gained the board level reliability. Both are the primary acceptance criteria for implementation. Knowledge about melting characteristic, surface tension depend on temperature and organic vehicles, wetting behavior, electrical conductivity, thermal conductivity, specific heat, mechanical strength, creep and relaxation properties, interactions to preferred finishes (minor impurities), intermetallic growth, content of IMC, brittleness depend on solved elements/IMC, fatigue resistance, damage mechanism, affinity against oxygen, reduction potential, decontamination efforts, endo-/exothermic reactions, diffusion properties related to finishes or bare materials, isothermal fatigue, thermo-cyclic fatigue, corrosion properties, lifetime prediction based on board level results, compatibility with rework/repair solders, rework temperatures of modified solders (Impurities, change in the melting point or range), compatibility to components and laminates.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.1007-1013
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• 2013

This study aims to analyze the aerodynamics when the geometry of the turbine rotor is modified. The turbine used in this study is a small engine used in the APU of a helicopter. It is difficult to improve the performance of small engines owing to the structural weakness of the blade tip. Therefore, the improvement of the hub geometry is investigated in many ways. The working fluid of a turbine is a high-temperature and high-pressure gas. The heat transfer rate of the turbine surface should be considered to avoid the destruction of blade owing to the heat load. The SST turbulence model gives an excellent prediction of the aerodynamic behavior and heat transfer characteristics when the numerical simulations are compared with the experimental results. In conclusion, the aerodynamic efficiency is improved when a bulbous design is applied to the leading edge near the hub. The endwall loss is reduced by 15%.

• Journal of the Korean Society for Railway
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• v.16 no.1
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• pp.20-25
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• 2013

The frame elements of modern high speed trains are typically fabricated with extruded aluminum panels. However, the sound transmission loss (STL) of extruded aluminum panels is less satisfactory than flat panels with the same surface density. This study proposes a method for prediction of the sound transmission loss of extruded aluminum panels using finite element analysis. The panel is modeled by finite element analysis, and the STL is calculated using a measure of Sommerfeld radiation at the specimen surface, boundary conditions, and the internal loss factor of the material. In order to verify the validity of the predicted value, intensity transmission loss was measured on the aluminum specimen according to ASTM E2249-02. The proposed method of analysis will be utilized to predict the sound insulation performance of extruded aluminum panels for railway vehicles in the design stage, and to establish measures for their improvement.

• Steel and Composite Structures
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• v.52 no.6
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• pp.621-626
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• 2024

The work researched the application of artificial intelligence to the design and analysis of advanced nanoplates, with a particular emphasis on size and surface effects. Employing an integrated theoretical framework, this study developed a more accurate model of complex nanoplate behavior. The following analysis considers nanoplates embedded in a Pasternak viscoelastic fractional foundation and represents the important step in understanding how nanoscale structures may respond under dynamic loads. Surface effects, significant for nanoscale, are included through the Gurtin-Murdoch theory in order to better describe the influence of surface stresses on the overall behavior of nanoplates. In the present analysis, the modified couple stress theory is utilized to capture the size-dependent behavior of nanoplates, while the Kelvin-Voigt model has been incorporated to realistically simulate the structural damping and energy dissipation. This paper will take a holistic approach in using sinusoidal shear deformation theory for the accurate replication of complex interactions within the nano-structure system. Addressing different aspectsof the dynamic behavior by considering the length scale parameter of the material, this work aims at establishing which one of the factors imposes the most influence on the nanostructure response. Besides, the surface stresses that become increasingly critical in nanoscale dimensions are considered in depth. AI algorithms subsequently improve the prediction of the mechanical response by incorporating other phenomena, including surface energy, material inhomogeneity, and size-dependent properties. In these AI- enhanced solutions, the improvement of precision becomes considerable compared to the classical solution methods and hence offers new insights into the mechanical performance of nanoplates when applied in nanotechnology and materials science.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.6
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• pp.815-823
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• 1993

In this paper, the structure of modified multiplication-free adaptive filter(M-MADF) and convergence analysis are presented. To evaluate the performance of proposed M-MADF algorithm, fractionally spaced equalizer (FSE) is used. The input signals are quantized using DPCM and the reference signals is processed using a first-order linear prediction filter, and the outputs are processed by a conventional adaptive filter. The filter coefficients are updated using the Sign algorithm. Under the assumption that the primary and reference signals are zero mean, wide-sense stationary and Gaussian, theoretical results for the coefficient misalignment vector and its autocorrelation matrix of the filter are driven. The convergence properties of Sign. MADF and M-MADF algorithm for updating of the coefficients of a digital filter of the fractionally spaced equalizer (FSE) are investigated and compared with one another. The convergence properties are characterized by the steady state error and the convergence speed. It is shown that the convergence speed of M-MADF is almost same as Sign algorithm and is faster that MADF in the condition of same steady error. Especially it is very useful for high correlated signals.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.10
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• pp.961-969
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• 2013

In this study, the numerical analysis of a turbulent flow around both a staggered and an inline tube bundle was conducted using ANSYS CFX V.13, a commercial CFD software. The flow was assumed to be steady, incompressible, and isothermal. According to the CFD Best Practice Guideline, the sensitivity study for grid size, accuracy of the discretization scheme for convection term, and turbulence model was conducted, and its result was compared with the experimental data to estimate the applicability of the CFD Best Practice Guideline. It was concluded that the CFD Best Practice Guideline did not always guarantee an improvement in the prediction performance of the commercial CFD software in the field of tube bundle flow.