• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.2
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• pp.109-115
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• 2019

In case of the cracks in concrete, the penetration of deterioration ions such as chloride ions in to cracks is accelerated. According to the penetration of chloride ions, structural and durability problems to RC(Reinforced Concrete) structures are caused. In this study, the accelerated chloride diffusion coefficient which is in steady state is evaluated for 2 year aged normal and high strength FA(Fly Ash) concrete, after a range of crack depths are induced up to 1.0 mm in 56 aged day. Considering crack effect by linear regression analysis, high strength concrete has slightly less increasing ratio of diffusion coefficient by crack than normal strength concrete, and diffusion coefficient increases non-linearly as crack width is increased. Also, In two types of concrete, crack effect decrease as the curing period increase. In the case of quantifying crack and curing effect by using exponential function form, the coefficients of determination are higher than those of linear regression analysis. Under steady state, it is thought that there is not a high correlation between the crack effect and the curing effect, and considering the two independent effects, it is believed that reasonable prediction equation for diffusion of concrete with crack can be proposed.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.104-114
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• 2019

In the global market competition, countries and businesses are actively engaged in technology prediction activities to maximize their profits by attempting to enter and preempting the core technology of the future. In this paper, we propose a growth model based on patent application trends to predict the time to replace a product with a promising new technology to dominate the market. Although the Fisher-Pry model that Bhargava generalized to predict the emergence of promising alternative technologies was relatively satisfactory compared to the original Fisher-Pry model, it was difficult to predict the replacement rate behavior properly due to a parameter problem. The application of the Fisher-Pry Modification Model in the form of a quadratic equation through the patent trend analysis of the optical storage system for the purpose of verifying the time alternative to the light storage technology has resulted in satisfactory verification results. It is expected that small and medium-sized companies and individual researchers will apply this model and use it more easily to predict the time to replace the market for promising replacement technologies.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.93-101
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• 2019

The objective of this study is to develop a model which can predict the seismic performance of the slope relatively accurately and efficiently by using artificial neural network(ANN) technique. The quantification of such the seismic performance of the slope is not easy task due to the randomness and the uncertainty of the earthquake input and slope model. Under these circumstances, probabilistic seismic fragility analyses of slope have been carried out by several researchers, and a closed-form equation for slope seismic performance was proposed through a multiple linear regression analysis. However, a traditional statistical linear regression analysis has shown a limit that cannot accurately represent the nonlinearistic relationship between the slope of various conditions and seismic performance. In order to overcome these problems, in this study, we attempted to apply the ANN to generate prediction models of the seismic performance of the slope. The validity of the derived model was verified by comparing this with the conventional multi-linear and multi-nonlinear regression models. As a result, the models obtained through the ANN basically showed excellent performance in predicting the seismic performance of the slope, compared to the models obtained by the statistical regression analyses of the previous study.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.103-108
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• 2019

Non-equilibrium molecular dynamics simulation on the thermal boundary resistance(TBR) of an aluminum(Al)/silicon(Si) interface was performed in the present study. The constant heat flux across the Si/Al interface was simulated by adding the kinetic energy in hot Si region and removing the same amount of the energy from the cold Al region. The TBR estimated from the sharp temperature drop at the interface was independent of heat flux and equal to $5.13{\pm}0.17K{\cdot}m^2/GW$ at 300K. The simulation result was experimentally confirmed by the time-domain thermoreflectance technique. A 90nm thick Al film was deposited on a Si(100) wafer using an e-beam evaporator and the TBR on the film/substrate interface was measured using the time-domain thermoreflectance technique based on a femtosecond laser system. A numerical solution of the transient heat conduction equation was obtained using the finite difference method to estimate the TBR value. Experimental results were compared to the prediction and discussions on the nanoscale thermal transport phenomena were made.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.78-82
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• 2022

Phenology determines the timing of crop development, and the timing of phenological events is strongly influenced by the temperature during the growing season. In process-based model, leaf area is simulated dynamically by coupling of morphology and phenology module. Therefore, the prediction of leaf appearance rate and final leaf number affects the performance of whole crop model. The dataset for the model equation was collected from SPA R chambers with five different temperature treatments. Beta distribution function (proposed by Yan and Hunt (1999)) was used for describing the leaf appearance rate as a function of temperature. The optimum temperature and the critical value were estimated to be 26.0℃ and 35.3℃, respectively. For evaluation of the model, the accumulated number of onion leaves observed in a temperature gradient chamber was compared with model estimates. The model estimate is the result of accumulating the daily increase in the number of onion leaves obtained by inputting the daily mean temperature during the growing season into the temperature model. In this study, the coefficient of determination (R²) and RMSE value of the model were 0.95 and 0.89, respectively.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.261-269
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• 2021

Without any validation of the incompressible assumption, most of previous studies on cavitation flow and its noise have utilized numerical methods based on the incompressible Reynolds Average Navier-Stokes (RANS) equations because of advantage of its efficiency. In this study, to investigate the effects of the flow compressibility on the Tip Vortex Cavitation (TVC) flow and noise, both the incompressible and compressible simulations are performed to simulate the TVC flow, and the Ffowcs Williams and Hawkings (FW-H) integral equation is utilized to predict the TVC noise. The DARPA Suboff submarine body with an underwater propeller of a skew angle of 17 degree is targeted to account for the effects of upstream disturbance. The computation domain is set to be same as the test-section of the large cavitation tunnel in Korea Research Institute of Ships and Ocean Engineering to compare the prediction results with the measured ones. To predict the TVC accurately, the Delayed Detached Eddy Simulation (DDES) technique is used in combination with the adaptive grid techniques. The acoustic spectrum obtained using the compressible flow solver shows closer agreement with the measured one.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.33-41
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• 2023

As carbon-free has been getting interest, renewable energy sources have been increasing. However, renewable energy is intermittent and variable so it is difficult to predict the produced electrical energy from a renewable energy source. In this study, digital-twin concept is applied to solve difficulties in predicting electrical energy from a renewable energy source. Considering that rotation of wind turbine has high correlation with produced electrical energy, a model which simulates rotation in the drivetrain of a wind turbine is developed. The base of a drivetrain simulation model is set with well-known state equation in mechanical engineering, which simulates the rotating system. Simulation based machine learning is conducted to get unknown parameters which are not provided by manufacturer. The simulation is repeated and parameters in simulation model are corrected after each simulation by optimization algorithm. The trained simulation model is validated with 27 real wind turbine operation data set. The simulation model shows 4.41% error in average compared to real wind turbine operation data set. Finally, it is assessed that the drivetrain simulation model represents the real wind turbine drivetrain system well. It is expected that wind-energy-prediction accuracy would be improved as wind turbine digital twin including the developed drivetrain simulation model is applied.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.185-194
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• 2023

There are more than 22,300 small streams distributed nationwide in Korea, and they have various runoff characteristics depending on basin area, topography and land use. For small stream disaster management, establishing detailed design standards suitable for the small streams is important, but most of the formulas currently proposed in the small stream design standard are based on the river design standard aimed at national and local rivers or foreign river design standards. The design-width is an important factor in determining the size of the stream. It is determined by using design-flood discharges or more variables such as design-flood discharges, basin area, slop, etc in the small stream design standard. This study collected various characteristics information such as the design-flood discharges, basin area, river length and river slop, and design-width values from 4,073 small streams distributed in 12 cities and provinces in Korea to suggest the appropriated design-width formula. This study developed two design-width formulas by using the regression analysis which one is using the design-flood discharges and the other is using various variables such as the design-flood discharges, basin area, river length and river slope collected from the small steams. It is expected that both equations developed in here can be used for small stream disaster management, such as improving small stream design standard or establishing a comprehensive small stream maintenance plan.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.227-241
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• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.

• Korean Journal of Poultry Science
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• v.50 no.2
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• pp.73-80
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• 2023

Vitamin D3 is an essential nutrient which plays an important role in calcium metabolism for eggshell formation, in calcium and phosphorus metabolism for bone mineralization, and in maintaining host immunity. Although there have been a great deal of studies investigating the role of vitamin D3 in eggshell quality and vitamin D3 contents in eggs, no attempts have been made to monitor the eggshell quality and vitamin D3 contents in eggs at farm level. Thus, this survey was conducted to measure eggshell quality and vitamin D3 contents in eggs laid from laying hens fed diets containing different levels of vitamin D3. Eggs from four commercial laying hen farms were sampled before and 1, 2, 3 and 5 weeks after provision of the vitamin D3-enriched diets added with the level of 16,500 IU and 29,000 IU. Dietary vitamin D3 did not affect the eggshell color and breaking strength, but increase the eggshell thickness. In addition, vitamin D3 contents in eggs were elevated as vitamin D3 in diets was increased. It is concluded that addition of dietary vitamin D3 into the diets of laying hens at the commercial laying hen farms could improve eggshell quality and vitamin D3 contents in eggs. It is expected that the prediction equation for egg vitamin D3 contents might be produced if more data on vitamin D3 contents in diets and eggs at the farms are to be analyzed.