• Journal of Wetlands Research
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• v.25 no.4
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• pp.297-305
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• 2023

The recycled irrigation is a type of irrigation that uses downstream water to fulfill irrigation demand in the upstream agricultural areas; the used irrigation water returns back to the downstream. The recycled irrigation is advantageous for securing irrigation water for plant growth, but the returned water typically contains high levels of nutrients due to excess nutrients inputs during the agricultural activities, potentially deteriorating stream water quality. Therefore, quantitative assessment on the effect of the recycled irrigation on the stream water quality is required to establish strategies for effective irrigation water supply and water quality management. For this purpose, a watershed model is generally used; however no functions to simulate the effects of the recycled irrigation are provided in the existing watershed models. In this study, we used multi-reservoir model coupled with the Hydrological Simulation Program-Fortran (HSPF) to estimate the effect of the recycled irrigation on the stream water quality. The study area was the Gwangok stream watershed, a subwatershed of Gyeseong stream watershed in Changnyeong county, Gyeongsangnam-do. The HSPF model was built, calibrated, and used to produce time series data of flow and water quality, which were used as hypothetical observation data to calibrate the multi-reservoir model. The calibrated multi-reservoir model was used for simulating the recycled irrigation. In the multi-reservoir model, the Gwangok watershed consisted of two subsystems, irrigation and the Gwangok stream, and the reactions (plant uptake, adsorption, desorption, and decay) within each subsystem, and fluxes of water and materials between the subsystems, were modeled. Using the developed model, three scenarios with different combinations of the operating conditions of the recycled irrigation were evaluated for their effects on the stream water quality.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

• Journal of the Korean Society for Railway
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• v.15 no.4
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• pp.413-421
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• 2012

The purpose of this study is to evaluate the structural dynamic behavior under hybrid control system. The hybrid test is to consider the interaction between the numerical and physical models. In this paper, single degree of freedom hybrid test was performed with one-bay, two-story steel frame structure. One column at the first floor was selected as a physical substructure and one actuator was used for applying the displacement load in horizontal direction. El Centro as earthquake waves was inputted and OpenSees was employed as the numerical analysis program for the hybrid real-time simulation. As a result, the total time of the hybrid test was about 9.6% of actual measured seismic period. The experimental results agreed well with the numerical one in terms of the maximum displacement. In nonlinear analysis, however, material nonlinearity made a difference of residual strain. Therefore, this hybrid dynamic test can be used to predict the structural dynamic performance more effectively than shaking table test, because of the spatial and economic limitations.

• Geomechanics and Engineering
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• v.23 no.2
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• pp.151-163
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• 2020

Grouting method is an effective way of reinforcing cracked rock masses and plugging water gushing. Current grouting diffusion models are generally developed for horizontal cracks, which is contradictory to the fact that the crack generally occurs in rock masses with irregular spatial distribution characteristics in real underground environments. To solve this problem, this study selected a cement-sodium silicate slurry (C-S slurry) generally used in engineering as a fast-curing grouting material and regarded the C-S slurry as a Bingham fluid with time-varying viscosity for analysis. Based on the theory of fluid mechanics, and by simultaneously considering the deadweight of slurry and characteristics of non-uniform spatial distribution of viscosity of fast-curing grouts, a theoretical model of slurry diffusion in an oblique crack in rock masses at constant grouting rate was established. Moreover, the viscosity and pressure distribution equations in the slurry diffusion zone were deduced, thus quantifying the relationship between grouting pressure, grouting time, and slurry diffusion distance. On this basis, by using a 3-d finite element program in multi-field coupled software Comsol, the numerical simulation results were compared with theoretical calculation values, further verifying the effectiveness of the theoretical model. In addition, through the analysis of two engineering case studies, the theoretical calculations and measured slurry diffusion radius were compared, to evaluate the application effects of the model in engineering practice. Finally, by using the established theoretical model, the influence of cracking in rock masses on the diffusion characteristics of slurry was analysed. The results demonstrate that the inclination angle of the crack in rock masses and azimuth angle of slurry diffusion affect slurry diffusion characteristics. More attention should be paid to the actual grouting process. The results can provide references for determining grouting parameters of fast-curing grouts in engineering practice.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.1-8
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• 2004

The INS(Inertial Navigation System) provides high rate position, velocity and attitude data with good short-term stability while the GPS(Global Position System) provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to Provide highly accurate navigation Performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the loosely-coupled and the tightly-coupled GPS/INS integration systems. Linearized error models for the position and velocity matching GPS/INS integrated systems are Int derived by linearizing with respect to its time-delay and augmenting the delay-state into the conventional state equations for each case. And then separate bias Kalman Inter is introduced to estimate the time-delay during only initial navigation stage. The simulation results show that the present method is effective enough resulting in considerably less position error.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.95-101
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• 2009

Random numbers are used in many sorts of applications. Some applications, like simple software simulation tests, communication protocol verifications, cryptography verification and so forth, need various levels of randomness with various process speeds. In this paper, we propose a fast pseudorandom generator module for embedded systems. The generator module is implemented in hardware which can run in two modes, one of which can generate random numbers with higher randomness but which requires six cycles, the other providing its result within one cycle but with less randomness. An ASIP (Application Specific Instruction set Processor) was designed to implement the proposed pseudorandom generator instruction sets. We designed a processor based on the MIPS architecture,, by using LISA, and have run statistical tests passing the sequence of the Diehard test suite. The HDL models of the processor were generated using CoWare's Processor Designer and synthesized into the Dong-bu 0.18um CMOS cell library using the Synopsys Design Compiler. With the proposed pseudorandom generator module, random number generation performance was 239% faster than software model, but the area increased only 2.0% of the proposed ASIP.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.12 no.3
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• pp.191-198
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• 2014

Using results of groundwater flow system modeling for a hypothetical deep geological repository site, a distribution of groundwater flow rates at the disposal depth was analyzed and a method of applying this distribution to a safety assessment for a disposal of radioactive wastes was suggested. The distribution of groundwater flow rates was produced by hydraulic heads simulated from regional and local scale groundwater flow models for the hypothetical disposal site. The flow rates at the locations where deposition holes would be located were estimated. These rates were normalized by the maximum of the flow rates in order to probabilistically illustrate a possibility of canister failures at the deposition holes. From the normalized distribution, probabilistic expectations for mass discharges of radionuclides released from the canisters assumed to be failed were calculated and compared with those deterministically estimated under the assumption that the canisters at the same deposition holes were definitely failed. The suggested method can be contributed to constructing a methodology for safety assessment of a geological repository by reflecting natural conditions of a disposal site in more detail.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.961-970
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• 2017

The differential power analysis calculates the intermediate value related to sensitive information and substitute into the power model to obtain (hypothesized) power consumption. After analyzing the calculated power consumption and measuring power consumption, the secret information value can be obtained. Hamming weight and hamming distance models are most commonly used power consumption model, and the power consumption model is obtained through the modeling technique. If the power consumption model assumed by the actual equipment differs from the power consumption of the actual equipment, the side channel analysis performance is declined. In this paper, we propose a method that records measured power consumption and exploits as power consumption model. The proposed method uses the power consumption at the time when the information (plain text, cipher text, etc.) available in the encryption process. The proposed method does not need template in advance and uses the power consumption measured by the actual equipment, so it accurately reflects the power consumption model of the equipment.. Simulation and experiments show that by using our proposed method, side channel analysis is improved on the existing power modeling method.

• International Journal of Highway Engineering
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• v.17 no.4
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• pp.11-18
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• 2015

PURPOSES: This study aims to evaluate the runoff reduction with permeable pavements using the SWMM analysis. METHODS: In this study, simulations were carried out using two different models, simple and complex, to evaluate the runoff reduction when an impermeable pavement is replaced with a permeable pavement. In the simple model, the target area for the analysis was grouped into four areas by the land use characteristics, using the statistical database. In the complex model, simulation was performed based on the data on the sewer and road network configuration of Yongsan-Gu Bogwang-Dong in Seoul, using the ArcGIS software. A scenario was created to investigate the hydro-performance of the permeable pavement based on the return period, runoff coefficient, and the area of permeable pavement that could be laid within one hour after rainfall. RESULTS : The simple modeling analysis results showed that, when an impervious pavement is replaced with a permeable pavement, the peak discharge reduced from $16.7m^3/s$ to $10.4m^3/s$. This represents a reduction of approximately 37.6%. The peak discharge from the whole basin showed a reduction of approximately 11.0%, and the quantity decreased from $52.9m^3/s$ to $47.2m^3/s$. The total flowoff reduced from $43,261m^3$ to $38,551m^3$, i.e., by approximately 10.9%. In the complex model, performed using the ArcGIS interpretation with fewer permeable pavements applicable, the return period and the runoff coefficient increased, and the total flowoff and peak discharge also increased. When the return period was set to 20 years, and a runoff coefficient of 0.05 was applied to all the roads, the total outflow reduced by $5195.7m^3$, and the ratio reduced to 11.7%. When the return period was increased from 20 years to 30 and 100 years, the total outflow reduction decreased from 11.7% to 8.0% and 5.1%, respectively. When a runoff coefficient of 0.5 was applied to all the roads under the return period of 20 years, the total outflow reduction was 10.8%; when the return period was increased to 30 and 100 years, the total outflow reduction decreased to 6.5% and 2.9%, respectively. However, unlike in the simple model, for all the cases in the complex model, the peak discharge reductions were less than 1%. CONCLUSIONS : Being one of the techniques for water circulation and runoff reduction, a high reduction for the small return period rainfall event of penetration was obtained by applying permeable pavements instead of impermeable pavement. With the SWMM analysis results, it was proved that changing to permeable pavement is one of the ways to effectively provide water circulation to various green infrastructure projects, and for stormwater management in urban watersheds.