• Steel and Composite Structures
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• v.31 no.1
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• pp.85-98
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• 2019

Nonlinear seismic performances of code designed Perforated Steel Plate Shear Walls (P-SPSW) were studied. Three multi-storey (4-, 8-, and 12-storey) P-SPSWs were designed according to Canadian seismic provisions and their performance was evaluated using time history analysis for ground motions compatible with Vancouver response spectrum. The selected code designed P-SPSWs exhibited excellent seismic performance with high ductility and strength. The current code equation was found to provide a good estimation of the shear strength of the perforated infill plate, especially when the infill plate is yielded. The applicability of the strip model, originally proposed for solid infill plate, was also evaluated for P-SPSW and two different strip models were studied. It was observed that the strip model with strip widths equal to center to center diagonal distance between each perforation line could reasonably predict the inelastic behavior of unstiffened P-SPSWs. The strip model slightly underestimated the initial stiffness; however, the ultimate strength was predicted well. Furthermore, applicability of simple shear-flexure beam model for determination of fundamental periods of P-SPSWs was studied.

• Korean Journal of Agricultural Science
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• v.47 no.1
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• pp.19-28
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• 2020

This study proposed a simple estimation method for irrigation return flow from paddy fields using the water balance model. The merit of this method is applicability to other paddy fields irrigated from agricultural reservoirs due to the simplicity compared with the previous monitoring based estimation method. It was assumed that the unused amount of irrigation water was the return flow which included the quick and delayed return flows. The amount of irrigation supply from a reservoir was estimated from the reservoir water balance with the storage rate and runoff model. It was also assumed that the infiltration was the main source of the delayed return flow and that the other delayed return flow was neglected. In this study, the amount of reservoir inflow and water demand from paddy field are calculated on a daily basis, and irrigation supply was calculated on 10-day basis, taking into account the uncertainty of the model and the reliability of the data. The regression rate was calculated on a yearly basis, and yearly data was computed by accumulating daily and 10-day data, considering that the recirculating water circulation cycle was relatively long. The proposed method was applied to the paddy blocks of the Jamhong and Seosan agricultural reservoirs and the results were acceptable.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.11-19
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• 2012

PURPOSES: The new methodology is proposed for estimation of long-term performance and pavement life based on the national highway database in Daejeon area. Furthermore, this study tried to verify the applicability of performance estimation using NHPCI (National Highway Pavement Condition Index) on tendency of pavement deterioration as time goes by under Korean road environments. METHODS: Reliability theories are applied to estimate the mean life and to determine the appropriate distribution using 3 levels of traffic loads (high, medium, low) based on maintenance and rehabilitation history data for 15 years. RESULTS: As a result, Lognormal distribution is suitable for explanation of pavement lifetime in Daejeon area regardless of traffic loads. In addition, we found that the results of mean life and maintenance timing based on NHPCI for the pavement sections of 3 levels of traffic loads are available. CONCLUSIONS: Based on this study, it was found that mean life of high, medium and low levels of traffic loads are about 8.1 years, 12.2 years and 12.7 years, respectively. Higher level of traffic loads shorten the pavement mean life.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.11
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• pp.599-609
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.3
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• pp.351-361
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• 2009

Many manufacturers define the system of a new product flexibility, and take advantage of previous-product information using the product configuration concept. Product configuration is an approach that defines the system of a new product centered on the product structure by referring to the previous-product information. In this paper, it is established how to apply the concept of a product configuration utilizing previous-ships information in construction cost estimation process systematically and effectively. For this, we define the advanced-construction cost estimation process based on a naval ship product model, and design construction cost estimating model. It is validated that this process and model have the applicability through the case study of the construction cost estimating of the mine-warfare ship.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.33-38
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• 2021

This paper presents a comparative study between the parameter-optimized Pacejka model and artificial neural network model for the tire force estimation. The two different approaches are investigated and compared in this study. First, offline optimization is conducted based on Pacejka Magic Formula model to determine the proper parameter set for the minimization of tire force error between the model and test data set. Second, deep neural network model is used to fit the model to the tire test data set. The actual tire forces are measured using MTS Flat-Track test platform and the measurements are used as the reference tire data set. The focus of this study is on the applicability of machine learning technique to tire force estimation. It is shown via the regression results that the deep neural network model is more effective in describing the tire force than the parameter-optimized Pacejka model.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Journal of the Korean Geotechnical Society
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• v.21 no.4
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• pp.99-114
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• 2005

In Part I of this paper, a conceptual approach of the stress path method was newly proposed for a rational estimation of settlements of saturated clay deposits. A detailed procedure for effective evaluation and use of settlement-related characteristic deformation behaviors was developed in order to provide practicality to the new approach. In this Part II, on the basis of the results of Part 1, the concept of the new approach was embodied in the form of a detailed settlement estimation procedure. The applicability and usefulness of the new procedure were strongly supported by various application examples. In addition, possible errors of other conventional settlement estimation methods were investigated by comparing with the new procedure. Because of its flexible applicability for wide range of field conditions, the new procedure will have great usefulness in the practical side. For example, a reasonable foundation design based on allowable settlement criteria can be easily performed and modification of design factors can be readily reflected even during the subsequent construction stage. Especially, the new procedure will be of great use for preliminary work in a large scale construction site where various structures are planned to be constructed on a nearly identical ground condition.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.781-793
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• 2017

In this study, applicabilities of aerodynamic approaches for the estimation of pan evaporation were evaluated on 56 study stations in South Korea. To accomplish this study purpose, previous researchers' evaporation estimation equations based on aerodynamic approaches were grouped into seven generalized evaporation models. Furthermore, four multiple linear regression (MLR) models were developed and tested. The independent variables of MLR models are meteorological variables such as wind speed, vapor pressure deficit, air temperature, and atmospheric pressure. These meteorological variables are required for the application of aerodynamic approaches. In order to consider the effect of autocorrelation, MLR models were developed after differencing variables. The applicability of MLR models with differenced variables was compared with that of MLR models with undifferenced variables and the comparison results showed no significant difference between the two methods. The study results have indicated that there is strong correlation between estimated pan evaporation (using aerodynamic models and MLR models) and measured pan evaporation. However, pan evaporation are overestimated during August, September, October, November, and December. Most of meteorological variables that are used for MLR models show statistical significance in the estimation of pan evaporation. Vapor pressure deficit was turned out to be the most significant meteorological variable. The second most significant variable was air temperature; wind speed was the third most significant variable, followed by atmospheric pressure.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.549-559
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• 2012

This paper presents a comparative analysis on the applicability of a priori statistic information about adjustment models when the surface shape parameters are estimated at an arbitrary point in an elevation data. Although the reliability of the estimates are known to be affected by surface condition and the adjustment models, there has been little research in a systematic and detail way. When the raw data have been taken from a real measurement, its true value cannot be known, however, thus this study used simulation data in order to analyze clearly the applicability of adjustment models. The generation of simulated data was performed by superimposing horizontal, slope, and curve surfaces and adding a certain amount of noise. Comparative analysis was performed by associating the a posteriori estimates with a priori statistics of each adjustment models. The experimental results show the estimation characteristics of adjustment models against varying surface conditions.