• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1071-1074
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• 2008

In this study, the behavior of dredged soil was measured by repeated tide and analyzed the change of settlements and cone penetration resistance by centrifuge model about dredged soil of Kunsan-Janghang site that maximum tidal range is 7.4m. Consequently the settlements of dredged soil by repeated tide in the 2nd month was 0.489 m. After 12th month, the total settlements was 0.524 m in the model. It meaned the settlements of dredged soil by repeated tide in the 2th month was 80% of the settlements. Also, with the lapse of time, cone penetration resistance increased centrifuge model test for catching the strength change of dredged soil by repeated tide. After 10th month, there were not almost changes. cone penetration resistance in 10th month was measured more 3.5~5.6 times than that in its early stages. Also, with the lapse of time, cone penetration resistance increased almost linearly. And, when we surveyed the relation between cone penetration resistance and time, as depth increased, cone penetration resistance rose.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2581-2588
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• 2000

In previous studies, the dynamic resistance, which was calculated by the process variables measured at the electrode of the welding machine, and the electrode displacement were used for quality exa mination. However, in-process usage of such systems is not effective in systems that include a welding gun attached to a robot. In order to overcome such problems, we obtained and used the process variables from the welding machine timer. This would allow us to estimate real time in -process weld quality. For quality estimation, the features were extracted as factors from the primary dynamic resistance patterns, which were measured in t he welding machine timer. The relationship between the indexes and nugget size of the welds was observed through the regression analysis. Using the analyzed factors, a regression model that could estimate nugget diameter was developed. Two regression equations of the model were suggested depending on the factors, and it was showed that the model developed by stepwise method was effective one for weld quality estimation. The developed estimation model was in good linearity with the nugget diameter obtained through the experimentation.

• Steel and Composite Structures
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• v.44 no.6
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• pp.769-788
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• 2022

In this paper a mathematical model for the prediction of the fire resistance of slim-floor steel beams based on an Artificial Neural Network modeling procedure is presented. The artificial neural network models are trained and tested using an analytical database compiled for this purpose from analytical results based on FEM. The proposed model was selected as the optimum from a plethora of alternatives, employing different activation functions in the context of Artificial Neural Network technique. The performance of the developed model was compared against analytical results, employing several performance indices. It was found that the proposed model achieves remarkably improved predictions of the fire resistance of slim-floor steel beams. Moreover, based on the optimum developed AN model a closed-form equation for the estimation of fire resistance is derived, which can prove a useful tool for researchers and engineers, while at the same time can effectively support the teaching of this subject at an academic level.

• Steel and Composite Structures
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• v.49 no.1
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• pp.109-123
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• 2023

Headed studs welded to steel beams and embedded within the concrete of deck slabs are vital components of modern composite floor systems, where safety and economy depend on the accurate predictions of the stud shear resistance. The multitude of existing deck profiles and the complex behavior of studs in deck slab ribs makes developing accurate and reliable mechanical or empirical design models challenging. The paper addresses this issue by presenting a machine learning (ML) model developed from the natural gradient boosting (NGBoost) algorithm capable of producing probabilistic predictions and a database of 464 push-out tests, which is considerably larger than the databases used for developing existing design models. The proposed model outperforms models based on other ML algorithms and existing descriptive equations, including those in EC4 and AISC 360, while offering probabilistic predictions unavailable from other models and producing higher shear resistances for many cases. The present study also showed that the stud shear resistance is insensitive to the concrete elastic modulus, stud welding type, location of slab reinforcement, and other parameters considered important by existing models. The NGBoost model was interpreted by evaluating the feature importance and dependence determined with the SHapley Additive exPlanations (SHAP) method. The model was calibrated via reliability analyses in accordance with the Eurocodes to ensure that its predictions meet the required reliability level and facilitate its use in design. An interactive open-source web application was created and deployed to the cloud to allow for convenient and rapid stud shear resistance predictions with the developed model.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.107-124
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• 2021

This study is a study on the innovation resistance that may arise in connection with the introduction and use of smart factory-related technologies by SMEs. It is to study the effect of the leading factors of innovation resistance on innovation resistance and the effect of innovation resistance on use intention by using the extended innovation resistance model. A total of 176 survey data were used for the study, and the study was conducted using SPSS 25 and Smart PLS 2.0. Relative advantage, suitability, perceived risk, social impact, and organizational characteristics have a significant effect on innovation resistance, and innovation resistance was tested to have a significant effect on the intention to use. As an implication according to the research, a plan to improve the level of introduction and use of smart factories using the expanded innovative storage model was presented by dividing positive and negative factors, and factors that should be improved and factors that should be reduced are presented. It was specifically presented.

• Journal of Ship and Ocean Technology
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• v.11 no.4
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• pp.55-71
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• 2007

The primary objective of this work is to develop methodologies for virtual model basin and to demonstrate the capabilities for generic multi-hull ship geometry. A computational fluid dynamics approach is used to simulate various model basin tests for steady resistance, maneuvering and seakeeping. For a catamaran hull configuration, the methodologies are used for solving these problems and the results are discussed. Computational results are compared with the results of a benchmarked potential flow theory method for calm water resistance.

• 한국전산유체공학회:학술대회논문집
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• 2009.11a
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• pp.77-83
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• 2009

In this study, we conducted resistance and propulsion performance test of ship composed of the Resistance Test, Propeller Open Water Test and Self Propulsion Test using the CFD(Computational Fluid Dynamics). We used commercial RANS(Reynolds Averaged Navier Stokes equation) solver, as a calculating tool. The unstructured grids were used in a bow and stern of ship, having complex shape, for a convenience of generating grids, and the structured grids were adopted in a central hull and rest of hull having a relatively simple shape which is called hybrid grid method. In addition, The sliding mesh method was adopted to rotate a propeller directly in the Propeller Open Water and Self Propulsion Test. The Resistance Test and Self Propulsion Test were calculated using Volume of Fluid (VOF) model and considering a free surface. And all The three cases were applied realizable k-epsilon model as the turbulence model. The results of calculations were verified for the suitability of calculations by comparing MOERI's EFD results.

• Journal of Korean Society of Water and Wastewater
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• v.10 no.1
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• pp.85-95
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• 1996

Although the specific resistance to filtration is the most frequently employed means for characterizing dewaterability of a sludge, it presently is not possible to design nor to prediet performance of dewatering facilities using traditional linearized parabolic filtration equation, that is, the specific resistance model because of theoretical and practical inadequacies of the concept. Limitations of the specific resistance model reflect the need to examine fundamental sludge properties and filtration behaviors affecting dewaterability. From this study, two major limitations of the specific resistance model were noted. First, specific resistance values are very dependent on the sludge concentration because of the variations of particle size distribution and cake clogging to occur when surface area mean diameter is less than $25{\mu}m$ for activated sludge, $18{\mu}m$ for water treatment plant sludge. Second, nonparabolic filtration behavior can result from cake clogging, caused by the migration of fine particles into the cake pores, accelated by skin effect with highly compressible sludges.

• Journal of Environmental Science International
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• v.17 no.11
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• pp.1203-1210
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• 2008

Flow resistance in a natural stream is caused by complex factors, such as the grains on the bed, vegetation, and bed-form, reach profile. Flow resistance in a generally stable gravel bed stream is due to protrudent grains from bed. Therefore, the flow resistance can be calculated by equivalent roughness in gravel bed stream, but estimation of equivalent roughness is difficult because nonuniform size and irregular arrangement of distributed grain on natural stream bed. In previous study, equivalent roughness is empirically estimated using characteristic grain size. However, application of empirical equation have uncertainty in stream that stream bed characteristic differs. In this study, we developed a model using an analytical method considering grain diameter distribution characteristics of grains on the bed and also taking into account flow resistance acting on each grain. Also, the model consider the protrusion height of grain.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1656_1657
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• 2009

This paper presents a new method for estimating rotor resistance of induction motor. The rotor resistance changes dramatically with temperature and frequency. Speed is controlled by PID as it is simplest and most intuitive control method. The change in rotor resistance has a great influence on the performance of IM. In this paper rotor resistance is estimated using Non Linear Disturbance Observer. The model uncertainty and system non linearity are treated as disturbance in this method. Using NDO it does not require an accurate dynamic model to achieve high precision motor control. Controller with NDO has more superior tracking performance. Simulation results are presented to show the validity of the proposed controller.