• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.11 no.2
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• pp.12-18
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• 2015

The energy pile, used for both structural foundations and heat exchangers, brings about heat exchange with the ground formation by circulating a working fluid for heating and cooling buildings. As heat exchange occurs in the energy pile, thermal stress and strain is generated in the pile body and surrounding ground formation. In order to investigate the thermo-mechanical behavior of an energy pile, a comprehensive experimental program was conducted, monitoring the thermal stress of a cast-in place energy pile equipped with five pairs of U-type heat exchanger pipes. The heating and cooling simulation both continued for 30 days. The thermal strain in the longitudinal direction of the energy pile was monitored for a 15 operation days and another 15 days monitoring followed, without the application of heat exchange. In addition, a finite element model was developed to simulate the thermo-mechanical behavior of the energy pile. A non-linear contact model was adopted to interpret the interaction at the pile-soil interface, and thermal-induced structure mechanics was considered to handle the thermo-mechanical coupled multi-field problem.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.29-39
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• 2019

As mobile robot applications increase in real life, the need of low cost autonomous driving are gradually increasing. We propose a novel vision-based real-time lane detection and tracking system that supports autonomous driving of mobile robots in constrained tracks which are designed considering indoor driving conditions of mobile robots. Considering the processing of lanes with various shapes and the pre-adjustment of operation parameters, the system structure with multi-operation modes are designed. In parameter tuning mode, thresholds of the color filter is dynamically adjusted based on the geometric property of the lane thickness. And in the unstable input mode of curved tracks and the stable input mode of straight tracks, lane feature pixels are adaptively extracted based on the geometric and temporal characteristics of the lanes and the lane model is fitted using the least-squared method. The track centerline is calculated using lane models and the motion model is simplified and tracked by a linear Kalman filter. In the driving experiments, it was confirmed that even in low-performance robot configurations, real-time processing produces the accurate autonomous driving in the constrained track.

• Journal of the Korean GEO-environmental Society
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• v.20 no.12
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• pp.5-14
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• 2019

Recently in Korea, researches on seismic analyses for high-rise buildings in a large city have been increasing because earthquakes have occurred. However, the ground conditions are not included in most of seismic researches and analyses on a high-rise building. Also the influence of the predominant period of a seismic wave is not considered in reality. Therefore, in this study, the influence of the predominant period of a seismic wave on the dynamic behavior of high-rise buildings was analyzed based on the complete system model which can consider the grounds. For this purpose, 2D dynamic analyses based on a linear time history analysis were performed using MIDAS GTS NX, a finite-element based program. Dynamic behavior was analyzed in terms of horizontal displacements, drift ratios, bending stresses, and building weak zones. As a result, in overall, the dynamic response of a high-rise building become bigger as the predominant period of a seismic wave become longer. It was also found that the predominant period had a greater influence than other parameters, ground conditions and peak ground acceleration.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.3
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• pp.175-182
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• 2022

In many engineering problems, the dynamic substructuring can be useful to analyze complex structures which made with many substructures, such as aircrafts and automotive vehicles. It was originally intended as a method to simplify the engineering problem. The powerful advantage to this is that computational efficiency dramatically increases with eliminating unnecessary degrees-of-freedom of the system and the system targets are concurrently satisfied. Craig-Bampton method has been widely used for the linear system reduction. Recently, multi-level optimization (such as target cascading), which propagates the system-level targets to the subsystem-level targets, has been widely utilized. To this concept, the genetic algorithm which one of the global optimization technique has been utilized to the substructure optimization. The number of internal modes for each substructure can be obtained by the genetic algorithm. Simultaneously, the reduced system meets the top-level targets. In this paper, various numerical examples are tested to verify this concept.

• Steel and Composite Structures
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• v.46 no.6
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• pp.839-856
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• 2023

This work presents a simple four-unknown refined integral plate theory for mechanical and thermal buckling behaviors of functionally graded (FG) plates resting on Visco-Pasternak foundations. The proposed refined high order shear deformation theory has a new displacement field which includes indeterminate integral variables and contains only four unknowns in which any shear correction factor not used, with even less than the conventional theory of first shear strain (FSDT). Governing equations are deduced from the principle of minimum total potential energy and a Navier type analytical solution is adopted for simply supported FG plates. The Visco-Pasternak foundations is considered by adding the impact of damping to the usual foundation model which characterized by the linear Winkler's modulus and Pasternak's foundation modulus. The accuracy of the present model is demonstrated by comparing the computed results with those available in the literature. Some numerical results are presented to show the impact of material index, elastic foundation type, and damping coefficient of the foundation, on the mechanical and thermal buckling behaviors of FG plates.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.453-465
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• 2024

This paper presents a logarithmic shear deformation theory to study the thermal buckling response of power-law FG one-dimensional structures in thermal conditions with different boundary conditions. It is assumed that the functionally graded material and thermal properties are supposed to vary smoothly according to a contentious function across the vertical direction of the beams. A P-FG type function is employed to describe the volume fraction of material and thermal properties of the graded (1D) beam. The Ritz model is employed to solve the thermal buckling problems in immovable boundary conditions. The outcomes of the stability analysis of FG beams with temperature-dependent and independent properties are presented. The effects of the thermal loading are considered with three forms of rising: nonlinear, linear and uniform. Numerical results are obtained employing the present logarithmic theory and are verified by comparisons with the other models to check the accuracy of the developed theory. A parametric study was conducted to investigate the effects of various parameters on the critical thermal stability of P-FG beams. These parameters included support type, temperature fields, material distributions, side-to-thickness ratios, and temperature dependency.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.2
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• pp.81-93
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• 2020

The fatigue characteristics of glass fiber reinforced plastic (GFRP) composites were studied under repeated loads using the finite element method (FEM). To realize the material characteristics of GFRP composites, Digimat, a mean-field homogenization tool, was employed. Additionally, the micro-structures and material models of GFRP composites were defined with it to predict the fatigue behavior of composites more realistically. Specifically, the fatigue characteristics of polybutylene terephthalate with short fiber fractions of 30wt% were investigated with respect to fiber orientation, stress ratio, and thickness. The injection analysis was conducted using Moldflow software to obtain the information on fiber orientations. It was mapped over FEM concerned with fatigue specimens. LS-DYNA, a typical finite element commercial software, was used in the coupled analysis of Digimat to calculate the stress amplitude of composites. FEMFAT software consisting of various numerical material models was used to predict the fatigue life. The results of coupled analysis of linear and nonlinear material models of Digimat were analyzed to identify the fatigue characteristics of GFRP composites using FEMFAT. Neuber's rule was applied to the linear material model to analyze the fatigue behavior in LCF regimen. Additionally, to evaluate the morphological and mechanical structure of GFRP composites, the coupled and fatigue analysis were conducted in terms of thickness.

• Journal of the Korean Geotechnical Society
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• v.23 no.12
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• pp.83-94
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• 2007

Piled raft foundations have been highlighted as an economical design concept of pile foundations in recent years. However, piled raft foundations have not been widely used in Korea due to the difficulty in estimating the complex interaction effects among rafts, piles and soils. The authors developed an effective numerical program to analyze the behavior of piled raft foundations for practical design purposes and presented it briefly in this paper. The developed numerical program simulates the raft as a flexible plate consisting of finite elements with eight nodes and the raft is supported by a series of elastic springs representing subsoils and piles. This study imported another model to simulate pile groups considering non-linear behavior and interaction effects. The apparent stiffnesses of the soils and piles were estimated by iterative calculations to satisfy the compatibility between those two components and the behavior of piled raft foundations can be predicted using these stiffnesses. For the verification of the program, the analysis results about some example problems were compared with those of rigorous three dimensional finite element analysis and other approximate analysis methods. It was found that the program can analyze non-linear behaviors and interaction effects efficiently in multi-layered soils and has sufficient capabilities for application to practical analysis and design of piled raft foundations.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.