• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.611-620
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• 2006

The composite two plate-girder bridges are generally defined as a non-redundant load path structure because the bridge can collapse if one of the two girders is seriously damaged by a fatigue crack. In this paper, a numerical study on the evaluation of the after-fracture redundancy of the composite two-girder bridges was accomplished. The evaluation has been performed on the simple and three-span continuous bridges with I-section cross beams which serve as transverse bracing, and with or without the bottom lateral bracing system. The load carrying capacities of the intact and damaged bridges with or without lateral bracing were evaluated from material and geometric nonlinear analysis, respectively and the redundancy was evaluated for each case. It was acknowledged from the analytical results that both simple and continuous intact two-girder bridges have sufficient redundancy even without lateral bracing, but it takes an important role to improve the redundancy of damaged bridges.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.386-392
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• 2024

This paper constructs a precise dynamics model using flightlab, a specialized program for rotor modeling and performance analysis, to simulate urban air mobility (UAM). flightlab is well-suited for detailed modeling of UAM, particularly requiring detailed aerodynamic characteristics under high-altitude and urban wind conditions. The study focuses on implementing and analyzing a lift-cruise UAM model with distributed propulsion using flightlab. The lift-cruise model integrates motors for vertical take-off and fixed-wing flight. Given the limited specific examples of such UAM models in flightlab and challenges in evaluating with conventional fixed-wing or drone models, this research implements and verifies the lift-cruise model using matlab, comparing its performance against flightlab results to validate the modeling approach. This research aims to explore the potential of flightlab for detailed UAM modeling and contribute to technological advancements in future urban transportation.

• Advances in concrete construction
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• v.17 no.5
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• pp.273-284
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• 2024

The steel-concrete composite system has been playing a vital role in the construction sector for the past two decades. By using steel and concrete together, we achieve strong load resistance with minimal deflection and bending stress. The study focuses on the numerical and analytical behaviour of concrete encased steel castellated beams and compared them with previous experiments. The study used five composite beams, including one control reinforced concrete beam (CC), one fully concrete encased steel beam (FCES), and three fully concrete encased castellated beams. The major variable is the opening configuration of the castellated beam, such as openings along the longitudinal axis, above the longitudinal axis, and below the longitudinal axis. The 150 mm × 250 mm cross section and 2000 mm in length of beams were used. Using the finite element software ANSYS, we conduct nonlinear finite element analysis for the entire beam and compare it with test data. The numerical load carrying capacity of concrete encased steel castellated beam with a hexagonal opening above the longitudinal axis (FCESCB H2) is 160 kN is closer to the experimental observation. Von Mises strain of FCESB is 0.004232, which is lower than CB and composite castellated beam. The ductility factor and energy absorption capacity of FCESB are 5.090 and 1688.47 kNm. It was observed that the configuration of the opening will influence the strength of the composite beam. Plastic moment methods were employed to estimate the ultimate load carrying capacity of the beam. In the analytical study the beams were assumed as perfectly plastic. The ultimate analytical load carrying capacity of FCESCB H2 is 21.87% higher than FCESB. It found that performing FCESCB H2 is superior to the entire specimen.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.6
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• pp.706-714
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• 2007

This study suggested a method for prediction of residual chlorine and THMs in water distribution system by measurement of residual chlorine, THMs, and other parameters, estimation of chlorine decay coefficients and THM formation coefficients, and simulation of water qualities using pipe network analysis. Bulk decay coefficients of parallel first-order were obtained by bottle tests, and pipe wall decay coefficients of first-order were estimated through evaluation of 5 models, which showed the lowest values of 0.03 for MAE(mean absolute error) and 0.037 MAE in comparison with the observed in field. And bottle tests were conducted to model first-order reaction of THM formation by nonlinear least square regression and the resultant coefficients were compared with the observed in field. As a result, the coefficients of determination$(R^2)$ for the observed and the predicted values were 0.98 in September and 0.82 in November, and the formation of THMs was predicted by modeling.

• Earthquakes and Structures
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• v.12 no.4
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• pp.397-407
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• 2017

To estimate the structural seismic demand, some methods are based on an equivalent linear system such as the Capacity Spectrum Method, the N2 method and the Equivalent Linearization method. Another category, widely investigated, is based on displacement correction such as the Displacement Coefficient Method and the Coefficient Method. Its basic concept consists in converting the elastic linear displacement of an equivalent Single Degree of Freedom system (SDOF) into a corresponding inelastic displacement. It relies on adequate modifying or reduction coefficient such as the inelastic deformation ratio which is usually developed for systems with known ductility factors ($C_{\mu}$) and ($C_R$) for known yield-strength reduction factor. The present paper proposes a rational approach which estimates this inelastic deformation ratio for SDOF bilinear systems by rigorous nonlinear analysis. It proposes a new inelastic deformation ratio which unifies and combines both $C_{\mu}$ and $C_R$ effects. It is defined by the ratio between the inelastic and elastic maximum lateral displacement demands. Three options are investigated in order to express the inelastic response spectra in terms of: ductility demand, yield strength reduction factor, and inelastic deformation ratio which depends on the period, the post-to-preyield stiffness ratio, the yield strength and the peak ground acceleration. This new inelastic deformation ratio ($C_{\eta}$) is describes the response spectra and is related to the capacity curve (pushover curve): normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), natural period (T), peak ductility factor (${\mu}$), and the yield strength reduction factor ($R_y$). For illustrative purposes, instantaneous ductility demand and yield strength reduction factor for a SDOF system subject to various recorded motions (El-Centro 1940 (N/S), Boumerdes: Algeria 2003). The method accuracy is investigated and compared to classical formulations, for various hysteretic models and values of the normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), and natural period (T). Though the ductility demand and yield strength reduction factor differ greatly for some given T and ${\eta}$ ranges, they remain take close when ${\eta}>1$, whereas they are equal to 1 for periods $T{\geq}1s$.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.21-33
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• 2022

Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.108-117
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• 2023

Objectives : Somatic symptom disorder (SSD) is characterized by the manifestation of a variety of physical symptoms, but little is known about differences in autonomic nervous system activity according to symptom severity, especially within patient groups. In this study, we examined differences in heart rate variability (HRV) across symptom severity in a group of SSD patients to analyze a representative marker of autonomic nervous system changes by symptoms severity. Methods : Medical records were retrospectively reviewed for patients who were diagnosed with SSD based on DSM-5 from September 18, 2020 to October 29, 2021. We applied inverse probability of treatment weighting (IPTW) methods to generate more homogeneous comparisons in HRV parameters by correcting for selection biases due to sociodemographic and clinical characteristic differences between groups. Results : There were statistically significant correlations between the somatic symptom severity and LF (nu), HF (nu), LF/HF, as well as SD1/SD2 and Alpha1/Alpha2. After IPTW estimation, the mild to moderate group was corrected to 27 (53.0%) and the severe group to 24 (47.0%), and homogeneity was achieved as the differences in demographic and clinical characteristics were not significant. The analysis of inverse probability weighted regression adjustment model showed that the severe group was associated with significantly lower RMSSD (β=-0.70, p=0.003) and pNN20 (β=-1.04, p=0.019) in the time domain and higher LF (nu) (β=0.29, p<0.001), lower HF (nu) (β=-0.29, p<0.001), higher LF/HF (β=1.41, p=0.001), and in the nonlinear domain, significant differences were tested for SampEn15 (β=-0.35, p=0.014), SD1/SD2 (β=-0.68, p<0.001), and Alpha1/Alpha2 (ß=0.43, p=0.001). Conclusions : These results suggest that differences in HRV parameters by SSD severity were showed in the time, frequency and nonlinear domains, specific parameters demonstrating significantly higher sympathetic nerve activity and reduced ability of the parasympathetic nervous system in SSD patients with severe symptoms.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.301-306
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• 2018

Urbanization causes urban floods and urban heat island in the summer, so it is necessary to understanding the changes of the thermal environment through urban climate and energy balance. This can be explained by the energy balance, but in urban areas, unlike the typical energy balance, the storage heat flux saved in the building or artificial land cover should be considered. Since the environment of each city is different, there is a difficulty in applying the method of retrieving the storage heat flux of the previous research. Especially, most of the previous studies are focused on the overseas cities, so it is necessary to study the storage heat retrieval suitable for various land cover and building characteristics of the urban areas in Korea. Therefore, the object of this study, it is to derive the regression formula which can quantitatively retrieve the storage heat using the data of the area where various surface types exist. To this end, nonlinear regression analysis was performed using net radiation and surface temperature data as independent variables and flux tower based storage heat estimates as dependent variables. The retrieved regression coefficients were applied to each independent variable to derive the storage heat retrieval regression formula. As a result of time series analysis with flux tower based storage heat estimates, it was well simulated high peak at day time and the value at night. Moreover storage heat retrieved in this study was possible continuous retrieval than flux tower based storage heat estimates. As a result of scatter plot analysis, accuracy of retrieved storage heat was found to be significant at $50.14Wm^{-2}$ and bias $-0.94Wm^{-2}$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.607-615
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• 2020

The purpose of this study was to analyze the research status and trends related to the industrial mathematics based on text mining techniques with a sample of 4910 papers collected in the SIAM Journal on Applied Mathematics from 1970 to 2019. The R program was used to collect titles, abstracts, and key words from the papers and to analyze topic modeling techniques based on LDA algorithm. As a result of the coherence score on the collected papers, 20 topics were determined optimally using the Gibbs sampling methods. The main results were as follows. First, studies on industrial mathematics were conducted in a variety of mathematics fields, including computational mathematics, geometry, mathematical modeling, topology, discrete mathematics, probability and statistics, with a focus on analysis and algebra. Second, 5 hot topics (mathematical biology, nonlinear partial differential equation, discrete mathematics, statistics, topology) and 1 cold topic (probability theory) were found based on time series regression analysis. Third, among the fields that were not reflected in the 2015 revised mathematics curriculum, numeral system, matrix, vector in space, and complex numbers were extracted as the contents to be covered in the high school mathematical curriculum. Finally, this study suggested strategies to activate industrial mathematics in Korea, described the study limitations, and proposed directions for future research.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.5
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• pp.333-340
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• 2019

Tests using a middle velocity propulsion impact machine (MVPIM) were performed to verify the impact resistance capability of sandwich concrete panels (SCP) in a modular liquefied natural gas (LNG) outer tank, and numerical models were constructed and analyzed. $2{\times}2m$ specimens with plain sectional characteristics and specimens including a joint section were used. A 51 kg missile was accelerated above 45 m/s and impacted to have the design code kinetic energy. Impact tests were performed twice according to the design code and once for the doubled impact speed. The numerical models for simulating impact behaviors were created by LS-DYNA. The external steel plate and filled concrete of the panel were modeled as solid elements, the studs as beam elements, and the steel plates as elasto-plastic material with fractures; the CSCM material model was used for concrete. The front plate deformations demonstrated good agreement with those of other tests. However the rear plate deformations were less. In the doubled speed test for the plain section specimen, the missile punctured both plates; however, the front plate was only fractured in the numerical analysis. The impact energy of the missile was transferred to the filled concrete in the numerical analysis.