• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.529-542
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• 2020

As limited well-documented experimental data are available for assessing the attributes of different deformation components of flanged walls, few appropriate models have been established for predicting the inelastic responses of flanged walls, especially those of asymmetrical flanged walls. This study presents the experimental results for three large-scale T-shaped reinforced concrete walls and examines the variations in the flexural, shear, and sliding components of deformation with the total deformation over the entire loading process. Based on the observed deformation behavior, a simple model based on moment-curvature analysis is established to estimate flexural deformations, in which the changes in plastic hinge length are considered and the deformations due to strain penetration are modeled individually. Based on the similar gross shapes of the curvature and shear strain distributions over the wall height, a proportional relationship is established between shear displacement and flexural rotation. By integrating the deformations due to flexure, shear, and strain penetration, a new load-deformation analytical model is proposed for flexure-dominant flanged walls. The proposed model provides engineers with a simple, accurate modeling tool appropriate for routine design work that can be applied to flexural walls with arbitrary sections and is capable of determining displacements at any position over the wall height. By further simplifying the analytical model, a simple procedure for estimating the ultimate displacement capacity of flanged walls is proposed, which will be valuable for performance-based seismic designs and seismic capacity evaluations.

• Earthquakes and Structures
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• v.17 no.5
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• pp.511-519
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• 2019

The concrete gravity dam is one of the most important parts of the nation's infrastructure. Besides the benefits, the dam also has some potentially catastrophic disasters related to the life of citizens directly. During the lifetime of service, some degradations in a dam may occur as consequences of operating conditions, environmental aspects and deterioration in materials from natural causes, especially from dynamic loads. Cumulative Absolute Velocity (CAV) plays a key role to assess the operational condition of a structure under seismic hazard. In previous researches, CAV is normally used in Nuclear Power Plant (NPP) fields, but there are no particular criteria or studies that have been made on dam structure. This paper presents a method to calculate the limitation of CAV for the Bohyeonsan Dam in Korea, where the critical Peak Ground Acceleration (PGA) is estimated from twelve sets of selected earthquakes based on High Confidence of Low Probability of Failure (HCLPF). HCLPF point denotes 5% damage probability with 95% confidence level in the fragility curve, and the corresponding PGA expresses the crucial acceleration of this dam. For determining the status of the dam, a 2D finite element model is simulated by ABAQUS. At first, the dam's parameters are optimized by the Minitab tool using the method of Central Composite Design (CCD) for increasing model reliability. Then the Response Surface Methodology (RSM) is used for updating the model and the optimization is implemented from the selected model parameters. Finally, the recorded response of the concrete gravity dam is compared against the results obtained from solving the numerical model for identifying the physical condition of the structure.

• Smart Structures and Systems
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• v.13 no.2
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• pp.257-280
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• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• Steel and Composite Structures
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• v.31 no.1
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• pp.69-83
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• 2019

This paper investigates the structural behavior of very high strength concrete encased steel composite columns via combined experimental and analytical study. The experimental programme examines stub composite columns under pure compression and eccentric compression. The experimental results show that the high strength encased concrete composite column exhibits brittle post peak behavior and low ductility but has acceptable compressive resistance. The high strength concrete encased composite column subjected to early spalling and initial flexural cracking due to its brittle nature that may degrade the stiffness and ultimate resistance. The analytical study compares the current code methods (ACI 318, Eurocode 4, AISC 360 and Chinese JGJ 138) in predicting the compressive resistance of the high strength concrete encased composite columns to verify the accuracy. The plastic design resistance may not be fully achieved. A database including the concrete encased composite column under concentered and eccentric compression is established to verify the predictions using the proposed elastic, elastoplastic and plastic methods. Image-oriented intelligent recognition tool-based fiber element method is programmed to predict the load resistances. It is found that the plastic method can give an accurate prediction of the load resistance for the encased composite column using normal strength concrete (20-60 MPa) while the elastoplastic method provides reasonably conservative predictions for the encased composite column using high strength concrete (60-120 MPa).

• The Korean Journal of Franchise Management
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• v.10 no.4
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• pp.43-52
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• 2019

Purpose: As a research on the effects of the characteristics of franchise educational institution and contents on the educational transition, commitment, and recommendation intention, this study aimed to suggest the basic data that could be used for the performance of educational training of franchise headquarters, and also to suggest an empirical research helpful for the development of actual educational system and the operation of curriculum for franchise educational institutions. Research design, data, and methodology: This study selected the trainees who recently completed the training in a franchise educational institution as the samples. The survey was conducted for 20 days from October 1st to October 20th 2018, targeting total 230 people, and total 207 questionnaires were collected (Missing value 23). To verify the validity of the measurement tool used for this study, this study reviewed the factor loading of each factor by conducting the confirmatory factor analysis(CFA), and then verified the average variance extracted(AVE) and the composite construct reliability(CCR). Lastly, the structural equation model(SEM) was verified based on the research hypotheses and research model. The SPSS Win Ver. 20.0 & AMOS 20.0 were used for every analysis of this study. Results: The results of this study could be summarized as follows. First, the reputation and interaction of the characteristics of franchise educational institution had significantly positive(+) effects on the educational transition. Second, all the sub - variables of educational contents such as job relevance, education method, and instructors' professionalism had positive(+) effects on the educational transition while the educational transition had positive effects on the organizational commitment, career commitment, and job commitment. Lastly, the organizational commitment and job commitment had positive(+) effects on the recommendation intention. Thus, the trainees with higher organizational commitment and job commitment in a franchise educational institution, showed higher intention to recommend the educational institution to others. Conclusions: The results of this study imply that the franchise educational institutions could increase the actual performance of education such as educational transition, commitment, and recommendation intention by increasing interactions within educational institutions and also designing effective educational contents, so that the trainees could highly perceive the educational transition of education.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.27-37
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• 2020

The Fukushima Daiichi accident in 2011 revealed some vulnerabilities of existing Nuclear Power Plants (NPPs) under extended Station Blackout (SBO) accident conditions. One of the key Severe Accident Management (SAM) strategies developed post Fukushima accident is the In-Vessel Retention (IVR) Strategy which aims to retain the structural integrity of the Reactor Pressure Vessel (RPV). RELAP/SCDAPSIM/MOD3.4 is selected to predict the thermal-hydraulic response of APR1400 undergoing an extended SBO. To assess the effectiveness of the IVR strategy, it is essential to quantify the underlying uncertainties. In this work, both the epistemic and aleatory uncertainties are considered to identify the success window of the IVR strategy. A set of in-vessel relevant phenomena were identified based on Phenomena Identification and Ranking Tables (PIRT) developed for severe accidents and propagated through the thermal-hydraulic model using Wilk's sampling method. For this work, a Systems Engineering (SE) approach is applied to facilitate the development process of assessing the reliability and robustness of the APR1400 IVR strategy. Specifically, the Kossiakoff SE method is used to identify the requirements, functions and physical architecture, and to develop a design verification and validation plan. Using the SE approach provides a systematic tool to successfully achieve the research goal by linking each requirement to a verification or validation test with predefined success criteria at each stage of the model development. The developed model identified the conditions necessary for successful implementation of the IVR strategy which maintains the vessel integrity and prevents a melt-through.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.265-277
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• 2021

Data is the core of AI technology. With the development of technology, AI technology is also accelerating as the amount of data increases explosively than before. However, compared to the interest in AI education, research on data education with AI is still insufficient. According to the case analysis of exsisting AI data education, there were cases of educating the process and part of data science, but it was hard to find studies related to data collection. Cause physical computing tools have a positive effect on AI education for elementary school students, data collection cases using tools were studied, but researches related to data collection were rare. Therefore, in this study, an efficient data collection method using physical tools was designed. A structural diagram of a data collection program was created using COBL S, a modular physical computing teaching tool, and examples of program screens from the service side and the user side were configured. This study has limitations in that the establishment of an AI education platform that can be used in conjunction with future program production and programs should be prioritized as a proposal in terms of design.

• Journal of Korea Trade
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• v.25 no.6
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• pp.105-125
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• 2021

Purpose - This study analyzes the effects that the response to the technical barriers to trade (TBT), which are used by various countries as means to restrict imports, exerts on exports at a time when protectionism is emerging in the face of a global economic downturn. TBT has been widely used in developed countries for the safety and protection of their people. Recently, the use of TBT as a tool of protectionism has increased considerably in developing countries as well. Therefore, this study analyzes the South Korean SMEs' response and export performance. Design/methodology - To analyze SMEs' response to TBT and their export performance, this study conducted empirical analysis through statistical analysis. To this end, the research established a theory based on previous research and designed its hypothesis and research model. To verify the hypothesis and research model, factor analysis addressing validity and reliability was performed using SPSS 25 and AMOS 26, and the structural equation model was analyzed. Findings - This study found the causal relationship between the independent variable, the mediating variable, and the dependent variable adopted against the theoretical background to have little or no effect, in contrast with previous studies. In a break from previous studies, all hypotheses were rejected for innovation strategic competencies, one of the sub-factors of the independent variable, which is believed to be a result of the lack of practical research related to TBT. Originality/value - Previous studies performed analysis using trade statistics or macro data. A number of such studies analyzed the relationship between technical regulation and trade volume. This study differs from previous studies in some respects, because it analyzed the export performance of companies by establishing a hypothesis and implementing a research model with the factors analyzed in previous studies. In addition, a new attempt has been made by classifying the TBT response factors into technology competencies, human resource competencies, and innovation strategic competencies, and utilizing technology innovation and the export support system as mediating effects.

• Structural Engineering and Mechanics
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• v.84 no.1
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• pp.17-33
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• 2022

An experimental study is carried out to investigate the performance of the cutting tool regarding the insert wear, surface roughness, cutting forces, cutting power and material removal rate of three coated carbides GC2015 (TiCN-Al₂O₃-TiN), GC4215 (Al₂O₃-Ti(C,N)) and GC1015 (TiN) during the dry turning of AISI4140 steel. For this purpose, a Taguchi design (L₉) was adopted for the planning of the experiments, the effects of cutting parameters on the surface roughness (R_a), tangential cutting force (F_z), the cutting power (P_c) and the material removal rate (MRR) were studied using analysis of variance (ANOVA), the response surface methodology (RSM) was used for mathematical modeling, with which linear mathematical models were developed for forecasting of R_a, F_z, P_c and MRR as a function of cutting parameters (V_c, f, and a_p). Then, Multi-Objective Ant Lion Optimizer (MOALO) has been implemented for multi-objective optimization which allows manufacturers to enhance the production performances of the machined parts. Furthermore, in order to characterize and quantify the flank wear of the tested tools, some machining experiments were performed for 5 minutes of turning under a depth of 0.5 mm, a feed rate of 0.08 mm/rev, and a cutting speed of 350 m/min. The wear results led to a ratio (V_B-GC4215/V_B-GC2015) of 2.03 and (V_B-GC1015/V_B-GC2015) of 4.43, thus demonstrating the efficiency of the cutting insert GC2015. Moreover, SEM analysis shows the main wear mechanisms represented by abrasion, adhesion and chipping.

• Structural Engineering and Mechanics
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• v.86 no.1
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.