• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.97-104
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• 2018

Recently, as the shape and function of high-rise buildings have become more complex, engineering for reflecting the constructability in the design phase has the increasing importance. However, engineering tasks are not performed at the appropriate level and timing in most projects, which leads to inefficient work such as design changes and reworks. Hence, this study investigated the constructability knowledge, design elements, and supporting tools required to conduct engineering tasks related to temporary work at the design phase, and also analyzed the relationship between these factors using the correlation analysis. As a result, when the engineering tasks are applied in the design phase, constructability knowledge related to 'construction method and process' is the most important and the design factor related to 'layout/arrangement' should be considered as the most important factor. Based on the results of this study, the project participants can efficiently use necessary constructability knowledge during the design phase and facilitate effective decision-making and design alternatives for enhancing constructability.

• Journal of Fashion Business
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• v.23 no.3
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• pp.1-9
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• 2019

The purpose of this study was to develop questions for fashion design development, by applying 7 elements of the scamper to the fashion design elements, and to present a scamper checklist of fashion design elements, and item structures. In this study, the scope of research was limited to clothing design among various fashion products, and among various design development stages. Fashion design development focusing on design sketching, was limited to the research scope. The research method was based on an empirical study that derived scamper questions through FGI (Focus Group Interview), consisting of 5 fashion experts. Fashion design elements applied to development of scamper questions consisted of silhouettes, constructive lines, structural details, decorative details, patterns and textures of fabrics, and item structures, derived by applying these elements to the individual 7 elements of the scamper: substitute, combine, adjust, modify, put to other uses, eliminate, and reverse. Results of the study included 7 questions for substituting, 8 questions for combining, 6 questions for applying, 15 questions for modifying, 4 questions for putting to other uses, 4 questions for eliminating, and 7 questions for reversal. The scamper checklist for fashion design elements and item structures drew to 5 lists of silhouette variations, 7 lists of constructive line variations, 11 lists of structural detail variations, 10 lists of decorative detail variations, 11 lists of fabric variations, and 9 lists of structural modifications of items.

• Composites Research
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• v.31 no.6
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• pp.340-346
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• 2018

This paper addresses the stress analysis and design of composite double lead spiral which is boarded in 20mm universal ammunition drum by finite element method. The spiral system is very important to transfer the ammunition in stable and reliable manners for aircraft. Some verifications are done to check the possibility of composite application in spiral system. The design variables, stacking sequence and fiber orientation angles, are investigated for reliable design for practical design. The Tsai-Wu failure theory is applied to see the safety of the spiral structure. The design result is suggested to manufacture the double lead spiral part.

• Korean Journal of Artificial Intelligence
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• v.10 no.2
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• pp.7-11
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• 2022

OLED displays cannot be used permanently due to burn-in or generation of dark spots due to degradation. Therefore, the time when the display can operate normally is very important. It is close to impossible to physically measure the time when the display operates normally. Therefore, the time that works normally should be predicted in a way other than a physical way. Therefore, if you do computer simulations based on artificial intelligence, you can increase the accuracy of prediction by saving time and continuous learning. Therefore, if we do computer simulations based on artificial intelligence, we can increase the accuracy of prediction by saving time and continuous learning. In this paper, a dataset in the form of development from generation to diffusion of dark spots, which is one of the causes related to the life of OLED, was generated by applying the finite element method. The dark spots were generated in nine conditions, such as 0.1 to 2.0 ㎛ with the size of pinholes, the number was 10 to 100, and 50% with water content. The learning data created in this way may be a criterion for generating an artificial intelligence-based dataset.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Geomechanics and Engineering
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• v.24 no.3
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• pp.267-280
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• 2021

The research presented in this paper deals with dynamic stability analysis of the graphene nanoplatelets (GPLs) reinforced composite spinning disk. The presented small-scaled structure is simulated as a disk covered by viscoelastic substrate which is two-parametric. The centrifugal and Coriolis impacts due to the spinning are taken into account. The stresses and strains would be obtained using the first-order-shear-deformable-theory (FSDT). For Poisson ratio, as well as various amounts of mass densities, the mixture rule is employed, while a modified Halpin-Tsai model is inserted for achieving the elasticity module. The structure's boundary conditions (BCs) are obtained employing GPLs reinforced composite (GPLRC) spinning disk's governing equations applying principle of Hamilton which is based on minimum energy and ultimately have been solved employing numerical approach called generalized-differential quadrature-method (GDQM). Spinning disk's dynamic properties with different boundary conditions (BCs) are explained due to the curves drawn by Matlab software. Also, the simply-supported boundary conditions is applied to edges 𝜃=𝜋/2, and 𝜃=3𝜋/2, while, cantilever, respectively, is analyzed in R=R_i, and R₀. The final results reveal that the GPLs' weight fraction, viscoelastic substrate, various GPLs' pattern, and rotational velocity have a dramatic influence on the amplitude, and vibration behavior of a GPLRC rotating cantilevered disk. As an applicable result in related industries, the spinning velocity impact on the frequency is more effective in the higher radius ratio's amounts.

• Journal of KIBIM
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• v.10 no.2
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• pp.21-28
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• 2020

As the number of aging bridges increases, more studies are being conducted on developing effective and reliable methods for the assessment and maintenance of bridges. With the advancement in new sensing systems and data learning techniques through AI technology, there is growing interests in how to evaluate bridges using these advanced techniques. This paper presents a CNN(Convolution Neural Network) deep learning based technique for evaluating the damage existence and for estimating the damage location in PSC bridges using static strain data. Simulation studies were conducted to investigate the proposed method with error analysis. Damage was simulated as the reduction in the stiffness of a finite element. A data learning model was constructed by applying the CNN technique as a type of deep learning. The damage status and its location were estimated using data set built through simulation. It was assumed that the strain gauges were installed in a regular interval under the PSC bridge girders. In order to increase the accuracy in evaluating damage, the squared error between the intact and measured strains are computed and applied for training the data model. Considering the damage occurring near the supports, the results of error analysis were compared according to whether strain data near the supports were included.

• Smart Structures and Systems
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• v.29 no.6
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• pp.785-790
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• 2022

Condition monitoring of permanent magnet synchronous motors (PMSMs) and detecting faults such as eccentricity and demagnetization are essential for ensuring system reliability. Motor current signal analysis is the most commonly used precursor for detecting faults in the PMSM drive system. However, the current signature responds sensitively to the load and temperature of the motor, thereby making it difficult to monitor faults in real- applications. Therefore, in this study, a condition monitoring methodology that detects motor faults, including their classification with standstill conditions, is proposed. The objective is to detect and classify faults of PMSMs by using programmable inverter without additional sensors and systems for detection. Both DC and AC were applied through the d-axis of a three-phase motor, and the change in incremental inductance was investigated to detect and classify faults. Simulation with finite element analysis and experiments were performed on PMSMs in healthy conditions as well as with eccentricity and demagnetization faults. Based on the results obtained from experiments, the proposed method was confirmed to detect and classify types of faults, including their severity.

• Earthquakes and Structures
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• v.23 no.1
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• pp.13-21
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• 2022

Masonry constructions exhibit uncertain behaviors under dynamic effects such as seismic action. Complex issues arise in the idealization of structural systems of buildings having different material types and mechanical properties. In this study, the structural behavior of a vaulted masonry building constructed using full clay brick and lime-based mortar and sitting on consecutive arches was investigated by experimental and numerical approaches. The dimensions of the structure built in the laboratory were 391 × 196 cm, and its height was 234 cm. An incremental repetitive loading was applied to the prototype construction model. Along the gradually increasing loading pattern, the load-displacement curves of the masonry structure were obtained with the assistance of eight linear displacement transducers. In addition, crack formation areas, and relevant causes of its formation were determined. The experimental model was idealized using the finite element method, and numerical analyses were performed for the area considered as linear being under similar loading effect. From the linear analyses, the displacement values and stress distribution of the numerical model were obtained. In addition, the effects of tie members, frequently being used in the supports of curved load-bearing elements, on the structural behavior were examined. Consequently, the experimental and numerical analysis results were comparatively evaluated.

• Structural Engineering and Mechanics
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• v.81 no.4
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• pp.493-502
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• 2022

Shear lag phenomenon has long been considered in numerous structural codes; however, the AISC provisions have now no longer proposed any unique equation to calculate the shear lag ratio in bolted connections for angles in general. It is noticeable that, however, codes used in this case are largely conservative and need to be amended. A parametric study consisting of 27 angle sections with equal legs and different with bolted connections was performed to investigate the effects of shear lag on the ultimate tensile capacity of angle members. The main parameters were: steel grade, connection length and eccentricity from the center of the plate, as well as the number of rows of bolts parallel to the applied force. The test results were compared with the predictions of the classical 1-x/l law proposed by Mons and Chesen to investigate its application to quantify the effect of shear lag. A parametric study was performed using valid FE models that cover a wide range of parameters. Finally, based on the numerical results, design considerations were proposed to quantify the effect of shear lag on the ultimate tensile capacity of the tensile members.