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최승겸,강영종(Young Jong Kang),임남형(Nam Hyoung Lim) 한국강구조학회 1997 韓國鋼構造學會誌 Vol.9 No.3
In the design of plate gider web and flange panels, it is required to evaluate accurately the elastic buckling strength under bending stress, whether or not the post-buckling strength is accounted for. Currently, elastic bending buckling stress of web and flange panels are determined by assuming conservatively that web and flange panels are simply supported at the juncture between the flange and web. However, when the I girder is applied bending stress flange and web panels buckled at the same time. In the present study, a series of numerical analyses based on a three-dimensional finite element modeling is carried out to investigate the effects of the flange-web interactive buckling
한순영,최해진,최승겸,오재성 한국정밀공학회 2019 International Journal of Precision Engineering and Vol.20 No.2
Fault diagnosis plays a key role in monitoring manufactured products for the purpose of quality control. Among the several fault diagnosis approaches, knowledge-based fault diagnosis, which uses signals from sensors and machine learning algorithms instead of a priori information, is widely employed to diagnose the status of products. In this paper, we propose a knowledge-based procedure to establish a fault diagnosis model. The model is aimed to diagnose planetary gear carrier packs, which have many fault types and an unbalanced number of samples in the sample classes, using transmission error. In the procedure, the best feature subset that contains the most important features is selected using two different feature selection processes. Several ensemble algorithms are used during the model training process. The imbalance ratio between classes of samples is addressed. The number of weak learners is automatically determined by a genetic algorithm. Finally, the performance of the proposed procedure is validated by comparison with other models trained without applying the proposed procedure. We observed that it is important to incorporate the class imbalance technique in the training process as it reduces the misclassification of faulty products as normal ones. This reduction is important in production quality control.
Soonyoung Han,도민득,Mingeon Kim,조승연,최승겸,Hae-Jin Choi 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.12
Workpiece localization is an essential process in modern engineering that relies on three-dimensional scanning to measure shape and position. We propose a three-dimensional scanning method using stereo vision with our designed markers and a novel stitching process. Our designed marker includes a set of nine designed points in a marker which increases the measurement accuracy. In addition, sets of marker points in multiple image shots are stitched together to accurately position the markers in our stitching process. Repeatability values measured in-plane are 7.03 and 8.14 micrometers in x and y-direction, respectively. Repeatability in zdirection (out-of-plane) is 19.71 micrometers. We also validated the performance of our method by recording displacement measurement error. The average error while measuring the displacement of 1 mm was 5.90 micrometers and its standard deviation 3.08 micrometers with repeated tests.
Recep M. Gorguluarslan,Ramana V. Grandhi,최해진,최승겸 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.3
In the design of lattice structures fabricated by additive manufacturing, a multiscale modeling process is usually required to effectively account for fine scale uncertainties. The validation of the multiscale model predictions, on the other hand, is a challenging task. In this research, two prediction assessment approaches, namely the area validation metric and the Kolmogorov-Smirnov test, are presented in a systematic validation pyramid approach with u-pooling method to address this issue. The use of these two approaches are evaluated in terms of being an unbiased decision criterion for the prediction assessment and validation of the multiscale models. The fine scale material and geometry uncertainties are propagated onto homogenized properties using a stochastic upscaling method at each scale of interest. The homogenized model predictions are validated using the experimental data obtained for the lattice structure example fabricated by material extrusion process. The results indicate that the presented approach is capable of effectively validate the predictions of the multiscale models under uncertainty.
이윤하,한순영,장성우,김원재,최해진,최승겸 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.7
The recent development of the coal-fired power plant purposes to enhance environmental-friendliness and efficiency. In order to achieve these goals, many research studies are underway to develop advanced ultra-supercritical (A-USC) boilers, which requires materials that can withstand extreme conditions. Integrated materials and product design (IMPD) is a new approach for designing products able to yield effective operation in extreme conditions. Based on the IMPD approach, we optimized the geometry of the superheater tube of the A-USC boiler as well as its constituent materials. To apply the IMPD to the tube design problem, we developed a creep deformation model based on finite element analysis, a heat transfer model, and two material models constructed via artificial neural networks. The material models predict creep properties and thermal conductivity for a given heat treatment condition and weight ratio of the chemical constituents. These four models are used in combination to form an analysis model chain, which is subsequently incorporated into an optimization routine for finding optimum material constituents and shapes of the superheater tube at the same time. An optimal tube design was developed to achieve minimum creep deformation and maximum heat transfer amount under the stringent operating conditions of the A-USC boiler.