• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2002.10a
• /
• pp.179-182
• /
• 2002

Rapid Prototyping (RP) technologies provide the ability to fabricate initial prototypes from various model materials. Stratasys' Fused Deposition Modeling (FDM) is a typical RP process that can fabricate prototypes out of plastic materials, and the parts made from FDM were often used as load-carrying elements. Because FDM deposits materials in about $300\mutextrm{m}$ thin filament with designated orientation, parts made from FDM show anisotropic material properties. This paper proposes an analytic model to predict the tensile strength of FDM parts. Applying the Classical Lamination Theory, which was developed for laminated composite materials, a computer code was implemented. Tsai-Wu failure criterion was added to the code to predict the failure of the FDM parts. The tensile strengths predicted by the analytic model were compared with experimental data. The data and prediction agreed reasonably well to prove the validity of the model. In addition, a web-based advisory service was developed to provide to strength prediction and design rules for FDM parts.

• Current Photovoltaic Research
• /
• v.2 no.3
• /
• pp.140-145
• /
• 2014

The globally used PV qualification tests and reports the pass/fail only. Therefore, the reliability of new PV materials and parts can't be compared quantitatively with the reliability of the PV parts and materials in the market. Global PV materials and parts companies test and compare their materials, parts, and modules using the failure-to-test (FTT). However, it takes a long accelerated stress test (AST) until failure. It also needs to test the new and existing materials and parts. Therefore, it requires excessive equipment time and cost. In order to reduce the time and cost, a new reliability enhancement methodology has been developed. It tests the PV materials, parts, and modules in the global market and stores them in the PV reliability database. It reduces the time and cost of the comparison and enhancement of PV reliability. An example of the reliability enhancement of the PV encapsulant, EVA is presented.

• Journal of Powder Materials
• /
• v.30 no.3
• /
• pp.217-222
• /
• 2023

Machine learning-based data analysis approaches have been employed to overcome the limitations in accurately analyzing data and to predict the results of the design of Nb-based superalloys. In this study, a database containing the composition of the alloying elements and their room-temperature tensile strengths was prepared based on a previous study. After computing the correlation between the tensile strength at room temperature and the composition, a material science analysis was conducted on the elements with high correlation coefficients. These alloying elements were found to have a significant effect on the variation in the tensile strength of Nb-based alloys at room temperature. Through this process, a model was derived to predict the properties using four machine learning algorithms. The Bayesian ridge regression algorithm proved to be the optimal model when Y, Sc, W, Cr, Mo, Sn, and Ti were used as input features. This study demonstrates the successful application of machine learning techniques to effectively analyze data and predict outcomes, thereby providing valuable insights into the design of Nb-based superalloys.

• Composites Research
• /
• v.36 no.5
• /
• pp.329-334
• /
• 2023

The classical multiscale finite element (FE² ) method involves iterative calculations of micro-boundary value problems for representative volume elements at every integration point in macro scale, making it a computationally time and data storage space. To overcome this, we developed the data-driven multiscale analysis method based on the mean-field homogenization (MFH). Data-driven computational mechanics (DDCM) analysis is a model-free approach that directly utilizes strain-stress datasets. For performing multiscale analysis, we efficiently construct a strain-stress database for the microstructure of composite materials using mean-field homogenization and conduct data-driven computational mechanics simulations based on this database. In this paper, we apply the developed multiscale analysis framework to an example, confirming the results of data-driven computational mechanics simulations considering the microstructure of a hyperelastic composite material. Therefore, the application of data-driven computational mechanics approach in multiscale analysis can be applied to various materials and structures, opening up new possibilities for multiscale analysis research and applications.

• Korean Journal of Occupational Health Nursing
• /
• v.15 no.2
• /
• pp.94-103
• /
• 2006

Purpose: This study was to understand foreign workers' experiences exposed hazard chemical materials in korean industry. Method: The research subjects were 92 foreign workers worked in seoul, namyangju, ansan, suwon, pocheon, incheon, jincheon, and daejeon. It was that grounded theory method as qualitative approach was applied with in-depth interview, recording and dictation, and collected data was analysed line-by-line by research teams. The analysis process of in depth interview data was three phase. Results: The first phase was that find out meaningful data and confronted data for meaningful data was 53 meaningful items. The second phase was coding process of meaningful data, total coding items were 9, difficulty of new environment, existence of health hazard factors originated in work, performance of basic health management, management of hazard materials in work-site, self care of hazard materials in work-site, discrimination of disaster-compensation originated in work, perception of work stress, motivation of leaving position, satisfaction for present life. The third phase was 5 adaptation process, copying phase for new environment, management phase for health hazard factors, health change phase, life change phase, illegal stay phase. Conclusion: In summary, as a results it was concluded that foreign workers was experienced new environment and then has various problems in working site. But these evidences were not different from korean workers basically, undoubtedly reality of a korean small and medium enterprise. And foreign workers with long time stay have had many health problems probably, but they have want to long stay and so reach an unexpected result, illegal long stay. Therefore, we should make efforts for adequate foreign workers' health management at work-site and overall life in governmental and industrial nursing level.

• Journal of Powder Materials
• /
• v.26 no.5
• /
• pp.369-374
• /
• 2019

The properties of powder metallurgy products are related to their densities. In the present work, we demonstrate a method to apply artificial neural networks (ANNs) trained on experimental data to predict the bulk density of barium titanates. The density is modeled as a function of pressure, press rate, heating rate, sintering temperature, and soaking time using the ANN method. The model predictions with the training and testing data result in a high coefficient of correlation (R2 = 0.95 and Pearson's r = 0.97) and low average error. Moreover, a graphical user interface for the model is developed on the basis of the transformed weights of the optimally trained model. It facilitates the prediction of an infinite combination of process parameters with reasonable accuracy. Sensitivity analysis performed on the ANN model aids the identification of the impact of process parameters on the density of barium titanates.

• Education of Primary School Mathematics
• /
• v.3 no.2
• /
• pp.109-113
• /
• 1999

To improve the elementary student's ability to classify the data and obtain the information from the data through graphics, it is necessary to use the teaching and learning material which encourage the student to study with interest and is adjacent to the student's environment. In this thesis. several materials to satisfy the condition is proposed together with some remarks to direct the teaching. These materials is recommended to use for the maturity learning and teaching in grade 6.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2005.04a
• /
• pp.158-161
• /
• 2005

The fiber-reinforced composite materials have been advanced for various applications because of its excellent mechanical and electromagnetic properties. On their manufacturing processes, however, thermo-curing inherently produces the undesired thermal deformation mainly from temperature drop from the process temperature to the room temperature, so called spring-back. The spring-back must be removed to keep the precision of designed shape. In this research, the spring-back of {glass fiber / epoxy}+{carbon fiber / epoxy} unsymmetric hybrid composites were predicted using Classical Lamination Theory (CLT), and compared with the experimental data. Additionally, using finite element analysis (ANSYS), the predicted data and experimental data were compared. The predicted values by CLT and ANSYS were well matched with experimental data.

• Journal of the Korean Society for information Management
• /
• v.14 no.1
• /
• pp.207-222
• /
• 1997

This study is aimed at design and implementation of data format for non-book materials in the field of library user interface. The ba-sic data elements were complied with KORMARC and some amend-ments with detailed expansions were applied for development of the use of at libraries. The data formats of various types of media such as books, audio materials, image data, pamphlets, posters which stored in art library were designed respectively through the use of Graphical User Interface.

• Proceedings of the KSME Conference
• /
• 2003.04a
• /
• pp.195-200
• /
• 2003

An expert system for estimation of fatigue properties from simple tensile data of material is developed, considering nearly all important estimation methods proposed so far, i.e., 7 estimation methods. The expert system is developed using an expert system shell, UNIK, and the knowledge base is constructed with production rules and frames. Forward chaining is employed as a reasoning method. The expert system has three major functions including the function to update the knowledge base. The performance of the expert system is tested using the 54 ${\sigma}-N$ curves consisting of 381 ${\sigma}-N$ data points obtained for 22 materials. It is found that the expert system developed has excellent performance especially for steel materials, and reasonably good for titanium alloys.