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Applicability of the Ti6Al4V Alloy to the Roller Arm for Aircraft Parts Made Using the DMLS Method
김종건,신도훈,장성화,김태규,Kim Gun-He,정경환,Kim Hyung Giun,박재현 한국항공우주학회 2022 International Journal of Aeronautical and Space Sc Vol.23 No.5
Additive manufacturing (also called 3D printing) technology is so well known that it is inaccurate to call it a new technology anymore, and it is being applied in many industrial fields. In the aviation industry, the influence of process variables and post-treatment processes on additive manufacturing technology has been studied extensively. In this study, the mechanical properties of aircraft parts made of Ti6Al4V powder and their suitability for applications involving aircraft were reviewed. A specimen was prepared and tested; then its microstructure was analyzed and compared with Ti6Al4V plate material. Selected mechanical properties were reviewed. The target product was fabricated using the same process parameters under the same conditions as used for the specimen. The influence analyses of the build orientation and post-processing were performed by dividing the build orientation of the target product into three parts. The shape deformation that occurred after post-processing was reviewed. In addition, the adequacy of the target product to resist the required loads was determined through a functional test of the product.
김종건,Kwanho Park,Sang Yun Ji,Beob Gyun Kim 한국축산학회 2023 한국축산학회지 Vol.65 No.5
The objectives of the present study were to determine the nutrient digestibility of fish meal, defatted black soldier fly larvae (BSFL), and adult flies and to develop equations for estimating in vitro nutrient digestibility of BSFL for pigs. In vitro digestion procedures were employed to mimic the digestion and absorption of nutrients in the pig intestine. Correlation coefficients between chemical composition and in vitro nutrient digestibility of BSFL were calculated. In Exp. 1, in vitro ileal digestibility (IVID) of dry matter (DM) and crude protein (CP) and in vitro total tract digestibility (IVTTD) of DM and organic matter in defatted BSFL meal were less (p < 0.05) than those in fish meal but were greater (p < 0.05) than those in adult flies. In Exp. 2, CP concentrations in BSFL were negatively correlated with ether extract (r = −0.91) concentration but positively correlated with acid detergent fiber (ADF; r = 0.98) and chitin (r = 0.95) concentrations. ADF and chitin concentrations in BSFL were negatively correlated with IVID of DM (r = −0.98 and −0.88) and IVTTD of DM (r = −1.00 and −0.94) and organic matter (r = −0.99 and −0.98). Prediction equations for in vitro nutrient digestibility of BSFL were developed: IVID of CP (%) = −0.95 × ADF (% DM) + 95 (r2 = 0.75 and p = 0.058) and IVTTD of DM (%) = −2.09 × ADF + 113 (r2 = 0.99 and p < 0.001). The present in vitro experiments suggest that defatted BSFL meal was less digestible than fish meal but was more digestible than adult flies, and nutrient digestibility of BSFL can be predicted using ADF as an independent variable.
머신러닝 기법을 활용한 유황별 LOADEST 모형의 적정 회귀식 선정 연구: 낙동강 수계를 중심으로
김종건,박윤식,이서로,신용철,임경재,김기성,Kim, Jonggun,Park, Youn Shik,Lee, Seoro,Shin, Yongchul,Lim, Kyoung Jae,Kim, Ki-sung 한국농공학회 2017 한국농공학회논문집 Vol.59 No.4
This study is to determine the coefficients of regression equations and to select the optimal regression equation in the LOADEST model after classifying the whole study period into 5 flow conditions for 16 watersheds located in the Nakdonggang waterbody. The optimized coefficients of regression equations were derived using the gradient descent method as a learning method in Tensorflow which is the engine of machine-learning method. In South Korea, the variability of streamflow is relatively high, and rainfall is concentrated in summer that can significantly affect the characteristic analysis of pollutant loads. Thus, unlike the previous application of the LOADEST model (adjusting whole study period), the study period was classified into 5 flow conditions to estimate the optimized coefficients and regression equations in the LOADEST model. As shown in the results, the equation #9 which has 7 coefficients related to flow and seasonal characteristics was selected for each flow condition in the study watersheds. When compared the simulated load (SS) to observed load, the simulation showed a similar pattern to the observation for the high flow condition due to the flow parameters related to precipitation directly. On the other hand, although the simulated load showed a similar pattern to observation in several watersheds, most of study watersheds showed large differences for the low flow conditions. This is because the pollutant load during low flow conditions might be significantly affected by baseflow or point-source pollutant load. Thus, based on the results of this study, it can be found that to estimate the continuous pollutant load properly the regression equations need to be determined with proper coefficients based on various flow conditions in watersheds. Furthermore, the machine-learning method can be useful to estimate the coefficients of regression equations in the LOADEST model.