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띠뚜말라이쿠마란,고태조,쿠르니아완렌디,Changping Li,M. Uthayakumar 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.8
This study discusses the development of an Adaptive neuro–fuzzy inference system (ANFIS) model for determining the surface roughness (Ra) during machining of multidirectional woven fabric Carbon fiber reinforced plastics (CFRP) using Abrasive waterjet machining (AWM). Three variable input parameters—Jet pressure (JP), Traverse speed (TS), and Standoff distance (SOD)—were selected to assess the roughness of the CFRP along the traverse direction of the cut surface. The experimental results show that a lower JP deteriorated the finish by creating surface rupture. On the other hand, a poor surface finish was observed in the case of machining at higher TS and SOD. Further, the developed ANFIS model was used to validate the results and it was found that the predicted values were in good agreement with a 95 % confidence level. It was also evident that the ANFIS technique is helpful for better prediction of the experimental data with minimum error. Finally, the cut surface morphology was analyzed using a 3D non-contact surface profilometer and the results are discussed.
Kumaran, S. Thirumalai,Ko, Tae Jo,Uthayakumar, M.,Islam, Md. Mofizul Elsevier 2017 Journal of Alloys and Compounds Vol.724 No.-
<P><B>Abstract</B></P> <P>In the present work, two different carbon fiber-reinforced plastics (CFRP), namely, unidirectional (UD) and UD with a woven fabric surface, were selected in order to investigate the surface roughness as a result of machining with an abrasive water jet machine (AWJM). The experiments were conducted based on an L27 orthogonal array by varying the process parameters such as jet pressure (JP), traverse speed (TS), and standoff distance (SOD). Regression models were developed to predict the correlation between the input parameters and the surface roughness for each composite. The experimental results showed that increased pressure with lower TS and SOD produced a good surface finish on the composites. Very low roughness was achieved when machining the UD with woven fabric surface CFRP composite. The developed regression models indicated the significance of the design (at a 95% confidence level) with reduced error. The JP followed by the SOD were found to be the major parameters affecting the surface roughness. Finally, the deformation, delamination, and machined surface morphology were studied using a non-contact three-dimensional surface measurement system and scanning electron microscopy (SEM) images.</P>
R.V. Mangalaraja,S. Ananthakumar,Kasimayan Uma,Romel M. Jiménez,S.Uthayakumar,Marta López,Carlos P. Camurri 한양대학교 세라믹연구소 2012 Journal of Ceramic Processing Research Vol.13 No.1
An in-situ sulphated-combustion synthesis is reported to obtain gadolinium [Ce0.9Gd0.1O1.95] and samarium [Ce0.9Sm0.1O1.95]doped ceria electrolytes for solid oxide fuel cells (SOFCs). Nitrate precursors of cerium, gadolinium and samarium reactants were mixed homogenously with a citric acid fuel with an in-situ addition of 10 and 20 mol% ammonium sulphate [(NH4)2SO4]. The mixture was combusted at 500 oC and subsequently calcined at 700 oC. The influence of the sulphate addition on the morphology of ceria particles has been analyzed. It is seen that the in-situ SO42- ions highly favors the nucleation and growth of doped ceria electrolytes on a nanometer scale with an added advantage of improved crystallinity. TEM analysis indicates loosely agglomerated and nearly spherically shaped ceria nano particles with a maximum particle size of 20 nm.
Rotary ultrasonic machining of woven CFRP composite in a cryogenic environment
Thirumalai Kumaran, S.,Ko, Tae Jo,Li, Changping,Yu, Zhen,Uthayakumar, M. ELSEVIER SCIENCE 2017 JOURNAL OF ALLOYS AND COMPOUNDS Vol.698 No.-
<P><B>Abstract</B></P> <P>In the present study, rotary ultrasonic machining (RUM) was adopted to perform drilling of carbon fiber reinforced plastics (CFRP) in a cryogenic environment. An L27 orthogonal array was selected to conduct experiments by varying the spindle speed (denoted as N), feed rate (denoted as f), and ultrasonic power (denoted as P). The thrust force (denoted as Fz), exit burr area, and surface roughness (denoted as Ra) were measured to evaluate the machining performance. The influence of process parameters and the regression model were derived for each output quality response. Additionally, multi-objective optimization was performed using desirability analysis, and the predicted levels were used for confirmation. The results indicated that the feed rate (f) contributed more to the thrust force (Fz) by 45.85% and a maximum thrust force was recorded at 0.1 mm/rev. A decrease in spindle speed (N) was associated with an increase in feed rate (f) and ultrasonic power (P), and it resulted in minimum exit burr area. The influence of ultrasonic power (P) was highly significant in reducing burrs with a contribution of 52.45%. Conversely, the surface roughness (Ra) of the drill holes decreased at 3000 rpm, and this was attributed to the brittle fracture of the fibers at a lower temperature. Both N (30.88%) and f (30.83%) had an equal influence on producing a better surface finish in the drill holes. Furthermore, the predicted optimal settings were used to validate the results and were found to be within 95% confidence and prediction interval. Finally, the microscopic images of tool wear, burr formation, and drill hole surface morphology were analyzed and examined.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Prediction of regression model for RUM of CFRP in a cryogenic environment. </LI> <LI> Output responses such as thrust force, burr area and roughness are investigated. </LI> <LI> The adequacy of an ANOVA model is checked for each output response. </LI> <LI> Optimization is performed by desirability analysis and the results are validated. </LI> <LI> Tool wear, burr formation, and drill hole surface morphology are analyzed. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>