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Oxidation Resistance of Co-10Cr-5Si-0.3Y Alloys at 800 °C Peng Li1, Junhuai Xiang2,a, Honghua Zhang2, Yang Zhang1 and Jianrong Zhu1 1School of Materials Science and Engineering, Jiangxi Science and Technology Normal University, Nanchang 330013, China 2Jiangxi Key Laboratory of Surface Engineering, Jiangxi Science and Technology Normal University, Nanchang 330013, China axiangjunhuai@163.com Keywords: Reactive-element effect; Co-10Cr-5Si; Oxidation resistance; High temperature Abstract.
In addition, Co-based amorphous or nano-crystalline alloys such as CoSi [2,3] have been studied as better materials for hydrogen storage.
Ishida: Science Vol. 312 (2006), p. 90 [2] G.
Wang: International Journal of Hydrogen Energy Vol. 35 (2010), p. 1669 [4] K.
Ye: Journal of the Chinese Rare Earth Society Vol. 23 (2005), p. 75 [8] J.

Introduction Composite materials have many interesting properties such as light weight, high strength, high stiffness and fatigue performance, compared to metals, which make them very attractive for engineering fields.
Introduction to composite materials [M].Taylor & Francies Inc. , Phildelphia,1999
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Journal of Sound and Vibration, 2006, 291:802–823
Chinese Journal of Mechanical Engineering, 2012, 25(5):1030-1044.

Maximum failure loads of CT specimens obtained by test and analysis are presented. 1.0 Introduction R curve analysis is a procedure generally used in elastic-plastic behavior of materials to characterize the resistance to fracture of materials during incremental slow stable crack extension.
S.Sundaresan,C.Pany, M.K.Sundaresan and B.Nageswara Rao, “Mathematical model for failure load evaluation of maraging steel compact tension specimens”, International Journal of Mathematical Sciences and Engineering Applications (IJMSEA), Vol.6.pp.281-297 (2012)
Nageswara Rao, “On the fracture toughness evaluation in weldments of a maraging steel rocket motor case”, Materials and Design, Vol.31, pp.4921-4926 (2010)
ASTM E399 -06, “Standard Test method for Linear Elastic Plane Strain Fracture Toughness KIC of Metallic Materials”, Annual Book of ASTM Standards, Vol.03.01 (2008)
Kapp, “Improved Wide Range Expressions for Displacements and Inverse Displacements for Standard Fracture Mechanics Specimens”, Journal of Testing and Evaluation, Vol.19, pp.45-54 (1991)

A large number of non-dispersible underwater concrete materials will be extensively used in works which span over rivers and sea, so it is important to study the performance of non-dispersible under water concrete structures.
Acknowledgement This work has been funded by Project 50708011 supported by National Natural Science Foundation of China.
References [1] S.J JI, B.Q Ma, “Matching and Construction of Non-dispersible Underwater Concrete”, Journal of water carriage engineering, Vol. 6, No.1, 2006, pp. 78-79
[2] Y.L SONG, “Experiment Research of Non-dispersible Underwater Concrete”, Journal of road traffic technology, Vol. 12, No. 3, 1995, p. 25-31
[3] Y.LIU, “Application of Non-dispersible Underwater Concrete to Restoration of Dalian Harbor Dock”, Journal of water carriage engineering, Vol. 3, No.1, 2003, pp. 29-43

Materials and Method Material.
Journal of Applied Sciences, 8: 1541-1547
Journal of Materials Processing Technology 205(1-3): 353-359
Friction and Wear of Materials.
World Applied Sciences Journal 9(2): 118-126, 2010 [11] M.

A Study on the Prediction and Comparison of processing using the Artificial Neural Network in Nitinol Electrochemical Machining WooJae Song1,a, EunSang Lee2,b 1Graduate School of Metal Materials and Machining Process Engineering, Inha University, Incheon 22212, Republic of Korea 2Department of Mechanical Engineering, Inha University, Incheon 22212, Republic of Korea atorsten@inha.edu, bleees@inha.ac.kr Keywords: Nitinol(SMA), Electrochemical Machining, Artificial Neural Network, Machining Prediction Abstract.
In addition, there is a limit to the application of the Design of Experiments(DOE- RSM,Taguchi), which requires the highest precision of machining, to the machining processing of the advanced composite materials that are difficult to machining. [6] Therefore, this study applied Artificial Neural networks to electrochemical machining(ECM), which provide more accurate data than traditional Design of Experiments(DOE).
Therefore applying DNN to advanced materials, such as machineability shape memory alloys(SMA), provides more accurate predictions and results compared to traditional design of experimental(DOE) methods.
Acknowledgments This research was supported by Korea Institute of Science and Technology Job Promotion.
Ugrasen, 2017, “ Estimation of Machining Performances in WEDM of Aluminium based Metal Matrix Composite Material using ANN, “Materials Today: Proceedings, Volume 4, Issue 9, pp. 10035-10038,,

Experimental Materials preparation.
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Wessel (edt), Handbook of advanced materials, John Wiley & Sons, Inc., Hoboken, New Jersey 2004
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Derby, Ceramic nanocomposites: mechanical properties, Current Opinion in Solid State and Materials Science, 3/5 (1998) 490-495

Defect Formation Mechanism and Influence of Processing Parameters on Surface Quality of Copper Clad Steel Composite Wires Prepared by Core-Cladding Continuous Casting Weiyu Wu1, a, Xuefeng Liu1,2, b, Feng Yi1, c 1School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083, China 2Beijing Laboratory of Metallic Materials and Processing for Modern Transportation, University of Science and Technology Beijing, Beijing 100083, China awuweiyutoday@163.com, bliuxuefengbj@163.com, cyifeng0810@126.com Keywords: Core-cladding continuous casting method, Copper clad steel wire, Processing parameters, Surface quality, Defect formation mechanism.
Many processing methods are used for the preparation of bimetal composite materials.
Parkins, Localized corrosion and crack initiation, J.Materials Science and Engineering A.103(1988) 143-156
Kim, Evaluation of copper coating ratio in steel/copper clad wire drawing, J.Journal of Materials Processing Technology. 186(2007) 22-26
Thompson, Microstructural evolution of copper clad steel bimetallic wire, J.Materials Science and Engineering A., 528(2011) 2974-2981

Experimental Materials.
Laksmono et al.: IOP Conference Series: Materials Science and Engineering Vol. 201 (2017) 012006 [11] D.
Adeyi et al.: Materials Vol. 12 (2019), pp. 1734-1750 [24] J.
Gao et al.: Journal of Zhejiang University Science B Vol. 14 (2013), pp. 650-658 [25] F.
Yassaa: IOP Conference Series: Materials Science and Engineering Vol. 323 (2018) [26] H.

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Briggs: Formation of highly adherent nano-porous alumina on Ti-based substrates: A novel bone implant coating Journal of Materials Science: Materials in Medicine 15 (9) (2004) p.1021-1029
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