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For example, when designing an aircraft wing, a large amount of uncertainty is typically present on the crisp parameters of the constitutive models of the composite materials, but also concerning the exact loading that this wing has to withstand during its entire service life time.
Mullen, Interval-Based Approach for Uncertainty Propagation in Inverse Problems, Journal of Engineering Mechanics 4 (1) (2014) 1-7.[7] S.
Proceedings of the European Congress on Computational Methods in Applied Sciences and Engineering: Vol. 7.
European Congress on Computational Methods in Applied Sciences and Engineering.
International Journal for Numerical Methods in Engineering, 110(2017) 1272-1300

Research on Energy-Saving Control Technology of Boiler Yao Yi1, a, Guangjian Chen 2, b and Jinling Jia 2, c 1School of Automation and Electronic Information Sichuan University of Science & Engineering Zigong, China 2School of Computer Science Sichuan University of Science & Engineering Zigong , China ayaoyi6166@suse.edu.cn, b8326127@qq.com, cjiajinling@suse.edu.cn Keywords: boiler; energy-saving control; smoke detection; neural network model Abstract.
These four methods regard the smoke as a whole and make the measurement, however, O2, CO, CO2 gas in flue gas and Fe, Al, Ca, Mg, S and other materials in fly ash will cause the changes in dielectric constant of fly ash.
The concentration relationship between CO and CO2 Fig. 3.Controlling model of combustion neural network Here, if all feeders are regarded as feeding equivalent materials we can see the amount of coal delivery as a parameter.
A Microwave System within the Boiler Flue forMeasuring Unburnt Carbon in Fly Ash,journal Of Eastchina Normal University(Natural Science), 1999,8:4~6 [10] Yao Yi, Yao Yachuan.

Remanufacturing cost is only 50% of new products, and it can save 60% of energy, 70% of material [1].
Acknowledgment This work was finally supported by National Social Science Fund of China (Grant No. 13CGL127), Sichuan Science and technology project (Grant No. 2013ZR0041), Chengdu Science and technology project (Grant No. 12RKYB087ZF-002), china society of logistics research project (Grant No. 2013CSLKT107).
[10] S.Chen, Dismantling and Reuse of Discarded Automobiles, Automobile technology & materials, 7 (2007)06-09
[11] Frank Schultmann, Moritz Zumkeller,Otto Rentz, Modeling reverse logistic tasks within closed-loop supply chains- An example from the automotive industry, European Journal of Operational Research 171(2006) 1033-1050 
Management Science, 28(2000)653-666

ZnO is a wide semiconductor material that has an energy bandgap of 3.3 eV and a large exciton binding energy of 60 meV.
Science Officer) and Mr.
Shi: Journal of Crystal Growth Vol. 300 (2007) p. 353 [6] S.
Qing: Science China Physics, Mechanics & Astronomy Vol. 54(1) (2011), p. 102 [7] X.C.
Que: Solar Energy Materials & Solar Cells Vol. 94 (2010), p. 2181

The solid waste and weak acid water mixed in a certain solid-to-liquid ratio (1:10) and the leachate was obtained by filtering the undissolved materials.
Zheng: Environment Science.Vol. 22 (2001)No.3, p.126-128
Liu: Journal of Liaoning Technical University.
Xu:Environmental Science and Management.Vol. 20 (2007) No.2, p.39-44
Duan,et al: Research of Environmental Sciences.

The Design and Analysis on Communication Physical layer of high-speed inter-missile networking Qi Yong1, a, Li Qianmu1,b , Wei Xianghe1,c and Yin Jie2,d 1School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China 2School of Computer Science & Technology, Jiangsu Police Institute, China Anjqiyong2003@yahoo.com.cn, bliqianmu@126.com, chouxiaozhu@126.com, ayinjie@jspi.cn Keywords: high-speed inter-missile networking, Physical layer, Communication solution Abstract.
Acknowledgements This work was financially supported by the National Natural Science Foundation of China (60903027, 90718021), Jiangsu Public Security Department Scientific Project and NUST Research Funding (2010XQTR04).
Key Engineering Materials , 2010, Vols. 440 [2] Li Qianmu, Wang Rui, Yin Jie and Hou Jun.
Key Engineering Materials, 2010, Vols. 439 [3] Xu Jia, Li Qian-mu, ZHANG Hong, LIU Feng-yu.
Computers & Electrical Engineering, 2010 , Vol.36, Issue 3 [4] Li QM, Zhang H, Liu FY, A Data-link User’s Safeguard Strategy Based on Reliability Theory , Journal of Computational Information Systems，2006，2(3)

State Key Laboratory of Advanced Metallurgy, University of Science and Technology, Beijing 100083, China; axdong_ustb@yeah.net; bcangdaqiang@metall.ustb.edu.cn, clinglingzhangll@hotmail.com, dlixue40522024@163.com, eduanjianfeng_1987@126.com Keywords: converter; nozzle angle; mixing gas blowing; BOF dust Abstract: The hot experiment was carried out to study the effect of lance nozzle and mixing gas blowing on steelmaking.
Acknowledgement This work is sponsored by the National Natural Science Foundation of China (51034008) and Major Project of the National 12th Five-Year Plan of China (2011BAC06B10).
Metallurgical and Materials Transactions B-Process Metallurgy and Materials Processing Science, Vol. 27(1996): p.35-41
Journal of University of Science and Technology Beijing. 2007, Vol. 29(2007): p 77-80.

Methods and Materials Theory of SVR Suppose a sample is represented by (x, y), where x is the independent variables, y the dependent one.
Ren, “Back propagation neural network (BPNN) prediction model and control strategies of methanogen phase reactor treating traditional Chinese medicine wastewater (TCMW),” Journal of Biotechnology, vol. 144, no. 1, pp. 70-74, 2009
Zhu and T.T Xiao, “Corrosion rate prediction of 3C steel under different seawater environment by using support vector regression,” Corrosion Science vol. 51, pp. 349-355, 2009
Kennedy, “A new Optimizer using Particle swarm optimization,” Proceedings of The 6th International Symposium on Micro Machine and Human Science, pp. 39-43, 1995
Shang, “Prediction of tungsten tensile strength with artificial BP neural network method," Materials Science and Technology, vol. 14, pp. 63-65, 2006.

Experimental Materials.
Acknowledgments We would like to thank for the financial support from Foundation for Innovative Research Groups of the Natural Science Foundation of China (51221003), National Natural Science Foundation of China (51474231 and U1262201) and Foundation from Major Programs of China during 13th Five-Year Plan Period (2016ZX05022-001-001-001, 2016ZX05040-001-002 and 2016ZX05020-004) for this work.
Applied Clay Science 2016;121–122:1-8
Journal of Petroleum Science and Engineering 2015;135:505-514
ACS Applied Materials & Interfaces 2015;7:5006-5016

Local residual stress distribution at the tooth root surface of a broached steel component Tobias Strauß1,a, Harald Meier2,b , Jens Gibmeier1,c , Volker Schulze2,d , Alexander Wanner 1,e 1Karlsruhe Institute of Technology (KIT), IAM-WK Institute for Applied Materials, Kaiserstraße 12, 76131 Karlsruhe, Germany 2Karlsruhe Institute of Technology (KIT), wbk Institute of Production Science, Kaiserstraße 12, 76131 Karlsruhe, Germany aTobias.Strauss@kit.edu, bMeier@wbk.uka.de, cJens.Gibmeier@kit.edu, dSchulze@wbk.uka.de, eAlexander.Wanner@kit.edu Keywords: process chain, broaching, residual stress, surface integrity, X-ray diffraction, surface layer characterization Abstract.
When machining material, residual stresses and work hardening are generated in the component’s surface layer due to material shearing, friction and temperature development [1-3].
The plate material was case hardening steel SAE 5120.
To consider potentials in reducing machining times and to take development of new tool materials into account a further cutting speed has been set to 50 m/min.
International Journal of Machine Tools and Manufacture 51 (2011), p. 331-338