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., M.S.Tang, A.Al-Tabbaa, MgO expansive cement and concrete in China: Past, present and future, Cem.
Bull. 28 (10) (2019) 7655-7660 [7] M.Liska, L.J.Vandeperre, A.Al-Tabbaa, Influence of carbonation on the properties of reactive magnesia cement-based pressed masonry units, ICE J.
Sci. 30 (2007) 239-246 [12] A.M.Kandeel, M.S.El-Mahllawy, H.A.Hassan, W.H.Sufe, S.R.Zeedan, Effect of type of mixing water and sand on the physico-mechanical properties of magnesia cement masonry units, HBRC Journal 8 (2012) 8-13 [13] U.
Nasonova et al., Magnesium binder with the micro-silica additive, Proc.

. %) was: 0.09 С; 0.32 Si; 0.63 Mn; 0.79 Cr; 0.2 Ni; 0.16 Cu; 0.08 Mo; 0.032 Al; 0.026 Ti; 0.03 Nb; 0.06 V.
Mechanical properties of the steel with different structure Structure YS, MPa UTS, MPa EL, % YS/ UTS Initial 367 558 33 0.66 UFG 646 842 17 0.77 In the Fig. 2 the stress-strain diagrams of specimens with UFG (curve 1) and initial (2) structure and also the change in the acoustic emission activity during the tests of ECAPed steel (3) are shown.
Kopylov et al.: Processes of Plastic Structure Formation in Metals (Nauka i Tekhnika, Minsk, Belorus 1994) (in Russian)
[8] Byoungchul Hwang, Han Sang Lee, et.al. // Metallurgical and materials transactions. 2005, V. 36A. p. 389-397 [9] Ho-Kyung Kim, Myung-Il Choi, Chin-Sung Chung, Dong Hyuk Shin.

Abrao et al.[4]revealed that feed rate is the dominant factor which effects on surface roughness in turning hardened 100Cr6 bearing steel with ceramic and CBN cutting tools, and the influence of cutting speed is relatively less.
After made a prediction of flank wear based on artificial neural network and multiple linear regression modeling when cutting hardened AISI H-13 steel with chamfered and honed CBN tools, Özel T et al. found that artificial neural network modeling is a better way to predict workpiece surface roughness and flank wear considering multiple factors.
In hard turning of case-hardened 27MnCr5 steel, Rech J et al. [5] pointed out that the surface roughness is influenced principally by feed rate under the suitable cutting conditions; and cutting speed is the dominant factor effected on surface residual stresses. 2.
(In Chinese) [2] El-Wardany T I, Kishawy H A, Elbestawi M A.

Al-Hartomy, A.A.
Al-Ghamdi, F.
Al-Salamy, N.
El-Tantawy: J.

The bands at the wavenumbers 470 and 1000 cm-1 corresponded to the Si–O–Si vibrations, whereas the band at the wavenumber 530 cm-1 corresponded to Si–O–Al bending vibrations [8,9].
The band at 918 cm-1 is from the Al–O–Al vibrations [10,11].
Zouhri Abderrazak, El Albani,  N.

Barlat et al. [2] introduced Yld2000-2d, which considers stresses and r-values based on uniaxial tension test results in three directions, equi-biaxial stress and its strain increment ratio.
Vegter et al. [3] proposed a plane stress yield function based on interpolation by second order Bézier curves.
Tsutamori el al. [4, 5] have proposed a plane stress yield function using third order Bézier curves, which connects uniaxial stress states and equi-biaxial stress states.

J.Paulo Davim et al conducted an experimental study of drilling GFRP manufactured by hand layup and investigated the influence of cutting parameters on the damage around holes[1].It was found that the damage increased with increase in cutting speed and feed rate.
Tom sunny et al conducted drilling experiments with twist drill, end mill and Kevlar drill and found that increasing spindle speed and decreasing feed rate can reduce delamination[2].K.Palanikumar optimized the parameters in drilling of GRFP using Taguchi method with grey relational analysis[3].Several authors used different techniques to optimize process parameters in drilling of GFRP composites[4-6].
Langella et al developed a thrust and torque prediction model for drilling of composite materials [9].
[5] Jinyang Xu, Ali Mkaddem, Mohamed El Mansori, “Recent advances in drilling hybridFRP/ Ticomposite: A state-of-the-art review”, Composite Structures 135 (2016) 316–338

[5] Al-Hamouz, Z.
M. and Al-Faraj, A.
[11] Al-Saba, T. and El-Amin, I. (2002).

FE Exp Theory Al St Al St Al St Pmean (KN, N=5) 27.95 70.48 - 67.92 18.30 59.19 Pmax (KN, N=5) 32.6 93.14 - 92.8 - - Et (KJ, N=5) 1.55 4.97 - 4.84 1.53 4.97 Pmean (KN, N=7) 50 59.86 - 58.38 15.27 49.42 Pmax (KN, N=7) 28.41 80.35 - 78 - - Et (KJ, N=7) 1.25 4.78 - 4.75 1.24 4.01 Optimization Problem definition.Single objective optimization of energy absorbers is not suitable for most real life situations hence here a multi objective optimization is considered.
El-Hage, P.K.

The problem was solved by Carpinteri et al. using three actuators in 1994, [4] and by Akita et al. in 2000, when a specially designed adjusting gear system was developed to eliminate the flexure, [5].
It makes significant progress form the previous attempts which was made on evaluating tension softening curves for one mixture by mathematical formulas proposed by Reinhardt, [9], Lee [10] and lastly by Akita at el. [11].
[3] J.G.M. van Mier et al.: Tensile cracking in concrete and sandstone.