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Online since: October 2022
Authors: Xing Ran, Zhi Gang Lv, Pei Jie Li, Zhe Wang, Cheng Cheng Liu
It was found that the fracture toughness of TC18 titanium alloy decreased from 77.8 MPa·m1/2 to 65.4 MPa·m1/2 as the deformation temperature raised from 881℃ to 896℃.
The deformed temperature of forgings in present study was 881℃ and 896℃.
Fig. 3 is the optical morphology, showing the microstructure of TC18 titanium alloy deformed at 881℃ and 896℃.
Conclusions The fracture toughness tests of TC18 titanium alloy forgings deformed at 881℃ and 896℃ have been carried out. 1.
The fracture toughness of TC18 titanium alloy decreased from 77.8 MPa·m1/2 to 65.4 MPa·m1/2 when the deformation temperature increased from 881℃ to 896℃. 3.
Online since: December 2016
Authors: Ivo Kusák, Miroslav Lunak, Pavel Rovnaník, Maria Mikova
In a frequency range of 40 Hz to 1 MHz values of electrical resistance and permittivity values of the beams with different content of graphite powder, labeled Cond 896 were determined.
As filler both test norm-sand PG1-3, graphite powder COND 896, non-ionic detergent Triton X-100 and defoamer Lukosan S were used.
Online since: January 2016
Authors: Jakrapong Kaewkhao, Natthakridta Chanthima
On excitation, with 584 and 805 nm, it is found that the emission peaks are located at 896 (904), 1060 and 1332 nm that correspond to the emission transitions from 4F3/2 to 4I9/2, 4I11/2 and 4I13/2, respectively.
The results show that, the emission spectra have exhibited three emission transitions, which are assigned to 4F7/2 → 4I9/2 (896, 904 nm), 4F7/2 → 4I11/2 (1060 nm) and 4F7/2 → 4I13/2 (1332 nm) transitions.
Online since: September 2008
Authors: Gwiy Sang Chung, Jun Ho Jeong
The biaxial stress of poly 3C-SiC/AlN was calculated as 896 MPa from the Raman shifts of 3C-SiC deposited at 1180 °C on AlN of after annealing.
When these values were inserted into Eq. (3) mentioned in the Ref. [13], the biaxial stresses of 3C-SiC/AlN and /SiO2 were obtained as σbi ≈ 896 MPa and 428 MPa respectively.
Online since: August 2022
Authors: Jin Jun Tang, Cui Liang, Chen Guang Xu, Ji Qiang Li
The peak stresses corresponding to 25℃, 250℃, 350℃ and 500℃ are 1230 MPa, 896 MPa, 723 MPa and 471 MPa respectively.
The peak stress corresponding to 25℃, 250℃, 350℃ and 500℃ increased to 1230 MPa, 896 MPa, 723 MPa and 471 MPa respectively.
Online since: August 2011
Authors: Hong Lei Wu, Rui Sheng Zheng, Wei Zheng, Zheng Yan
Hall-effect measurement shows that the AlN crystals have a high hole density of 1.4×1014 cm-3 and mobility of 52 cm2V-1s-1 in spite of the high resistivity (896 Ω•cm).
The hole density is 1.4×1014 cm-3 and the mobility is 52 cm2V-1s-1 in spit of the high resistivity (896 Ω•cm).
Online since: April 2008
Authors: Aurelia Meghea, Maria Giurginca, M. Elisa, Ileana Cristina Vasiliu, Cristiana Eugenia Ana Grigorescu, B. Grigoras, H. Niciu, Daniela Niciu, Nicoleta Iftimie, Patrascu Roxana, Joe Trodahl, M. Dalley
The peak ranged at 946 cm -1 is attributed to PO3 2 symmetrical vibration and that from 896 cm -1 to P-O-P asymmetrical stretch.
IR optical phonons (cm-1) Phosphate units P2O5 pure glass [6, 7] S1 S2 S3 S4 P-O-H (water absorption) 1380 - - - - P=O stretch 1240-1270 1303 1301 1301 1301 [P2O7] 4 pyrophosphate units 1027; 1179 - - - - PO4 stretch 1030 - - - - PO2 symmetrical stretch 1100-1170 1092 1089 1089 1089 PO43 symmetrical 1015 - - - - P-O-P asymmetrical stretch 840-950 894 896 896 896 P-O-P symmetrical stretch 670-800 740; 790 742; 792 742; 792 742; 792 P-O-P bend 420-620 480 476 476 476 PO2 asymmetrical stretch 1200-1300 1303 1301 1301 1301 PO32 symmetrical 980-1050 950 946 946 946 PO32 asymmetrical 1110-1190 1092 1089 1089 1089 500 1000 1500 2000 2500 3000 3500 4000 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 Absorbance (a.u.)
Online since: June 2012
Authors: Su Zhen Cheng, Rong Cong, Ke Liang Wang, Shang Jie Xu
Table 1 Mix design of concrete with different rubber and plastic [Kg · m-3] Number Water-Binder ratio Cement Sand Rubber granule Crushed stone Bentonite Clay Admixtures 1 0.9 100 765 0 765 40 160 3.0 2 0.9 100 730 10 765 40 160 3.3 3 0.9 100 695 20 765 40 160 3.6 4 0.9 100 660 30 765 40 160 4.0 5 0.9 100 625 40 765 40 160 4.5 6 0.9 100 590 50 765 40 160 4.8 7 0.9 100 555 60 765 40 160 5.0 Table 2 Different water-Binder ratio mix design of concrete with different amount of plastic[Kg · m-3] Number Cement Water-Binder ratio Rubber granule Sand Crushed stone Bentonite Clay Admixtures 8 100 0.9 0 765 765 40 160 3.0 9 100 0.8 0 763 827 40 160 3.6 10 100 0.7 0 794 896 40 160 4.8 11 100 0.6 0 837 983 40 160 6.0 12 100 0.9 10 730 765 40 160 3.3 13 100 0.8 10 728 827 40 160 4.2 14 100 0.7 10 759 896 40 160 6.0 15 100 0.6 10 802 983 40 160 6.9 16 100 0.9 20 695 765 40 160 3.6 17 100 0.8 20 693 827 40 160 5.4 18 100 0.7 20 724 896 40 160 6.3 19 100 0.6 20 767 983 40 160 7.8 20 100 0.9 30 660 765
40 160 4.0 21 100 0.8 30 658 827 40 160 6.0 22 100 0.7 30 689 896 40 160 8.1 23 100 0.6 30 732 983 40 160 9.0 Test content and method.
Online since: September 2013
Authors: Wen Yang, Tong Liu, Xiao Qin Liu, Xiao Deng, Bao Jun Cheng
Table 4 Design of wollastonite micro fiber reinforced mortar mix(/g) Type of specimen Cement Fly ash Silica fume Wollastonite micro fiber Water Water reducing agent Quartz sand A1 896 256 128 0 256 9.4 384 A2 851.2 243.2 121.6 64 256 10 384 A3 806.4 230.4 115.2 128 256 10.8 384 A4 761.6 217.6 115.2 192 256 11.6 384 A5 716.8 204.8 102.4 256 256 12.9 384 A6 672 192 96 320 256 14.5 384 A7 627.2 179.2 89.6 384 256 15.1 384 Table5 Design of ARGF reinforced mortar mix(/g) Type of specimen Cement Fly ash Silica fume Quartz sand Water Water Reducing Agent ARGF B1 896 256 128 384 256 9.4 0 B2 896 256 128 384 256 11.9 11.4 B3 896 256 128 384 256 14.0 22.8 B4 896 256 128 384 256 15.3 34.2 B5 896 256 128 384 256 16.8 45.6 2.2 Test method Firstly, cementitious material, fiber, water and quartz sand, were accurately weighed in accordance with table 1-4 and table 1-5, and mixed well.
Online since: November 2012
Authors: Zhi Yong Wang, Yi Geng Li
Table1 1 Comparison of performance to set rolling force [×104N] Group number measured rolling force Mathematical model Neural network model Fuzzy model calculation error % calculation error % calculation error % 1 691 713 3.2 739 6.7 725 4.9 2 802 846 5.5 896 11.7 827 3.1 3 1025 926 -9.6 940 -8.3 1110 8.3 4 858 957 11.6 902 5.1. 842 -1.9 5 818 916 12.1 896 9.5 855 4.6 6 896 821 -8.4 958 6.9 861 -3.9 7 698 804 15.2 749 7.3 728 4.3 8 1029 1144 11.2 904 -12.2 1068 3.8 9 1067 953 -10.8 1117 4.7 1006 -5.7 10 998 1052 9.8 1107 7.4 1044 4.7 Summary The mathematical rolling force prediction model has limited precision, intelligence technology must be adopted in practical control systems to improve forecast accuracy.