Aggregate Grading and Mechanical Property Study on Particulate-Reinforced Composite

2011 ◽  
Vol 225-226 ◽  
pp. 13-16
Author(s):  
Jian Xiong Xie ◽  
Zhe An Lu

The aggregate gradation and mechanical property of particle reinforced composite (resin and quartz sand composite ) were studied with test, the results show that: The more optimal scheme of aggregate gradation can be obtained with right ratio of larger particle quartz sand and small particle quartz plate , which can make the gradation resin content from the original 20% ~ 25% reduced to 12% ~ 14%, so as to reduce the cost and improve the economic benefit and guarantee bending strength of winding layer not decrease in the meantime

Author(s):  
Lucas Moreira Maia ◽  
Wilson Bambirra Júnior ◽  
Kênia Maria Toubes ◽  
Gil Moreira Júnior ◽  
Vinicius de Carvalho Machado ◽  
...  

2013 ◽  
Vol 589-590 ◽  
pp. 590-593 ◽  
Author(s):  
Min Wang ◽  
Jun Zhao

In order to investigate the effects of TiN content on Al2O3/TiN ceramic material (ATN), the ATN ceramic materials were prepared of TiN content in 30%, 40%, 50%, 60% in the condition of hot press sintering. The sintering temperature is 1700°C, the sintering press is 32MPa, and the holding time are 5min, 10min, 15min. The effects of TiN content on mechanical properties and microstructure of ATN ceramic materials were investigated by analyzing the bending strength, hardness, fracture toughness. The results show that ATN50 has the best mechanical property, its bending strength is 659.41MPa, vickers hardness is 13.79GPa, fracture toughness is 7.06MPa·m1/2. It is indicated that the TiN content has important effect on microstructure and mechanical properties of ATN ceramic materials.


BioResources ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. 4891-4904
Author(s):  
Selahattin Bardak ◽  
Timucin Bardak ◽  
Hüseyin Peker ◽  
Eser Sözen ◽  
Yildiz Çabuk

Wood materials have been used in many products such as furniture, stairs, windows, and doors for centuries. There are differences in methods used to adapt wood to ambient conditions. Impregnation is a widely used method of wood preservation. In terms of efficiency, it is critical to optimize the parameters for impregnation. Data mining techniques reduce most of the cost and operational challenges with accurate prediction in the wood industry. In this study, three data-mining algorithms were applied to predict bending strength in impregnated wood materials (Pinus sylvestris L. and Millettia laurentii). Models were created from real experimental data to examine the relationship between bending strength, diffusion time, vacuum duration, and wood type, based on decision trees (DT), random forest (RF), and Gaussian process (GP) algorithms. The highest bending strength was achieved with wenge (Millettia laurentii) wood in 10 bar vacuum and the diffusion condition during 25 min. The results showed that all algorithms are suitable for predicting bending strength. The goodness of fit for the testing phase was determined as 0.994, 0.986, and 0.989 in the DT, RF, and GP algorithms, respectively. Moreover, the importance of attributes was determined in the algorithms.


Cerâmica ◽  
2013 ◽  
Vol 59 (351) ◽  
pp. 351-359 ◽  
Author(s):  
F. M. Bertan ◽  
A. P. Novaes de Oliveira ◽  
O. R. K. Montedo ◽  
D. Hotza ◽  
C. R. Rambo

This work reports on the characterization of ZrSiO4 particulate-reinforced Li2O-ZrO2-SiO2-Al2O3 (LZSA) glass-ceramic matrix composites. The typical physical/mechanical and chemical properties of the glass batches and the composites were measured. A composition with 60 wt.% ZrSiO4 was preliminarily selected because it demonstrated the highest values of bending strength (190 MPa) and deep abrasion resistance (51 mm³). To this same composition was given a 7 wt.% bentonite addition in order to obtain plasticity behavior suitable for extrusion. The sintered samples (1150 ºC for 10 min) presented a thermal linear shrinkage of 14% and bending strength values of 220 MPa.


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