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Lü, Weijie; Zhang, Di; Zhang, Xiaonong; Bian, Yujun; Wu, Rui; Sakata, Takao; Mori, Hirotarô

doi:10.1023/a:1017917631855

Cited by 57 publications

(52 citation statements)

References 8 publications

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“…After the OS is selected and the MF is generated, operation of the network is tested with the use of them (OS & MF). Twenty sample data (data of samples [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] were used from the total of 30, as data sets for network training. Table 3 shows the normalized sample data used for networks training.…”

Section: Resultsmentioning

confidence: 99%

“…5,6 TMCs can be reinforced with continuous fibers, whiskers or particles. 7 As is well known, the mechanical properties of the composites depend on matrix, reinforcement and reinforcement/matrix interface, which bonds the formers together. 8 Compared with continuous fibers, TMCs reinforced with whiskers or particles exhibit more isotropic behaviors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling of shot-peening effects on the surface properties of a (TiB + TiC)/Ti–6Al–4V composite employing artificial neural networks

Maleki¹,

Zabihollah²

2016

Mater. Tehnol.

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Titanium matrix composites (TMCs) have wide application prospects in the field of aerospace, automobile and other industries because of their good properties, such as high specific strength, good ductility, and excellent fatigue properties. However, in order to improve their fatigue strength and life, crack initiation and growth at the surface layers must be suppressed using surface treatments. Shot peening (SP) is an effective surface mechanical treatment method widely used in industry which can improve the mechanical properties of a surface. However, artificial neural networks (ANNs) have been used as an efficient approach to predict and optimize the science and engineering problems. In the present study the effects of SP on TMC were modeled by means of ANN and the capability of the ANN in predicting the output parameters is investigated. A back-propagation (BP) error algorithm is developed for the network training. Data of experimental tests on the (TiB + TiC)/Ti-6Al-4V composite are employed in order to train the network. The volume fractions of the reinforcements (TiB + TiC) were 5 % and 8 %. ANN testing is accomplished using different experimental data thaat were not used during the network training. The distance from the surface (depth) and SP intensity are regarded as input parameters and residual stress and hardness of the Ti-6Al-4V before and after the SP and adding reinforcements are gathered as the output parameters of the network. A comparison was made between experimental and predicted data. The predicted results were in good agreement with experimental ones, which indicates that developed neural network can be used for modeling the SP process on TMCs. Keywords: titanium matrix composites, surface treatment, shot peening, artificial neural networks, residual stress, hardness Kompoziti na osnovi titana (TMCs) imajo {iroko mo`nost uporabe na podro~ju letalstva, avtomobilske in druge industrije zaradi njihovih dobrih lastnosti, kot so: velika specifi~na trdnost, dobra duktilnost in odli~na odpornost na utrujanje. Vseeno pa je za pove~anje odpornosti na utrujanje in`ivljenjsko dobo, potrebna povr{inska obdelava, da se zavre nastanek razpok in njihova rast na povr{ini. Hladno povr{insko kovanje (SP) je u~inkovita mehanska metoda, ki se v industriji pogosto uporablja za izbolj{anje mehanskih lastnosti povr{ine. Umetne nevronske mre`e (ANNs) se uporabljajo kot u~inkovit pribli`ek za napovedovanje in optimiranje znanstvenih osnov in in`eniringa tega problema. V {tudiji so bili modelirani vplivi SP na TMC s pomo~jo ANN in preiskovana je bila zmo`nost napovedovanja izhodnih parametrov z ANN. Za usposabljanje mre`e je bil razvit algoritem vzvratnega {irjenja napak (BP). Podatki iz eksperimentalnih preizkusov na (TiB + TiC)/Ti-6Al-4V kompozitu so uporabljeni za usposabljanje mre`e. Volumska dele`a delcev (TiB + TiC) za oja~anje sta bila 5 % in 8 %. ANN preizku{anje je bilo izvedeno z uporabo razli~nih eksperimentalnih podatkov, ki niso bili uporabljeni pri usposabljanju mre`e. Razdalja od povr{ine (globina) in...

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling of shot-peening effects on the surface properties of a (TiB + TiC)/Ti–6Al–4V composite employing artificial neural networks

Maleki¹,

Zabihollah²

2016

Mater. Tehnol.

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“…The different shapes of the reinforcements are related to their crystal structures and growth mechanisms during solidification process. 11) 3.2 The transus temperature and various forgings of 5 vol% (TiB+TiC)/Ti-1100 composite It is well known that transus temperature is a very important parameter for the thermomechanical processing of Ti alloys and its composite. Metallographic techniques were used to measure the transus temperature of the composite, and the results were presented in Fig.…”

Section: Methodsmentioning

confidence: 99%

Effect of Forging Temperature on Microstructure and Mechanical Properties of <I>In Situ</I> (TiB+TiC)/Ti Composites

Lü

Qin

et al. 2006

Mater. Trans.

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In this paper, 5 vol% (TiB+TiC)/Ti-1100(Ti-6Al-2.75Sn-4Zr-0.4Mo-0.45Si) composite were fabricated using in situ technologies between Ti and B 4 C powders. Phase identification was carried out by X-ray diffraction. transus temperature of the composite was measured by metallographic techniques. The composite after ingot breakdown was forged in various temperature ranges. Microstructure of the composite after forging at various temperatures was studied by optical microscopy (OM). Mechanical properties of the composite after forging at various temperatures were evaluated by tensile tests at 873 K. It was found that the transus temperature of the composites was around 100 K higher than that of monolithic Ti-1100 alloy. Different microstructures were obtained after forging at different temperatures. The composite with different microstructures offered different mechanical properties, which was shown in the tensile tests.

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“…On the basis of the former papers, [3][4][5][6] the commercial pure titanium and TMCs reinforced with TiB were in situ fabricated by non-consumable vacuum arc remelting. The total volume percentage of reinforcements TiB was 8% and 5%, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…4) The microstructure and mechanical properties at room temperature and elevated temperature have also been investigated. [5][6][7] The main aim to develop the TMCs is to widen the utilization field at high temperature. In spite of numerous studies on physical and mechanical properties of the in situ synthesized TMCs, an understanding of the oxidation behavior of the TMCs has not yet been fully achieved, which is an important factor for use at high temperature.…”

Section: Introductionmentioning

confidence: 99%

Oxidation Behavior of <i>In Situ</i> Synthesized TiB/Ti Composite in Air Environment

et al. 2004

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Isothermal oxidation behavior of in situ synthesized TiB/Ti composites has been investigated. Samples of titanium matrix composites reinforced with 0, 5 and 8 vol% TiB particulates were oxidized at 823, 873, and 923 K for 300 h in atmospheric air. Scanning electron microscopy (SEM) with energy dispersive X-ray spectrometry, and transmission electron microscopy (TEM) were used to identify oxidation products and characterize oxide scale morphology. Oxidation was observed to follow parabolic kinetics. Rate of oxidation decreased with the increase of TiB reinforcements. The oxide scale formed on TiB/Ti composites was rutile-type TiO 2 . No other oxides were observed within the oxide scale. The increased oxidation resistance due to the addition of the in situ synthesized TiB reinforcement was attributed to the improved tendency for the formation of thin and dense oxide avoiding crack and spallation, the strong enough interfacial cohesion and the clean interfacial microstructure between the reinforcements and the titanium matrix alloy.

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Cited by 57 publications

References 8 publications

Modeling of shot-peening effects on the surface properties of a (TiB + TiC)/Ti–6Al–4V composite employing artificial neural networks

Modeling of shot-peening effects on the surface properties of a (TiB + TiC)/Ti–6Al–4V composite employing artificial neural networks

Effect of Forging Temperature on Microstructure and Mechanical Properties of <I>In Situ</I> (TiB+TiC)/Ti Composites

Oxidation Behavior of <i>In Situ</i> Synthesized TiB/Ti Composite in Air Environment

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