A high ductility TiAl alloy made by two-step heat treatment

Tang, Jiancheng; Huang, Baiyun; Liu, Wensheng; He, Yuehui; Zhou, Kechao; Wu, Aiping; Peng, Kun; Qin, Wei; Du, Youwei

doi:10.1016/j.materresbull.2003.07.014

Cited by 17 publications

(3 citation statements)

References 7 publications

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“…Ductility values were consolidated from literature [5][6][7][8][9][10][11][25][26][27][28][29][30] and three important parameters viz. alloy chemistry, grain size and heat treatment cycles were identified, which has major influence in ductility of the alloy.…”

Section: Ductility Parameters and Data For Modelmentioning

confidence: 99%

Ductility prediction of Ti aluminide intermetallics through neuro-fuzzy set approach

Gupta

Mehta

Agarwala

et al. 2010

Trans Indian Inst Met

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Several studies have been conducted to improve the room temperature ductility of titanium aluminide intermetallics through alloy design and microstructure modifications. Ductility of two phase (D 2 +J) binary Ti aluminide intermetallics centered on Ti-48Al (at%) was reported as maximum (~1.5%) in desirable heat treatment condition and so more studies were attempted near to this composition. In the present work also, ductility has been studied for the alloy variants of this composition through fuzzy modeling. Neuro-fuzzy models were developed through Adaptive Neural Fuzzy Inference System (ANFIS) using subtractive cluster techniques. The input parameters were fuzzified with Gaussian membership functions to develop the fuzzy rules. The output of each rule was obtained by the evaluation of the membership values. Finally the overall fuzzy model response was obtained as the weighted average of the individual rule response. Ductility database were prepared and three parameters viz. alloy type, grain size and heat treatment cycle were selected for modeling. Additional, ductility data were generated from literature based experimental data for training and validation of models on the basis of linearity and considering the primary effect of these three parameters. Adequacy of developed models was evaluated with the generated data sets. Different evaluation measures were considered and the resulting graphs from the developed model were analyzed. The results of the fuzzy models were found to be very close to the literature based generated data and it also showed the possibility of improving ductility upto 7% for multicomponent alloy with grain size of 10-50Pm following a multistep heat treatment cycle.

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Section: Ductility Parameters and Data For Modelmentioning

confidence: 99%

Ductility prediction of Ti aluminide intermetallics through neuro-fuzzy set approach

Gupta

Mehta

Agarwala

et al. 2010

Trans Indian Inst Met

View full text Add to dashboard Cite

show abstract

“…Ductility values were consolidated from the literature [5][6][7][8][9][10][11][28][29][30][31][32][33], and three important parameters, namly alloy chemistry, grain size, and heat treatment cycles were identified, which have major influence in ductility of the alloy. Alloy chemistry, grain size, and heat treatment cycles have important influence on ductility.…”

Section: Ductility Parameters and Data For Modelmentioning

confidence: 99%

Study on Ductility of Ti Aluminide Using Artificial Neural Network

Gupta

Mehta

Agarwala

et al. 2011

International Journal of Aerospace Engineering

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Improvement of ductility at room temperature has been a major concern on processing and application of Ti aluminides over the years. Modifications in alloy chemistry of binary alloy (Ti48 Al) and processing conditions were suggested through experimental studies with limited success. Using the reported data, the present paper aims to optimize the experimental conditions through computational modeling using artificial neural network (ANN). Ductility database were prepared, and three parameters, namely, alloy type, grain size, and heat treatment cycle were selected for modeling. Additionally, ductility data were generated from the literature for training and validation of models on the basis of linearity and considering the primary effect of these three parameters. Model was trained and tested for three different datasets drawn from the generated data. Possibility of improving ductility by more than 5% is observed for multicomponent alloy with grain size of 10-50 μm following a multistep heat treatment cycle.

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“…Compositional variations including controlling gaseous impurities such as oxygen (O) and nitrogen (N), and the addition of chromium (Cr) and manganese (Mn) to TiAl alloys have been previously addressed with the aim of ductility improvement [9][10][11]. Furthermore, employing wrought processing techniques followed by post-treatments have also been extensively experimented [12][13][14]. However, microstructural inconsistencies resulting from solidification and phase transformations further deteriorate and scatter the mechanical properties of the alloys [15,16].…”

Section: Introductionmentioning

confidence: 99%

Spark Plasma Sintering of Titanium Aluminides: A Progress Review on Processing, Structure-Property Relations, Alloy Development and Challenges

Mogale

Matizamhuka

2020

Metals

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Titanium aluminides (TiAl) have the potential of substituting nickel-based superalloys (NBSAs) in the aerospace industries owing to their lightweight, good mechanical and oxidation properties. Functional simplicity, control of sintering parameters, exceptional sintering speeds, high reproducibility, consistency and safety are the main benefits of spark plasma sintering (SPS) over conventional methods. Though TiAl exhibit excellent high temperature properties, SPS has been employed to improve on the poor ductility at room temperature. Powder metallurgical processing techniques used to promote the formation of refined, homogeneous and contaminant-free structures, favouring improvements in ductility and other properties are discussed. This article further reviews published work on phase constituents, microstructures, alloy developments and mechanical properties of TiAl alloys produced by SPS. Finally, an overview of challenges in as far as the implementation of TiAl in industries of interest are highlighted.

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A high ductility TiAl alloy made by two-step heat treatment

Cited by 17 publications

References 7 publications

Ductility prediction of Ti aluminide intermetallics through neuro-fuzzy set approach

Ductility prediction of Ti aluminide intermetallics through neuro-fuzzy set approach

Study on Ductility of Ti Aluminide Using Artificial Neural Network

Spark Plasma Sintering of Titanium Aluminides: A Progress Review on Processing, Structure-Property Relations, Alloy Development and Challenges

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