Development of mathematical model to predict the mechanical properties of friction stir  welded AA6351 aluminum alloy

Palanivel, R.; Mathews, P. Koshy; Murugan, N.

doi:10.25103/jestr.041.03

Cited by 55 publications

(30 citation statements)

References 15 publications

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“…Hsieh and Chen (2008) determined the tensile strength of AA 6061 T-6 alloy to be within the range of 225.4-247.9 MPa and the % Elong of 5.5-6.8%. Palanivel et al (2011) used regression model to predict UTS, YS, and % Elong of AA 6351 aluminum alloy. They obtained for measured UTS, a range of 193-219 MPa, YS within the range of 166-190 MPa and % Elong of between 3.61 and 5.24%, whereas the predicted values for UTS are within the range of 199.70-216.54 MPa, predicted YS is within the range of 172.92-187.29 MPa, and predicted % Elong is within the range of 3.52-5.08%.…”

Section: Discussionmentioning

confidence: 99%

“…The predicted results were compared with the actual experimental results Khorram, Ghoreishi, Yazdi, and Moradi (2011) employed the response surface methodology to model and predict weld bead geometry parameters. Palanivel, Mathews, and Murugan (2011) used mathematical model to predict the mechanical properties of AA 6351 aluminum alloy. Cavaliere, Campanile, Panella, and Squillace (2006) studied the effect of welding parameters on mechanical and microstructural properties of AA 6056 joints produced by friction stir welding.…”

Section: Introductionmentioning

confidence: 99%

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Development of a predictive model for determining mechanical properties of AA 6061 using regression analysis

Achebo

2015

Production & Manufacturing Research

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Aluminum alloys (AA) such as AA 6061 are difficult to weld, and their application to high-strength demands tends to be limited because of their inherently low-strength threshold levels when compared to other alloys. To effectively use this alloy to its full potential, its tensile strength, is investigated. In actual manufacturing settings, it has proven beneficial to attempt a prediction of the tensile properties of potential weld joints. To achieve this, a model was developed using the multiple linear regression analysis to predict these tensile properties such as the ultimate tensile strength, the yield strength (YS), and percentage elongation (% Elong). It was found from the scattered diagrams that the measured and predicted values were almost a perfect fit with a coefficient of determination of between 0.99 and 1.0. The analysis of variance further validated the adequacy of the model. The analysis showed that the claims observed in the study match with those of other investigators. The predictive model obtained is expected to help the welding community to pre-determine the tensile properties of AA 6061 weldment using selected values for each of the process parameters applied in this study.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of a predictive model for determining mechanical properties of AA 6061 using regression analysis

Achebo

2015

Production & Manufacturing Research

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“…The developed regression equation [10] for each response such as tensile strength, impact strength, strength coefficient, hardening exponent, intial yield strain are given below from equation (2) …”

Section: Regression Equationsmentioning

confidence: 99%

Study of Relation between Welding and Hardening Parameters of Friction Stir Welded Aluminium 2024 Alloy

Karthikeyan

Thiagarajan

Mahadevan

2014

Procedia Engineering

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This work focuses on studying the relationship between the welding and hardening parameters of friction stir welded Al 2024 alloy. The experiments were conducted using Box Behnken design of Response surface methodology. The conducted experiments were then subjected to mechanical testing such as ultimate tensile strength and izod impact tests. Then the identified Least Square hardening model was compared with the welding parameters to explain the relationship between them. The Statistical software "Minitab 16" was used to generate models of the responses. This relation between the identified models of the responses with the welding parameters helps to predict the mechanical property behavior of the friction stir welded Al 2024 alloy. This prediction helps to understand the behavior of the alloy during friction stir welding thereby minimizing the experimental cost and time in the future.

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“…They were found the increase in the rotational speed, welding speed and axial force leads to the increase in the ultimate strength and its reaches a maximum value and then decreases [5]. Effect of FSW process parameters on mechanical properties of welded AA6061 aluminum alloy.…”

Section: G Swaminathan and S Sathiyamurthymentioning

confidence: 99%

Experimental Study of Mechanical and Metallurgical Properties of Friction Stir Welded Dissimilar Aluminum Alloys

Tjprc¹

2018

IJMPERD

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Development of mathematical model to predict the mechanical properties of friction stir welded AA6351 aluminum alloy

Cited by 55 publications

References 15 publications

Development of a predictive model for determining mechanical properties of AA 6061 using regression analysis

Development of a predictive model for determining mechanical properties of AA 6061 using regression analysis

Study of Relation between Welding and Hardening Parameters of Friction Stir Welded Aluminium 2024 Alloy

Experimental Study of Mechanical and Metallurgical Properties of Friction Stir Welded Dissimilar Aluminum Alloys

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