Effect of Friction Stir Welding Process Parameters with Interlayer Strip on Microstructural Characterization and Mechanical Properties

Abu–Okail, Mohamed; Abu-Oqail, Ahmed; Ata, Moataz H.

doi:10.1007/s11668-020-00813-0

Cited by 15 publications

(8 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Aeronautical structural applications have become an increasingly attractive and very important issue when it comes to the complex issue of the different loading rates [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ], especially involving thin-walled structures (TWS) [ 10 , 11 , 12 ]. TWS can be produced by using fiber-reinforced polymers (FRPs) [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Synthesis and Characterization of Hybrid Fiber-Reinforced Polymer by Adding Ceramic Nanoparticles for Aeronautical Structural Applications

et al. 2021

Self Cite

View full text Add to dashboard Cite

The multiscale hybridization of ceramic nanoparticles incorporated into polymer matrices reinforced with hybrid fibers offers a new opportunity to develop high-performance, multifunctional composites, especially for applications in aeronautical structures. In this study, two different kinds of hybrid fibers were selected, woven carbon and glass fiber, while two different ceramic nanoparticles, alumina (Al2O3) and graphene nanoplatelets (GNPs), were chosen to incorporate into a polymer matrix (epoxy resin). To obtain good dispersion of additive nanoparticles within the resin matrix, the ultrasonication technique was implemented. The microstructure, XRD patterns, hardness, and tensile properties of the fabricated composites were investigated here. Microstructural characterization demonstrated a good dispersion of ceramic nanoparticles of Al2O3 and GNPs in the fabricated composites. The addition of GNPs/Al2O3 nanoparticles as additive reinforcements to the fiber-reinforced polymers (FRPs) induced a significant increase in the hardness and tensile strength. Generally, the FRPs with 3 wt.% nano-Al2O3 enhanced composites exhibit higher tensile strength as compared with all other sets of composites. Particularly, the tensile strength was improved from 133 MPa in the unreinforced specimen to 230 MPa in the reinforced specimen with 3 wt.% Al2O3. This can be attributed to the better distribution of nanoparticles in the resin polymer, which, in turn, induces proper stress transfer from the matrix to the fiber phase. The hybrid mode mechanism depends on the interaction among the mechanical properties of fiber, the physical and chemical evolution of resin, the bonding properties of the fiber/resin interface, and the service environment. Therefore, the hybrid mode of woven carbon and glass fibers at a volume fraction of 64% with additive nanoparticles of GNPs/Al2O3 within the resin was appropriate to produce aeronautical structures with extraordinary properties.

show abstract

Section: Introductionmentioning

confidence: 99%

Synthesis and Characterization of Hybrid Fiber-Reinforced Polymer by Adding Ceramic Nanoparticles for Aeronautical Structural Applications

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore neither high heat/low heat nor process parameter, the appropriate wt% of reinforcements influences the mechanical properties of the interlock lap joints. This is due to presence of ceramics in Al 2 O 3 at recrystallization temperature and plasticized deformation occurring at the nugget zone of the joints [24]. The SiC grains are reduced due to the presence of second-phase particulates that creates loop dislocations and cell structure around the particles with aluminum matrix during deformation at a constant decrease in grain size as shown in Fig.…”

Section: Microstructure Of the Interlock Lap Joints With Reinforcemenmentioning

confidence: 96%

Effects of SiC and Al2O3 Reinforcement of Varied Volume Fractions on Mechanical and Micro Structure Properties of Interlock FSW Dissimilar Joints AA7075-T6-AA7475-T7

Anand¹,

Sridhar²

2020

Silicon

View full text Add to dashboard Cite

In this research work, the effect of SiC and Al 2 O 3 reinforcements is analyzed on the interlock dissimilar joints. The joints are welded with different wt% of SiC and Al 2 O 3 (1 to 5 wt%) placed in the groove of 0.5 mm depth between the sheets. The rotational speed of 1400 rpm, weld speed of 30 mm/s and plunge speed rate of 0.06 mm/s are selected input parameters to perform the weld. Thereafter Micro-hardness, tensile strength and microstructure properties of interlock lap joints were investigated. AA7075 T6-AA7475 T7/2wt% SiC showed maximum tensile strength and hardness of 190.51 MPa, 220 HV respectively. All the SiC reinforced FSW interlock lap joints mechanical properties showed improvement on the static properties than the joints made with Al 2 O 3 reinforcement, because of the hard silica particles and substantial increase in grain refinement that occurred in the stir zone of the reinforced welded joints. The microstructure analysis of joints revealed that reinforcements have mixed uniformly and homogenous distribution occurred in the entire weld. The fracture analysis revealed that the joints with SiC possess ductile fracture.

show abstract

“…The connection between measure boundaries and the width of remuneration interlayer strips has played a significant role in influencing welded joints' microstructural and mechanical properties [16].…”

Section: Understanding the Processmentioning

confidence: 99%

A Survey of Machine Learning in Friction Stir Welding, including Unresolved Issues and Future Research Directions

Chadha

Selvaraj

Gunreddy

et al. 2022

Material Design & Processing Communications

View full text Add to dashboard Cite

Friction stir welding is a method used to weld together materials considered challenging by fusion welding. FSW is primarily a solid phase method that has been proven efficient due to its ability to manufacture low-cost, low-distortion welds. The quality of weld and stresses can be determined by calculating the amount of heat transferred. Recently, many researchers have developed algorithms to optimize manufacturing techniques. These machine learning techniques have been applied to FSW, which allows it to predict the defect before its occurrence. ML methods such as the adaptive neurofuzzy interference system, regression model, support vector machine, and artificial neural networks were studied to predict the error percentage for the friction stir welding technique. This article examines machine learning applications in FSW by utilizing an artificial neural network (ANN) to control fracture failure and a convolutional neural network (CNN) to detect faults. The ultimate tensile strength is predicted using a regression and classification model, a decision tree model, a support vector machine for defecting classification, and Gaussian process regression (UTS). Machine learning implementation mainly promotes uniformity in the process and precision and maximally averts human error and involvement.

show abstract

Effect of Friction Stir Welding Process Parameters with Interlayer Strip on Microstructural Characterization and Mechanical Properties

Cited by 15 publications

References 13 publications

Synthesis and Characterization of Hybrid Fiber-Reinforced Polymer by Adding Ceramic Nanoparticles for Aeronautical Structural Applications

Synthesis and Characterization of Hybrid Fiber-Reinforced Polymer by Adding Ceramic Nanoparticles for Aeronautical Structural Applications

Effects of SiC and Al2O3 Reinforcement of Varied Volume Fractions on Mechanical and Micro Structure Properties of Interlock FSW Dissimilar Joints AA7075-T6-AA7475-T7

A Survey of Machine Learning in Friction Stir Welding, including Unresolved Issues and Future Research Directions

Contact Info

Product

Resources

About