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additive friction stir deposition of AZ31B magnesium alloy

Journal of Magnesium and Alloys 2022年第9期10卷 2404-2420页

作者： Sameehan S.Joshi Shreyash M.Patil Sangram Mazumder Shashank Sharma Daniel A.Riley Shelden Dowden Rajarshi Banerjee Narendra B.Dahotre Department of Materials Science and Engineering University of North Texas3940 N Elm StDentonTX 76207USA Center for Agile and Adaptive additive Manufacturing University of North Texas3940 N Elm StDentonTX 76207USA

The current work explored additive friction stir deposition of AZ31B magnesium alloy with the aid of MELD?***31B magnesium bar stock was fed through a hollow friction stir tool rotating at constant velocity of 400 rpm and translating at linear velocity varied from 4.2 to 6.3 mm/s.A single wall consisting of five layers with each layer of 140×40×1 mm^(3)dimensions was deposited under each processing ***,phase,and crystallographic texture evolutions as a function of additive friction stir deposition parameters were studied with the aid of scanning electron microscopy including electron back scatter diffraction and X-ray *** feed material and additively produced samples consisted of theα-Mg *** additively produced samples exhibited a refined grain structure compared to the feed *** feed material appeared to have a weak basal texture,while the additively produced samples experienced a strengthening of this basal *** additively produced samples showed a marginally higher hardness compared to the feed *** current work provided a pathway for solid state additive manufacturing of Mg suitable for structural applications such as automotive components and consumable biomedical implants.

关键词： additive friction stir deposition Magnesium alloys additive manufacturing Thermomechanical processing Materials processing Solid state additive manufacturing

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A comparative study of machine learning in predicting the mechanical properties of the deposited AA6061 alloys via additive friction stir deposition

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Materials Genome Engineering Advances 2024年第1期2卷 134-147页

作者： Qian Qiao Quan Liu Jiong Pu Haixia Shi Wenxiao Li Zhixiong Zhu Dawei Guo Hongchang Qian Dawei Zhang Xiaogang Li C.T.Kwok L.M.Tam Department of Electromechanical Engineering University of MacaoMacaoChina Institute for the Development and Quality MacaoChina IDQ Science and Technology Development(Hengqin Guangdong)Co.LtdHengqinGuangdongChina Aerospace Engineering Equipment(Suzhou)Co.Ltd SuzhouChina National Materials Corrosion and Protection Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijingChina

additive friction stir deposition(AFSD)provides strong flexibility and better performance in component design,which is controlled by the process *** is an essential and difficult task to tune those *** recent exploration of machine learning(ML)exhibits great potential to obtain a suitable balance between productivity and set *** this study,ML techniques,including support vector machine(SVM),random forest(RF)and artificial neural network(ANN),are applied to predict the mechanical properties of the AFSD-based AA6061 *** for the stable parameters(temperature,force and torque)in situ monitored by the self-developed process-aware kit during the AFSD process and the other factors(rotation speed,traverse speed,feed rate and layer thickness)are also set as input *** output variables are microhardness and ultimate tensile strength(UTS).Prediction results show that the ANN model performs the best prediction accuracy with the highest R2(0.9998)and the lowest mean absolute error(MAE,0.0050)and root mean square error(RMSE,0.0063).Furthermore,analysis suggests that the feed rate(24.8%/24.1%)and layer thickness(25.6%/26.6%)indicate a higher contribution that affects the mechanical properties.

关键词： additive friction stir deposition in-situ monitored machine learning mechanical properties prediction

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Preheating-assisted solid-state friction stir repair of Al-Mg-Si alloy plate at different rotational speeds

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International Journal of Minerals,Metallurgy and Materials 2024年第4期31卷 725-736页

作者： Hui Wang Yidi Li Ming Zhang Wei Gong Ruilin Lai Yunping Li State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410083China Research Institute of Light Alloy Central South UniversityChangsha 410083China

additive friction stir deposition(AFSD)is a novel structural repair and manufacturing technology has become a research hotspot at home and abroad in the past five *** this work,the microstructural evolution and mechanical performance of the Al-Mg-Si alloy plate repaired by the preheating-assisted AFSD process were *** evaluate the tool rotation speed and substrate preheating for repair quality,the AFSD technique was used to additively repair 5 mm depth blind holes on 6061 aluminum alloy *** results showed that preheat-assisted AFSD repair significantly improved joint bonding and joint strength compared to the control non-preheat substrate ***,increasing rotation speed was also beneficial to improve the metallurgical bonding of the interface and avoid volume *** preheating conditions,the UTS and elongation were positively correlated with rotation *** the process parameters of preheated substrate and tool rotation speed of 1000 r/min,defect-free specimens could be obtained accompanied by tensile fracture occurring in the substrate rather than the repaired *** UTS and elongation reached the maximum values of 164.2MPa and 13.4%,which are equivalent to 99.4%and 140%of the heated substrate,respectively.

关键词： additive friction stir deposition structural repair tool rotation speed Al alloy

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3D printing of fine-grained aluminum alloys through extrusion-based additive manufacturing:Microstructure and property characterization

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Journal of Materials Science & Technology 2023年第8期139卷 126-136页

作者： Fengchao Liu Pingsha Dong Abdul Sayeed Khan Yuning Zhang Randy Cheng Alan Taub Zongyi Ma Department of Naval Architecture and Marine Engineering University of MichiganAnn ArborMI 48109USA Shi-changxu Innovation Center for Advanced Materials Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China Department of Mechanical Engineering University of MichiganAnn ArborMI 48109USA Department of Materials Science and Engineering University of MichiganAnn ArborMI 48109USA

additive manufacturing(AM)has the potential to transform manufacturing by enabling previously un-thinkable products,digital inventory and delivery,and distributed *** we presented an extrusion-based metal AM method(refer to“SoftTouch”depositionin thefiledpatent)thatis suitablefor making the metal feedstock flowable prior to the deposition through dynamic recrystallization induced grain refinement at elevated *** flowable metal was extruded out of the printer head like a paste for building dense metal parts with fine equiaxed grains and wrought mechanical ***-the-shelf metal rods were used as feedstock and the printing process was completed in an open-air environment,avoiding pricy powders and costly inert or vacuum *** resulting multi-layer de-posited 6061 aluminum alloys yield strength and ductility comparable to wrought 6061 aluminum alloys after the same T6 heat *** extrusion-based metal AM method can also be advanced as green manufacturing technologies for fabricating novel alloys and composites,adding novel features to existing parts,repairing damaged metal parts,and welding advanced metals for supporting sustainable manufac-turing,in addition to being developed into a cost-effective manufacturing process for the fabrication of dense metal of complex structural forms.

关键词： additive friction extrusion deposition Microstructure refinement Solid state additive manufacturing additive friction stir deposition friction stir welding

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