Production and characterization of mechanical and microstructural behaviour of friction stir welded Al6063 composites reinforced with Gr/B4C/SiC particles

Suresh Babu B,Chandramohan G,Boopathi C,Pridhar T,Srinivasan R 한양대학교 세라믹연구소 2018 Journal of Ceramic Processing Research Vol.19 No.1

The present study elucidates the influence of reinforcement particles in friction stir welded aluminium (Al 6063) matrixcomposites on mechanical properties of the metal matrix composition. Initially composites were successfully fabricated withdifferent weight percentage and combination of reinforcements (graphite (gr), B4C and SiC) through stir casting technique. All sets of composite specimen were welded through solid state joining process of friction stir welding technique, theparameters such as tool rotational speed (800, 1000 and 1200 rpm), welding speed (20 and 40 mm/min) and axial loading (10and 20 kN) are taken for characterization of fabricated composites. The effects of friction stir welding parameters wereexamined by mechanical and microstructural characterizations. The composites microstructure and dispersion of particlereinforcements were analysed through optical microscope and also the mechanical properties of yield strength, ultimatestrength and elongation were analysed using universal testing machine. The optimized friction stir weld parameters wereidentified for 20% weight fraction reinforced hybrid composites.

Optimization of friction stir welding process parameters on AA 6063-SiC-B4C hybrid metal matrix composites by genetic algorithm

R. Srinivasan,B. Suresh Babu,P. Prathap,Ruban Whenish,R. Soundararajan,G. Chandramohan 한양대학교 세라믹연구소 2021 Journal of Ceramic Processing Research Vol.22 No.1

Friction Stir Welding (FSW) is a metal joining process has its own benefits over fusion welding processes. FSW AluminiumMetal Matrix Composites (AMMC) replaced conventional metals for structural applications in aerospace, automobile andmarine sectors. In this present investigation, process parameters of FSW for joining AA 6063-SiC-B4C hybrid MMCs wereoptimized in order to achieve maximum tensile strength. Initially, AMMC was manufactured through stir casting with thematrix AA 6063 and reinforcements SiC and B4C. The hybrid MMC work pieces were subjected to FSW process by varyingthe process parameters such as tool rotation speed, welding speed and axial force using Taguchi L27 orthogonal array. Tensilestrength of hybrid composite was examined and regression analysis were done using MINITAB V17 software. GeneticAlgorithm technique was used to optimize the tensile strength with FSW parametric combinations. The optimum parametersfor FSW of AA6063-SiC-B4C hybrid composites were Tool rotational speed (TRS) – 1050 rpm; Axial Force (AF) – 10 kN andWeld Speed (WS) – 45 mm/min obtained. The optimal parameters were applied to experimental study and the results werevalidated.

Multi objective optimization of wear characteristics on Al7075/Al2O3/B4C composites - Desirability approach

Pridhar T,Ravikumar. K,Suresh Babu B,Srinivasan R,Sathishkumar. B 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.2

Aluminium hybrid metal matrix composites comprises of Al alloy embedded with multiple hard particulates to improve thewear characteristics. In this study Al 7075/Al2O3/B4C hybrid composite was fabricated with 5 wt.% B4C particles addition and2, 4, 6, 8 and 10 wt.% of Al2O3 by liquid metallurgy route. The dry sliding wear behaviour of hybrid composites wasinvestigated under various sliding parameters using a pin on disc tribometer. Numerical models were developed to predict thefrictional and wear characteristics of the composites. Analysis of variance method and confirmation experiments wereemployed to validate the adequacy of the developed model. The composites with high particle content exhibits better wearresistance at various sliding conditions. Detailed metallurgical investigations were carried out on the on worn surface. Thewear rate was severe at higher loads due to the crater formation and in addition to abrasive wear. The wear rate andcoefficient of friction were optimized using desirability based multi criteria optimization technique.

Study on effect of welding speed on friction stir welded aluminium metal matrix hybrid composite

P. Gopi Krishnan,B. Suresh Babu,S. Madhu,S. J. Gowrishankar,C. Bibin,S. Saran,S. Shree Ram,A. R. Sri Hari,S.Vidyasagar 한양대학교 세라믹연구소 2021 Journal of Ceramic Processing Research Vol.22 No.5

The development of aluminum series matrix hybrid composites with ceramic reinforcements has recently caught the interestof new researchers. The addition of more than one or two reinforcements in aluminium alloy leads to the fabrication of theAluminium Metal Matrix Hybrid Composite (AMMHC). The present investigation is aimed at the development of newlydeveloped AMMHC followed by friction stir welding for obtaining the improved mechanical properties. The stir castedAA6063 with reinforcement of 5%, 10% and 15% wt. Silicon Carbide (SiC) and 10% wt. Boron Carbide (B4C) werefabricated by stir casting technique and the AMMHC with 10% each of SiC and B4C showed higher mechanical properties. Further the AMMHC are joined by friction stir welding (FSW) route. A prime experimental work has been tried out in theFSW process by varying welding speed (20, 30, 40, 50 and 60 mm/min). The effect of welding speed on AMMHCs were studiedon macro and microstructural observations followed by micro hardness and ultimate tensile. Strength, in which 40 mm/minof welding speed gives better properties than other processing condition. The weldment reveals the better joint strength withthe presence of fine particle dispersion in the microstructure.

Adaptive Firefly Algorithm based OPF for AC/DC Systems

Babu, B. Suresh,Palaniswami, S. The Korean Institute of Electrical Engineers 2016 Journal of Electrical Engineering & Technology Vol.11 No.4

Optimal Power Flow (OPF) is an important operational and planning problem in minimizing the chosen objective functions of the power systems. The recent developments in power electronics have enabled introduction of dc links in the AC power systems with a view of making the operation more flexible, secure and economical. This paper formulates a new OPF to embrace dc link equations and presents a heuristic optimization technique, inspired by the behavior of fireflies, for solving the problem. The solution process involves AC/DC power flow and uses a self adaptive technique so as to avoid landing at the suboptimal solutions. It presents simulation results of IEEE test systems with a view of demonstrating its effectiveness.

Adaptive Firefly Algorithm based OPF for AC/DC Systems

B. Suresh Babu,S. Palaniswami 대한전기학회 2016 Journal of Electrical Engineering & Technology Vol.11 No.4

Optimal Power Flow (OPF) is an important operational and planning problem in minimizing the chosen objective functions of the power systems. The recent developments in power electronics have enabled introduction of dc links in the AC power systems with a view of making the operation more flexible, secure and economical. This paper formulates a new OPF to embrace dc link equations and presents a heuristic optimization technique, inspired by the behavior of fireflies, for solving the problem. The solution process involves AC/DC power flow and uses a self adaptive technique so as to avoid landing at the suboptimal solutions. It presents simulation results of IEEE test systems with a view of demonstrating its effectiveness.

Deposition rate dependent phase/mechanical property evolution in zirconia and ceria-zirconia thin film by EB-PVD technique

Arunkumar, P.,Aarthi, U.,Sribalaji, M.,Mukherjee, B.,Keshri, Anup Kumar,Tanveer, Waqas Hassan,Cha, Suk-Won,Babu, K. Suresh Elsevier 2018 Journal of alloys and compounds Vol.765 No.-

<P><B>Abstract</B></P> <P>Pure zirconia (ZrO<SUB>2</SUB>) and ceria (16 mol%) stabilized zirconia (CeSZr) thin films were prepared by electron beam physical vapor deposition with varying deposition rates (1, 4 and 8 Å/s) in order to correlate the phase changes to the mechanical property. X-ray diffraction and Raman spectra results indicate the presence of mixed monoclinic and tetragonal phases in ZrO<SUB>2</SUB> film, but tetragonal phase dominated at lower deposition rate. However, irrespective of the deposition rate, cerium addition to ZrO<SUB>2</SUB> resulted in complete stabilization of tetragonal phase. Depending on the presence of dual (ZrO<SUB>2</SUB>) or single (CeSZr) phase, either surface cracks or well-connected grain structure was observed in SEM, respectively. Thus, CeSZr film showed a four-fold increase in hardness in comparison to ZrO<SUB>2</SUB>, which can be attributed to the complete stabilization of tetragonal phase that hinders the crack propagation along the grain. Plastic deformation of CeSZr film was found to be 1.80 × 10<SUP>−2</SUP> GPa, which is about ∼55% higher as compared to pure ZrO<SUB>2</SUB> film (8.04 × 10<SUP>−3</SUP> GPa). Thus, the development of CeSZr coating may lead to better surface protection of many components.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Zirconia and ceria (16 mol%) stabilized zirconia (CeSZr) films deposited by EB-PVD. </LI> <LI> ZrO2 thin film showed mixed tetragonal and cubic structure. </LI> <LI> CeSZr thin film formed with single phase tetragonal structure. </LI> <LI> CeSZr film exhibited a four-fold increase in hardness in comparison to ZrO2 film. </LI> <LI> Deposition rate and chemistry influence the mechanical property of films. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Optimization of process parameters in friction stir welding of aluminium matrix SiC-Al2O3 composites by genetic algorithm

P. Gopi Krishnan,B. Suresh Babu,K. Siva 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.2

Friction stir welding (FSW) grabs more attention since the past decade among the researchers worldwide due to its excellentcharacteristics such as no emission of fumes, no filler material, comparatively economical and so on. Friction stir weldingis effectively used in bringing better joint without any appreciable defects in light materials such as Aluminium, Magnesiumetc., Experiments in FSW of materials with high density such as steel, copper alloys etc., have also been tried out. Theselection of proper welding parameters determines a good weldment. In this work, Aluminium matrix hybrid compositewas manufactured through stir casting with the matrix AA7010 and reinforcements SiC and Al2O3. The hybrid compositeworkpieces were subjected to friction stir welding process by varying the process parameters such as tool rotation speed,welding speed and axial force using Taguchi L27 orthogonal array. Tensile strength of FS welded composite was examinedand regression analysis was done. Genetic Algorithm technique was used to optimize the weld tensile strength within thedesign space of 53 = 125 alternatives of parametric combinations. The study focuses on the improvement of the tensilestrength of the welded specimens.

An Improved Intrusion Detection System for SDN using Multi-Stage Optimized Deep Forest Classifier

Saritha Reddy, A,Ramasubba Reddy, B,Suresh Babu, A International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.4

Nowadays, research in deep learning leveraged automated computing and networking paradigm evidenced rapid contributions in terms of Software Defined Networking (SDN) and its diverse security applications while handling cybercrimes. SDN plays a vital role in sniffing information related to network usage in large-scale data centers that simultaneously support an improved algorithm design for automated detection of network intrusions. Despite its security protocols, SDN is considered contradictory towards DDoS attacks (Distributed Denial of Service). Several research studies developed machine learning-based network intrusion detection systems addressing detection and mitigation of DDoS attacks in SDN-based networks due to dynamic changes in various features and behavioral patterns. Addressing this problem, this research study focuses on effectively designing a multistage hybrid and intelligent deep learning classifier based on modified deep forest classification to detect DDoS attacks in SDN networks. Experimental results depict that the performance accuracy of the proposed classifier is improved when evaluated with standard parameters.