Effect of Ni and Si addition on electrical, tribological and corrosion behavior of novel Cu-Zn alloy

Saravanan. R,Suresh. P,Prabu. M,Bagyalakshmi. Pd 한양대학교 세라믹연구소 2022 Journal of Ceramic Processing Research Vol.23 No.4

The goal of this research is to evaluate the electrical, dry sliding wear and corrosion behaviour of copper-zinc alloy reinforcedwith Ni and Si through Powder Metallurgy (P/M) technique. Six different wt. % of novel copper-zinc alloy are considered forthis research study namely 90Cu-10Zn, 88.16Cu-10Zn-1.5Ni-0.34Si, 85Cu-15Zn, 83.16Cu-15Zn-1.5Ni-0.34Si, 80Cu-20Zn and78.16Cu-20Zn-1.5Ni-0.34Si. The fabricated composites were characterized by using Scanning Electron Microscope (SEM) withEnergy Dispersive Spectroscopy (EDS) line mapping. The electrical, wear and corrosion behaviour of the fabricatedcomposites was assessed. The hardness of the fabricated composites was evaluated using Vickers Hardness Tester. Theelectrical conductivity was assessed using four-point probe tester. The result shows a significant improvement on electrical andtribological properties by increasing the wt.% of Zn, Ni and Si led of the composites. The research results concludes that78.16Cu-20Zn-1.5Ni-0.34Si composite possessed better hardness about 287 HV and the electrical conductivity about 121%IACS. The investigation result shows that Zn acts as a vital role to enhance the properties in all aspects. Also, theexperimentation results portrays that Cu-20Zn-1.5Ni-0.34Si composite possessed better specific wear rate and coefficient offriction such as 1.85 * 105 mm3/N-m and 0.29 respectively.

Generation Scheduling with Large-Scale Wind Farms using Grey Wolf Optimization

R. Saravanan,S. Subramanian,V. Dharmalingam,S. Ganesan 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.4

Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.

Generation Scheduling with Large-Scale Wind Farms using Grey Wolf Optimization

Saravanan, R.,Subramanian, S.,Dharmalingam, V.,Ganesan, S. The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.8 No.1

Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.

Effect of graphene addition on the mechanical characteristics of AA7075 aluminium nanocomposites

R. Ranga Raj,J. Yoganandh,M. S. Senthil Saravanan,M. S. Senthil Saravanan,S. Sathiesh Kumar 한국탄소학회 2021 Carbon Letters Vol.31 No.1

Processing and characterization of graphene (Gr)-reinforced aluminium alloy 7075 (AA7075) microcomposites and nanocomposites are reported in this work. Composites are fabricated by mechanical alloying process at wet conditions. The bulk composites are prepared by uniaxial die pressing to get higher densification and sintered in an inert atmosphere. Density of the nanocomposites is higher than the microcomposites due to the reduction of grain size by increased milling time. X-ray diffraction (XRD) analysis confirms graphene interaction with the AA7075 matrix lattice spaces. The effective distribution of graphene with aluminium alloy is further confirmed by the Transmission Electron Microscopy (TEM) analysis. The hardness of the composites proportionally increases with the graphene addition owing to grain refinement. Wear morphology is characterized using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Microcomposites reveal abrasive and ploughing wear mechanism of material removal from the surface. Nanocomposites show adhesive wear with delamination and particle pull-out from the material surface.

Optimization of Wear Behavior on Cenosphere -Aluminium Composite

Saravanan, V.,Thyla, P.R.,Balakrishnan, S.R. Materials Research Society of Korea 2015 한국재료학회지 Vol.25 No.7

The magnitude of wear should be at a minimum for numerous automobile and aeronautical components. In the current work, composites were prepared by varying the cenosphere content using the conventional stir casting method. A uniform distribution of particles was ensured with the help of scanning electron microscopy (SEM). Three major parameters were chosen from various factors that affect the wear. A wear test was conducted with a pin-on-disc apparatus; the controlling parameters were volume percentages of reinforcement of 5, 10, 15, and 20%, applied loads of 9.8, 29.42, and 49.03 N, and sliding speeds of 1.26, 2.51, and 3.77 m/s. The design of the experiments (DOE) was performed by varying the different influencing parameters using the full factorial method. An analysis of variance (ANOVA) was used to analyze the effects of the parameters on the wear rate. Using regression analysis, a response curve was obtained based on the experimental results. The parameters in the resulting curve were optimized using the Genetic Algorithm (GA). The GA results were compared with those of an alternate efficient algorithm called Neural Networks (NNs).

Drying and energy aspects of tapioca sago processing-An experimental field study

Sivakumar R.,Elayaperumal A.,Saravanan R. 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.6

The drying characteristics of tapioca sago were studied using four different drying methods--Open sun drying (OSD), Conveyor beltdrying (CBD), Bin drying (BD) and Fluidized bed drying (FBD)--in an industry located in Tamilnadu, India (Latitude: 11.494347° N;Longitude: 78.272264° E). The BD and FBD dryers were designed and fabricated as pilot scale models in the laboratory with respectivecapacity of 5 kg/h and 10 kg/h; CBD (1000 kg/h) and OSD are the commercial drying operations currently employed in industrial processing. The drying time, energy and exergy aspects of all the drying methods were compared along with the achieved final moisture content,color and quality of the dried products. The highest Energy utilization ratio (EUR) was found in CBD and FBD in the range of 20-76 % and 10-67 %, respectively. The exergy efficiency was initially low in all the cases but increased to 80 % towards the end of thedrying process.

Ultrasonic modified corn pith for the sequestration of dye from aqueous solution

R. Jothirani,P. Senthil Kumar,A. Saravanan,Abishek S. Narayan,Abhishek Dutta 한국공업화학회 2016 Journal of Industrial and Engineering Chemistry Vol.39 No.-

In this research, the ultrasonic waves were used to prepare the novel material from corn pith for theremoval of malachite green (MG) dye from aqueous solution. The prepared material was characterizedby BET, FTIR, SEM, TGA and XRD analyses. Adsorption system followed Freundlich and pseudo-first orderkinetic models. Langmuir monolayer capacity of the adsorbent was calculated as 488.3 mg g 1 whichwas higher as compared with other local materials. Adsorption thermodynamics was found to beexothermic and spontaneous. The adsorber was designed using Freundlich model. The novel materialshowed good adsorption capacity for sequestration of MG dye from wastewater.

Performance Analysis of a Novel Reduced Switch Cascaded Multilevel Inverter

R. Nagarajan,M. Saravanan 전력전자학회 2014 JOURNAL OF POWER ELECTRONICS Vol.14 No.1

Multilevel inverters have been widely used for high-voltage and high-power applications. Their performance is greatly superior to that of conventional two-level inverters due to their reduced total harmonic distortion (THD), lower switch ratings, lower electromagnetic interference, and higher dc link voltages. However, they have some disadvantages such as an increased number of components, a complex pulse width modulation control method, and a voltage-balancing problem. In this paper, a novel nine-level reduced switch cascaded multilevel inverter based on a multilevel DC link (MLDCL) inverter topology with reduced switching components is proposed to improve the multilevel inverter performance by compensating the above mentioned disadvantages. This topology requires fewer components when compared to diode clamped, flying capacitor and cascaded inverters and it requires fewer carrier signals and gate drives. Therefore, the overall cost and circuit complexity are greatly reduced. This paper presents modulation methods by a novel reference and multicarrier based PWM schemes for reduced switch cascaded multilevel inverters (RSCMLI). It also compares the performance of the proposed scheme with that of conventional cascaded multilevel inverters (CCMLI). Simulation results from MATLAB/SIMULINK are presented to verify the performance of the nine-level RSCMLI. Finally, a prototype of the nine-level RSCMLI topology is built and tested to show the performance of the inverter through experimental results.

Stabilization of Delayed Fuzzy Neutral-type Systems Under Intermittent Control

R. Vadivel,S. Saravanan,B. Unyong,P. Hammachukiattikul,Keum-ShikHong,Gyu M. Lee 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.3

This study is concerned about the stabilization for delayed fuzzy neutral-type system (DFNTS) with uncertain parameters under intermittent control. Firstly, by constructing the augmented Lyapunov-Krasovskii functional (LKF) about different time delays along with single and double auxillary function-based integral inequalities (SAFBII, and DAFBII, respectively), a new class of delay-dependent adequate conditions are proposed, so that the robust fuzzy neutral-type system under consideration is guaranteed to be globally asymptotically stable (GAS). Secondly, the intermittent control (IC) is introduced to stabilize the system with mixed time-varying delays. In the view of inferred adequate conditions, the IC parameters are determined as for the arrangement of linear matrix inequalities (LMIs). It is noted that the strategies exploited in this work are apart from the other methods engaged in the literature, and the proposed conditions are less conservative. Finally, numerical examples are given to demonstrate the effectiveness of the developed techniques in this work. One of the practical applications is single-link robot arm(SLRA) model to show the viability and benefits of the structured intermittet control.

Analysis of Neural Network Approaches for Nonlinear Modeling of Switched Reluctance Motor Drive

Saravanan, P,Balaji, M,Balaji, Nagaraj K,Arumugam, R The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.8 No.1

This paper attempts to employ and investigate neural based approaches as interpolation tools for modeling of Switched Reluctance Motor (SRM) drive. Precise modeling of SRM is essential to analyse the performance of control strategies for variable speed drive application. In this work the suitability of Generalized Regression Neural Network (GRNN) and Extreme Learning Machine (ELM) in addition to conventional neural network are explored for improving the modeling accuracy of SRM. The neural structures are trained with the data obtained by modeling of SRM using Finite Element Analysis (FEA) and the trained neural network is incorporated in the model of SRM drive. The results signify the modeling accuracy with GRNN model. The closed loop drive simulation is performed in MATLAB/Simulink environment and the closeness of the results in comparison with the experimental prototype validates the modeling approach.