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Surface integrity of ball burnished bioresorbable magnesium alloy

Advances in Manufacturing 2023年第2期11卷 342-362页

作者： G.V.Jagadeesh srinivasu gangi setti Department of Mechanical Engineering National Institute of Technology RaipurChhattisgarh492010India

Magnesium alloys are potential biodegradable and biocompatible implant materials because of their excellent biological properties. Recently, interest in these alloys as a promising alternative for temporary orthopedic implants has grown owing to their desirable biological, mechanical, and physical properties. However, the application of magnesium alloys is hindered by their rapid degradation and low corrosion resistance in physiological fluids, leading to the failure of implants. Thus, the current challenge is to enhance the corrosion resistance and control the degradation rate of magnesium under physiological conditions. The rapid degradation of magnesium alloys can be controlled by improving their surface integrity, such as surface roughness and microhardness. The present study aims to improve the surface integrity of the Mg Ze41A alloy by the ball burnishing technique. The surface roughness improved by 94.90% from 0.941 μm to 0.048 μm with a burnishing force of 50 N, burnishing speed of 1 300 r/min, burnishing feed of 130 mm/min, and three passes. Similarly, the microhardness improved by 50.62% from 75.2 HV to 113.27 HV with a burnishing force of 60 N, burnishing speed of 1 100 r/min, burnishing feed of 100 mm/min, and five passes. The variations in microhardness, which were observed up to 400 μm beneath the surface, exhibited a linear nature. These variations may be attributed to the movement of dislocations, formation of new dislocations, nanocrystal structures, metastable phases and subgrains, and lattice distortion or grain refinement. The surface features obtained from optical images demonstrated the fundamental mechanisms involved in the ball burnishing process. The concept of burnishing maps and zones will assist in the design of the ball burnishing parameters of a material with an equivalent yield strength of 140 MPa. The significant improvement in the surface integrity of the Mg Ze41A alloy by the ball burnishing technique is expected to improve its func

关键词： Magnesium alloy Bioresorbable Orthopedic implants Surface integrity Ball burnishing

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Artificial neural network approach for prediction of stress–strain curve of near b titanium alloy

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Rare Metals 2014年第3期33卷 249-257页

作者： srinivasu gangi setti R.N.Rao Mechanical Engineering National Institute of Technology

In the present study, artificial neural network（ANN） approach was used to predict the stress-strain curve of near beta titanium alloy as a function of volume fractions of a and b. This approach is to develop the best possible combination or neural network（NN） to predict the stress-strain curve. In order to achieve this, three different NN architectures（feed-forward back-propagation network,cascade-forward back-propagation network, and layer recurrent network）, three different transfer functions（purelin, Log-Sigmoid, and Tan-Sigmoid）, number of hidden layers（1 and 2）, number of neurons in the hidden layer（s）,and different training algorithms were employed. ANN training modules, the load in terms of strain, and volume fraction of a are the inputs and the stress as an *** system was trained using the prepared training set（a,16 % a, 40 % a, and b stress-strain curves）. After training process, test data were used to check system accuracy. It is observed that feed-forward back-propagation network is the fastest, and Log-Sigmoid transfer function is giving the best results. Finally, layer recurrent NN with a single hidden layer consists of 11 neurons, and Log-Sigmoid transfer function using trainlm as training algorithm is giving good result, and average relative error is1.27 ± 1.45 %. In two hidden layers, layer recurrent NN consists of 7 neurons in each hidden layer with trainrp as the training algorithm having the transfer function of LogSigmoid which gives better results. As a result, the NN is founded successful for the prediction of stress-strain curve of near b titanium alloy.

关键词： Artificial neural network (ANN) Stressstrain curve Titanium alloys

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Experimental investigation and prediction of tribological behavior of unidirectional short castor oil fiber reinforced epoxy composites

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Friction 2021年第2期9卷 250-272页

作者： Rajesh EGALA G V JAGADEESH srinivasu gangi setti Department of Mechanical Engineering National Institute of Technology RaipurChhattisgarh 492010India Department of Mechanical Engineering Gudlavalleru Engineering CollegeGudlavalleruAndhra Pradesh 521356India

The present study aims at introducing a newly developed natural fiber called castor oil fiber,termed ricinus communis,as a possible reinforcement in *** short castor oil fiber reinforced epoxy resin composites of different fiber lengths with 40%volume fraction were fabricated using hand layup *** sliding wear tests were performed on a pin-on-disc tribometer based on full factorial design of experiments(DoE)at four fiber lengths(5,10,15,and 20 mm),three normal loads(15,30,and 45 N),and three sliding distances(1,000,2,000,and 3,000 m).The effect of individual parameters on the amount of wear,interfacial temperature,and coefficient of friction was studied using analysis of variance(ANOVA).The composite with 5 mm fiber length provided the best tribological properties than 10,15,and 20 mm fiber length *** worn surfaces were analyzed under scanning electron ***,the tribological behavior of the composites was predicted using regression,artificial neural network(ANN)-single hidden layer,and ANN-multi hidden layer *** confirmatory test results show the reliability of predicted *** with multi hidden layers are found to predict the tribological performance accurately and then followed by ANN with single hidden layer and regression model.

关键词： natural fiber castor oil fiber epoxy composite full factorial design of experiments(DoE) analysis of variance(ANOVA) prediction regression artificial neural network(ANN)

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Novel design and composition optimization of self-lubricating functionally graded cemented tungsten carbide cutting tool material for dry machining

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Advances in Manufacturing 2021年第1期9卷 34-46页

作者： Rityuj Singh Parihar Raj Kumar Sahu srinivasu gangi setti Department of Mechanical Engineering National Institute of Technology RaipurRaipurIndia

The functionally graded cemented tungsten carbide (FGCC) is a suitable material choice for cutting tool applications due to balanced hardness and fracture *** presence of cobalt and CaF2 composition gradient in FGCC may enhance mechanical as well as antifriction ***,structural design of selflubricating FGCC was proposed using Power law composition gradient model and thermal residual stresses (TRSs) as a key ***,*** and *** model was adopted for estimation of TRS,and optimum composition gradient was identified at Power law exponent n =*** designed material displayed compressive and tensile TRS at surface and core respectively;subsequently fabricated by spark plasma sintering and characterized via scanning electron microscope (SEM),indentation *** agreement between experimental and analytical values of TRS demonstrated the effectiveness of intended design model in the composition optimization of self-lubricating *** work will be helpful in implementation of dry machining for clean and green manufacturing.

关键词： Functionally graded cemented tungsten carbide(FGCC) Thermal residual stress(TRS) Solid lubricant Power law

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Finite Element Modeling of Stress Strain Curve and Micro Stress and Micro Strain Distributions of Titanium Alloys— A Review

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Journal of Minerals and Materials Characterization and Engineering 2012年第10期11卷 953-960页

作者： gangi setti srinivasu Narasimha Rao Raja Department Mechanical Engineering National Institute of Technology Warangal India

Most of the alloys like titanium, steel, brass, copper, etc., are used in engineering applications like automobile, aero- space, marine etc., consist of two or more phases. If a material consists of two or more phases or components it is very difficult to predict the properties like mechanical and other properties based on simple laws such as rule of mixtures. Titanium alloys are capable of producing different microstructures when it subjected to heat treatments, so much of money and time are squandering to study the effect of microstructure on mechanical properties of titanium alloys. This squandering can be reduced with the help of modeling and optimization techniques. There are many modeling tech- niques like Finite element method, Mat lab, Mathematical modeling etc. are available. But Finite element method is widely used for prediction because of capable of producing distributions of stresses and strains at any different loads. From the literature it is observed that there is a good agreement between the calculated and measured stress strain curves. This review paper describes the effect of volume fraction and grain size of alpha phase on the stress strain curve of the titanium alloys. It also can predict the effect of strength ratio on stress strain curve by using FEM. This informa- tion will be of great use in designing and selecting the titanium alloys for various engineering applications.

关键词： Titanium Alloys Finite Element Modeling Stress-Strain Curve

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