Showing papers in "Journal of The Brazilian Society of Mechanical Sciences and Engineering in 2017"

Buckling analysis of nonlocal third-order shear deformable functionally graded piezoelectric nanobeams embedded in elastic medium

Abstract: This paper investigates buckling response of higher-order shear deformable nanobeams made of functionally graded piezoelectric (FGP) materials embedded in an elastic foundation. Material properties of FGP nanobeam change continuously in thickness direction based on power-law model. To capture small size effects, Eringen’s nonlocal elasticity theory is adopted. Employing Hamilton’s principle, the nonlocal governing equations of FGP nanobeams embedded in elastic foundation are obtained. To predict buckling behavior of embedded FGP nanobeams, the Navier-type analytical solution is applied to solve the governing equations. Numerical results demonstrate the influences of various parameters such as elastic foundation, external electric voltage, power-law index, nonlocal parameter and slenderness ratio on the buckling loads of size-dependent FGP nanobeams.

Modeling of the air conditions effects on the power and fuel consumption of the SI engine using neural networks and regression

Abstract: Engine performance varies significantly due to the variations in weather conditions in different regions. So, in order to optimize the performance and fuel consumption, engines should be calibrated according to the weather conditions in which they operate. In this paper the effects of the air conditions (such as pressure and temperature) on the power and fuel consumption of the SI engine are modeled. First a comprehensive one-dimensional model of the real engine is constructed in GT POWER®, and validated with experimental data from actual engine. Next, using this model, a set of experiments is carried out by varying pressure, temperature, and humidity of the incoming air, and engine speed. The measuring outputs are the power and BSFC of the engine. Then, two mathematical models are developed using MLP Neural Networks and also regression technique to estimate the outputs in terms of the inputs. At last, the estimation ability of the models is shown by a set of new experiments. These models could be used in engine calibration and shift the process from a near blind one to the one in which prior information have a significant role.

Magnetohydrodynamic micropolar nanofluid past a permeable stretching/shrinking sheet with Newtonian heating

Abstract: In this present study, a numerical investigation has been carried out to discuss the steady, two dimensional flow and heat transfer on micropolar nanofluid over a stretching/shrinking sheet with variable suction or injection in the presence of magnetic field and Newtonian heating. Copper ( $$ {\text{Cu}} $$ ), alumina ( $$ {\text{Al}}_{ 2} {\text{O}}_{ 3} $$ ) and titanium ( $$ {\text{TiO}}_{ 2} $$ ) in water-based micropolar nanofluid has been considered for the present investigation. The solutions of the transformed nonlinear equations have been obtained using Runge–Kutta–Gill procedure together with the shooting method. The results are presented graphically and discussed for various resulting parameters. Dual solutions are found to exist in a certain range of the governing parameters. The thickness of thermal boundary layer for Cu nanofluid is more than that of other nanofluids in the cases of shrinking and stretching sheets. Newtonian heating effect significantly increases the thermal boundary layer thickness for both sheets under investigation.

Thermophysical aspects of stagnation point magnetonanofluid flow yields by an inclined stretching cylindrical surface: a non-Newtonian fluid model

Abstract: In various attempts, researchers considered Eyring–Powell fluid flow past a flat stretching surface supported with different physical effects, but as yet few explorations are proposed with accuracy regarding cylindrical stretching surface. In this work, we have considered magnetohydrodynamic Eyring–Powell nanofluid flow brought by an included stretching cylindrical surface under the region of stagnation point. To report thermophysical aspects, Joule heating, thermal radiations, mixed convection, temperature stratification, and heat generation effects are taken into account. The flow conducting differential equations are fairly converted into system of coupled non-linear ordinary differential equations by means of appropriate transformation. A numerical communication is made against these obtained coupled equations through shooting method supported with fifth-order Runge–Kutta scheme. It is found that fluid temperature shows an inciting nature towards Eckert number, thermophoresis parameter, Brownian motion parameter, thermal radiation parameter, and heat generation parameter, but it reflects opposite trends for Lewis number and thermal stratification parameter. Furthermore, the obtained results are validated by providing comparison with existing values which set a benchmark of quality of computational algorithm.

Investigation on performance, emission and combustion characteristics of variable compression engine fuelled with diesel, waste plastics oil blends

Abstract: Presently plastics are major contributors in solid waste which has higher thermal energy. Waste plastics can be converted into alternate fuel by pyrolysis which can replace diesel in compression ignition engines. The present study deals with the performance, combustion and emission characteristics of variable compression ratio engine fuelled with plastic oil, diesel and its blends with diethyl ether as an additive. Three blends 2.5, 7.5 and 12.5 % were tested in variable compression ratio engine. Waste plastic oil blend, pure plastic oil and diesel were considered for comparison. This study reveals that brake thermal efficiency increases for all the blends when compression ratio increases from 12 to 20. The specific fuel consumption of the blends and plastic oil were higher than the diesel. But the brake thermal efficiency for all the blends, plastic oil was comparatively lower than that of diesel. The regulated emissions of the variable compression ratio engine under varying loads and compression ratio for different blends were discussed.

Investigation of cutting parameters affecting on tool wear and surface roughness in dry turning of Ti-6Al-4V using CVD and PVD coated tools

Abstract: There are some problems in the machining of titanium alloys with excellent properties such as high strength, good corrosion resistance, long service life and low weight. The leading problem appears to be the fast tool wear and the bad machining surface. Therefore, in this study, it was investigated whether cutting parameters have effect on tool wear and surface roughness by turning under dry cutting condition of Ti-6Al-4V alloy with excellent properties. CVD (TiCN + Al2O3 + TiN) and PVD (TiAlN) coated WC tools were used in the experiments. Then the Ti-6Al-4V alloy turned with the combinations of the different cutting speed, feed rate, cutting long and depth of cut. We observed that the tools wear in both CVD and PVD coated WC tools increased with increasing the cutting speed, feed rate, depth of cut and cutting length. However, while tools wear increased with increasing cutting speed, the surface roughness reduced to an optimum level. Especially, the surface roughness was worsened above the optimum level changing with increasing the feed rate, cutting length and depth of cut. The tool wear with PVD coated WC tools was observed to be less than the CVD coated WC tools. However, the values of the surface roughness obtained with PVD coated WC tools with increase in depth of cut, feed rate and cutting length has given us higher values when compared to CVD coated WC tools.

Risk quantification combining geostatistical realizations and discretized Latin Hypercube

Abstract: This work presents an alternative way to combine different types of uncertainty to quantify risk in petroleum field development. Risk quantification is key in decision analysis. Some areas need special attention, namely: (1) generating simulated scenarios compatible with geological models and (2) statistical techniques that address different types of uncertainty (especially continuous and discrete attributes, and realizations represented by geostatistical images) using the fewest possible simulation runs. Several statistical techniques address this, but most present significant drawbacks, potentially yielding incorrect risk quantification or demanding excessive time (for simulation runs) to reach good results. This simple, efficient methodology combines geostatistical realizations with other types of uncertainty (e.g., reservoir structure, fluid characterization and economic parameters) using a Discretized Latin Hypercube sampling. To verify the results, we applied the methodology to the UNISIM-I-D benchmark case showing that the method can be applied to a complex case yielding good results. We found the methodology to meet our initial objectives, to reliably and easily quantify risk within a minimal timeframe.

MHD forced convection and entropy generation of CuO-water nanofluid in a microchannel considering slip velocity and temperature jump

Abstract: Flow field, heat transfer and entropy generation of forced convection of CuO-water nanofluid is investigated in a parallel plate microchannel in the presence of magnetic field. Two vertical micromixers are attached on the hot walls of the microchannel. To consider the effect of the Brownian motion of the nanoparticles, the KKL model is utilized to estimate thermal conductivity of the nanofluid. The governing equations, which are accompanied with the slip velocity and temperature jump boundary conditions, are solved by the finite volume method (FVM) and SIMPLER algorithm. The study is conducted for the Reynolds numbers in the range of 10 < Re < 100, Hartmann numbers in the range of 0 < Ha < 40, Knudsen numbers ranging of 0 < Kn < 0.1 and volume fraction of nanoparticles ranging of 0 < φ < 0.04. The results show that when the Hartmann or Reynolds numbers, or the volume fraction of nanoparticles increase, the average Nusselt number and the total entropy generation rate increase. Furthermore, when Knudsen number increases, the total entropy generation rate decreases.

Thermocycling effect on mechanical and tribological characterization of two indirect dental restorative materials

Abstract: The purpose of this study is to evaluate the effects of aging by thermocycling on the mechanical and tribological properties of two indirect filling commercial resin-based restorative composite materials. The studied composites are referenced by the capital letters: A and B. The commercial trade names are omitted, to avoid commercial references. Forty specimens of each material were produced and divided into three groups: a control group not subjected to aging, and two groups, T1 and T2 submitted to different thermocycling conditions. The studied properties were surface roughness, elastic modulus (determined dynamically by impulse excitation of vibration, and statically by four-point bending test), flexural strength and work of fracture (four-point bending test), micro-hardness (Vickers micro-indentation) and coefficient of friction (scratch test). From this study, it was possible to conclude that Composite A, in addition to having better mechanical properties, is less affected by thermocycling than Composite B, which suggests that it will better withstand the stresses, both mechanical and thermal, which it is subjected to. It is also possible to infer that the thermocycling regimen proposed by Standard ISO 11405 (Dental materials—testing of adhesion to tooth structure, 2003) is not sufficient to adequately simulate the degradation caused by the oral environment on current commercial resin-based restorative composites.

Bending and shearing responses for dynamic analysis of single-layer graphene sheets under moving load

Abstract: In this paper, the size-dependent effects on the time-dependent bending and shearing responses of single-layer graphene sheets (SLGSs) induced by displacement of the concentrated moving load along the SLGSs are studied. Hence, the equations of motion are derived by applying two-variable refined plate theory in conjunction with the nonlocal elasticity theory via Hamilton’s principle. The two independent unknowns denoting the dynamic behaviour of plates are defined by the developing state-space method for this case, and Navier-solution method is employed to obtain the bending and shearing deflections due to the variation of velocity and time. The primary results for free and forced vibrations of nanoplates are approved by existing literature to illustrate the correctness of the present formulation and solution methods. Next, a solution including both the bending and shearing dynamic deflections of SLGSs under the moving load is derived for the first time in this research. Moreover, the roles of different parameters such as load velocity, length-to-thickness ratio, and small-scale effects on the dynamic deflections of SLGSs are addressed and discussed.

Chemically reactive flow of upper-convected Maxwell fluid with Cattaneo–Christov heat flux model

Abstract: This attempt concentrates on impact of chemically reactive flow of upper-convected Maxwell liquid Nonlinear slip condition for Maxwell fluid is employed The processes of heat and mass transfer through theory of Cattaneo–Christov flux are studied Ordinary differential systems have been considered Convergent solutions are constructed for the governing equations Incoming nonlinear modeled problems have been computed for the velocity, temperature and concentration The impact of emerging variables, namely Deborah number (β), Schmidt number (Sc), Thermal relaxation parameter (γ), Prandtl number (Pr) and chemical reaction parameter (δ) on quantities of interest is graphically investigated Both temperature and concentration fields decay when thermal relaxation and chemical reaction parameters are increased

Efficient fault diagnosis of ball bearing using ReliefF and Random Forest classifier

Abstract: The present study focuses on identifying various faults present in ball bearing from the measured vibration signal. Features such as kurtosis, skewness, mean, and root mean square, and complexity measure such as Shannon Entropy are calculated from time domain and Discrete Wavelet Transform. To select the best wavelet function, Maximum Energy to Shannon Entropy ratio criterion is used. Information Gain and ReliefF ranking methods are used to assess the quality of features and features are ranked based on the weight gain obtained from the methods used. Support Vector Machine and Random Forest classifier are selected to identify bearing faults and comparison is made to diagnose faults on the ranked feature set. Experiments are conducted on Case Western Reserve University bearing data sets. Results show that ranking method is useful for identifying best feature set and to improve classification accuracy simultaneously. Cross-validation efficiency of 98.38% is obtained when ReliefF is used with Random Forest.

Machining performance optimization for electro-discharge machining of Inconel 601, 625, 718 and 825: an integrated optimization route combining satisfaction function, fuzzy inference system and Taguchi approach

Abstract: Nickel-based super alloy (such as Inconel) is widely used in aerospace, nuclear, and chemical industries because of its excellent mechanical and chemical properties at elevated temperatures. Inconel comes under the category of “difficult-to-cut” materials. Difficulty is faced whilst machining of Inconel because of its poor thermal conductivity, high toughness, high hardness, and extremely high work hardening behaviour. Moreover, it contains highly abrasive carbide particles which tend to stick on the tool surface, resulting in inferior surface finish. Moreover, enormous heat is generated during machining which leads to reduction in tool life. Hence, machining and machinability aspects of Inconel have become a predominant research agenda today. Technological advances have led to an extensive usage of high strength, high hardness materials in manufacturing industries. In course of machining of “difficult-to-cut” materials, conventional manufacturing processes are increasingly being replaced by the advanced techniques such as electro-discharge machining (EDM), ultrasonic machining, electro-chemical machining and laser machining. Amongst these, EDM has found widespread application in micro-electro-mechanical systems; tool and die, automobile and aerospace industries. Therefore, promoting the quality of the EDMed product and thereby achieving satisfactory machining performance; a thorough understanding of the relationship between the EDM parameters and the machined surface integrity in consideration with the tool-work combination has become an important research focus. EDM is an electro-thermal machining process, where electrical energy is used to generate electrical spark and material removal mainly occurs due to thermal energy of the spark. It has become an excellent option to machine “difficult-to-cut” materials and high temperature resistant alloys; super alloy Inconel, in the present case. An experimental investigation on assessing machining performance during EDM of Inconel 625, 718, 601 and 825 has been delineated herein. Attempt has been made on evaluating optimal machining parameters setting to achieve satisfactory machining yield. Based on 5-factor-4-level L16 orthogonal array, experiments have been carried out by varying gap voltage, peak current, pulse-on time, duty factor and flushing pressure (each varied at four discrete levels) to examine the extent of machining performance in terms of material removal rate, electrode wear rate, surface roughness, and surface crack density of EDMed end products obtained by utilizing different parameters settings (for Inconel of different grades, respectively). An integrated optimization route combining satisfaction function approach, fuzzy inference system in conjugation with Taguchi’s philosophy has been proposed for simultaneous optimization of aforementioned multiple performance indices. The most favourable machining parameters setting have been obtained as: [gap voltage = 90 V, peak current = 5 A, pulse-on time = 200 µs, duty factor = 70%, flushing pressure = 0.6 bar] for Inconel 625; [gap voltage = 90 V, peak current = 5 A, pulse-on time = 200 µs, duty factor = 85%, flushing pressure = 0.4 bar] for Inconel 718; [gap voltage = 80 V, peak current = 7 A, pulse-on time = 500 µs, duty factor = 80%, flushing pressure = 0.3 bar] for Inconel 601; and [gap voltage = 80 V, peak current = 5 A, pulse-on time = 300 µs, duty factor = 85%, flushing pressure = 0.4 bar] for Inconel 825. In addition to that, analysis of SEM micro-graphs has been carried out to understand surface irregularities in terms of surface cracks, white layer for EDMed Inconel end products (of different grades).

Effects of EGR rate on performance and emissions of a diesel power generator fueled by B7

Abstract: This paper analyses the impacts of the application of an exhaust gas recirculation (EGR) system on the performance and emissions of a stationary, direct-injection diesel engine operating with diesel oil containing 7% biodiesel (B7). Experiments were carried out in a 49-kW diesel power generator with the adapted EGR system, and engine performance and emissions were evaluated for different load and EGR settings. The results were compared with the engine operating with its original configuration without the EGR system, and revealed a reduction of peak cylinder pressure and fuel conversion efficiency, mainly at high engine loads. The use of EGR caused opposite effects on carbon dioxide (CO2), carbon monoxide (CO) and total hydrocarbons (THC) emissions, depending on load and EGR rate, showing an increase in most situations. The application of EGR consistently reduced oxides of nitrogen (NOX) emissions, reaching a maximum reduction close to 30%. In general, the use of EGR increased CO2, CO and THC emissions at high loads. The use of 7.5% EGR was found to be at an adequate rate to simultaneously reduce CO, THC and NOX emissions at low and moderate loads, without major penalties on CO2 emissions and engine performance.

MHD boundary layer flow and heat transfer of micropolar fluid past a stretching sheet with second order slip

Abstract: The intention of this article is to examine a second order slip flow and magnetic field on boundary layer flow of micropolar fluid past a stretching sheet. Employing appropriate similarly transformation and non-dimensional variables, the governing non-linear boundary-value problems were reduced into coupled higher order non-linear ordinary differential equation. Then, solution for velocity, microrotation and temperature has been obtained numerically. The equations were numerically solved using the function bvp4c from the matlab for different values of governing parameters. Numerical results have been discussed for non-dimensional velocity, temperature, microrotation, the skin friction coefficient and local Nusselt number. The results indicate that the skin friction coefficient $$ C_{\text {f}}$$ increases as the values of slip parameter $$\gamma $$ increase. However, the local Nusselt number $$-\theta '(0)$$ decreases as both slip parameter $$\gamma $$ and $$\delta $$ increase. A comparison with previous studies available in the literature has been done and an excellent agreement is obtained.

Estimation of surface roughness using cutting parameters, force, sound, and vibration in turning of Inconel 718

Abstract: The present work is aimed at in-process estimation of surface roughness using cutting parameters along with cutting force, sound, and vibration in turning of Inconel 718 with cryogenically treated and untreated carbide inserts Initially, prediction models are developed by regression analysis using only cutting parameters and then using only force, sound, and vibration Later on, these models are modified to include all the parameters after performing correlation analysis for determining significant parameters The modified models are developed using only significant parameters from the cutting parameters and measured responses The prediction results of modified regression models are compared with experimental results and fine association of fit between measured and estimated surface roughness is confirmed Based on coefficient of determination (R 2) values, the regression models are found to be better for estimating surface roughness Finally, it is found that modified regression models are estimating surface roughness with more than 90% accuracy which can be said as acceptable for the two types of inserts used Use of sound emitted while machining along with values of cutting parameters, force, and vibration to predict surface roughness has not been reported earlier particularly for Inconel 718 As cutting force, sound, and vibration can be measured during the turning process, this method can be useful for real-time control of the process to get the desired surface roughness for machining of difficult to cut material like Inconel 718

Developing of ANN model for prediction of performance and emission characteristics of VCR engine with orange oil biodiesel blends

Abstract: Biodiesel is used as a valuable alternative to the conventional fossil fuel, as it is non-toxic, renewable and biodegradable resource. Engine parameters like compression ratio, injection timing and injection pressure play key role in the combustion of fuel. The present study focuses on ANN model for predicting the performance characteristics like brake thermal efficiency, brake specific fuel consumption and emission characteristics like carbon monoxide, oxides of nitrogen and hydrocarbon emissions at varying loads and compression ratios (17, 17.5, 18). Seven training algorithms each with four combinations of training functions were investigated. Levenberg–Marquardt (trainlm) with log and tan sigmoidal transfer function provided the best results amongst the other six training algorithms. It was found to be an accurate predicting model for analyzing the performance and emission characteristics VCR engine with biodiesel blends. In all compression ratios, 20 OME showed better thermal efficiency and reduced fuel consumption than diesel. Lower CO and HC emissions were observed with 20 OME than diesel except NOx.

Emerging application of nanoparticle-enriched cutting fluid in metal removal processes: a review

Abstract: In metal removal processes, the role of cooling and lubricating fluid is very crucial for improving the performance of machining. When metallic and non-metallic nanoparticles (less than 100 nm) are added to the base fluid, it is termed as a nanofluid. Due to excellent heat-carrying capacity, lubrication and rheological properties, nanofluids have gained immense importance for growing research activities. Researchers are also exploring synthesis and newer application of nanofluids. In the process, scientists are trying to develop new types of nano-cutting fluids, which are economic and eco-friendly. In this connection, investigations are also underway to find out possible mechanisms for improving cooling and lubricating properties of nanofluids. This paper presents a summary of published literature on the application of nano-enriched cutting fluid in various conventional metal removal processes, such as turning, milling, drilling and grinding. This paper also discusses the effects of different nano-enriched cutting fluids on various metal removal processes and factors influencing their process performance.

Influence of the process parameters on the surface roughness, micro-hardness, and residual stresses in slide burnishing of high-strength aluminum alloys

Abstract: It is well known that apart from compressive residual stresses, smooth surface and microstructuring of the surface and subsurface layers are beneficial for enhancement of fatigue strength and load-carrying capacity of structural and machine components. This complex of properties can be achieved using surface severe plastic deformation. For symmetric rotational components made of high-strength aluminum alloys, slide burnishing is appropriate because of its simplicity and easy realization. The effect of the process parameters on the surface roughness, micro-hardness, and residual stresses obtained in slide burnishing of D16T aircraft aluminum alloy has been analyzed. The optimal values of the basic governing factors, which ensure minimum roughness (up to $$0.05\,\upmu\,{\text{m}}$$ ), have been established on the basis of a one-factor-at-the-time method, followed by a planned experiment and additional experiments. With the established combination of optimal values, the effect of number of passes and lubricant-cooler on the roughness, micro-hardness, and residual stresses in the surface being treated has been studied for two working schemes. To establish residual stress–depth profiles depending on the tool radius and burnishing force, FEM analysis of the slide burnishing process has been conducted. Thus, an evaluation of the effectiveness of slide burnishing as “mixed burnishing” has been made.

Experimental investigations into the effects of SPIF forming conditions on surface roughness and formability by design of experiments

Abstract: Single point incremental forming (SPIF) is a sheet metal forming process used to obtain customized products with complex shapes. A hemispherical tool producing a series of local plastic deformations leads to increase in the formability of the final product. However, this forming technology still carries some drawbacks. The investigation of SPIF in terms of quality production and process optimization has always been a challenge to the researchers. An attempt has been made to study the effect of SPIF process parameters such as feed rate (f), step depth (p), tool diameter (d) and sheet thickness (t i) on surface roughness (R a) and maximum forming angle (O max) while forming of high strength AA5052-H32 alloy sheet. Response surface methodology (RSM) with the Box–Behnken design is used to develop a mathematical model in terms of the above parameters. An analysis of variance (ANOVA) test shows that step depth, tool diameter has a significant effect on the surface roughness and formability (P < 0.0001). The average surface roughness is found to increase with an increase in step depth and decrease in tool diameter, whereas the maximum forming angle is found to decrease with increase in step depth and tool diameter. The confirmation experiments are performed to check the adequacy of the proposed model.

Modelling and multiobjective optimization for productivity improvement in high speed milling of Ti–6Al–4V using RSM and GA

Abstract: Productivity can be improved in machining by achieving higher material removal rate (MRR) and better surface finish at lower power consumption along with higher tool life. Present work focuses on analyzing power consumption, material removal rate; surface roughness and tool wear in high speed milling of Ti–6Al–4V using response surface methodology. Models are developed with experimental data measured after performing face milling operation sequentially using design of experiments. Developed models are validated and reformed using Analysis of variance (ANOVA) and stepwise backward elimination method. Developed models showed correlation coefficient (R 2) more than 95% which means models can best explain the experimental data. Further, multiobjective optimization is performed to minimize power consumption; surface roughness and tool wear as well as to maximize MRR using response optimizer with desirability approach. Optimum process parameters obtained are: cutting speed = 133.5 m/min, feed rate = 0.14 mm/tooth and depth of cut = 2.33 mm. Validation of optimized results is done with three confirmation experiments at the optimum conditions and the responses are taken as average of the three confirmation experiments. Additionally, Pareto optimal points are found for conflicting objective functions using multiobjective genetic algorithm.

An electro-magneto-hydrodynamic flow Maxwell nanoliquid past a Riga plate: a numerical study

Abstract: The temperature-dependent heat source/sink in Maxwell nanoliquid flow towards a riga plate is investigated. In this model, we incorporated convective heat and mass boundary conditions. Similarity transformations are applied to convert the governing dimensional expressions into non-dimensional forms. Finite difference method along with Richardson extrapolation technique is utilized to elaborate the numerical solutions of physical phenomenon. Effects of different values of governing parameters on velocity, temperature and concentration profiles are evaluated via graphs. The quantities of interest like Nusselt and Sherwood numbers are discussed in detail through numerical data.

Application of particle swarm optimization and response surface methodology for machining parameters optimization of aluminium matrix composites in milling operation

Abstract: Face milling is extensively used machining operation to generate the various components. Usually the selection of the process parameters are incorporated by trial and error method, literature survey and the machining hand book. This kind of selection of process parameters turns out to be very tedious and time-consuming. In order to overcome this there is a need to develop a technique that could be able to find the optimal process parameters for the desired responses in machining. The present paper illustrates an application of response surface methodology (RSM) and particle swarm optimization (PSO) technique for optimizing the process parameters of milling and provides a comparison study among desirability and PSO techniques. The experimental investigations are carried out on metal matrix composite material AA6061-4.5%Cu-5%SiCp to study the effect of process parameters such as feed rate, spindle speed and depth of cut on the cutting force, surface roughness and power consumption. The process parameters are analyzed using RSM central composite face-centered design to study the relationship between the input and output responses. The interaction between the process parameters was identified using the multiple regression technique, which showed that spindle speed has major contribution on all the responses followed by feed rate and depth of cut. It has shown good prediction for all the responses. The optimized process parameters are acquired through multi-response optimization using the desirability approach and the PSO technique. The results obtained from PSO are closer to the values of the desirability function approach and achieved significant improvement.

Process optimization for maximizing bushing length in thermal drilling using integrated ANN-SA approach

Abstract: Thermal drilling is a new hole producing method in sheet material applications that uses the frictional heat generated at the intersection of workpiece and drilling tool with an intention of softening and subsequently, penetrating the hole. According to L27-Taguchi orthogonal array approach, the thermal drilling experiments were executed on galvanized steel which is engaged in boat yards construction and automobile body manufacture applications. All the way through experimentation of thermal drilling with the noteworthy process conditions like rotational speed (S), workpiece thickness (W t) as well as tool angle ( $$\alpha$$ ) were varied in different levels. Using the experimental outcomes, an appropriate artificial neural network technique (ANN) is established to develop bushing length model. Bushing length (B L) is considered as the most important output parameter in thermal drilling, since it is directly linked by tapping operation. Thus, the effects of thermal drilling input parameters on bushing length is studied since it is involved in fastening the galvanized steel by means of fasteners as required in numerous engineering problems. Furthermore, process optimization is established by means of simulated annealing (SA) algorithm approach under constraint boundaries with a view to maximization of bushing length. Besides, compare the optimal value of bushing length as predicted by SA algorithm with experimental bushing length value and this validates the development of thermal drilling on galvanized steel. An outstanding conformity has been detected between the predicted optimum and experimental value of bushing length.

Entropy generation analysis of radiative heat transfer effects on channel flow of two immiscible couple stress fluids

Abstract: An analysis is presented to investigate the effects of radiative heat transfer on entropy generation in flow of two immiscible non-Newtonian fluids between two horizontal parallel plates. Both the plates are maintained at constant temperatures higher than that of the fluid. The Stokes’ couple stress flow model is employed. The flow region consists of two zones with the flow of the heavier fluid taking place in the lower zone. The classical “no-slip” condition is prescribed at the plates and continuity of velocity, vorticity, shear stress, couple stress, temperature and heat flux are imposed at the interface. The original partial differential Navier–Stokes equations are converted to ordinary differential equations by assuming velocity and temperature are functions of vertical distance and solved mathematically by usual classical methods. The derived velocity and temperature profiles are used to compute the expressions for the entropy generation number and Bejan number. The effects of relevant parameters on velocity, temperature, entropy generation number and Bejan number are investigated. The computations show that the entropy production decreases with thermal radiation, whereas it increases with viscous dissipation. The effect of viscous dissipation is justified since it significantly affects heat transfer and entropy generation characteristics and therefore should not be ignored.

Performance analysis of an industrial system using soft computing based hybridized technique

Abstract: Due to imprecise information, it is always difficult for the system analyst to predict and enhance the performance of the system up to the desired degree of accuracy. Therefore, the main task is to reduce the uncertainty level for decision makers, so as to take a more sound decision in a reasonable time. For handling these issues, this paper addressed the various reliability parameters of the industrial system, which depicts the behavior of the system, by quantifying the uncertainties in the data in the form of fuzzy numbers. The corresponding membership functions of the system’s parameters are computed by formulating a nonlinear optimization model and solve it. The obtained results were compared with the existing as well as traditional methodology and results and found that they had less range of uncertainties during the analysis. A sensitivity as well as performance analysis has also been done for depicting the most critical component of the system. Finally, an approach has been illustrated through a case study of cattle feed plant, a repairable industrial system.

Formability of a wire arc deposited aluminium alloy

Abstract: This paper is focused on the formability of the aluminium alloy AA5083 deposited by wire arc additive manufacturing (WAAM). The presentation draws from metal deposition with a robotic welding system to mechanical and formability characterization by means of standard test specimens. Finite element analysis using porous metal plasticity is utilized to model strain hardening and the changes in porosity due to plastic deformation. Results show that the deposited aluminium alloy has excellent ductility and that its final stress response can significantly improve as a result of strain hardening. Voids resulting from metal deposition are closed by negative values of stress-triaxiality resulting from compression forming. The investigation is also a step towards understanding the potential of including intermediate forming operations in conventional wire arc additive manufacturing (WAAM), consisting of metal deposition and machining.

Numerically framing the impact of radiation on magnetonanoparticles for 3D Sisko fluid flow

Abstract: A numerical investigation is carried out to study the three-dimensional Sisko fluid flow in the presence of nonlinear thermal radiation and convective boundary conditions over a bidirectional stretching surface. In addition, the impact of newly suggested model for nanofluid is considered that requires nanoparticles volume fraction at the wall to be passively rather than strongly controlled. The numerical solutions for resulting flow, heat, and mass transfer have been computed utilizing the two different techniques, namely, the bvp4c function in Matlab and shooting method with Runge–Kutta–Fehlberg and Newton–Raphson methods. It is perceived that the temperature profile declines as the power-law index enhances. Furthermore, it is anticipated from the graphs that the concentration profile decays as the Brownian motion parameter rises, while the opposite behavior is observed for the thermophoresis parameter. In addition, these results are more prominent for shear-thinning fluids when compared with shear-thickening fluids. To see the validity of the numerical computations, we compare the results of the shooting technique with the bvp4c and perceived an excellent agreement. The numerical solutions obtained in the limiting cases have shown an admirable agreement with the existing literature

Numerical and experimental investigation on the camber performance of a non-pneumatic mechanical elastic wheel

Abstract: Tire safety is a pretty important performance for the vehicle. To overcome some disadvantages of the conventional pneumatic tire, a new non-pneumatic mechanical elastic wheel (ME-Wheel) is developed, and the camber performance of ME-Wheel is studied with numerical and experimental methods. A nonlinear three-dimensional finite element model of the ME-Wheel, which includes material nonlinearities, large deformation and the anisotropy of rubber–cord composites, is established. The rubber components of the ME-Wheel are analyzed by Moony–Rivlin model. With a vertical test rig, static loading tests are performed to validate the accuracy and reliability of the finite element model. Experiments and simulations under the static and rolling conditions are conducted to study the influence of different camber angles on the vertical stiffness, wheel deformation, contact pressure distribution and wheel force at the interface. The simulation results and the test results are compared and discussed in detail. The results show that the proposed method is useful for the investigation of mechanical characteristics of ME-Wheel and the later optimal design.

Numerical study for MHD stagnation-point flow of a micropolar nanofluid towards a stretching sheet

Abstract: In this paper, we investigated the magnetohydrodynamic (MHD) stagnation-point flow of micropolar nanofluid over a stretching sheet. A uniform magnetic field is applied normal to the flow. Nonlinear micropolar nanofluid problem in the presence of the strong concentration of microelements is modeled and then solved by numerical techniques. A parametric study of the involved parameters in the presence of spin gradient viscosity is conducted, and representative set of numerical results is illustrated in the graphical and tabular forms. The complete formulation of the Keller-box method for the considered flow problem is given, and a comparison of the obtained results is performed with the previous published results. The comparison shows that our present results have an excellent match with the previous results in a limiting case. We found that the non-dimensional temperature and its associated thermal boundary layer thickness are enhanced when we use the larger values of thermophoresis and Brownian motion parameter. The non-dimensional concentration is higher for larger thermophoresis parameter but smaller for higher Brownian motion parameter. It is also observed that the smaller values of Lewis number correspond to higher non-dimensional concentration and its associated boundary layer thickness.