Emission reduction on ethanol–gasoline blend using cerium oxide nanoparticles as fuel additive

In this study, the effect of ethanol–gasoline blend with cerium oxide nanoparticles as additive on a Tata Nano twin–cylinder SI engine was investigated. In this work, the combustion, performance and emission tests were conducted. The experiment fuels were prepared using 99.9% pure ethanol and gasoline with cerium oxide nanoparticles. The volumetric percentages of ethanol–gasoline blends with cerium oxide nanoparticles additive are in the ratio of E30, E40 and E50. These represent the ratios of ethanol amount in the total blend and the rest of gasoline. Additionally, 100?mg, 150?mg and 200?mg cerium oxide nanoparticles additive are mixed to E30, E40 and E50, respectively. The venture of this investigation was to reformulate the fuel to utilize the cerium oxide nanoparticles with ethanol and gasoline blend to develop the fuel’s performance and to decrease the pollution from the engine. The experimental results expose an increase in brake thermal efficiency for the nanoparticles blends. In the emission test CO, CO₂, HC and NOx are noticeably reduced, and O₂ increased for all the blends. In combustion analyses, the cylinder pressure is higher for nanoparticles blends, when compared to that of the sole fuel.     

Optimization of Machining Parameters for Milling Operations Using Non-conventional Methods

In this paper, optimization procedures based on the genetic algorithm, tabu search, ant colony algorithm and particle swarm optimization Algorithm were developed for the optimization of machining parameters for milling operation. This paper describes development and utilization of an optimization system, which determines optimum machining parameters for milling operations. An objective function based on maximum profit in milling operation has been used. An example has been presented at the end of the paper to give a clear picture from the application of the system and its efficiency. The results are compared and analysed using the method of feasible directions and handbook recommendations.     

Evaluation of scatter-search approach for scheduling optimization of flexible manufacturing systems

This paper presents an automatic welding control system for the alternating current shield metal arc welding process. A nominal nonlinear mathematical model containing uncertainties such as dead-zone, welding control system saturation, and the identified system parameters is derived. A novel variable structure model reference control scheme is designed to modulate the rate of the electrode feed mechanism, thereby regulating the arc current. The developed controller assures the global reaching condition of the sliding mode of the controlled welding system. In the sliding mode, the electric current error between the plant and the model asymptotically approaches zero. Moreover, the welding system remains insensitive to uncertainties and disturbance as the systems with friction. The simulation and experimental results confirm that the automatic welding control system, based on the proposed model-following variable structure controller, successfully maintains the magnitude of the arc current at the desired value and preserves the stability of the arc length, thereby ensuring excellent welding performance.     

Tuning violet to green emission in luminomagnetic Dy,Er co-doped ZnO nanoparticles

This paper discusses the synthesis of undoped ZnO, 2?mol% Dy doped ZnO, 2?mol% Er doped ZnO and 1?mol% Dy,Er co-doped ZnO nanoparticles by simple combustion technique and the characterization of their structural, morphological, magnetic and optical properties by X-ray diffraction (XRD), X-Ray Photoelectron Spectroscopy(XPS), Field Emission Scanning Electron Microscope (FESEM), High Resolution Transmission Electron Microscope (HRTEM), Diffuse Reflectance Spectroscope (DRS), Vibrating Sample Magnetometer (VSM) and Photoluminescence(PL). All samples are of hexagonal wurzite type structure which was found from XRD analysis. The effects of annealing on morphology and luminescence emission wavelengths were noticed in FESEM and PL, respectively. As-prepared sample displayed spherical morphology and annealed co-doped sample showed interwoven hexagonal stacking like morphology. VSM revealed the room temperature ferromagnetism in doped samples. The photoluminescence under the UV and IR excitations was observed in experiment. The as-prepared samples had violet region emission at the 325?nm excitation. The annealed samples had green region emission under the same excitation. Due to the annealing effect, the enhancement of upconversion luminescence intensity in co-doped sample in green (535?nm) and red (665?nm) regions was observed at the 980?nm excitation.     

Effect of Process Parameters on Microstructure and Mechanical Properties of Al-11.5%Si-1%Mg/bimodal SiC(m–n)composites

Silicon - Bimodal size SiC particles reinforced Al-Si alloy composites were fabricated by powder metallurgy route. Three different bimodal reinforcements with various volume fractions of micro and...     

Finite-Time Stability of Stochastic Cohen–Grossberg Neural Networks with Markovian Jumping Parameters and Distributed Time-Varying Delays

In this paper, the finite-time stability problem is considered for a class of stochastic Cohen–Grossberg neural networks (CGNNs) with Markovian jumping parameters and distributed time-varying delays. Based on Lyapunov–Krasovskii functional and stability analysis theory, a linear matrix inequality approach is developed to derive sufficient conditions for guaranteeing the stability of the concerned system. It is shown that the addressed stochastic CGNNs with Markovian jumping and distributed time varying delays are finite-time stable. An illustrative example is provided to show the effectiveness of the developed results.     

Synthesis and characterization of poly (aniline-co-acrylonitrile) using organic benzoyl peroxide by inverted emulsion method

An inverted emulsion process was adopted to synthesize conducting copolymers of aniline and acrylonitrile using benzoyl peroxide (BPO) as a novel oxidizing agent. The influence of polyacrylonitrile (PAN) ratio on the properties of conducting copolymers is reported. The chemical structures of the copolymers were characterized spectroscopically by UV-Vis, FT-IR, FT-Raman and EPR. The solubility of polyaniline (PAni) and PAni–PAN copolymers in dimethyl sulphoxide (DMSO) was confirmed by electronic absorption spectra. The conductivity of these copolymers lie in the range (1.26–4.20)×10⁻² S/cm. TGA thermogram of copolymers showed multi-step thermal degradation behaviour. X-ray scattering studies reflected that the copolymers are semicrystalline and showed two crystalline peaks at 17 and 25 (2θ).     

Evolutionary collision-free optimal trajectory planning for intelligent robots

This paper presents optimization procedures based on evolutionary algorithms such as the elitist non-dominated sorting genetic algorithm (NSGA-II) and differential evolution (DE) for solving the trajectory planning problem of intelligent robot manipulators with the prevalence of fixed, moving, and oscillating obstacles. The aim is the minimization of a combined objective function, with the constraints being actuator constraints, joint limits, and the obstacle avoidance constraint by considering dynamic equations of motion. Trajectories are defined by B-spline functions. This is a non-linear constrained optimization problem with six objective functions, 31 constraints, and 42 variables. The combined objective function is a weighted balance of transfer time, the mean average of actuator efforts and power, penalty for collision-free motion, singularity avoidance, joint jerks, and joint accelerations. The obstacles are present in the workspace of the robot. The distance between potentially colliding parts is expressed as obstacle avoidance. Further, the motion is represented using translational and rotational matrices. The proposed optimization techniques are explained by applying them to an industrial robot (PUMA 560 robot). Also, the results obtained from NSGA-II and DE are compared and analyzed. This is the first research work which considers all the decision criteria for the trajectory planning of industrial robots with obstacle avoidance. A comprehensive user-friendly general-purpose software package has been developed using VC++ to obtain the optimal solutions using the proposed DE algorithm.