Microstructure and properties of flame sprayed tungsten carbide coatings

This article reports on feasibility experiments carried out with oxy-acetylene spray system with various oxygen to fuel ratios using two different tungsten carbide powders and powder feeding methods, to evaluate the newly developed fused WC, synthesised by transferred arc thermal plasma method. Transferred arc thermal plasma method is more economical and less energy intensive than the conventional arc method and results in a fused carbide powder with higher hardness. The microstructure and phase composition of powders and coatings were analysed by optical and scanning electron microscopy, energy dispersive spectroscopy and X-ray diffraction. Carbon content of the powders and coatings were determined to study the decarburisation of the material during spraying process. Coatings were also characterised by their hardness and abrasive wear. The effects of metallurgical transformation and phase content are related to wear performance. The results demonstrate that the powders exhibit various degree of phase transformation during the spray process depending on the type of powder, powder feeding and spray parameters. The carbon loss during the spray process in excess of 45% resulted in reduced hardness and wear resistance of the coatings. Coatings with high amount of WC and W₂C along with FeW₃C showed higher wear resistance. Thus, coatings of high wear resistance can be produced using fused tungsten carbide powder with WC and W₂C phases, which can be economically synthesised by thermal plasma transferred arc method.     

Casting/mold thermal contact heat transfer during solidification of Al-Cu-Si alloy (LM 21) plates in thick and thin molds

Heat flow at the casting/mold interface was assessed and studied during solidification of Al-Cu-Si (LM 21) alloy in preheated cast iron molds of two different thicknesses, coated with graphite and alumina based dressings. The casting and the mold were instrumented with thermocouples connected to a computer controlled temperature data acquisition system. The thermal history at nodal locations in the mold and casting obtained during experimentation was used to estimate the heat flux by solving the one-dimensional inverse heat conduction problem. The cooling rate and solidification time were measured using the computer-aided cooling curve analysis data. The estimated heat flux transients showed a peak due to the formation of a stable solid shell, which has a higher thermal conductivity compared with the liquid metal in contact with the mold wall prior to the occurrence of the peak. The high values of heat flux transients obtained with thin molds were attributed to mold distortion due to thermal stresses. For thin molds, assumption of Newtonian heating yielded reliable interfacial heat transfer coefficients as compared with one-dimensional inverse modeling. The time of occurrence of peak heat flux increased with a decrease in the mold wall thickness and increase in the casting thickness.     

Hydrogen effects on the passive film formation and pitting susceptibility of nitrogen containing type 316L stainless steels

The effects of hydrogen on the passivity and pitting susceptibility of type 316L stainless steels have been investigated with alloys containing different nitrogen contents (0.015, 0.198 and 0.556 wt.% N). The study revealed that electrochemically pre-charged hydrogen significantly reduced the pitting resistance of alloys conatining 0.015 and 0.198 wt.% nitrogen contents. In alloy with highest nitrogen content (0.556 wt.% N), an increase in the passive film current density with hydrogen was observed without affecting breakdown potential. Auger electron spectroscopy (AES) analysis of the passive film indicated the presence of nitrogen in the passive film. On other hand, for hydrogen charged samples, nitrogen was found to be significantly less in the passive film. In Electrochemical impedance spectroscopy (EIS) measurement, the decrease in semi-circle radius of Nyquist plot, and the polarization resistance, R_P associated with the resistance of the passive film was observed with hydrogen, indicating that hydrogen decreased the stability of the passive film. The present investigation indicated that precharged hydrogen deteriorated the passive film stability and pitting corrosion resistance in these alloys, and the increase in nitrogen content of the alloy offsets the deleterious effect of precharged hydrogen.     

Studies on the hot corrosion of a nickel-base superalloy,Udimet 700

The hot corrosion of a nickel-base superalloy, Udimet 700, has been studied in the temperature range 900–950°C. The effect of the amount of Na ₂SO₄ on the corrosion kinetics was determined. Large weight gains and severe corrosion were associated with two different modes of degradation: (1) formation of large, interconnected sulfides beneath the external scale, and (2) formation of a Na₂MoO₄-MoO₃ melt. The corrosion due to formation of the Na₂MoO₄-MoO₃ melt occurred for all the salt-coating thicknesses, whereas, large sulfides were formed only for the heavier coatings of Na₂SO₄. The formation of Na₂MoO₄-MoO₃ melt required an induction period, and the length of the induction period was observed to be a function of the amount of Na₂SO₄ and of temperature.Work funded under NASA Grant NCC 3-43.     

Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: A Case Study of an International Bank

The customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six‐step procedure. The back‐propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory.     

An application of PSO technique for harmonic elimination in a PWM inverter

Harmonic elimination problem in PWM inverter is treated as an optimization problem and solved using particle swarm optimization (PSO) technique. The derived equation for computation of total harmonic distortion (THD) of the output voltage of PWM inverter is used as the objective function in the PSO algorithm. The objective function is minimized to contribute the minimum THD in the voltage waveform and the corresponding switching angles are computed. The method is applied to investigate the switching patterns of both unipolar and bipolar case. While minimizing the objective function, the individual selected harmonics like 5th, 7th, 11th and 13th can be controlled within the allowable limits by incorporating the constraints in the PSO algorithm. The results of the unipolar case using five switching angles are compared with that of a recently reported work and it is observed that the proposed method is effective in reducing the voltage THD in a wide range of modulation index. The simulated results are also validated through suitable experiments.     

Fuzzy and Deep Belief Network Based Malicious Vehicle Identification and Trust Recommendation Framework in VANETs

Wireless Personal Communications - This work aims to implement a clustering scheme to separate vehicles into a cluster that is based on various parameters, such as the total number of relay nodes,...     

Effect of process parameters and optimization for photochemical machining of brass and german silver

This article focuses on parametric optimization for photochemical machining (PCM) of brass and german silver. The aim of the study is to analyze the effect of control parameters on response measures, that is, surface roughness, material removal rate, and edge deviation and optimization of parameters considering different weight percentage for each performance measure. The control parameters have been selected as etchant concentration, etching temperature, and etching time. Using full factorial method of design of experiments, PCM has been carried out using ferric chloride as etchant. Surface roughness and edge deviation should be less, while material removal rate is desired high. For satisfying this multi-objective condition, overall evaluation criteria (OEC) have been formulated by assigning different and equal weight percentage to response measures. The optimized condition for particular OEC is obtained, and analysis of variance (ANOVA) has been performed for observing effect of control parameters on response measures. Surface topography study has been performed using scanning electron microscopy, and material composition analysis has been carried out using energy dispersive spectroscopy. The surface roughness is observed lower for brass, while the edge deviation is found lesser for german silver. The material removal rate is observed higher for brass compared to german silver.     

Modulated Triple‐Material Nano‐Heterostructures: Where Gold Influenced the Chemical Activity of Silver in Nanocrystals

For efficient charge separations, multimaterial hetero‐nanostructures are being extensively studied as photocatalysts. While materials with one heterojunction are widely established, the chemistry of formation of multijunction heterostructures is not explored. This needs a more sophisticated approach and modulations. To achieve these, a generic multistep seed mediated growth following controlled ion diffusion and ion exchange is reported which successfully leads to triple‐material hetero‐nanostructures with bimetallic‐binary alloy‐binary/ternary semiconductors arrangements. Ag₂S nanocrystals are used as primary seeds for obtaining AuAg‐AuAgS bimetallic‐binary alloyed metal–semiconductor heterostructures via partial reduction of Ag(I) using Au(III) ions. These are again explored as secondary seeds for obtaining a series of triple‐materials heterostructures, AuAg‐AuAgS‐CdS (or ZnS or AgInS₂), with introduction of different divalent and trivalent ions. Chemistry of each step of the gold ion–induced changes in the rate of diffusion and/or ion exchanges are investigated and the formation mechanism for these nearly monodisperse triple material heterostructures are proposed. Reactions without gold are also performed, and the change in the reaction chemistry and growth mechanism in presence of Au is also discussed.