Oxidation behaviour of the near α-titanium alloy IMI 834

Oxidation behaviour of the near α-titanium alloy IMI 834 was investigated over a range of temperatures, from 600–800°C, in air. Specimens were solution-treated in the α + β and β phase fields for 1 h and 1/2 h, respectively and cooled in air to room temperature. The solution treated samples were subjected to stabilization treatment at 700°C for 2 h, followed by cooling in air. Oxidation behaviour of these samples was studied from 600–800°C in air, for 50 h. The morphology of the scales formed was examined by SEM and the phases present in the scales were characterized by X-ray diffraction. While there was little oxidation at 600°C, the rate of oxidation increased at higher temperatures. In general, the rate of oxidation was found to be more in the α + β treated condition than that in the β treated one. The results are discussed in terms of the characteristics of the oxide film formed under different conditions.     

Influence of parameters and optimization of EDM performance measures on MDN 300 steel using Taguchi method

Maraging steel (MDN 300) exhibits high levels of strength and hardness. Optimization of performance measures is essential for effective machining. In this paper, Taguchi method, used to determine the influence of process parameters and optimization of electrical discharge machining (EDM) performance measures on MDN 300 steel, has been discussed. The process performance criteria such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) were evaluated. Discharge current, pulse on time, and pulse off time have been considered the main factors affecting EDM performance. The results of the present work reveal that the optimal level of the factors for SR and TWR are same but differs from the optimum levels of the factors for MRR and RWR. Further, discharge current, pulse on time, and pulse off time have been found to play a significant role in EDM operations. Detailed analysis of structural features of machined surface was done by using scanning electron microscope (SEM) to understand the influence of parameters. SEM of electrical discharge machining surface indicates that at higher discharge current and longer pulse on duration give rougher surface with more craters, globules of debris, pockmarks or chimneys, and microcracks than that of lower discharge current and lower pulse on duration.     

Optimization of process parameters for rehabilitation of pipes through adhesive bonding: experimental study

Abstract

In many industries maintenance and repairing of pipes are crucial elements to engineers. The processes may consume a lot of money and time. Conventional methods like welding, riveting etc. may damage the base material or some times the pipe may carry inflammable fluids which can not be possible to repair by conventional methods. In such a case, adhesive bond may provide an alternative solution to the pipe repair or strengthening applications. The present work focuses on the optimization of process parameters which enhances the adhesive bond capacity (Tensile shear load) between carbon fiber reinforced polymer (CFRP) composite patch and SS (SS 304) plates. Epoxy resin and adhesive combination, pre cure temperature and surface preparation was considered as parameters. The surface roughness of pre-bond surfaces was measured using a 3D-microscope. The quality of the adhesive bond was evaluated using non-destructive testing (Digital Radiography) before performing tensile test. The failed surface morphology was studied using FE-SEM images. The optimal parameters were derived form the tensile test data of the adhesive joint. The bond capacity for lateral loadings was also studied using a three point bending test at the derived conditions. These parameters were also applied to rehabilitate the damaged pipe and its ability was evaluated through hydrostatic pressure test. From the results, it was observed that these parameters hold good for pipe rehabilitation also.     

Role of Ti<Subscript>3</Subscript>Al/silicides on tensile properties of Timetal 834 at various temperatures

Extremely fine coherent precipitates of ordered Ti₃Al and relatively coarse incoherent precipitates of S₂ silicide exist together in the near α-titanium alloy, Timetal 834, in the dual phase matrix of primary α and transformed β. In order to assess the role of these precipitates, three heat treatments viz. WQ, WQ-A and WQ-OA, were given to have no precipitates, Ti₃Al and silicide and only silicide precipitates in the respective conditions. Tensile properties in the above three heat treated conditions were determined at room temperature, 673 K and 873 K. It was observed that largely Ti₃Al precipitates were responsible for increase in the yield strength and decrease in ductility in this alloy.     

CH selection and compressive sensing-based data aggregation in WSN using hybrid Golden circle-inspired optimization

The arbitrary distribution of sensor nodes and irregularity of the routing path led to unordered data, which is complex to handle in a wireless sensor network (WSN). To increase WSN lifetime, data aggregation models are developed to minimize energy consumption or ease the computational burden of nodes. The compressive sensing (CS) provides a new technique for prolonging the WSN lifetime. A hybrid optimized model is devised for cluster head (CH) selection and CS-based data aggregation in WSN. The method aids to balance the energy amidst different nodes and elevated the lifetime of the network. The hybrid golden circle inspired optimization (HGCIO) is considered for cluster head (CH) selection, which aids in selecting the CH. The CH selection is done based on fitness functions like distance, energy, link quality, and delay. The routing is implemented with HGCIO to transmit the data projections using the CH to sink and evenly disperse the energy amidst various nodes. After that, compressive sensing is implemented with the Bayesian linear model. The convolutional neural network-long short term memory (CNN-LSTM) is employed for the data aggregation process. The proposed HGCIO-based CNN-LSTM provided the finest efficiency with a delay of 0.156 s, an energy of 0.353 J, a prediction error of 0.044, and a packet delivery ratio (PDR) of 76.309%.     

Recycling of thermoplastic polystyrene waste using citrus peel extract for oil spill remediation

In this work, we report a low-cost, less energy intensive, and an innovative way of recycling thermoplastic polystyrene (PS) waste objects into submicron, aligned fibers using extract from citrus peel, an agricultural waste. As-fabricated recycled PS fabric is then structurally characterized and tested as an oil sorbent material. The hydrophobic-oleophilic PS fabric is found to absorb 40.5 ± 3.6 g/g of oil, with 77.3% oil retention within 1 h. To investigate the practical application of recycled PS fabric for oil spills remediation, we tested its buoyancy properties in oil-over-water static and dynamic system besides examining their reusability. The as-fabricated fabric floats on water after oil sorption indicating its high buoyancy and therefore can be collected easily after soaking the oil. This work is a simple illustration of systematic analysis of recycling two different waste materials (thermoplastic polystyrene and citrus peels) and reusing them into a more valuable product. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47886.