Magnetic quadrupole doublet focusing system for high energy ions

A high energy focused ion beam microprobe using a doublet arrangement of short magnetic quadrupole lenses was used to focus 1-3 MeV protons to spot sizes of 1x1 microm2 and 1-4.5 MeV carbon and silicon ion beams to spot sizes of 1.5x1.5 microm2. The results presented clearly demonstrate that this simple doublet configuration can provide high energy microbeams for microanalysis and microfabrication applications.     

Sentiment Analysis with Tweets Behaviour in Twitter Streaming API

Twitter is a radiant platform with a quick and effective technique to analyze users’ perceptions of activities on social media. Many researchers and industry experts show their attention to Twitter sentiment analysis to recognize the stakeholder group. The sentiment analysis needs an advanced level of approaches including adoption to encompass data sentiment analysis and various machine learning tools. An assessment of sentiment analysis in multiple fields that affect their elevations among the people in real-time by using Naive Bayes and Support Vector Machine (SVM). This paper focused on analysing the distinguished sentiment techniques in tweets behaviour datasets for various spheres such as healthcare, behaviour estimation, etc. In addition, the results in this work explore and validate the statistical machine learning classifiers that provide the accuracy percentages attained in terms of positive, negative and neutral tweets. In this work, we obligated Twitter Application Programming Interface (API) account and programmed in python for sentiment analysis approach for the computational measure of user’s perceptions that extract a massive number of tweets and provide market value to the Twitter account proprietor. To distinguish the results in terms of the performance evaluation, an error analysis investigates the features of various stakeholders comprising social media analytics researchers, Natural Language Processing (NLP) developers, engineering managers and experts involved to have a decision-making approach.     

A matching game framework for users clustering and resource allocation with wireless power transfer in a CR-NOMA network

This paper investigates the resource allocation in a massively deployed user cognitive radio enabled non-orthogonal multiple access (CR-NOMA) network considering the downlink scenario. The system performance deteriorates with the number of users who are experiencing similar channel characteristics from the base station (BS) in NOMA. To address this challenge, we propose a framework for maximizing the system throughput that is based on one-to-one matching game theory integrated with the machine learning technique. The proposed approach is decomposed to solve users clustering and power allocation subproblems. The selection of optimal cluster heads (CHs) and their associated cluster members is based on Gale-Shapley matching game theoretical model with the application of Hungarian method. The CHs can harvest energy from the BS and transfer their surplus power to the primary user (PU) through wireless power transfer. In return, they are allowed to access the licensed band for secondary transmission. The power allocation to the users intended for power conservation at CHs is formulated as a probabilistic constraint, which is then solved by employing the support vector machine (SVM) algorithm. The simulation results demonstrate the efficacy of our proposed schemes that enable the CHs to transfer the residual power while ensuring maximum system throughput. The effects of different parameters on the performance are also studied.     

Simultaneous selection of optimal parameters and tolerance of manipulator using evolutionary optimization technique

For precise industrial applications, a manipulator must have high positioning accuracy and repeatability. However, variations in performance of the manipulator are attributed to improper selection of dimensions of design and process parameters and its tolerance. There have been almost no attempts to optimize these parameters and tolerance of the manipulator, by which performance variations will be minimum. This paper presents an offline approach to select optimal parameters and tolerance simultaneously which minimizes the manufacturing cost and delivers the target performance level. To determine the optimal parameters and tolerances, a modification in differential evolution algorithm is proposed, which helps in incorporating the effect of uncertainty in optimization process. Proposed approach has been illustrated by selecting optimal parameters and tolerance of a 2-DOF RR planar manipulator. The performance of this approach has been compared with modified genetic algorithm. It is observed that differential evolution algorithm provides optimal results with lesser computations compared to genetic algorithm.     

Step slider bearing with viscoelastic lubricant

The performance of an idealized step slider bearing with a viscoelastic lubricant is investigated theoretically. The elasticity of the lubricant is characterized by a dimensionless number α. The effects of the elasticity of the lubricant on the pressure, load-bearing capacity, frictional resistance, coefficient of friction and maximum film thickness were studied in detail and are presented in several graphs and tables.     

Novel organic–inorganic hybrid coatings prepared by the sol–gel process: corrosion and mechanical properties

(Hyperbranched polyurethane‐urea)/[(3‐aminopropyl)triethoxysilane]‐ZnO (HBPUU‐APTES‐ZnO) hybrid coatings were synthesized using an inexpensive mixing technique by varying the APTES‐modified ZnO concentration. The mechanical and surface properties of the hybrid coating films were studied and compared with unmodified and modified ZnO. The corrosion, solvent and abrasion resistance show significant enhancement in HBPUU‐APTES‐ZnO hybrids and their properties are increased with increasing APTES‐ZnO concentration. This hybrid coating has opened up an opportunity for automotive topcoat application. Copyright © 2012 Society of Chemical Industry     

Modeling of Droplet Generation in a Top Blowing Steelmaking Process

Metallurgical and Materials Transactions B - Quantification of metal droplets ejected due to impinging gas jet on the surface of liquid metal is an important parameter for the understanding and for...     

Analysis of steelmaking kinetics from IMPHOS pilot plant data

It is widely accepted that understanding the kinetics of steelmaking is a complex task, and reliable and validated kinetics models are required for developing successful steelmaking process models. Therefore, as an initial attempt, this paper analyses the applicability of first order kinetics to explain the steelmaking reaction kinetics using the published data in the IMproving Phosphorus Refining research report. The process data for 20 heats in a 6?tonne pilot plant were analysed for the removal of carbon, silicon, manganese and phosphorus using first order kinetics with static and dynamic equilibrium conditions. It was observed that the removal behaviour of silicon closely followed a first order kinetics relationship, while that of carbon only approximately followed a first order kinetics relationship. The removal of manganese did not show a good degree of fit with first order kinetics using static equilibrium condition, but a clear improvement was observed when calculated using dynamic equilibrium condition. In contrast, the kinetics of phosphorus oxidation did not follow any first order relationship.     

Recovery of copper from a surface altered chalcopyrite contained ball mill spillage through bio-hydrometallurgical route

Bioleaching studies for chalcopyrite contained ball mill spillages are very scarce in the literature. We developed a process flow sheet for the recovery of copper metal from surface activated (600 °C, 15 min) ball mill spillage through bio-hydrometallurgical processing route. Bioleaching of the activated sample using a mixed meso-acidophilic bacterial consortium predominantly A. ferrooxidans strains was found to be effective at a lixiviant flow rate of 1.5 L/h, enabling a maximum 72.36% copper recovery in 20 days. Mineralogical as well as morphological changes over the sample surface were seen to trigger the bioleaching efficiency of meso-acidophiles, thereby contributing towards an enhanced copper recovery from the ball mill spillage. The bio-leach liquor containing 1.84 g/L Cu was purified through solvent extraction using LIX 84I in kerosene prior to the recovery of copper metal by electrowinning. Purity of the copper produced through this process was 99.99%.     

General heat balance for oxygen steelmaking

Energy balances are a general fundamental approach for analyzing the heat requirements for metallurgical processes.The formulation of heat balance equations was...