Vapor-liquid equilibrium of ethanol/ethyl acetate mixture in ultrasonic intensified environment

A vapor-liquid equilibrium (VLE) study was conducted on ethanol/ethylacetate mixture as a preliminary step towards developing an ultrasonic-assisted distillation process for separating azeotropic mixtures. The influence of ultrasonic intensity and frequency on the vapor-liquid equilibrium (VLE) of the mixture was examined using a combination of four ultrasonic intensities in range of 100–400W/cm² and three frequencies ranging from 25–68 kHz. The sonication was found to have significant impacts on the VLE of the system as it alters both the relative volatility and azeotrope point, with preference to lower frequency operation. A maximum relative volatility of 2.32 was obtained at an intensity of 300 W/cm2 and a frequency of 25 kHz coupled with complete elimination of ethanol-ethyl acetate azeotrope. Results from this work were also congruent with some experimental and theoretical works presented in the literature. These findings set a good beginning towards the development of an ultrasonic assisted distillation that is currently in progress.     

Investigating Factors Affecting Water-In-Diesel Fuel Nanoemulsions

In this work, water-in-diesel fuel nanoemulsions were prepared with mixed nonionic surfactants. Several mixtures of sorbitan monooleate and polyoxyethylene (20) sorbitan monooleate, with different Hydrophilic–Lipophilic Balance (HLB) values (9.6, 9.8, 10, 10.2 and 10.4) were prepared to achieve the optimal HLB value. Three mixed surfactant concentrations were prepared at 6, 8 and 10 wt% to identify the optimum concentration. Five emulsions with different water contents: 5, 6, 7, 8 and 9 % (wt/wt) were prepared using a high energy method under the optimum conditions (HLB = 10 and mixed surfactant concentration = 10 %). The effect of the HLB value, mixed surfactant concentration and water content on the droplet size has been studied. The interfacial tension and thermodynamic properties of the individual and the blended emulsifiers were investigated. Droplet size of the prepared nanoemulsions was determined by dynamic light scattering and the nanoemulsion stability was assessed by measuring the variation of the droplet size as a function of time. From the results obtained, it was found that the mean droplet size was formed between 49.5 and 190 nm depending on the HLB value, surfactant concentration and water content of the blended emulsifiers.     

A combinatorial approach to evaluation of monomer conversion and particle size distribution in vinyl chloride emulsion polymerization

This work is targeted to study emulsion polymerization of vinyl chloride monomer (VCM) using experimental and mathematical methods. To fulfill this goal, a computer code was developed on the basis of zero–one population balance by which the effects of initiator and emulsifier concentration on the evolution of VCM conversion were investigated in the course of polymerization. The model was also trained to capture the coagulation of the particles. This enabled to adopt a reliable way of evaluating the particle size distribution (PSD). In particular, the rates of homogeneous and micellar nucleation mechanisms were simulated and reasonably predicted alterations in the PSD and the number of polymer particles under the influence of aforementioned parameters. The results from modeling were satisfactorily consistent with the experimental outputs and obviously visualized the impact of initiator and surfactant concentration on the PSD of the prepared PVC latexes.     

Neuro-fuzzy control strategy for an offshore steel jacket platform subjected to wave-induced forces using magnetorheological dampers

Magnetorheological (MR) damper is a prominent semi-active control device to vibrate mitigation of structures. Due to the inherent non-linear nature of MR damper, an intelligent non-linear neuro-fuzzy control strategy is designed to control wave-induced vibration of an offshore steel jacket platform equipped with MR dampers. In the proposed control system, a dynamic-feedback neural network is adapted to model non-linear dynamic system, and the fuzzy logic controller is used to determine the control forces of MR dampers. By use of two feedforward neural networks required voltages and actual MR damper forces are obtained, in which the first neural network and the second one acts as the inverse dynamics model, and the forward dynamics model of the MR dampers, respectively. The most important characteristic of the proposed intelligent control strategy is its inherent robustness and its ability to handle the non-linear behavior of the system. Besides, no mathematical model needed to calculate forces produced by MR dampers. According to linearized Morison equation, wave-induced forces are determined. The performance of the proposed neuro-fuzzy control system is compared with that of a traditional semi-active control strategy, i.e., clipped optimal control system with LQG-target controller, through computer simulations, while the uncontrolled system response is used as the baseline. It is demonstrated that the design of proposed control system framework is more effective than that of the clipped optimal control scheme with LQG-target controller to reduce the vibration of offshore structure. Furthermore, the control strategy is very important for semi-active control.     

An optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool for best surface finish

High-speed machining (HSM) has emerged as a key technology in rapid tooling and manufacturing applications. Compared with traditional machining, the cutting speed, feed rate has been great progress, and the cutting mechanism is not the same. HSM with coated carbide cutting tools used in high-speed, high temperature situations and cutting more efficient and provided a lower surface roughness. However, the demand for high quality focuses extensive attention to the analysis and prediction of surface roughness and cutting force as the level of surface roughness and the cutting force partially determine the quality of the cutting process. This paper presents an optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool to achieve minimum cutting forces and better surface roughness. Taguchi optimization method is the most effective method to optimize the machining parameters, in which a response variable can be identified. The standard orthogonal array of L₉ (3⁴) was employed in this research work and the results were analyzed for the optimization process using signal to noise (S/N) ratio response analysis and Pareto analysis of variance (ANOVA) to identify the most significant parameters affecting the cutting forces and surface roughness. For such application, several machining parameters are considered to be significantly affecting cutting forces and surface roughness. These parameters include the lubrication modes, feed rate, cutting speed, and depth of cut. Finally, conformation tests were carried out to investigate the improvement of the optimization. The result showed a reduction of 25.5% in the cutting forces and 41.3% improvement on the surface roughness performance.     

Free vibration analysis of orthotropic plates with variable thickness resting on non-uniform elastic foundation by element free Galerkin method

This study intends to investigate the vibration behavior of a thin square orthotropic plate resting on non-uniform elastic foundation and its thickness varying in one or two directions. By using the classical plate theory and employing element free Galerkin method, it is shown that the fundamental frequency coefficients obtained are in good agreement with available results in the literature. The effects of thickness variation, foundation parameter and boundary conditions on frequency are investigated. The results show that the method converges very fast regardless of parameters involved.     

Networked control of industrial automation systems—a new predictive method

A new method for real-time prediction of uncertain network transmission time delays and a method for closed-loop control of manufacturing and industrial plants through networks are introduced. The proposed delay prediction method is based on the multilayer perceptron neural model. In order to minimize the number of neurons in the first layer of the network and hence reducing the computational burden in a real-time implementation, a method for determination of the Markov order of the time delay sequence is presented. Using the predicted delay, and a zero-order hold equivalent discrete-time model of the plant, a time varying state feedback control algorithm with a real-time gain updating strategy is proposed. A sufficient condition for closed-loop stability is also derived using the switching theorem for linear systems. The proposed method is shown, through two industrial networked case studies, namely, a DC motor driving a transportation roller for paper sheets and a milling machine. Simulation studies depict the efficacy of the proposed method in controlling such challenging problems.     

Carbon nanotubes based strain sensors

This paper presents the design, fabrication and experimental results of carbon nanotubes (CNTs) based strain sensors. The sensors were fabricated by pressed CNTs tablets and elastic polymer beam. The diameter of multiwalled nanotubes (MWNTs) varied between 10 and 30 nm. The tablets of multiwalled CNTs having nominal thickness of 1.0 mm were pressed at a pressure of 200 and 300 MPa. The inter-electrodes distance (length) and width of the surface-type samples were in the range of 10–12 mm and 5–6 mm respectively. The DC resistance of the sensors having the strain sensitivity in the range of 50–80 in average increased under tension and decreased under compression.     

Palyno‐morphological characteristics of gymnosperm flora of pakistan and its taxonomic implications with LM and SEM methods

The present study is intended to assess gymnosperms pollen flora of Pakistan using Light Microscope (LM) and Scanning Electron Microscopy (SEM) for its taxonomic significance in identification of gymnosperms. Pollens of 35 gymnosperm species (12 genera and five families) were collected from its various distributional sites of gymnosperms in Pakistan. LM and SEM were used to investigate different palyno‐morphological characteristics. Five pollen types (i.e., Inaperturate, Monolete, Monoporate, Vesiculate‐bisaccate and Polyplicate) were observed. Six In equatorial view seven types of pollens were observed, in which ten species were sub‐angular, nine species were Traingular, six species were Perprolate, three species were Rhomboidal, three species were semi‐angular, two species were rectangular and two species were prolate. While five types of pollen were observed in polar view, in which ten species were Spheroidal, nine species were Angular, eight were Interlobate, six species were Circular, two species were Elliptic. Eighteen species has rugulate and 17 species has faveolate ornamentation. Eighteen species has verrucate and 17 have gemmate type sculpturing. The data was analysed through cluster analysis. The study showed that these palyno‐morphological features have significance value in classification and identification of gymnosperms. Based on these different palyno‐morphological features, a taxonomic key was proposed for the accurate and fast identifications of gymnosperms from Pakistan.     

Investigation on the feasibility of eliminating harmonic excitation signal en-route to performing experimental modal analysis (EMA) under operational condition

This study focuses on introducing a criteria for conducting harmonic excitation signal elimination as well as investigating its effectiveness towards achieving complete isolation of harmonic disturbance in performing EMA under operational condition. By modulating the ratio between harmonic excitation and impact knocking frequencies, it was revealed that the harmonic signal was efficiently attenuated with sufficient number of averaging blocks. The results highlighted close agreement between simulation and experimental approaches with maximum deviation of 2 %, under specific design criteria. It was determined that a non-periodic triggering frequency significantly affect the elimination performance in terms of trend and amplitude reduction. This work underlines the importance of controlling the triggering frequency to yield the desired design criteria for achieving rapid and highly efficient elimination of harmonic excitation signal. The results have proven that the proposed technique can be further adapted to isolate the harmonic in conventional EMA conducted under operational condition.