Experimental study of the frictional properties of friction spun yarns

This article reports the results from a study conducted to characterize the frictional properties of friction spun yarns. The aim of the study was to obtain data on the surface mechanical properties of a variety of friction spun yarns. The study was essential as the surface mechanical properties influence the fabric formation, bonding strength, and high‐performance properties of yarns. The yarns used in the study were made from different fibers and were spun at different speeds. The capstan method was used to obtain the friction force values between the yarns and a glass cylindrical rod. The experiment was conducted at different tensions. The results indicate that the friction of friction spun yarns are influenced by different factors such as the type of fiber and tensions applied. The results obtained help to understand the surface mechanical properties of high‐performance yarns and their influence on the performance characteristics of friction spun yarns. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 2450–2454, 2003     

Characterization of Microstructure,Strength, and Toughness of Dissimilar Weldments of Inconel 625 and Duplex Stainless Steel SAF 2205

The dissimilar combinations of Inconel 625 and duplex stainless steel SAF 2205 obtained from manual GTA welding process employing ER2209 and ERNi CrMo-3 filler metals have been investigated. Formation of secondary phases at the HAZ of Inconel 625 and grain coarsening at the HAZ of SAF 2205 were witnessed while using these filler wires. The average hardness of ER2209 weldments was found to be greater than ERNi CrMo-3 weld. Tensile fracture was observed at the weld zones for both the fillers. Impact test trials showed brittle mode of fracture on employing ER2209 filler and mixed(ductile–brittle) mode of fracture while using ERNi CrMo-3 filler. Further optical microscopy and SEM/EDS analysis were carried out across the weldments to investigate the structure–property relationships.     

An efficient key predistribution scheme for ad hoc network security

We introduce hashed random preloaded subsets (HARPS), a highly scalable key predistribution (KPD) scheme employing only symmetric cryptographic primitives. HARPS is ideally suited for resource constrained nodes that need to operate for extended periods without active involvement of a trusted authority (TA), as is usually the case for nodes forming ad hoc networks (AHNs). HARPS, a probabilistic KPD scheme, is a generalization of two other probabilistic KPDs. The first, random preloaded subsets (RPSs), is based on random intersection of keys preloaded in nodes. The second, proposed by Leighton and Micali (LM) is a scheme employing repeated applications of a cryptographic hash function. We investigate many desired properties of HARPS like scalability, computational and storage efficiency, flexibility in deployment modes, renewability, ease of extension to multicast scenarios, ability to cater for broadcast authentication, broadcast encryption, etc., to support its candidacy as an enabler for ad hoc network security. We analyze and compare the performance of the three schemes and show that HARPS has significant advantages over other KPDs, and in particular, over RPS and LM.     

A technical note on ‘Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation’

This study analyses the mixed-integer linear program (MILP) proposed by Kannan et al. [Kannan, G., Noorul Hag, A., and Devika, M., 2009. Analysis of closed loop supply chain using genetic algorithm and particle swarm optimization. International Journal of Production Research, 47 (5), 1175–1200] in their paper entitled ‘Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation’. Since we find inconsistencies in the model, we propose modifications to rectify the flaws. The revised model is presented and tested using a hypothetical problem.     

Electrostatic characteristics of a high-k stacked gate-all-around heterojunction tunnel field-effect transistor using the superposition principle

Journal of Computational Electronics - We use the superposition method to model the electrostatic characteristics of a high-k stacked gate-all-around heterojunction tunneling field-effect...     

Catalyst and its diameter dependent growth kinetics of CVD grown GaN nanowires

GaN nanowires were grown using chemical vapor deposition with controlled aspect ratio. The catalyst and catalyst-diameter dependent growth kinetics is investigated in detail. We first discuss gold catalyst diameter dependent growth kinetics and subsequently compare with nickel and palladium catalyst. For different diameters of gold catalyst there was hardly any variation in the length of the nanowires but for other catalysts with different diameter a strong length variation of the nanowires was observed. We calculated the critical diameter dependence on adatoms pressure inside the reactor and inside the catalytic particle. This gives an increasing trend in critical diameter as per the order gold, nickel and palladium for the current set of experimental conditions. Based on the critical diameter, with gold and nickel catalyst the nanowire growth was understood to be governed by limited surface diffusion of adatoms and by Gibbs–Thomson effect for the palladium catalyst.     

Optimization of operating parameters and performance evaluation of forced draft cooling tower using response surface methodology (RSM) and artificial neural network (ANN)

Optimization of cold water temperature in forced draft cooling tower with various operating parameters has been considered in the present work. In this study, response surface method (RSM) and an artificial neural network (ANN) were developed to predict cold water temperature in forced draft cooling tower. In the development of predictive models, water flow, air flow, water temperature and packing height were considered as model variables. For this propose, an experiment based on statistical five-level four factorial design of experiments method was carried out in the forced draft cooling tower. Based on statistical analysis, packing height, air flow and water flow were high significant effects on cold water temperature, with very low probability values (< 0.0001). The optimum operating parameters were predicted using RSM, ANN model and confirmed through experiments. The result demonstrated that minimum cold water temperature was optioned from the ANN model compared with RSM.     

The effect of process parameters on machining of magnesium nano alumina composites through EDM

The effects of electrical discharge machining (EDM) parameters on drilled-hole quality such as taper and surface finish are evaluated. Microwave-sintered magnesium nano composites (reinforced with 0.8 and 1.2 wt.% of nano alumina) are used as work materials. Experiments were conducted using Taguchi methodology to ascertain the effects of EDM process parameter. The process parameters such as pulse-on time, pulse-off time, voltage gap, and servo speed were optimized to get better surface finish and reduced taper. ANOVA analyses were carried out to identify the significant factors that affect the hole accuracy and the surface roughness. Confirmation tests were performed on the predicted optimum process parameters. Pulse-on time and the servo speed are identified as major response variables. Micro structural changes and the effects of nano particle reinforcement in the drilled hole were studied through SEM micrographs.     

Multiobjective optimization under uncertainty of the economic and life‐cycle environmental performance of industrial processes

The combined use of multiobjective optimization and life‐cycle assessment (LCA) has recently emerged as a useful tool for minimizing the environmental impact of industrial processes. The main limitation of this approach is that it requires large amounts of data that are typically affected by several uncertainty sources. We propose herein a systematic framework to handle these uncertainties that takes advantage of recent advances made in modeling of uncertain LCA data and in optimization under uncertainty. Our strategy is based on a stochastic, multiobjective, and multiscenario mixed‐integer nonlinear programming approach in which the uncertain parameters are described via scenarios. We investigate the use of two stochastic metrics: (1) the environmental impact in the worst case and (2) the environmental downside risk. We demonstrate the capabilities of our approach through its application to a generic complex industrial network in which we consider the uncertainty of some key life‐cycle inventory parameters. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2098–2121, 2014     

Flow stress modeling for copper under changing process conditions

Realistic simulation of metal forming processes requires constitutive equations that describe the behavior of a material under varying process conditions. The equations that have hitherto been developed to address this problem are generally too involved and require the determination of many constants. In this paper, a simple approach based on the representative nature of the work hardening rate, which enables the use of an elementary rate equation in such modelling, is introduced. A prediction methodology based on the concept of fading memory is developed and is found to give good predictions in the case of copper. A mechanistic interpretation of the approach is proposed.