One-dimensional nonlinear vibration analysis and coupled thermoelasticity based on Green-Naghdi model

Journal of Mechanical Science and Technology - The present article reports on a study on nonlinear coupled thermoelasticity based on Green-Naghdi type III model in one-dimensional form. Unlike...     

A routing protocol for vehicular ad hoc networks using simulated annealing algorithm and neural networks

Vehicular ad hoc network (VANET) is special type of mobile ad hoc networks which establish communications between adjacent vehicles and also between vehicles and roadside units. Thanks to their dynamic and fast topology changes, inter-vehicular ad hoc networks are like dynamic networks without organizations. Hence, developing a reliable routing algorithm is regarded as a notable challenge in these networks. In this paper, a clustering-based reliable routing algorithm was proposed for VANETs with reliable applications. In this way, simulated annealing was used for appropriate clustering of nodes and the parameters of node degree, coverage and ability were considered in the proposed method. For selecting cluster head, radial basis function neural network was used and a suitable fitness function with velocity and free buffer size parameters was used. Each cluster has two gateway nodes which are used as the communication interface for transmitting data from one cluster to another cluster. The simulation results indicated the efficiency of the proposed method in terms of route discovery rate and packet delivery rate.     

Photopolymerization behavior and phase separation effects in novel polymer dispersed liquid crystal mixture based on urethane trimethacrylate monomer

Polymer dispersed liquid crystals (PDLCs) are often formed by polymer induced phase separation, based on photopolymerization of multifunctional acrylate monomers. The emerged morphology is controlled by the interplay between polymerization rate and phase separation dynamics, which depends on different parameters such as monomer structure and functionality. In this work, a new PDLC formulation containing urethane trimethacrylate (UTMA) monomer is introduced, which has different molecular weight evolution, polymer gel point, and polymerization kinetics in comparison with some common ester acrylate (such as TMPTA and DPHPA) based PDLC compositions. UTMA is synthesized and characterized by Fourier transform infrared, ¹H‐NMR, and ¹³C‐NMR spectroscopic techniques. Simultaneous examination of polymer evolution and LC phase separation by real‐time infrared spectroscopy shows that the UTMA based PDLC, which contains trifunctional urethane acrylate monomer, has greater amount of bond conversion, polymerization rate, and liquid crystal (LC) phase separation in comparison with TMPTA based PDLC. In spite of the acrylate monomers, which show gel point conversions as low as 1.83–5.72%, UTMA reaches to its maximum rate at 19.5% conversion, which causes higher phase separation and therefore greater LC domain size. The experimental results are explained more precisely by means of SEM and optical microscopy analyses. The results are confirmed by electro‐optics measurements. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Mechanical and structural properties of melt spun polypropylene/nylon 6 alloy filaments

Investigated in the present study are the physical properties, morphology, and structure of PP/N6 alloy filaments (10, 20 wt % N6) made with or without PP‐g‐MAH as compatibilizer. The alloy filaments produced at the take‐up speeds of 300 and 800 m/min were drawn with draw ratio of 3.5 and 2, respectively. Stress–strain curves of PP and alloy filaments show ductile and brittle behavior, respectively. It is suggested that the brittle behavior of alloy filaments is due to the presence of microvoids or micropores at the interface of PP and N6; these lead to stress concentration and thus to a decrease in tenacity, modulus, and elongation at break. Effects of the blending of N6 with PP on birefringence and crystalline and amorphous orientation factors of the composite filaments are studied. The amorphous orientation factor, f_am, of PP was found to increase with an increase in the amount of N6. The alloy filaments behaved like isostrain materials and most of the force in spinning and drawing was born by the PP phase. The presence of N6 fibrils helped to orient PP chain molecules in amorphous regions. However, the crystalline factor, f_c, of PP decreased with the increase in nylon fraction. This means the presence of the crystals of N6 caused a decrease in the orientation of the PP crystals. LSCM micrographs of the filament showed the presence of matrix–fibril morphology with the N6 fibrils oriented along the axis. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 532–544, 2005     

Nonlinear Multi-Scale Modelling,Simulation and Validation of 3D Knitted Textiles

Three-dimensionally (3D) knitted technical textiles are spreading into industrial applications, since their geometric, structural and functional performance can be tailored and optimized on fibre-, yarn- and fabric levels by customizing yarn materials, knit patterns and geometric shapes. The ability to simulate their complex mechanical behaviour is thus an essential ingredient in the development of a digital workflow for optimal design and manufacture of 3D knitted textiles. Here, we present a multi-scale modelling and simulation framework for the prediction of the nonlinear orthotropic mechanical behaviour of single jersey knitted textiles and its experimental validation. On the meso-scale, representative volume elements (RVEs) of the fabric are modelled as single, interlocked yarn loops and their mechanical deformation behaviour is homogenized using periodic boundary conditions. Yarns are modelled as nonlinear 3D beam elements and numerically discretized using an isogeometric collocation method, where a frictional contact formulation is used to model inter-yarn interactions. On the macro-scale, fabrics are modelled as membrane elements with nonlinear orthotropic material behaviour, which is parameterized by a response surface constitutive model obtained from the meso-scale homogenization. The input parameters of the yarn-level simulation, i.e., mechanical properties of yarns and geometric dimensions of yarn loops in the fabrics, are determined experimentally and subsequent meso- and macro-scale simulation results are evaluated against reference results and mechanical tests of knitted fabric samples. Good agreement between computational predictions and experimental results is achieved for samples with varying stitch values, thus validating our novel computational approach combining efficient meso-scale simulation using 3D beam modelling of yarns with numerical homogenization and nonlinear orthotropic response surface constitutive modelling on the macro-scale.     

HYBRID GENETIC PROGRAMMING-BASED SEARCH ALGORITHMS FOR ENTERPRISE BANKRUPTCY PREDICTION

Bankruptcy is an extremely significant worldwide problem that affects the economic well- being of all countries. The high social costs incurred by various stakeholders associated with bankrupt firms imply the need to search for better theoretical understanding and prediction quality. The main objective of this paper is to apply genetic programming with orthogonal least squares (GP/OLS) and with simulated annealing (GP/SA) algorithms to build models for bankruptcy prediction. Utilizing the hybrid GP/OLS and GP/SA techniques, generalized relationships are obtained to classify samples of 136 bankrupt and nonbankrupt Iranian corporations based on financial ratios. Another important contribution of this paper is to identify the effective predictive financial ratios based on an extensive bankruptcy prediction literature review and a sequential feature selection (SFS) analysis. A comparative study on the classification accuracy of the GP/OLS- and GP/SA-based models is also conducted. The observed agreement between the predictions and the actual values indicates that the proposed models effectively estimate any enterprise with regard to the aspect of bankruptcy. According to the results, the proposed GP/SA model has better performance than the GP/OLS model in bankruptcy prediction.     

Doing the politics of technological decision making: due process and the debate about identity cards in the U.K.

The U.K. Government, in presenting its proposals for biometric identity cards, made strong claims about the technology and science underlying the proposed National Identity Scheme. In this paper, we use insights from science and technology studies (STS), particularly Latour's ‘Politics of Nature’ argument, to analyse the parliamentary debates about the technological and scientific aspects of the proposals. The authors were part of a team that produced a report that raised a series of perplexities about the Scheme in an attempt to counter the short-circuiting of discussion of these perplexities in the parliamentary debate. The paper analyses the government's attempts at short-circuiting in light of Latour's argument and the introduction of perplexities by our report. It demonstrates the extent to which this form of STS can enhance political debate about technological decisions.     

Analysis and design of a high efficiency bidirectional DC–DC converter for battery and ultracapacitor applications

This paper presents a high efficiency non-isolated bidirectional converter which can be employed as an interface circuit between ultracapacitors or batteries and DC bus voltage. All semiconductor devices in the proposed converter are soft switched while the control circuit remains PWM. So, the energy conversion through the converter is highly efficient. The proposed converter acts as a zero-voltage transition (ZVT) buck to charge an ultracapacitor or battery and acts as a ZVT boost to discharge an ultracapacitor or battery. The performance of the proposed converter with respect to abrupt load and operating mode change is shown through computer simulation results. The results confirm the aforementioned advantages and features of the proposed converter.     

Decentralized robust adaptive-output feedback controller for power system load frequency control

In this paper, a new model reference-decentralized robust adaptive-output feedback controller is proposed for the load frequency control (LFC) of large-scale power systems with unknown parameters. This control strategy requires only local input–output data and can follow random changes in the operating conditions. The controller is designed such that the trajectory errors and the control gains of each area remain uniformly bounded. In the proposed method, firstly an adaptive observer is designed to estimate the state variables and system parameters using local data only. Then a locally linear combination of the estimated states and the model reference states are used to design a robust adaptive-output feedback controller for each area. Simulation results for a three-area power system show that the proposed controller achieves good performance even in the presence of plant parameter changes and system non-linearities. Received: 18 October 2001/Accepted: 24 October 2001