Conceptual damage-sensitive features for structural health monitoring: Laboratory and field demonstrations

The use of damage-sensitive features to evaluate structural condition or health is a very critical aspect of structural health monitoring. The purpose of this paper is to investigate the potential of two different damage-sensitive features for detecting damage. Different damage scenarios are simulated on a large-scale laboratory structure and a three-span highway bridge for demonstration. The features presented in this paper are the modal flexibility-based deflection and curvature both of which are obtained directly from dynamic properties. In the literature, flexibility associated with mode shapes and mode shapes curvatures have been mostly explored. In this study, multi-input–multi-output dynamic data are used to obtain modal flexibility, which is a close approximation to the actual flexibility. A main novelty is that the curvature is calculated from the deflected shapes using the modal flexibility as opposed to using modal vectors. In this paper, the theory of the methodology is explained and then experimental studies and results are presented. For the experimental studies, the laboratory specimen and the three-span bridge were gradually damaged. It is shown that both deflection and curvature are conceptual and physically meaningful features for damage detection and localization. The issues and the requirements for these features to perform successfully are also presented.     

Synthesis and characterization of poly(N‐vinyl‐2‐pyrrolidone) grafted sodium alginate hydrogel beads for the controlled release of indomethacin

Graft copolymers of sodium alginate (NaAlg) with N‐vinyl‐2‐pyrrolidone were prepared using azobisisobutyronitrile as initiator. The graft copolymers (NaAlg‐g‐PVP) were characterized with Fourier transform infrared spectroscopy, elemental analysis, and differential scanning calorimetry. Polymeric hydrogel beads of NaAlg and NaAlg‐g‐PVP were prepared by crosslinking method using glutaraldehyde (GA) as a crosslinker in the hydrochloric acid catalyst (HCl) and these beads were used to deliver anti‐inflammatory drug, indomethacin (IM). Chemical stability of the IM after encapsulation into beads was confirmed by FTIR. Preparation conditions of the NaAlg‐g‐PVP beads were optimized by considering the percentage entrapment efficiency, particle size, swelling capacity and their release data. In vitro release studies were performed in simulated gastric fluid (pH 1.2) for the initial 2 h, followed by simulated intestinal fluid (pH 7.4) for 4 h. Effects of GA concentration, exposure time to GA, drug/polymer (d/p) ratio, and concentration of HCl on the release of IM were discussed. It was observed that IM release from the beads decreased with increasing GA concentration and exposure time. IM release also decreases with increasing d/p ratio and HCl concentration. The highest IM release was obtained to be 77% for beads crosslinked with 0.027M GA. Swelling experiments were also performed to compute molecular mass between crosslinks of the beads. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Accurate and simple synthesis formulas for coplanar waveguides

Simple and accurate closed‐form formulas obtained by using a differential evolution algorithm are presented for the synthesis of coplanar waveguides (CPW). The results of the synthesis formulas proposed in this article are compared with those of the quasi‐static analysis, the synthesis formulas reported by the other researchers and also the experimental works available in the literature. The accuracy of the proposed synthesis formulas is found to be better than 0.75% for 9256 CPWs samples. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

Corrosion morphologies on magnesium alloy AZ 91

Initiation and early propagation of pitting and filiform corrosion on bare alloy AZ91 (9% Al, 1% Zn) are investigated by natural immersion corrosion tests, electrochemical measurements and microanalytical studies. Initiation sites are few. Corrosion spreads from these sites first in the form of filiform corrosion for a limited period of time and pitting which later develops into a cellular type of etching. The important factors affecting filiform corrosion are temperature, material structure and degree of polarization at the anodic sites. Filiform attack on AZ91, unlike the classical mechanisms of filiform corrosion on coated metals, is driven by hydrogen evolution reaction on the cathodic sites of the surface, occurs under significant anodic control, propagates at a high, constant speed independent of degree of polarization along preferential paths determined by compositional and crystallographic factors, and is a temporary phenomenon under open circuit conditions. Pitting corrosion is more predominant with decreasing anodic polarization.     

Ultrasonic study of molecular association of poly(vinyl chloride) solution in tetrahydrofuran

Ultrasonic absorption, velocity, adiabatic compressibility, relaxation time and relaxation amplitude measurements are reported on poly(vinyl chloride) (PVC) solution in tetrahydrofuran (THF) using pulsed ultrasonic apparatus operating at 2 MHz and 313 K. Results show a linear increase of velocity. density, viscosity, absorption coefficient, relaxation time and relaxation amplitude values with the increase of PVC concentration in THF. In contrast the compressibility decreases with increasing PVC concentration. This suggests interaction between PVC and THF molecules.     

On the Fatty Acid Composition of Turkish Vegetable Oils

Because of the variety of climate conditions very different oil plants except of some tropical kinds grow in Turkey. In this work four groups of raw material of Turkish vegetable oils were investigated. The first group consists of olive, sunflower and cotton, which are important raw materials in Turkey. About 97% of the oil produced in Turkey base on these three raw materials. The second group consists of sesame, poppy, linseed, hemp-seed, rape, soyabean, safflower, castor bean and groundnut, which are temporary of lower importance for Turkey. The third group consists of the non-traditional oil raw materials like tobacco seed, grape seed, scabious, fig seed, tomato seed, laurel seed, pistacia terebinthus, rice bran, maize germs, anise seed, peach-stones and pumpkin seed. The fourth group consists of fruits rich in oil like hazel-nuts, walnuts, almonds and pistachio-nuts, whose production is of great importance in Turkey.     

Use of center of gravity with the common vector approach in isolated word recognition

In this paper, the subspace based classifier, common vector approach (CVA), with the center of gravity (COG) method is used for isolated word recognition. Since the CVA classifier is sensitive to shifts through the time axis, endpoint detection becomes extremely important for the recognition of isolated words. The COG method eliminates the need for endpoint detection. The effects of the COG method and a classical endpoint detection algorithm on the recognition rates of isolated words are investigated. The experimental results show that the COG method yields slightly higher recognition rates than the endpoint detection method in the TI-digit database when CVA is used.     

An automatic diabetes diagnosis system based on LDA-Wavelet Support Vector Machine Classifier

In this paper, an automatic diagnosis system for diabetes on Linear Discriminant Analysis (LDA) and Morlet Wavelet Support Vector Machine Classifier: LDA–MWSVM is introduced. The structure of this automatic system based on LDA-MWSVM for the diagnosis of diabetes is composed of three stages: The feature extraction and feature reduction stage by using the Linear Discriminant Analysis (LDA) method and the classification stage by using Morlet Wavelet Support Vector Machine (MWSVM) classifier stage. The Linear Discriminant Analysis (LDA) is used to separate features variables between healthy and patient (diabetes) data in the first stage. The healthy and patient (diabetes) features obtained in the first stage are given to inputs of the MWSVM classifier in the second stage. Finally, in the third stage, the correct diagnosis performance of this automatic system based on LDA–MWSVM for the diagnosis of diabetes is calculated by using sensitivity and specificity analysis, classification accuracy, and confusion matrix, respectively. The classification accuracy of this system was obtained at about 89.74%.     

The modeling of mode choices of intercity freight transportation with the artificial neural networks and adaptive neuro-fuzzy inference system

Mode choice modeling is probably the most important element of transportation planning. It affects the general efficiency of travel and the allocation of resources. The development of mode choice models has recently witnessed significant advances in many fields, such as passenger and freight transport. A large number of mathematical models have been used to model the traveler’s choice of mode and destination and the shipper’s choice of mode, shipment size and supply market, among others. Such models are not only becoming almost intractable but also data intensive, difficult to calibrate and update, and intransferable. These models cover a wide range of mathematical complexity and accuracy. This paper describes a new approach to mode choice of intercity freight transport modeling using artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) models. The new approach combines the learning ability of artificial neural networks and the transparent nature of fuzzy logic. The approach is found to be highly adaptive and efficient in investigating non-linear relationships among different variables. The adaptive neuro-fuzzy inference system model is tested on the freight transport market in Turkey, Germany, France and Austria by using information on the freight flows and their attributes. The ANNs and ANFIS models are more successful in the representation of the non-linear behavior of mode choice of intercity freight transport compared to the classical models.