Effect of fiber orientation on interfacial fracture toughness for adhesively bonded composite plates

In this study, interfacial fracture toughness was investigated experimentally and numerically in laminated composite plates with different fiber reinforcement angles bonded with adhesive. The composite plates are four-layered and the layer sequence is [0º/θ]_s. DCB test was applied to composite plates reinforced with epoxy resin matrix and unidirectional carbon fiber. The experimental sample model for the DCB test was made using the ANSYS finite element package program. In the numerical study, four layered composites were prepared in three dimensions. Under critical displacement value; mode I fracture toughness at the crack tip was calculated using VCC (virtual crack closure) technique. Numerical values consistent with experimental results have presented in graphical forms. At 60o and 75° the greatest fracture toughness was obtained. In addition, numerical results have shown that fiber orientation prevents the uniform distribution of stress on the interface crack tip and causes stress accumulation, especially at the edge of the plate.

     

Seismic earth pressures on flexible cantilever retaining walls with deformable inclusions

In this study, the results of 1-g shaking table tests performed on small-scale flexible cantilever wallmodels retaining composite backfill made of a deformable geofoam inclusion and granular cohesionlessmaterial were presented. Two different polystyrene materials were utilized as deformable inclusions.Lateral dynamic earth pressures and wall displacements at different elevations of the retaining wallmodel were monitored during the tests. The earth pressures and displacements of the retaining wallswith deformable inclusions were compared with those of the models without geofoam inclusions.Comparisons indicated that geofoam panels of low stiffness installed against the retaining wall modelaffect displacement and dynamic lateral pressure profile along the wall height. Depending on the inclusioncharacteristics and the wall flexibility, up to 50% reduction in dynamic earth pressures wasobserved. The efficiency of load and displacement reduction decreased as the flexibility ratio of the wallmodel increased. On the other hand, dynamic load reduction efficiency of the deformable inclusionincreased as the amplitude and frequency ratio of the seismic excitation increased. Relative flexibility ofthe deformable layer （the thickness and the elastic stiffness of the polystyrene material） played animportant role in the amount of load reduction. Dynamic earth pressure coefficients were compared withthose calculated with an analytical approach. Pressure coefficients calculated with this method werefound to be in good agreement with the results of the tests performed on the wall model having lowflexibility ratio. It was observed that deformable inclusions reduce residual wall stresses observed at theend of seismic excitation thus contributing to the post-earthquake stability of the retaining wall. Thegraphs presented within this paper regarding the dynamic earth pressure coefficients versus the wallflexibility and inclusion characteristics may serve for the seismic design of full-scale retaining walls withdeformable polystyren     

Predictive human operator model to be utilized as a controller using linear,neuro-fuzzy and fuzzy-ARX modeling techniques

Modeling human operator's behavior as a controller in a closed-loop control system recently finds applications in areas such as training of inexperienced operators by expert operator's model or developing warning systems for drivers by observing the driver model parameter variations. In this research, first, an experimental setup has been developed for collecting data from human operators as they controlled a nonlinear system. Appropriate reference signals and scenarios were designed according to the system identification and human operator modeling theory, to collect data from subjects. Different modeling schemes, namely ARX models as linear approach, and adaptive-network-based fuzzy inference system (ANFIS) as intelligent modeling approach have been evaluated. A hybrid modeling method, fuzzy-ARX (F-ARX) model, has been developed and its performance was found to be better in terms of predicting human operator's control actions as well as replacing the operator as a stand-alone controller. It has been concluded that F-ARX models can be a good alternative for modeling the human operator.     

Evaluation of trace metal contents of some wild edible mushrooms from Black sea region, Turkey

Fructification organs of Calvatia excipuliformis, Lycoperdon perlatum, Laccaria amethystea, Armillaria mellea, Marasmius oreades, Xerula radicata, Cantharellus cibarius, Craterellus cornucopioides, Cantharellus tubaeformis, Hypholoma fasciculare, Clitocybe gibba, Collybia dryophila, Lepista nuda and Mycena aetites were collected from different localities in Black sea region of Turkey. Their trace metals concentrations were determined by atomic absorption spectrometry after wet and microwave digestion. The results were (as mg/kg) 150–1741 for iron, 15.5–73.8 for copper, 28.6–145 for manganese, 43.5–205 for zinc, 4.8–42.7 for aluminium and 0.9–2.6 for lead. The levels of lead analyzed in some edible mushroom samples were found to be higher than legal limits. The relative standard deviations (R.S.D.) were found below 10%. The accuracy of procedure was confirmed by certified reference material.     

Prediction of manually controlled vessels’ position and course navigating in narrow waterways using Artificial Neural Networks

Despite modern navigation devices, there are still some problems for navigating of vessels in narrow waterways because of geographical structures and various disturbances. In this study, a guidance and an early warning method by means of predicting three-minute-ahead position of a vessel, especially in the turning points, has been developed for navigating in narrow waterways. The Istanbul Strait has been specifically studied as a model. Since operators in Vessel Traffic Services (VTS) can watch only straight bearing of vessels on VTS panels but especially for turning regions, they have to foresee a risk on time which may result in a disaster. The objective of this study is to predict the future coordinates of a manually controlled vessel using Artificial Neural Networks (ANN).Artificial Neural Networks have been trained by using position and speed data collected from vessels which navigated manually in the Strait. Three-minute-ahead position of vessels has been predicted by using the trained ANN. Some on-line experiments have been done in Istanbul VTS centre and it has been observed that the method satisfied the goal in especially turning points of the Strait. Hence the proposed method could be utilized for warning system by VTS operators and guidance system by vessel crew.     

In situ mullite foam fabrication using microwave energy

In situ mullite ceramic foams were fabricated using polymeric sponge replication method from ceramic slurry containing alpha alumina and kaolin mixtures. Ceramic preforms were processed using microwave energy and conventional heating. The sintered foam samples were characterized by SEM and XRD observations, density measurements and compression tests in order to observe the effect of two different sintering techniques on the structure and properties. It was found that the microwave processing was completed in a shorter burning out and sintering cycle and produced structures having higher mullite transformation ratio and fine grains.     

Iron Loss Reduction in an Interior PM Automotive Alternator

This paper examines the iron loss characteristics of a high-flux interior permanent-magnet machine. The machine was designed as a concept demonstrator for a 6-kW automotive alternator and has a wide field-weakening range. Initial experimental results revealed a high iron loss during field-weakening operation. Finite-element analysis was used to investigate the cause of the high iron losses and to predict their magnitude as a function of speed. The effects of changes in the machine design were examined in order to reduce iron losses and hence improve the machine performance     

Improved common weight MCDM model for technology selection

This paper presents an improvement on earlier work on a common weight multi-criteria decision-making (MCDM) approach for technology selection by (Karsak, E.E. and Ahiska, S.S., Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection. Int. J. Prod. Res., 2005, 43, 1537–1554.) benefiting from a bisection search algorithm. The proposed algorithm enables to calculate the values of discriminating parameter, k, which appears in the introduced efficiency measure, in a systematic and robust manner rather than requiring the decision analyst to assign an arbitrary step size value. In addition, the paper presents comments on the model proposed by (Amin, G.R., Toloo, M. and Sohrabis, B., An improved MCDM DEA model for technology selection. Int. J. Prod. Res., 2006, 44, 2681–2686.) for technology selection. Finally, the robustness of the proposed decision-making framework is illustrated via several numerical examples taken from the above-mentioned papers.