Experimental and numerical study of globe valve housing

Complex structure experimental analysis has always been a huge challenge for researchers. Conventional experimental methods (e.g., strain gauges) give only limited data sets regarding measurement on critical areas with high geometrical discontinuities. A 3D Digital Image Correlation method is an optical method that overcomes the limitations of conventional methods and enables full-field displacement and strain measurement of geometrically complex structures. System Aramis, based on Digital Image Correlation method, is used for experimental analysis and numerical model verification in this paper. Investigated complex structure is sphere/cylinder junction on globe valve housing subjected to axial loading. The highest experimentally measured von Mises strain values around 0.15% are recorded on cylinder/sphere intersection. Von Mises strain values on cylindrical and spherical part are several times smaller than on intersection itself. It is important to emphasize that, to the authors best knowledge, this is the first paper showing experimental results of 3D full and strain field of geometrically complex structure (sphere/cylinder intersection) on the intersection itself on pressure equipment. It is proven that 3D Digital Image Correlation method is fast and versatile method for recording strain during loading of complex structures

Liver phospholipids fatty acids composition in response to different types of diets in rats of both sexes

Background: Dietary intake influence changes in fatty acids (FA) profiles in liver which plays a central role in fatty acid metabolism, triacylglycerol synthesis and energy homeostasis. We investigated the effects of 4-weeks treatment with milk-and fish-based diet, on plasma biochemical parameters and FA composition of liver phospholipids (PL) in rats of both sexes. Methods: Adult, 4 months old, Wistar rats of both sexes, were fed with different types of diets: standard, milk-based and fish-based, during 4 weeks. Analytical characterization of different foods was done. Biochemical parameters in plasma were determined. Fatty acid composition was analyzed by gas-chromatography. Statistical significance of FA levels was tested with two-way analysis of variance (ANOVA) using the sex of animals and treatment (type of diet) as factors on logarithmic or trigonometric transformed data. Results: Our results showed that both, milk-and fish-based diet, changed the composition and ratio of rat liver phospholipids FA, in gender-specific manner. Initially present sex differences appear to be dietary modulated. Although, applied diets changed the ratio of total saturated fatty acids (SFA), monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA), and effects were gender specific. Milk-based diet lowered SFA and elevated MUFA in males and increased PUFA in females vs. standard diet. The same diet decreased n-3, increased n-6 and n-6/n-3 ratio in males. Fish-based diet increased n-3, decreased n-6 and n-6/n-3 ratio vs. standard and milk-based diet in females. However, the ratio of individual FA in liver PL was also dietary-influenced, but with gender specific manner. While in females fish-based diet decreased AA (arachidonic acid) increased level of EPA (eicosapentaenoic acid), DPA (docosapentaenoic acid) and DHA (docosahexaenoic acid), the same diet elevated only DHA levels in males. Conclusion: Gender related variations in FA composition of rat liver PL were observed, and results have shown that those initial differences could be significantly modulated by the type of diet. Furthermore, the modulatory effects of milk-and fish-based diets on liver phospholipids FA profiles appeared to be sex-specific

The Effects of Aphid Traits on Parasitoid Host Use and Specialist Advantage

Specialization is a central concept in ecology and one of the fundamental properties of parasitoids. Highly specialized parasitoids tend to be more efficient in host-use compared to generalized parasitoids, presumably owing to the trade-off between host range and hostuse efficiency. However, it remains unknown how parasitoid host specificity and host-use depends on host traits related to susceptibility to parasitoid attack. To address this question, we used data from a 13-year survey of interactions among 142 aphid and 75 parasitoid species in nine European countries. We found that only aphid traits related to local resource characteristics seem to influence the trade-off between host-range and efficiency: more specialized parasitoids had an apparent advantage (higher abundance on shared hosts) on aphids with sparse colonies, ant-attendance and without concealment, and this was more evident when host relatedness was included in calculation of parasitoid specificity. More traits influenced average assemblage specialization, which was highest in aphids that are monophagous, monoecious, large, highly mobile (easily drop from a plant), without myrmecophily, habitat specialists, inhabit non-agricultural habitats and have sparse colonies. Differences in aphid wax production did not influence parasitoid host specificity and host-use. Our study is the first step in identifying host traits important for aphid parasitoid host specificity and host-use and improves our understanding of bottom-up effects of aphid traits on aphid-parasitoid food web structure

Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly

This paper presents a methodology for generating a fuzzy inference mechanism (FIM) for recognizing contact states within robotic part mating using active compliant motion. In the part mating process, significant uncertainties are inherently present. As a result it is pertinent that contact states recognition systems operating in such environment be able to make decisions on the contact state currently present in the process, based on data full of uncertainties and imprecision. In such conditions, implementation of fuzzy logic and interval inference brings significant robustness to the system. As a starting point for FIM generation, we use a quasi-static model of the mating force between objects. By applying Discrete Wavelet Transform to the signal generated using this model, we extract qualitative and representative features for classification into contact states. Thus, the obtained patterns are optimally classified using support vector machines (SVM). We exploit the equivalence of SVM and Takagi-Sugeno fuzzy rules based systems for generation of FIM for classification into contact states. In this way, crisp granulation of the feature space obtained using SVM is replaced by optimal fuzzy granulation and robustness of the recognition system is significantly increased. The information machine for contact states recognition that is designed using the given methodology simultaneously uses the advantages of creation of machine based on the process model and the advantages of application of FIM. Unlike the common methods, our approach for creating a knowledge base for the inference machine is neither heuristic, intuitive nor empirical. The proposed methodology was elaborated and experimentally tested using an example of a cylindrical peg in hole as a typical benchmark test

Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly

This paper presents a methodology for generating a fuzzy inference mechanism (FIM) for recognizing contact states within robotic part mating using active compliant motion. In the part mating process, significant uncertainties are inherently present. As a result it is pertinent that contact states recognition systems operating in such environment be able to make decisions on the contact state currently present in the process, based on data full of uncertainties and imprecision. In such conditions, implementation of fuzzy logic and interval inference brings significant robustness to the system. As a starting point for FIM generation, we use a quasi-static model of the mating force between objects. By applying Discrete Wavelet Transform to the signal generated using this model, we extract qualitative and representative features for classification into contact states. Thus, the obtained patterns are optimally classified using support vector machines (SVM). We exploit the equivalence of SVM and Takagi-Sugeno fuzzy rules based systems for generation of FIM for classification into contact states. In this way, crisp granulation of the feature space obtained using SVM is replaced by optimal fuzzy granulation and robustness of the recognition system is significantly increased. The information machine for contact states recognition that is designed using the given methodology simultaneously uses the advantages of creation of machine based on the process model and the advantages of application of FIM. Unlike the common methods, our approach for creating a knowledge base for the inference machine is neither heuristic, intuitive nor empirical. The proposed methodology was elaborated and experimentally tested using an example of a cylindrical peg in hole as a typical benchmark test

Matematičko modeliranje raspodele površinske hrapavosti veštačkog ćelijskog zida

The plant cell walls play an important role in defining the shape and size of the plant cell, matter flow regulation, mitigation of environmental influences and achievement of homeostasis, as well as in defense and protection against pathogens in plant tissues and organs. This paper presents an original approach to the establishment of the mathematical model based upon the former study dealing with the surface nano-roughness distribution of the model cell wall. The differential equation accompanied with the appropriate additional conditions, which describes such kind of distributions, has been formulated and presented. The developed model was tested using the already reported experimental data of an artificial cell wall, made of polysaccharides based on bacterial cellulose supplemented with xyloglucan and pectin (BCPX) that imitate properties of the natural cell wall. It has been demonstrated that proposed differential equation, has an analytical solution in the form of the normal Gaussian distribution, which describes the surface roughness of cell walls made of this material accurately.Ćelijski zidovi biljaka imaju značajnu ulogu u definisanju oblika i veličina biljnih ćelija, kao i regulaciji razmene materija, zaštiti ćelijskih tkiva i organa od patogenih klica, ublažavanje nepovoljnih uticaja okoline itd. U ovom radu je prikazan originalni pristup formiranju matematičkog modela za opisivanje raspodele površinske nano-hrapavosti veštačkog modela ćelijskog zida. Formulisana je diferencijalna jednačina sa odgovarajućim dodatnim uslovima, koja opisuje raspodele navedenog tipa Razvijeni model je testiran koristeći postojeće (objavljene) eksperimentalne podatke merenja površinske hrapavosti veštačkih model-materijala ćelijskih zidova, izrađenih od polisaharida zasnovanih na bakterijskoj celulozi oplemenjenoj ksiloglukanom i pektinom (BCPX), koji imitira svojstva prirodnih ćelijskih zidova. Potvrđeno je da predložena diferencijalna jednačina ima analitičko rešenje u formi Gausove funkcije, koja precizno opisuje hrapavost ćelijskih zidova napravljenih od ovog materijala

Influence of the dynamical image potential on the rainbows in ion channeling through short carbon nanotubes

We investigate the influence of the dynamic polarization of the carbon valence electrons on the angular distributions of protons channeled through short (11,9) single-wall carbon nanotubes at speeds of 3 and 5 a.u. (corresponding to the proton energies of 0.223 and 0.621 MeV), with the nanotube length varied from 0.1 to 0.3 mu m. The dynamic image force on protons is calculated by means of a two-dimensional hydrodynamic model for the nanotubes dielectric response, whereas the repulsive interaction with the nanotubes cylindrical wall is modeled by a continuum potential based on the Doyle-Turner interatomic potential. The angular distributions of channeled protons are generated by a computer simulation method using the numerical solution of the proton equations of motion in the transverse plane. Our analysis shows that the inclusion of the image interaction causes qualitative changes in the proton deflection function, giving rise to a number of rainbow maxima in the corresponding angular distribution. We propose that observations of those rainbow maxima could be used to deduce detailed information on the relevant interaction potentials, and consequently to probe the electron distribution inside carbon nanotubes