3D-FE-Analysis of CT-specimens including viscoplastic material behavior and nonlocal damage

In order to describe the time-dependent inelastic behavior of steel structures up to failure, a material model is developed within the framework of thermodynamics considering viscoplastic material behavior, isotropic hardening, softening, and isotropic ductile damage. Since softening and damage lead to localization of deformations, the model is extended by a non-local implicit gradient formulation. An additional gradient equation is formulated for the local damage variable in order to achieve results independent of the finite-element discretization. The approach is verified by 3D-structural analysis of CT-specimens.     

Sound Velocity of Kaolin in the Temperature Range from 20 °C to 1100 °C

The sound velocity of Sedlec kaolin during heating from 20 °C to 1100 °C was investigated by modulated force thermomechanical analysis (mf-TMA). In the interval from 20 °C to 250 °C, the sound velocity increases which can be explained by liberation of the water molecules from pores and micropores. Dehydroxylation (450 °C to 650 °C) presents itself with a decrease of the sound velocity. After dehydroxylation, a two-step increase of the sound velocity was observed. The first step of the increase of the sound velocity is due to solid-state sintering at low temperatures. The second step starts at 950 °C as a consequence of the collapse of the metakaolinite structure. After the maximum, a steep increase of the sound velocity follows as a result of solid-state sintering.     

An adaptive technique for content-based image retrieval

We discuss an adaptive approach towards Content-Based Image Retrieval. It is based on the Ostensive Model of developing information needs—a special kind of relevance feedback model that learns from implicit user feedback and adds a temporal notion to relevance. The ostensive approach supports content-assisted browsing through visualising the interaction by adding user-selected images to a browsing path, which ends with a set of system recommendations. The suggestions are based on an adaptive query learning scheme, in which the query is learnt from previously selected images. Our approach is an adaptation of the original Ostensive Model based on textual features only, to include content-based features to characterise images. In the proposed scheme textual and colour features are combined using the Dempster-Shafer theory of evidence combination. Results from a user-centred, work-task oriented evaluation show that the ostensive interface is preferred over a traditional interface with manual query facilities. This is due to its ability to adapt to the user's need, its intuitiveness and the fluid way in which it operates. Studying and comparing the nature of the underlying information need, it emerges that our approach elicits changes in the user's need based on the interaction, and is successful in adapting the retrieval to match the changes. In addition, a preliminary study of the retrieval performance of the ostensive relevance feedback scheme shows that it can outperform a standard relevance feedback strategy in terms of image recall in category search.     

The morphology and substructure of {225}F martensite in an Fe−Mn−Cr−C alloy

A transmission electron microscopy and diffraction study of martensite plates in an Fe-3 pct Mn-3 pct Cr-1 pct C alloy was carried out with particular attention to details of the martensite substructure. A corresponding optical metallographic study of plate morphology was made. A variability in martensite substructure was observed from plate to plate, although a (252)_F ^* plate was generally associated with (112)_B transformation twins and {111}_F stacking faults. The particular (111)_F fault variant gave rise to a wedge-shaped plate morphology. Planar {101}_B inhomogeneities were frequently observed in the martensite, and most of these appear to be derived from austenite stacking faults. In general, more than one type of inhomogeneity was observed in a single martensite plate and the “typical” plate substructure was rather difficult to characterize, although the habit plane was found invariably to be (252)_F.     

Toxicity increases in ice containing monochlorophenols upon photolysis: environmental consequences

The toxic effects of photoproducts formed upon the photolysis of 2- and 4-chlorophenol (CP) frozen solutions in polycrystalline ice phase were determined with a bacterial luminescence test (Vibrio fisheri), and in vitro biomarker assay for dioxin-like effects (inductions of AhR-dependent luciferase in H4IIE-luc cells) and compared to the toxic effects of products of the same photoreaction in aquatic phase. Coupling photoproducts formed in ice samples (3'-chlorobiphenyl-2,4'-diol and 3-chlorobiphenyl-2,2'-diol from 2-CP photolysis and 5-chlorobiphenyl-2,4'-diol from 4-CP photolysis) were found to be more toxic to V. fisheri than parent CPs and elicited significant inductions of dioxin-like effects (the effective concentrations EC50 approximately 3 x 10(-5) mol L(-1) corresponded to known weaker ligands of AhR, such as nonplanar polychlorinated biphenyls or polycyclic aromatic hydrocarbons). To complete the picture, a photoproduct formed from 4-CP (5-chlorobiphenyl-2,4'-diol) was synthesized, and a detailed toxicity assessment with purified compound confirmed the results obtained with irradiated samples. Our findings support a recently proposed model according to which solar radiation can trigger the formation of new types of organic pollutants in polar ice or tropospheric ice cloud particles, presenting possibly greater risk to the environment than the parent compounds.     

Basic theorem as representation of heterogeneous concept lattices

We propose a method for representing heterogeneous concept lattices as classical concept lattices. Particularly, we describe a transformation of heterogeneous formal context into a binary one, such that corresponding concept lattices will be isomorphic. We prove the correctness of this transformation by the basic theorem for heterogeneous as well as classical concept lattices.     

Prediction of hopper discharge rate using combined discrete element method and artificial neural network

An Artificial Neural Network (ANN) was developed to predict the mass discharge rate from conical hoppers. By employing Discrete Element Method (DEM), numerically simulated flow rate data from different internal angles (20°–80°) hoppers were used to train the model. Multi-component particle systems (binary and ternary) were simulated and mass discharge rate was estimated by varying different parameters such as hopper internal angle, bulk density, mean diameter, coefficient of friction (particle-particle and particle-wall) and coefficient of restitution (particle-particle and particle-wall). The training of ANN was accomplished by feed forward back propagation algorithm. For validation of ANN model, the authors carried out 22 experimental tests on different mixtures (having different mean diameter) of spherical glass beads from different angle conical hoppers (60° and 80°). It was found that mass discharge rate predicted by the developed neural network model is in a good agreement with the experimental discharge rate. Percentage error predicted by ANN model was less than ±13%. Furthermore, the developed ANN model was also compared with existing correlations and showed a good agreement.     

Approximation schemes for load balanced clustering in wireless sensor networks

Clustering sensor nodes is an efficient technique to improve scalability and life time of a wireless sensor network (WSN). However, in a cluster based WSN, the leaders (cluster heads) consume more energy due to some extra load for various activities such as data collection, data aggregation, and communication of the aggregated data to the base station. Therefore, balancing the load of the cluster heads is a crucial issue for the long run operation of the WSNs. In this paper, we first present a load balanced clustering scheme for wireless sensor networks. We show that the algorithm runs in O(nlogn) time for n sensor nodes. We prove that the algorithm is optimal for the case in which the sensor nodes have equal load. We also show that it is a polynomial time 2-approximation algorithm for the general case, i.e., when the sensor nodes have variable load. We finally improve this algorithm and propose a 1.5-approximation algorithm for the general case. The experimental results show the efficiency of the proposed algorithm in terms of the load balancing of the cluster heads, execution time, and the network life.     

Simultaneous photoreductive removal of copper (II) and selenium (IV) under visible light over spherical binary oxide photocatalyst

Waste water of copper mines and copper processing plant contains both copper and selenium ions with other contaminants. In this paper simultaneous photoreductive removal of copper (II) and selenium (IV) is studied for the first time using spherical binary oxide photocatalysts under visible light. All the synthesized materials are found to be mesoporous in nature with reasonably high surface area. Among a range of hole scavengers, only EDTA (ethylene diamine tetraacetic acid) and formic acid are found to be the most active for the reduction reaction. A comparative study is carried out using both the hole scavengers varying reaction time, concentration, pH etc. For a single contaminant, EDTA is found to be the best for Cu(II) reduction whereas formic acid is the best for Se(IV) reduction. In a mixed solution both EDTA and formic acid perform very well under visible light irradiation. Highest photocatalytic reduction in a mixed solution is observed at pH 3. Among all the synthesized materials, TiZr-10 performs as the best photocatalyst for both Cu(II) and Se(IV) reduction. However under UV light, Degussa P25 performs slightly better than TiZr-10. Present study shows that 100 ppm of mixed solution can be removed under visible light in 40 min of reaction using TiZr-10 as catalyst. Photodeposited material is found to be copper selenide rather than pure copper and selenium metal. This indicates that the waste water containing copper and selenium ions can be efficiently treated under visible or solar light.