Multiple support excitations of open-plane frames by a filtered white noise and soil-structure interaction

Seismic structural design is essentially the estimation of structural response to a forced motion, which may be deterministic or stochastic, imposed on the ground. The assumption that the same ground motion acts at every point of the base of the structure (or at every support) is not always justifiable; particularly in case of very large structures when considerable spatial variability in ground motion can exist over significant distances example long span bridges. This variability is partly due to the delay in arrival of the excitation at different supports (which is called the wave passage effect) and due to heterogeneity in the ground medium which results in incoherency and local effects. The current study examines the influence of the wave passage effect (in terms of delay in arrival of horizontal ground excitation at different supports and neglecting transmission through the structure) on the response of a few open-plane frame building structures with soil-structure interaction. The ground acceleration has been modeled by a suitably filtered white noise. As a special case, the ground excitation at different supports has also been treated as statistically independent to model the extreme case of incoherence due to local effects and due to modifications to the ground motion resulting from wave reflections and refractions in heterogeneous soil media. The results indicate that, even for relatively short spanned building frames, wave passage effect can be significant. In the absence of soil-structure interaction, it can significantly increase the root mean square (rms) value of the shear in extreme end columns for the stiffer frames but has negligible effect on the flexible frames when total displacements are considered. It is seen that pseudo-static displacements increasingly contribute to the rms value of column shear as the time delay increases both for the stiffer and for the more flexible frames. When soil-structure interaction is considered, wave passage effect (in terms of total displacements) is significant only for low soil shear modulus, G. values (where soil-structure interaction significantly lowers the fundamental frequency) and for stiff frames. The contribution of pseudo-static displacement to these rms values is found to decrease with increase in G. In general, wave passage effect for most interactive frames is insignificant compared to the attenuating effect a decrease in G, has on the response of the interactive structure to uniform support excitation. When the excitations at different supports are statistically independent, it is seen that for both the stiff and flexible frames, the rms value of the column shear in extreme end columns is several times larger (more for the stiffer frames) than the value corresponding to uniform base excitation with the pseudo-static displacements contributing over 99% of the rms value of column shear. Soil-structure interaction has an attenuating effect on the rms value of the column shear, the effect decreasing with increase in G,. Here too, the pseudo-static displacements contribute very largely to the column shear. The influence of the wave passage effect on the response of three 2-bay frames with and without soil-structure interaction to a recorded horizontal accelerogram is also examined. (C) 2010 Elsevier Ltd. All rights reserved.

Reducing the babel in plant volatile communication: using the forest to see the trees

While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.

Support theorems on R-n and non-compact symmetric spaces

We consider convolution equations of the type f * T = g, where f, g is an element of L-P (R-n) and T is a compactly supported distribution. Under natural assumptions on the zero set of the Fourier transform of T, we show that f is compactly supported, provided g is. Similar results are proved for non-compact symmetric spaces as well. (C) 2010 Elsevier Inc. All rights reserved.

Strong metal-support interaction in nickel/niobium pentoxide and nickel/titania catalysts

EXAFS studies of Ni/Nb20, and Ni/Ti02 catalysts reduced at 773 K show evidence for the presence of a short Ni-Nb (Ti) and a long Ni-Nb (Ti) bond. The results provide evidence for considerable structural reorganization of the support in the vicinity of the Ni particles.

Easily Diagnosable Sequential Machines

This correspondence throws some light into the area of easily diagnosable machines. Given the behavior of a sequential machine in terms of a state table it explores the possibilities of designing a structure, that facilitates easy diagnosis of faults. The objective is achieved through structural decomposition which has already claimed to produce simpler physical realization.

Support-Dependent Activity of Noble Metal Substituted Oxide Catalysts for the Water Gas Shift Reaction

The water gas shift reaction was carried out over noble metal ion substituted nanocrystalline oxide catalysts with different supports. Spectroscopic studies of the catalysts before and after the reaction showed different surface phenomena occurring over the catalysts. Reaction mechanisms were proposed based upon the surface processes and intermediates formed. The dual site mechanism utilizing the oxide ion vacancies for water dissociation and metal ions for CO adsorption was proposed to describe the kinetics of the reaction over the reducible oxides like CeO2. A mechanism based on the interaction of adsorbed CO and the hydroxyl group was proposed for the reaction over ZrO2. A hybrid mechanism based on oxide ion vacancies and surface hydroxyl groups was proposed for the reaction over TiO2. The deactivation of the catalysts was also found to be support dependent. Kinetic models for both activation and deactivation were proposed. (C) 2010 American Institute of Chemical Engineers AIChE J, 56: 2662-2676, 2010

Anatase-rutile transformation in Fe/TiO2, Th/TiO2 and Cu/TiO2 catalysts and its possible role in metal-support interaction

Based on in-situ Mossbauer and X-ray diffraction studies, it is shown that in the Fe/TiO2 catalyst, the anatase-rutile transformation of the TiO2 support is facilitated by the Fe2+ ions formed during the reduction. The transformation occurs at lower temperatures in Th/TiO2 and Cu/TiO2 compared to pure TiO2. In general, the transformation of anatase to rutile seems to occur at or below the temperature (approximately 770 K) at which strong-metal-support-interaction manifests itself.

Mesoporous Carbon and Poly(3,4-ethylenedioxythiophene) Composite as Catalyst Support for Polymer Electrolyte Fuel Cells

In situ polymerization of 3,4-ethylenedioxythiophene with sol-gel-derived mesoporous carbon (MC) leading to a new composite and its subsequent impregnation with Pt nanoparticles for application in polymer electrolyte fuel cells (PEFCs) is reported. The composite exhibits good dispersion and utilization of platinum nanoparticles akin to other commonly used microporous carbon materials, such as carbon black. Pt-supported MC-poly(3,4-ethylenedioxythiophene) (PEDOT) composite also exhibits promising electrocatalytic activity toward oxygen reduction reaction, which is central to PEFCs. The PEFC with Pt-loaded MC-PEDOT support exhibits 75% of enhancement in its power density in relation to the PEFC with Pt-loaded pristine MC support while operating under identical conditions. It is conjectured that Pt-supported MC-PEDOT composite ameliorates PEFC performance/durability on repetitive potential cycling. (C) 2010 The Electrochemical Society. DOI: 10.1149/1.3486172] All rights reserved.

An electron spectroscopic study of the adsorption of nitrogen on a Ni/TiO2 catalyst prepared in situ in the spectrometer: evidence for dissociative adsorption in the strong-metal-support-interaction (SMSI) state

Nitrogen is dissociatively adsorbed on an annealed Ni/TiO2 surface just as on a Ti–Ni alloy surface while it is molecularly adsorbed on a Ni/Al2O3 surface.

Influence of an additional discrete elastic support on the stability of a Leipholz column

The stability characteristics of a conservatively loaded structure are expected to improve if additional supports are provided to the structure. The same, however, may not be said of a non-conservatively loaded structure; several factors, such as the location and stiffness of supports, type of structure and loading, have a significant influence on the stability characteristics. The influence of an arbitrarily located elastic support on the stability characteristics of a Leipholz column is examined.

Minimizing total completion time on batch processing machines

We study the problem of minimizing total completion time on single and parallel batch processing machines. A batch processing machine is one which can process up to B jobs simultaneously. The processing time of a batch is equal to the largest processing time among all jobs in the batch. This problem is motivated by burn-in operations in the final testing stage of semiconductor manufacturing and is expected to occur in other production environments. We provide an exact solution procedure for the single-machine problem and heuristic algorithms for both single and parallel machine problems. While the exact algorithms have limited applicability due to high computational requirements, extensive experiments show that the heuristics are capable of consistently obtaining near-optimal solutions in very reasonable CPU times.

Strong metal-support interaction in Ni/TiO2 catalysts: in situ EXAFS and related studies

In situ EXAFS and X-ray diffraction investigations of Ni/TiO2 catalysts show that NiTiO3 is formed as an intermediate during calcination of catalyst precursors prepared by the wet-impregnation method; the intermediate is not formed when ion-exchange method is used for the preparation. On hydrogen reduction, NiTiO3 gives rise to Ni particles dispersed in the TiO2(rutile) matrix. The occurrence of the anatase-rutile transformation of the TiO2 support, the formation and subsequent decomposition/reduction of NiTiO3 as well as the unique interface properties of the Ni particles are all factors of importance in giving rise to metal-support interaction. Active TiO2(anatase) prepared from gel route gives an additional species involving Ni3+.

Support vector machine for evaluating seismic-liquefaction potential using shear wave velocity

The use of the shear wave velocity data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because both shear wave velocity and liquefaction resistance are similarly influenced by many of the same factors such as void ratio, state of stress, stress history and geologic age. In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data. In this approach, an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set. Here SVM has been used as a classification tool to predict liquefaction potential of a soil based on shear wave velocity. The dataset consists the information of soil characteristics such as effective vertical stress (sigma'(v0)), soil type, shear wave velocity (V-s) and earthquake parameters such as peak horizontal acceleration (a(max)) and earthquake magnitude (M). Out of the available 186 datasets, 130 are considered for training and remaining 56 are used for testing the model. The study indicated that SVM can successfully model the complex relationship between seismic parameters, soil parameters and the liquefaction potential. In the model based on soil characteristics, the input parameters used are sigma'(v0), soil type. V-s, a(max) and M. In the other model based on shear wave velocity alone uses V-s, a(max) and M as input parameters. In this paper, it has been demonstrated that Vs alone can be used to predict the liquefaction potential of a soil using a support vector machine model. (C) 2010 Elsevier B.V. All rights reserved.