Changes of physical properties of glass surfaces exposed to KNO3 vapors

Modifications of glass surfaces were studied after exposure of samples to an atmosphere resulting from the decomposition of molten KNO3. The diffusion coefficient of K+ ions migrating into the surfaces of float glass and synthesized glasses doped with up to 5 wt% SnO2 was calculated by the Boltzmann-Matano technique. The Vickers hardness and the refractive index increase with exposure time. Infrared spectra show that the migration of K+ is responsible for an increase in the number of non-bridging oxygens in the exposed samples. The spectra of the synthesized glasses present evidences that their surfaces undergo crystallization during the exposure. All results lead to the conclusion that the presence of tin in the glasses hinders the diffusion of K+ ions, thus affecting the Vickers hardness, the refractive index and the infrared spectra. It is shown that the exposure method can be used as an alternative process to promote the K+ migration into glass surfaces. (c) 2006 Elsevier B.V. All rights reserved.

Diffusion coefficient of K+ in ion exchanged glasses calculated from the refractive index and the Vickers hardness profiles

The top faces of float glass samples were exposed to vapors resulting from the decomposition of KNO3 at 565 degrees C for up to 32 h. X-ray dispersive spectra (EDS) show that K+ ions migrate into the glass. The K+ concentration profile was obtained and its diffusion coefficient was calculated by the Boltzmann-Matano technique. The mean diffusion coefficient was approximately 10 X 10(-11) cm(2) s(-1). It was observed that the refractive index and the Vickers hardness decrease with the depth (after the removal of successive layers), and their profiles were thus obtained. These profiles enabled the calculation of the diffusion coefficient of K+ through the Boltzmann-Matano technique, with mean results ranging between 6 x 10(-11) and 30 x 10(-11) cm(2) s(-1). (c) 2006 Elsevier B.V. All rights reserved.

Physical properties of silicate glasses doped with SnO2

The presence of tin in the network of silicate glasses produces changes in several of their physico-chemical properties. Glasses with the composition (mol%) 22Na(2)O (.) 8CaO (.) 70SiO(2) containing up to 5 wt% of SnO2 were analyzed under several experimental techniques. Dilatometric measurements showed an increase of the glass transition temperature with increasing tin content, while the average thermal expansion coefficient is reduced. Vickers microhardness, density, and refractive index also increase with the tin content. Diffuse reflectance spectra in the infrared (DRIFT) showed that the presence of tin, even at low concentrations, is responsible for some structural changes since there is an increase of the bridging oxygen concentration. The doped glasses present a brown color and optical absorption spectra measurements are interpreted as being due to precipitation of tin in the form of colloidal particles during cooling of the melted glass. In the Na+ <-> K+ ion exchange process the presence of tin in the glass network hinders the diffusion of these ions. The diffusion coefficients of those ions were calculated by the Boltzmann-Matano technique, after concentration profiles obtained by EDS measurements. All results obtained present evidences that Sn4+ cation acts as a glass network former. (c) 2005 Elsevier B.V. All rights reserved.

Caracterização de superfícies de vidros expostas a vapores de KNO3

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

NiCrAlYSi涂层与镍基高温合金基体互扩散行为研究

采用电弧离子镀方法在镍基高温合金DZ125上沉积NiCrAlYSi涂层,通过对不同氧化时间后Al和Cr原子浓度分布曲线的分析,运用Boltzmann-matano方法,计算了Al和Cr元素在1373K分别加热0.5,2h和5h的互扩散系数,并拟合了这三个时间段的计算结果。结果表明:相同温度下,Al和Cr的互扩散系数分别随Al和Cr的原子浓度增加而增大。随氧化时间的延长,Al的互扩散系数随原子浓度的变化先增大然后基本不变,Cr的互扩散系数则逐渐减小;伴随着元素间互扩散行为的增强,涂层中的Al和Cr向基体扩散,基体合金元素Ni,Co,Mo,Ti和W则向涂层扩散,但涂层中Mo和Ti的含量相对较少。由于元素间互扩散行为,涂层中各元素的含量将趋向于更加均匀。

An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations

The Lattice-Boltzmann method (LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a state-of-the-art LBM solver such as Palabos, a user has to still manually write the program using library-supplied primitives. We propose an automated code generator for a class of LBM computations with the objective to achieve high performance on modern architectures. Few studies have looked at time tiling for LBM codes. We exploit a key similarity between stencils and LBM to enable polyhedral optimizations and in turn time tiling for LBM. We also characterize the performance of LBM with the Roofline performance model. Experimental results for standard LBM simulations like Lid Driven Cavity, Flow Past Cylinder, and Poiseuille Flow show that our scheme consistently outperforms Palabos-on average by up to 3x while running on 16 cores of an Intel Xeon (Sandybridge). We also obtain an improvement of 2.47x on the SPEC LBM benchmark.

Simple lattice Boltzmann model for traffic flows

A lattice Boltzmann model with 5-bit lattice for traffic flows is proposed. Using the Chapman-Enskog expansion and multi-scale technique, we obtain the higher-order moments of equilibrium distribution function. A simple traffic light problem is simulated by using the present lattice Boltzmann model, and the result agrees well with analytical solution.

A lattice Boltzmann method for KDV equation

We prepose a 5-bit lattice Boltzmann model for KdV equation. Using Chapman-Enskog expansion and multiscale technique, we obtained high order moments of equilibrium distribution function, and the 3rd dispersion coefficient and 4th order viscosity. The parameters of this scheme can be determined by analysing the energy dissipation.

A Semi-Quantitative Analysis of Essential Micronutrient in Folium Lycii Using Laser-Induced Breakdown Spectroscopy Technique

In this paper, the capabilities of laser-induced break down spectroscopy (LIBS) for rapid analysis to multi-component plant are illustrated using a 1064 nm laser focused onto the surface of folium lycii. Based on homogeneous plasma assumption, nine of essential micronutrients in folium lycii are identified. Using Saha equation and Boltzmann plot method electron density and plasma temperature are obtained, and the irrelative concentration (Ca, Mg, Al, Si, Ti, Na, K, Li, and Sr) are obtained employing a semi-quantitative method.

Ordinal Boltzmann machines for collaborative filtering

Collaborative filtering is an effective recommendation technique wherein the preference of an individual can potentially be predicted based on preferences of other members. Early algorithms often relied on the strong locality in the preference data, that is, it is enough to predict preference of a user on a particular item based on a small subset of other users with similar tastes or of other items with similar properties. More recently, dimensionality reduction techniques have proved to be equally competitive, and these are based on the co-occurrence patterns rather than locality. This paper explores and extends a probabilistic model known as Boltzmann Machine for collaborative filtering tasks. It seamlessly integrates both the similarity and cooccurrence in a principled manner. In particular, we study parameterisation options to deal with the ordinal nature of the preferences, and propose a joint modelling of both the user-based and item-based processes. Experiments on moderate and large-scale movie recommendation show that our framework rivals existing well-known methods.

Graph-induced restricted Boltzmann machines for document modeling

Discovering knowledge from unstructured texts is a central theme in data mining and machine learning. We focus on fast discovery of thematic structures from a corpus. Our approach is based on a versatile probabilistic formulation – the restricted Boltzmann machine (RBM) –where the underlying graphical model is an undirected bipartite graph. Inference is efficient document representation can be computed with a single matrix projection, making RBMs suitable for massive text corpora available today. Standard RBMs, however, operate on bag-of-words assumption, ignoring the inherent underlying relational structures among words. This results in less coherent word thematic grouping. We introduce graph-based regularization schemes that exploit the linguistic structures, which in turn can be constructed from either corpus statistics or domain knowledge. We demonstrate that the proposed technique improves the group coherence, facilitates visualization, provides means for estimation of intrinsic dimensionality, reduces overfitting, and possibly leads to better classification accuracy.

Learning entry profiles of children with autism from multivariate treatment information using restricted boltzmann machines

Entry profiles can be generated before children with Autism Spectrum Disorders (ASD) begin to traverse an intervention program. They can help evaluate the progress of each child on the dedicated syllabus in addition to enabling narrowing down the best intervention course over time. However, the traits of ASD are expressed in different ways in every individual affected. The resulting spectrum nature of the disorder makes it challenging to discover profiles of children with ASD. Using data from 491 children, traversing the syllabus of a comprehensive intervention program on iPad called TOBY Playpad, we learn the entry profiles of the children based on their age, sex and performance on their first skills of the syllabus. Mixed-variate restricted Boltzmann machines allow us to integrate the heterogeneous data into one model making it a suitable technique. The data based discovery of entry profiles may assist in developing systems that can automatically suggest best suitable paths through the syllabus by clustering the children based on the characteristics they present at the beginning of the program. This may open the pathway for personalised intervention.

Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spectrum reconstruction from a scattering measurement using the adjoint Boltzmann transport equation for photons

Quality control of medical radiological systems is of fundamental importance, and requires efficient methods for accurately determine the X-ray source spectrum. Straightforward measurements of X-ray spectra in standard operating require the limitation of the high photon flux, and therefore the measure has to be performed in a laboratory. However, the optimal quality control requires frequent in situ measurements which can be only performed using a portable system. To reduce the photon flux by 3 magnitude orders an indirect technique based on the scattering of the X-ray source beam by a solid target is used. The measured spectrum presents a lack of information because of transport and detection effects. The solution is then unfolded by solving the matrix equation that represents formally the scattering problem. However, the algebraic system is ill-conditioned and, therefore, it is not possible to obtain a satisfactory solution. Special strategies are necessary to circumvent the ill-conditioning. Numerous attempts have been done to solve this problem by using purely mathematical methods. In this thesis, a more physical point of view is adopted. The proposed method uses both the forward and the adjoint solutions of the Boltzmann transport equation to generate a better conditioned linear algebraic system. The procedure has been tested first on numerical experiments, giving excellent results. Then, the method has been verified with experimental measurements performed at the Operational Unit of Health Physics of the University of Bologna. The reconstructed spectra have been compared with the ones obtained with straightforward measurements, showing very good agreement.

Imaging and modeling of pore scale processes in porous media using X-ray computed tomography and lattice Boltzmann solver

In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.