Coupled thermal, structural and vibrational analysis of a hypersonic engine for flight test

This paper describes a relatively simple and quick method for implementing aerodynamic heating models into a finite element code for non-linear transient thermal-structural and thermal-structural-vibrational analyses of a Mach 10 generic HyShot scramjet engine. The thermal-structural-vibrational response of the engine was studied for the descent trajectory from 60 to 26 km. Aerodynamic heating fluxes, as a function of spatial position and time for varying trajectory points, were implemented in the transient heat analysis. Additionally, the combined effect of varying dynamic pressure and thermal loads with altitude was considered. This aero-thermal-structural analysis capability was used to assess the temperature distribution, engine geometry distortion and yielding of the structural material due to aerodynamic heating during the descent trajectory, and for optimising the wall thickness, nose radius of leading edge, etc. of the engine intake. A structural vibration analysis was also performed following the aero-thermal-structural analysis to determine the changes in natural frequencies of the structural vibration modes that occur at the various temperatures associated with the descent trajectory. This analysis provides a unique and relatively simple design strategy for predicting and mitigating the thermal-structural-vibrational response of hypersonic engines. (C) 2006 Elsevier SAS. All rights reserved.

Thermal, structural and optical properties of Al(2)CoO(4)-Crocoite composite nanoparticles used as pigments

Al(2)CoO(4)-PbCrO(4) and Al(2)CoO(4)-Pb(2)CrO(5) crystalline powders in different proportions were obtained by the polymeric precursor method. Differential scanning calorimetry (DSC) and thermogravimetry (TG) techniques were used to accurately characterize the distinct thermal events occurring during synthesis. The TG and DSC results revealed a series of overlapping decomposition reactions due to different exothermal events, which were identified as H(2)O and NO(x) elimination and polymer pyrolysis. The X-ray diffraction patterns of the xAl(2)CoO(4)-(1 - x)PbCrO(4) and xAl(2)CoO(4)-(1 - x)Pb(2)CrO(5) mixed compounds, with x = 1, 0.75, 0.5, 0.25 and 0, were obtained in the crystalline form with their respective phases, and proved consistent with the nominal compositions. The synthesis of these two systems yielded nine different colors and shades.

Zn(0.97)M(0.03)O (M = Co, Fe, and V) pigments: thermal, structural, and optical characterization

Zinc oxide is a widely used white inorganic pigment. Transition metal ions are used as chromophores and originate the ceramic pigments group. In this context, ZnO particles doped with Co, Fe, and V were synthesized by the polymeric precursors method, Pechini method. Differential scanning calorimetry (DSC) and thermogravimetry (TG) techniques were used to accurately characterize the distinct thermal events occurring during synthesis. The TG and DSC results revealed a series of decomposition temperatures due to different exothermal events, which were identified as H(2)O elimination, organic compounds degradation and phase formation. The samples were structurally characterized by X-Ray diffractometry revealing the formation of single phase, corresponding to the crystalline matrix of ZnO. The samples were optically characterized by diffuse reflectance measurements and colorimetric coordinates L*, a*, b* were calculated for the pigment powders. The pigment powders presented a variety of colors ranging from white (ZnO), green (Zn(0.97)Co(0.03)O), yellow (Zn(0.97)Fe(0.03)O), and beige (Zn(0.97)V(0.03)O).

Thermal, structural and optical properties of new tungsten lead-pyrophosphate glasses

Crystalline lead-pyrophosphate precursor was prepared in aqueous solution from lead nitrate and phosphoric acid and characterized by X-ray diffraction, thermogravimetry and Raman scattering. This crystalline lead-phosphate was then used to prepare glass samples in the binary system Pb(2)P(2)O(7)-WO(3). Dependence of WO(3) content on thermal, structural and optical properties were investigated by thermal analysis (DSC), Raman spectroscopy, UV-visible and near-infrared absorption and M-Line technique to access refractive index values. Incorporation of WO(3) in the lead-pyrophosphate matrix enhances the glass transition temperature and thermal stability against devitrification, favors formation of P-O-W bonds and WO(6) clusters. In addition, optical properties are strongly modified with a redshift of the optical bandgap with WO(3) incorporation as well as an increase of the refractive index from 1.89 to 2.05 in the visible. (C) 2011 Elsevier B.V. All rights reserved.

The role of Bi2O3 on the thermal, structural, and optical properties of tungsten-phosphate glasses

Glasses in the ternary system (70 - x)NaPO3-30WO 3-xBi2O3, with x = 0-30 mol %, were prepared by the conventional melt-quenching technique. X-ray diffraction (XRD) measurements were performed to confirm the noncrystalline nature of the samples. The influence of the Bi2O3 on the thermal, structural, and optical properties was investigated. Differential scanning calorimetry analysis showed that the glass transition temperature, Tg, increases from 405 to 440 C for 0 ≤ x ≤ 15 mol % and decreases to 417 C for x = 30 mol %. The thermal stability against devitrification decreases from 156 to 67 C with the increase of the Bi2O3 content. The structural modifications were studied by Raman scattering, showing a bismuth insertion into the phosphate chains by Bi-O-P linkage. Furthermore, up to 15 mol % of Bi 2O3 formation of BiO6 clusters is observed, associated with Bi-O-Bi linkage, resulting in a progressive break of the linear phosphate chains that leads to orthophosphate Q0 units. The linear refractive index, n0, was measured using the prism-coupler technique at 532, 633, and 1550 nm, whereas the nonlinear (NL) refractive index, n 2 was measured at 1064 nm using the Z-scan technique. Values of 1.58 ≤ n0 ≤ 1.88, n2 ≥ 10-15 cm 2/W and NL absorption coefficient, α2 ≤ 0.01 cm/GW, were determined. The linear and NL refractive indices increase with the increase of the Bi2O3 concentration. The large values of n0 and n2, as well as the very small α2, indicate that these materials have large potential for all-optical switching applications in the near-infrared. © 2012 American Chemical Society.

A simple procedure for the preparation of laponite and thermoplastic starch nanocomposites: Structural, mechanical, and thermal characterizations

The aim of this article is to propose advances for the preparation of hybrid nanocomposites prepared by the combination of intercalation from solution and melt-processing methods. This research investigates the effect of the laponite RDS content on the thermal, structural, and mechanical properties of thermoplastic starch (TPS). X-ray diffraction was performed to investigate the dispersion of the laponite RDS layers into the TPS matrix. The results show good nanodispersion, intercalation, and exfoliation of the clay platelets, indicating that these composites are true nanocomposites. The presence of laponite RDS also improves the thermal stability and mechanical properties of the TPSmatrix due to its reinforcement effect which was optimized by the high degree of exfoliation of the clay. Thus, these results indicate that the exfoliated TPS-laponite nanocomposites have great potential for industrial applications and, more specifically, in the packaging field. © The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Structural, thermal and optical properties of CaBO and CaLiBO glasses doped with Eu3+

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Preparation of glasses and glass ceramics of heavy metal oxides containing silver: optical, structural and electrochemical properties

Silver containing heavy metal oxide glasses and glass ceramics of the system WO3-SbPO4-PbO-AgCl with different AgCl contents have been prepared and their thermal, structural and optical properties characterized. Glass ceramics containing metallic silver nanoparticles have been prepared by annealing glass samples at temperatures above the glass transition and analyzed by transmission electron microscopy and energy dispersive X-ray microanalysis. The presence of the metallic clusters has been also confirmed by the observation of a surface plasmon resonance band in the visible range. Cyclic voltammetric measurements indicated the presence of metallic silver into the glasses, even before to perform the thermal treatment.

Dendrimer intercalation in layered double hydroxides

New organic/inorganic (O/I) hybrid assemblies based on Layered Double Hydroxide (LDH) with polyamide amine dendrimer (PAMAM, generation -0.5 and generation +0.5) were prepared by two different routes using either the direct coprecipitation at constant pH or the anion exchange procedure in double surfactant S(+)S(-) phases. The obtained materials were characterized by means of powder X-ray diffraction, thermal gravimetric analysis associated with mass spectrometry, and Fourier-transform infrared spectroscopy. X-ray powder diffraction pattern of the O/I LDH assembly exhibit characteristic profiles of LDH-based materials with basal spacing depending on the nature of the dendrimer. Indeed, for both synthetic procedures, interleaved PAMAM -0.5 gives rise to an interlayer space in agreement with a perpendicular molecular arrangement against the layer of the host structure. For PAMAM+0.5, considering its spherical dimension, a much smaller basal spacing was observed. This observation was interpreted as shrinkage of the molecule to accommodate the interlayer LDH gap, which was rendered possible by the bond angle twisting within PAMAM-0.5. FTIR spectra confirm the presence of both moieties inside both Zn(2)Al/PAMAM G-0.5 and Zn(2)Al/PAMAM G+0.5 assemblies. Finally, thermal analysis associated with mass spectrometry confirm this composition, and in situ temperature XRD data reveal that the highly constrained arrangement for the generation +0.5 is not accompanied by a gain in thermal structural stability; in fact, the assembly prepared from PAMAM -0.5 is more stable. Both O/I PAMAM LDH assemblies constitute well-defined materials which are candidate for catalytic applications.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Influência dos precursores de prata no crescimento de nanopartículas metálicas em vidros óxidos de metais pesados

In this work we report a systematic study on the influence of the chemical nature of silver precursors on the formation of glass-ceramics from oxide glasses. Thermal, structural and optical properties were analyzed as a function of the glass composition. Controlled crystallization was achieved by thermal treatment of the samples above glass transition. The influence of time of treatment on both nanoparticle growth and optical properties of the samples was studied by transmission electron microscopy and UV-Vis spectroscopy, respectively. Results showed that only glasses containing AgCl and AgNO3 led to glass-ceramics growth after thermal treatment.

Lightweight, liquid-cooled, direct-drive generator for highpower wind turbines: motivation, concept, and performance

Thesis: A liquid-cooled, direct-drive, permanent-magnet, synchronous generator with helical, double-layer, non-overlapping windings formed from a copper conductor with a coaxial internal coolant conduit offers an excellent combination of attributes to reliably provide economic wind power for the coming generation of wind turbines with power ratings between 5 and 20MW. A generator based on the liquid-cooled architecture proposed here will be reliable and cost effective. Its smaller size and mass will reduce build, transport, and installation costs. Summary: Converting wind energy into electricity and transmitting it to an electrical power grid to supply consumers is a relatively new and rapidly developing method of electricity generation. In the most recent decade, the increase in wind energy’s share of overall energy production has been remarkable. Thousands of land-based and offshore wind turbines have been commissioned around the globe, and thousands more are being planned. The technologies have evolved rapidly and are continuing to evolve, and wind turbine sizes and power ratings are continually increasing. Many of the newer wind turbine designs feature drivetrains based on Direct-Drive, Permanent-Magnet, Synchronous Generators (DD-PMSGs). Being low-speed high-torque machines, the diameters of air-cooled DD-PMSGs become very large to generate higher levels of power. The largest direct-drive wind turbine generator in operation today, rated just below 8MW, is 12m in diameter and approximately 220 tonne. To generate higher powers, traditional DD-PMSGs would need to become extraordinarily large. A 15MW air-cooled direct-drive generator would be of colossal size and tremendous mass and no longer economically viable. One alternative to increasing diameter is instead to increase torque density. In a permanent magnet machine, this is best done by increasing the linear current density of the stator windings. However, greater linear current density results in more Joule heating, and the additional heat cannot be removed practically using a traditional air-cooling approach. Direct liquid cooling is more effective, and when applied directly to the stator windings, higher linear current densities can be sustained leading to substantial increases in torque density. The higher torque density, in turn, makes possible significant reductions in DD-PMSG size. Over the past five years, a multidisciplinary team of researchers has applied a holistic approach to explore the application of liquid cooling to permanent-magnet wind turbine generator design. The approach has considered wind energy markets and the economics of wind power, system reliability, electromagnetic behaviors and design, thermal design and performance, mechanical architecture and behaviors, and the performance modeling of installed wind turbines. This dissertation is based on seven publications that chronicle the work. The primary outcomes are the proposal of a novel generator architecture, a multidisciplinary set of analyses to predict the behaviors, and experimentation to demonstrate some of the key principles and validate the analyses. The proposed generator concept is a direct-drive, surface-magnet, synchronous generator with fractional-slot, duplex-helical, double-layer, non-overlapping windings formed from a copper conductor with a coaxial internal coolant conduit to accommodate liquid coolant flow. The novel liquid-cooling architecture is referred to as LC DD-PMSG. The first of the seven publications summarized in this dissertation discusses the technological and economic benefits and limitations of DD-PMSGs as applied to wind energy. The second publication addresses the long-term reliability of the proposed LC DD-PMSG design. Publication 3 examines the machine’s electromagnetic design, and Publication 4 introduces an optimization tool developed to quickly define basic machine parameters. The static and harmonic behaviors of the stator and rotor wheel structures are the subject of Publication 5. And finally, Publications 6 and 7 examine steady-state and transient thermal behaviors. There have been a number of ancillary concrete outcomes associated with the work including the following. X Intellectual Property (IP) for direct liquid cooling of stator windings via an embedded coaxial coolant conduit, IP for a lightweight wheel structure for lowspeed, high-torque electrical machinery, and IP for numerous other details of the LC DD-PMSG design X Analytical demonstrations of the equivalent reliability of the LC DD-PMSG; validated electromagnetic, thermal, structural, and dynamic prediction models; and an analytical demonstration of the superior partial load efficiency and annual energy output of an LC DD-PMSG design X A set of LC DD-PMSG design guidelines and an analytical tool to establish optimal geometries quickly and early on X Proposed 8 MW LC DD-PMSG concepts for both inner and outer rotor configurations Furthermore, three technologies introduced could be relevant across a broader spectrum of applications. 1) The cost optimization methodology developed as part of this work could be further improved to produce a simple tool to establish base geometries for various electromagnetic machine types. 2) The layered sheet-steel element construction technology used for the LC DD-PMSG stator and rotor wheel structures has potential for a wide range of applications. And finally, 3) the direct liquid-cooling technology could be beneficial in higher speed electromotive applications such as vehicular electric drives.

Blue, Green and Orange-Red Light Emitting Polymers: Synthesis, Characterization and Prospects of Applications in Optoelectronic Devices

Light emitting polymers (LEPs) are considered as the second generation of conducting polymers. A Prototype LEP device based on electroluminescence emission of poly(p-phenylenevinylene) (PPV) was first assembled in 1990. LEPs have progressed tremendously over the past 20 years. The development of new LEP derivatives are important because polymer light emitting diodes (PLEDs) can be used for the manufacture of next-generation displays and other optoelectronic applications such as lasers, photovoltaic cells and sensors. Under this circumstance, it is important to understand thermal, structural, morphological, electrochemical and photophysical characteristics of luminescent polymers. In this thesis the author synthesizes a series of light emitting polymers that can emit three primary colors (RGB) with high efficiency

Preparação de vidros e vitrocerâmicas de óxidos de metais pesados contendo prata: propriedades ópticas, estruturais e eletroquímicas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of the network former on the properties of magnesium spinels

Undoped and/or doped with 1 mol% of Co2+ Mg2TiO4 and Mg2SnO4 powders were synthesized by the polymeric precursor method. The influence of the network former (Sn4+ or Ti4+) on the thermal, structural and optical properties was investigated. The recorded mass losses are due to the escape of water and adsorbed gases and to the elimination of the organic matter. Mg2TiO4 crystallizes at lower temperatures and also presents more ordered structure with a smaller unit call and having more intense green color than Mg2SnO4 has.