345 resultados para shape modeling
Resumo:
Experimental analyses of surface oscillations are reported in acoustically levitated, radiatively heated bicomponent droplets with one volatile and other being nonvolatile. Two instability pathways are observed: one being acoustically driven observed in low-vapor pressure fluid droplets and other being boiling driven observed in high-vapor pressure fluid droplets. The first pathway shows extreme droplets deformation and subsequent breakup by acoustic pressure and externally supplied heat. Also transition of instabilities from acoustically activated shape distortion regime to thermally induced boiling regime is observed with increasing concentration of volatile component in bicomponent droplets. Precursor phases of instabilities are investigated using Legendre's polynomial.
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Power densities required to operate active-matrix organic-light-emitting diode (AMOLED) based displays for high luminance applications, lead to temperature rise due to self heating. Temperature rise leads to significant degradation and consequent reduction in life time. In this work numerical techniques based computational fluid dynamics (CFD) is used to determine the temperature rise and its distribution for an AMOLED based display for a given power density and size. Passive cooling option in form of protruded rectangular fins is implemented to reduce the display temperature.
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Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.
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A comprehensive numerical investigation on the impingement and spreading of a non-isothermal liquid droplet on a solid substrate with heterogeneous wettability is presented in this work. The time-dependent incompressible Navier-Stokes equations are used to describe the fluid flow in the liquid droplet, whereas the heat transfer in the moving droplet and in the solid substrate is described by the energy equation. The arbitrary Lagrangian-Eulerian (ALE) formulation with finite elements is used to solve the time-dependent incompressible Navier-Stokes equation and the energy equation in the time-dependent moving domain. Moreover, the Marangoni convection is included in the variational form of the Navier-Stokes equations without calculating the partial derivatives of the temperature on the free surface. The heterogeneous wettability is incorporated into the numerical model by defining a space-dependent contact angle. An array of simulations for droplet impingement on a heated solid substrate with circular patterned heterogeneous wettability are presented. The numerical study includes the influence of wettability contrast, pattern diameter, Reynolds number and Weber number on the confinement of the spreading droplet within the inner region, which is more wettable than the outer region. Also, the influence of these parameters on the total heat transfer from the solid substrate to the liquid droplet is examined. We observe that the equilibrium position depends on the wettability contrast and the diameter of the inner surface. Consequently. the heat transfer is more when the wettability contrast is small and/or the diameter of inner region is large. The influence of the Weber number on the total heat transfer is more compared to the Reynolds number, and the total heat transfer increases when the Weber number increases. (C) 2015 Elsevier Ltd. All rights reserved.
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Affine transformations have proven to be very powerful for loop restructuring due to their ability to model a very wide range of transformations. A single multi-dimensional affine function can represent a long and complex sequence of simpler transformations. Existing affine transformation frameworks like the Pluto algorithm, that include a cost function for modern multicore architectures where coarse-grained parallelism and locality are crucial, consider only a sub-space of transformations to avoid a combinatorial explosion in finding the transformations. The ensuing practical tradeoffs lead to the exclusion of certain useful transformations, in particular, transformation compositions involving loop reversals and loop skewing by negative factors. In this paper, we propose an approach to address this limitation by modeling a much larger space of affine transformations in conjunction with the Pluto algorithm's cost function. We perform an experimental evaluation of both, the effect on compilation time, and performance of generated codes. The evaluation shows that our new framework, Pluto+, provides no degradation in performance in any of the Polybench benchmarks. For Lattice Boltzmann Method (LBM) codes with periodic boundary conditions, it provides a mean speedup of 1.33x over Pluto. We also show that Pluto+ does not increase compile times significantly. Experimental results on Polybench show that Pluto+ increases overall polyhedral source-to-source optimization time only by 15%. In cases where it improves execution time significantly, it increased polyhedral optimization time only by 2.04x.
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Thermal decomposition studies of 3-carene, a bio-fuel, have been carried out behind the reflected shock wave in a single pulse shock tube for temperature ranging from 920 K to 1220 K. The observed products in thermal decomposition of 3-carene are acetylene, allene, butadiene, isoprene, cyclopentadiene, hexatriene, benzene, toluene and p-xylene. The overall rate constant for 3-carene decomposition was found to be k/s(-1) = 10((9.95 +/- 0.54)) exp(-40.88 +/- 2.71 kcal mol(-1) /RT). Ab-initio theoretical calculations were carried out to find the minimum energy pathway that could explain the formation of the observed products in the thermal decomposition experiments. These calculations were carried out at B3LYP/6-311 + G(d,p) and G3 level of theories. A kinetic mechanism explaining the observed products in the thermal decomposition experiments has been derived. It is concluded that the linear hydrocarbons are the primary products in the pyrolysis of 3-carene.
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The electron recombination lifetime in a sensitized semiconductor assembly is greatly influenced by the crystal structure and geometric form of the light-harvesting semiconductor nanocrystal. When such light harvesters with varying structural characteristics are configured in a photoanode, its interface with the electrolyte becomes equally important and directly influences the photovoltaic efficiency. We have systematically probed here the influence of nanocrystal crystallographic structure and shape on the electron recombination lifetime and its eventual influence on the light to electricity conversion efficiency of a liquid junction semiconductor sensitized solar cell. The light-harvesting cadmium sulfide (CdS) nanocrystals of distinctly different and controlled shapes are obtained using a novel and simple liquid gas phase synthesis method performed at different temperatures involving very short reaction times. High resolution synchrotron X-ray diffraction and spectroscopic studies respectively exhibit different crystallographic phase content and optical properties. When assembled on a mesoscopic TiO2 film by a linker molecule, they exhibit remarkable variation in electron recombination lifetime by 1 order of magnitude, as determined by ac-impedance spectroscopy. This also drastically affects the photovoltaic efficiency of the differently shaped nanocrystal sensitized solar cells.
Resumo:
The electron recombination lifetime in a sensitized semiconductor assembly is greatly influenced by the crystal structure and geometric form of the light-harvesting semiconductor nanocrystal. When such light harvesters with varying structural characteristics are configured in a photoanode, its interface with the electrolyte becomes equally important and directly influences the photovoltaic efficiency. We have systematically probed here the influence of nanocrystal crystallographic structure and shape on the electron recombination lifetime and its eventual influence on the light to electricity conversion efficiency of a liquid junction semiconductor sensitized solar cell. The light-harvesting cadmium sulfide (CdS) nanocrystals of distinctly different and controlled shapes are obtained using a novel and simple liquid gas phase synthesis method performed at different temperatures involving very short reaction times. High resolution synchrotron X-ray diffraction and spectroscopic studies respectively exhibit different crystallographic phase content and optical properties. When assembled on a mesoscopic TiO2 film by a linker molecule, they exhibit remarkable variation in electron recombination lifetime by 1 order of magnitude, as determined by ac-impedance spectroscopy. This also drastically affects the photovoltaic efficiency of the differently shaped nanocrystal sensitized solar cells.
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This study presents a plausible dual-site mechanism and microkinetic model for CO oxidation over palladium-substituted ceria incorporating the theoretical oxygen storage capacity of different-catalysts into the kinetic model. A rate expression without prior assumption of rate-determining steps has been developed for the proposed microkinetic model using reaction route analysis. Experiments were conducted using various percentages of palladium in ceria that were synthesized by solution combustion. Obtained catalysts were characterized by X-ray diffraction, X-ray photoelectron spectra, and Brunauer-Emmett-Teller surface area measurements. A detailed mechanism was, developed, and the kinetic parameters and rate expression were validated with the conversion data obtained in the presence of the catalysts. Furthermore, a reduced rate expression based on rate-determining step and most abundant reactive intermediate approximation was obtained and tested against the original rate expression for different experimental conditions. From the results obtained it was concluded that the simulated rate predictions matched the experimental trend with reasonable accuracy, validating the kinetic parameters proposed it this study.
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Numerical simulation of separated flows in rocket nozzles is challenging because existing turbulence models are unable to predict it correctly. This paper addresses this issue with the Spalart-Allmaras and Shear Stress Transport (SST) eddy-viscosity models, which predict flow separation with moderate success. Their performances have been compared against experimental data for a conical and two contoured subscale nozzles. It is found that they fail to predict the separation location correctly, exhibiting sensitivity to the nozzle pressure ratio (NPR) and nozzle type. A careful assessment indicated how the model had to be tuned for better, consistent prediction. It is learnt that SST model's failure is caused by limiting of the shear stress inside boundary layer according to Bradshaw's assumption, and by over prediction of jet spreading rate. Accordingly, SST's coefficients were empirically modified to match the experimental wall pressure data. Results confirm that accurate RANS prediction of separation depends on the correct capture of the jet spreading rate, and that it is feasible over a wide range of NPRs by modified values of the diffusion coefficients in the turbulence model. (C) 2015 Elsevier Masson SAS. All rights reserved.
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With the advances in technology, seismological theory, and data acquisition, a number of high-resolution seismic tomography models have been published. However, discrepancies between tomography models often arise from different theoretical treatments of seismic wave propagation, different inversion strategies, and different data sets. Using a fixed velocity-to-density scaling and a fixed radial viscosity profile, we compute global mantle flow models associated with the different tomography models and test the impact of these for explaining surface geophysical observations (geoid, dynamic topography, stress, and strain rates). We use the joint modeling of lithosphere and mantle dynamics approach of Ghosh and Holt (2012) to compute the full lithosphere stresses, except that we use HC for the mantle circulation model, which accounts for the primary flow-coupling features associated with density-driven mantle flow. Our results show that the seismic tomography models of S40RTS and SAW642AN provide a better match with surface observables on a global scale than other models tested. Both of these tomography models have important similarities, including upwellings located in Pacific, Eastern Africa, Iceland, and mid-ocean ridges in the Atlantic and Indian Ocean and downwelling flows mainly located beneath the Andes, the Middle East, and central and Southeast Asia.
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Acoustic feature based speech (syllable) rate estimation and syllable nuclei detection are important problems in automatic speech recognition (ASR), computer assisted language learning (CALL) and fluency analysis. A typical solution for both the problems consists of two stages. The first stage involves computing a short-time feature contour such that most of the peaks of the contour correspond to the syllabic nuclei. In the second stage, the peaks corresponding to the syllable nuclei are detected. In this work, instead of the peak detection, we perform a mode-shape classification, which is formulated as a supervised binary classification problem - mode-shapes representing the syllabic nuclei as one class and remaining as the other. We use the temporal correlation and selected sub-band correlation (TCSSBC) feature contour and the mode-shapes in the TCSSBC feature contour are converted into a set of feature vectors using an interpolation technique. A support vector machine classifier is used for the classification. Experiments are performed separately using Switchboard, TIMIT and CTIMIT corpora in a five-fold cross validation setup. The average correlation coefficients for the syllable rate estimation turn out to be 0.6761, 0.6928 and 0.3604 for three corpora respectively, which outperform those obtained by the best of the existing peak detection techniques. Similarly, the average F-scores (syllable level) for the syllable nuclei detection are 0.8917, 0.8200 and 0.7637 for three corpora respectively. (C) 2016 Elsevier B.V. All rights reserved.
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Recent advancements of material science and its applications have been immensely influenced by the modern development of organic luminescent materials. Among all organic luminogens, boron containing compounds have already established their stature as one of the indispensable classes of luminescent dyes. Boron, in its various forms e. g. triarylboranes, borate dyes and boron clusters, has attracted considerable attention owing to its several unique and excellent photophysical features. In very recent times, beyond the realms of solution-state studies, luminescent boron-containing compounds have emerged as a large and versatile class of stimuli responsive materials. Based on several fundamental concepts of chemistry, researchers have come up with an admirable variety of boron-containing materials with AIE (aggregation-induced emission), mechano-responsive luminescence, thermoresponsive-luminescence as well as a number of purely organic phosphorescent materials and other standalone examples. The unique chemical as well as physical properties of boron-containing compounds are largely responsible for the development of such materials. In this review these new findings are brought together.
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The alarmone (p)ppGpp regulates transcription, translation, replication, virulence, lipid synthesis, antibiotic sensitivity, biofilm formation, and other functions in bacteria. Signaling nucleotide cyclic di-GMP (c-di-GMP) regulates biofilm formation, motility, virulence, the cell cycle, and other functions. In Mycobacterium smegmatis, both (p) ppGpp and c-di-GMP are synthesized and degraded by bifunctional proteins Rel(Msm) and DcpA, encoded by rel(Msm) and dcpA genes, respectively. We have previously shown that the Delta rel(Msm) and Delta dcpA knockout strains are antibiotic resistant and defective in biofilm formation, show altered cell surface properties, and have reduced levels of glycopeptidolipids and polar lipids in their cell wall (K. R. Gupta, S. Kasetty, and D. Chatterji, Appl Environ Microbiol 81:2571-2578, 2015, http://dx.doi.org/10.1128/AEM.03999-14). In this work, we have explored the phenotypes that are affected by both (p) ppGpp and c-di-GMP in mycobacteria. We have shown that both (p) ppGpp and c-di-GMP are needed to maintain the proper growth rate under stress conditions such as carbon deprivation and cold shock. Scanning electron microscopy showed that low levels of these second messengers result in elongated cells, while high levels reduce the cell length and embed the cells in a biofilm-like matrix. Fluorescence microscopy revealed that the elongated Delta rel(Msm) and Delta dcpA cells are multinucleate, while transmission electron microscopy showed that the elongated cells are multiseptate. Gene expression analysis also showed that genes belonging to functional categories such as virulence, detoxification, lipid metabolism, and cell-wall-related processes were differentially expressed. Our results suggests that both (p) ppGpp and c-di-GMP affect some common phenotypes in M. smegmatis, thus raising a possibility of cross talk between these two second messengers in mycobacteria. IMPORTANCE Our work has expanded the horizon of (p) ppGpp and c-di-GMP signaling in Gram-positive bacteria. We have come across a novel observation that M. smegmatis needs (p) ppGpp and c-di-GMP for cold tolerance. We had previously shown that the Delta rel(Msm) and Delta dcpA strains are defective in biofilm formation. In this work, the overproduction of (p) ppGpp and c-di-GMP encased M. smegmatis in a biofilm-like matrix, which shows that both (p) ppGpp and c-di-GMP are needed for biofilm formation. The regulation of cell length and cell division by (p) ppGpp was known in mycobacteria, but our work shows that c-di-GMP also affects the cell size and cell division in mycobacteria. This is perhaps the first report of c-di-GMP regulating cell division in mycobacteria.
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Recent studies have evaluated closed-loop supercritical carbon dioxide (s-CO2) Brayton cycles to be a higher energy density system in comparison to conventional superheated steam Rankine systems. At turbine inlet conditions of 923K and 25 MPa, high thermal efficiency (similar to 50%) can be achieved. Achieving these high efficiencies will make concentrating solar power (CSP) technologies a competitive alternative to current power generation methods. To incorporate a s-CO2 Brayton power cycle in a solar power tower system, the development of a solar receiver capable of providing an outlet temperature of 923 K (at 25 MPa) is necessary. The s-CO2 will need to increase in temperature by similar to 200 K as it passes through the solar receiver to satisfy the temperature requirements of a s-CO2 Brayton cycle with recuperation and recompression. In this study, an optical-thermal-fluid model was developed to design and evaluate a tubular receiver that will receive a heat input similar to 2 MWth from a heliostat field. The ray-tracing tool SolTrace was used to obtain the heat-flux distribution on the surfaces of the receiver. Computational fluid dynamics (CFD) modeling using the Discrete Ordinates (DO) radiation model was used to predict the temperature distribution and the resulting receiver efficiency. The effect of flow parameters, receiver geometry and radiation absorption by s-CO2 were studied. The receiver surface temperatures were found to be within the safe operational limit while exhibiting a receiver efficiency of similar to 85%.