8,580 research outputs found
Characterization of the pneumatic behavior of a novel spouted bed apparatus
Recently the importance of spouted bed technology has significantly increased in the context of drying processes as well as granulation, agglomeration or coating processes. Particulate systems concerning very fine or non spherical particles that are difficult to fluidize, often cannot be treated in conventional fluidized beds. In contrast to those fluidized beds, the spouted bed technology with its specific flow structure offers the opportunity of stable fluidization under controlled conditions. Within this work the fluid dynamics of a novel spouted bed with two adjustable gas inlets is investigated. By analysis of gas fluctuation spectra by means of a fast Fourier transformation algorithm, different operation regimes are identified and depicted graphically. Furthermore, continuum CFD-modeling of the granular solid phase motion by means of an Euler/Euler approach and comparisons with experimental obtained velocity vector fields by means of particle image velocimetry (PIV) measurements will be presented in this work
Analysis of the fluidization behaviour and application of a novel spouted bed\ud apparatus for spray granulation and coating
Spouted beds are well known for their good mixing of the solid phase and for their intensive heat\ud
and mass transfers between the fluid phase and the solid phase. Nearly isothermal conditions are\ud
enabled which is of advantage for the treatment of granular solid materials in granulation,\ud
agglomeration or coating processes. In this work the hydrodynamic behaviour of a novel spouted\ud
bed apparatus with two horizontal and slit-shaped gas inlets is investigated by high-frequency\ud
recordings of the gas phase pressure fluctuations over the entire bed. The hydrodynamic stable\ud
operation domain, which is of importance for operating the apparatus, will be identified and\ud
depicted in the Re-G-Ar-diagram by Mitev [1]. Another focus of this work is the simulation of the\ud
spouting process by application of a continuum approach in FLUENT 6.2. The effect of the\ud
frictional stresses on the hydrodynamic behaviour is examined by performing simulations with and\ud
without consideration of friction. The angle of internal friction fi in Schaeffer`s [10] model will be\ud
varied and the simulation results will be compared with experiments. It was found that the influence\ud
of friction is not very big by application of the quite simple and empirical frictional viscosity model\ud
by Schaeffer [10] basing on soil mechanical principles. Also the simulation results under negligence\ud
of friction were similar to those under consideration of friction. Another part of this work is the\ud
industrial application of the novel spouted bed in granulation and coating processes. Compared to\ud
classical fluidized beds, a much narrower particle size distribution, a higher yield and a higher\ud
product quality was obtained in the novel spouted be
Geometrical Considerations for the Design of Liquid-phase Biochemical Sensors Using a Cantilever\u27s Fundamental In-plane Mode
The influence of the beam geometry on the quality factor and resonance frequency of resonant silicon cantilever beams vibrating in their fundamental in-plane flexural mode in water has been investigated. Compared to cantilevers vibrating in their first out-of-plane flexural mode, utilizing the in-plane mode results in reduced damping and reduced mass loading by the surrounding fluid. Quality factors as high as 86 have been measured in water for cantilevers with a 20 μm thick silicon layer. Based on the experimental data, design guidelines are established for beam dimensions that ensure maximal Q-factors and minimal mass loading by the surrounding fluid, thus improving the limit-of-detection of mass-sensitive biochemical sensors. Elementary theory is also presented to help explain the observed trends. Additional discussion focuses on the tradeoffs that exist in designing liquid-phase biochemical sensors using in-plane cantilevers
Integrated Thematic Instruction : a Descriptive Case Study of Students\u27 Attitudes Toward School and Learning
The purpose of the study was to describe the operational form of the innovation— Integrated Thematic Instruction within the context of its implementation. An embedded single case study design was used to carry out this gualitative study, with Integrated Thematic Instruction (ITI) as the unit of the case study. The questions that guided the study were: What does ITI look like when implemented by the teacher? What are the contextual elements of implementation of this program? What variations are found in the implementation of this innovation by different teachers? A review of related literature revealed the historical, philosophical, and theoretical underpinnings of ITI. Several innovative educational practices were compared with ITI and parallels were drawn between them and ITI. Since this was the first descriptive research study of ITI, an Innovation Configuration of the program was developed. Interviews of the program developer, local program coordinators, as well as users (teachers), and observation of classroom implementation of ITI, helped in delineating its critical components; the ideal, acceptable, and unacceptable variations of its components were identified. The implementation context of ITI and the variations in teacher use of the components of the program were also studied. The case study was conducted at two different schools using ITI. The description of its context included school demography, the support systems, students, and selected psychological characteristics of the teachers. Implementation of the program is described first in general, and then in detail, focusing on its use by two teachers at each school. A brief analysis was made of the use of ITI at the two different sites. Several implications derived out of the study; these include those for further research, for staff developers and change facilitators, for principals, and for teachers using or intending to use ITI
Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data
We present a Bayesian non-negative tensor factorization model for
count-valued tensor data, and develop scalable inference algorithms (both batch
and online) for dealing with massive tensors. Our generative model can handle
overdispersed counts as well as infer the rank of the decomposition. Moreover,
leveraging a reparameterization of the Poisson distribution as a multinomial
facilitates conjugacy in the model and enables simple and efficient Gibbs
sampling and variational Bayes (VB) inference updates, with a computational
cost that only depends on the number of nonzeros in the tensor. The model also
provides a nice interpretability for the factors; in our model, each factor
corresponds to a "topic". We develop a set of online inference algorithms that
allow further scaling up the model to massive tensors, for which batch
inference methods may be infeasible. We apply our framework on diverse
real-world applications, such as \emph{multiway} topic modeling on a scientific
publications database, analyzing a political science data set, and analyzing a
massive household transactions data set.Comment: ECML PKDD 201
Unconventional Uses of Microcantilevers as Chemical Sensors in Gas and Liquid Media
The use of microcantilevers as (bio)chemical sensors usually involves the application of a chemically sensitive layer. The coated device operates either in a static bending regime or in a dynamic flexural mode. While some of these coated devices may be operated successfully in both the static and the dynamic modes, others may suffer from certain shortcomings depending on the type of coating, the medium of operation and the sensing application. Such shortcomings include lack of selectivity and reversibility of the sensitive coating and a reduced quality factor due to the surrounding medium. In particular, the performance of microcantilevers excited in their standard out-of-plane dynamic mode drastically decreases in viscous liquid media. Moreover, the responses of coated cantilevers operating in the static bending mode are often difficult to interpret. To resolve these performance issues, the following emerging unconventional uses of microcantilevers are reviewed in this paper: (1) dynamic-mode operation without using a sensitive coating, (2) the use of in-plane vibration modes (both flexural and longitudinal) in liquid media, and (3) incorporation of viscoelastic effects in the coatings in the static mode of operation. The advantages and drawbacks of these atypical uses of microcantilevers for chemical sensing in gas and liquid environments are discussed
To Learn or Not to Learn Features for Deformable Registration?
Feature-based registration has been popular with a variety of features
ranging from voxel intensity to Self-Similarity Context (SSC). In this paper,
we examine the question on how features learnt using various Deep Learning (DL)
frameworks can be used for deformable registration and whether this feature
learning is necessary or not. We investigate the use of features learned by
different DL methods in the current state-of-the-art discrete registration
framework and analyze its performance on 2 publicly available datasets. We draw
insights into the type of DL framework useful for feature learning and the
impact, if any, of the complexity of different DL models and brain parcellation
methods on the performance of discrete registration. Our results indicate that
the registration performance with DL features and SSC are comparable and stable
across datasets whereas this does not hold for low level features.Comment: 9 pages, 4 figure
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