Academic literature on the topic 'Flow pattern'

Knowledge of the two-phase flow state is fundamental for two-phase flow system design and operation. In traditional two-phase flow studies, the flow regime refers to the physical location of the gas and liquid in a conduit. Flow configuration is important for engineering correlations of heat and mass transfer, pressure drop, and wall shear. However, it is somewhat subjective since it is mostly defined by experimental observation, resulting in an approximate and equivocal definition. Thus, there is need for a better, objective flow regime identification. The void fraction is a key parameter in monitoring the operating state of a two-phase system and several tools have been developed in order to measure it. The purpose of this study is to use the void fraction and other parameters of the system to achieve a model for flow pattern identification. Recently, an experimental program using the Foster-Miller two-phase flow test bed and Creare Inc. capacitance void fraction sensors was conducted in the microgravity environment of the NASA KC-135 aircraft. Several data types were taken for each phase, such as flow rate, superficial velocity, density and transient void fraction at 100Hz. Several analytical approaches were pursued, including a statistical approach of the fluctuation of the void fraction, Martinelli analysis, and Drift Flux analysis, in order to reach a model for flow pattern identification in microgravity conditions. Several parameters were found to be good flow pattern identifiers such as the statistical moments variance and skewness, Signal -to- noise ratio (SNR), Half Height Value (HHV) and Linear Area Difference (LAD). Moreover, relevant conclusions were achieved using the Martinelli parameter and the Drift Flux model in microgravity conditions. These results were compared with the basic literature.

Protecting confidential information from improper disclosure is a fundamental security goal. While encryption and access control are important tools for ensuring confidentiality, they cannot prevent an authorized system from leaking confidential information to its publicly observable outputs, whether inadvertently or maliciously. Hence, secure information flow aims to provide end-to-end control of information flow. Unfortunately, the traditionally-adopted policy of noninterference, which forbids all improper leakage, is often too restrictive. Theories of quantitative information flow address this issue by quantifying the amount of confidential information leaked by a system, with the goal of showing that it is intuitively “small” enough to be tolerated. Given such a theory, it is crucial to develop automated techniques for calculating the leakage in a system. This dissertation is concerned with program analysis for calculating the maximum leakage, or capacity, of confidential information in the context of deterministic systems and under three proposed entropy measures of information leakage: Shannon entropy leakage, min-entropy leakage, and g-leakage. In this context, it turns out that calculating the maximum leakage of a program reduces to counting the number of possible outputs that it can produce. The new approach introduced in this dissertation is to determine two-bit patterns, the relationships among pairs of bits in the output; for instance we might determine that two bits must be unequal. By counting the number of solutions to the two-bit patterns, we obtain an upper bound on the number of possible outputs. Hence, the maximum leakage can be bounded. We first describe a straightforward computation of the two-bit patterns using an automated prover. We then show a more efficient implementation that uses an implication graph to represent the two- bit patterns. It efficiently constructs the graph through the use of an automated prover, random executions, STP counterexamples, and deductive closure. The effectiveness of our techniques, both in terms of efficiency and accuracy, is shown through a number of case studies found in recent literature.

The literature pertaining to the key stages of spray drying has been reviewed in the context of the mathematical modelling of drier performance. A critical review is also presented of previous spray drying models. A new mathematical model has been developed for prediction of spray drier performance. This is applicable to slurries of rigid, porous crust-forming materials to predict trajectories and drying profiles for droplets with a distribution of sizes sprayed from a centrifugal pressure nozzle. The model has been validated by comparing model predictions to experimental data from a pilot-scale counter-current drier and from a full-scale co-current drier. For the latter, the computed product moisture content was within 2%, and the computed air exit temperature within 10oC of experimental data. Air flow patterns have been investigated in a 1.2m diameter transparent countercurrent spray tower by flow visualisation. Smoke was introduced into various zones within the tower to trace the direction, and gauge the intensity, of the air flow. By means of a set of variable-angle air inlet nozzles, a variety of air entry configurations was investigated. The existence of a core of high rotational and axial velocity channelling up the axis of the tower was confirmed. The stability of flow within the core was found to be strongly dependent upon the air entry arrangement. A probe was developed for the measurement of air temperature and humidity profiles. This was employed for studying evaporation of pure water drops in a 1.2m diameter pilot-scale counter-current drier. A rapid approach to the exit air properties was detected within a 1m distance from the air entry ports. Measured radial profiles were found to be virtually flat but, from the axial profiles, the existence of plug-flow, well-mixed-flow and some degree of air short-circuiting can be inferred. The model and conclusions should assist in the improved design and optimum operation of industrial spray driers.

This paper explores the potential applications of existing spectral clustering algorithms to real life problems through experiments on existing road traffic data. The analysis begins with an overview of previous unsupervised machine learning techniques and constructs an effective spectral clustering algorithm that demonstrates the analytical power of the method. The paper focuses on the spectral embedding method’s ability to project non-linearly separable, high dimensional data into a more manageable space that allows for accurate clustering. The key step in this method involves solving a normalized eigenvector problem in order to construct an optimal representation of the original data. While this step greatly enhances our ability to analyze the relationships between data points and identify the natural clusters within the original dataset, it is difficult to comprehend the eigenvalue representation of the data in terms of the original input variables. The later sections of this paper will explore how the careful framing of questions with respect to available data can help researchers extract tangible decision driving results from real world data through spectral clustering analysis.

COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>O escoamento bifásico no regime de golfadas é um padrão de escoamento que requer esforço em sua caracterização e modelagem, devido às características marcantes da distribuição espacial das fases, que gera intermitência ao escoamento. Este escoamento ocorre na presença de uma grande faixa de vazões de gás e líquido, em tubulações de diâmetro médio e pequeno, com variação periódica da densidade, fração de vazio e pressões na seção transversal da tubulação. No presente trabalho estuda-se numericamente o regime de golfadas ao longo de tubulações horizontais utilizando-se o Modelo de Dois Fluidos. Uma análise detalhada das estatísticas do escoamento é realizada com a caracterização dos principais parâmetros de uma golfada, como comprimento, velocidade da frente e cauda e freqüência de passagem das golfadas ao longo da tubulação. Os dados obtidos das simulações são analisados através de histogramas de distribuição assim como de funções densidade de probabilidade (PDF) das variáveis hidrodinâmicas, destacando-se o caráter estocástico do escoamento no padrão de golfadas. Adicionalmente, comparações com dados de trabalhos experimentais da literatura foram realizadas com concordância muito boa.<br>Slug flow is a two-phase flow pattern that requires large effort in its characterization and modeling, due to special characteristics of the phase’s spatial distribution, which causes flow intermittency. This flow occurs in a wide range of gas and liquid flow rates in pipes of medium and small diameters, with periodic variation of density, void fraction and pressures in pipe-cross-section. This work presents a numerical study of the slug regime through horizontal pipes using the Two-Fluid Model. A detailed statistical analysis of the flow was carried out with characterization of main slug parameters, such as slug length, front and tail velocities and slug frequency along the pipeline. The numerical results were analyzed through distribution histograms as well as probability density function (PDF) of the hydrodynamic variables, showing the stochastic characteristic of slug flow pattern. Further, comparisons with experimental data from the literature were performed, showing very good agreement.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2012.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 70).<br>Introduction: In spring 2011, while I was working on my thesis in architectural Design degree, I came across with an interesting problem in design: a parametric river. I realized that it is not possible to control the river parameters without understanding the geometry of the surface of terrain. in other words, the shape of the terrain or topography may change the shape of the river down the hills. I started to look up more examples in geoscience and geomorphology to find out more about this topic. I came across drainage patterns which vary based on the shape of the terrain in different parts of the world [Howard 1967]. As a designer, the first thought passed through my mind was: "is it possible to design a terrain using drainage patterns?" There must be a way to derive the landscape geometry from the one of the river!" Later on, through searching related topics in geoscience, I realized that this topic has interested researchers from 1858 and there is a quite enormous body of research on that in geo-computation and geography and computer science. I made this topic as the main goal of present thesis to explore the design possibility of such representation in architecture and connecting the world of design with hydrological and geological characteristics of the land. Recently the design proposals tend to become more engaged in sustainability aspects, more recently in energy generation. Therefore, many designers now seek approaches to integrate architectural ideas with interdisciplinary subjects to tackle the different aspects of energy constrains and sustainability issues. There is a recently developed area of research among architects which tries to define the design through the lenses of energy production. This field has received more attention in landscape design and planning strategies. Among all energy generating methods such as wind and solar, there are no many examples of addressing the design through hydropower energy generation which is the main basis of investigation in current study. In order to explain the goals of the thesis it is important to clarify the objectives of this study in a simple question: Is it possible to construct complex geometry of the surface of the terrain using drainage analysis? Or is it possible to embed required information of 3-dimensional space into 2-dimensional drawing. In that case, designers can design complex geometries using simple plan drawings which might result in more function-oriented design.<br>by Masoud Akbarzadeh.<br>S.M.