As a solitary wave is usually used to characterize the behavior of a tsunami, a hydraulic experiment is set up for a detailed study of the associated celerity and particle trajectory. The size of the water tank of this experiment in this paper is 21m long, 0.5m width and 0.7m deep. Wave maker method used by Goring (1978) for simulating Solitary Waves is applied in the experiment of particle trajectories and mass transport. We also extend the particle trajectories theory to higher order that contains the non-linear terms. The method presented in this paper fixes the position of the camera, and the grid-point board is located in the center of the water tank, so that the particle and the two-dimensional grid surface coincide. Then, we analyze the particle trajectories within the grid with image processing techniques. This method not only save time of coordinate calibration, but also get a more accurate measurement. The water particle used in this paper has 1mm diameter, because it is difficult to locate the exact position of a large particle. Because of the small size in this experiment, we can get better results and the error is reduced. To compare with the experiment, the third-order Eulerian solution of Feton(1972) is transferred to the Lagrangian system in the present study to get the particle velocity. Then an integral with respect to time is used to obtain the trajectory. The accuracy of the theory is good, especially in the regime of small amplitude. For large wave amplitude in terms of the water depth, a higher order solution is suggested for the future study.

The airflow field and particle trajectories inside hard disk drive (HDD) are investigated in this study using commercial software Fluent and Gambit. Three-dimensional grids inside the HDD configuration are built using Gambit taking into account all the components and their geometric details. The airflow field inside HDD is simulated using three incompressible Navier-Stokes equations for various disk rotational speeds. The effects of using the various turbulence models inside the Fluent software such as the standard k - ε , RNG k - ε and Reynolds Stress Method on the computed airflow characteristics are also assessed. Steady flow fields and the effects of rotational speeds are assessed. Based on the computed steady airflow patterns, particle trajectories are computed using routines available in Fluent as well as special particle trajectory functions defined by the user via the user-defined functions. Particles of different sizes and materials are injected at various locations in the computed flow field and the corresponding particle trajectories are studied. Based on the investigation, the trajectory tends to be different according to sizes and materials. The present work forms a basis for further investigation of heat transfer processes inside the HDD to address thermal management issues and also the computation of unsteady flow fields in the HDD due to the movement of the actuator arm during data storage and retrieval / Singapore-MIT Alliance (SMA)

Despite the importance of single particle motion in biological systems, systematic inference approaches to analyze particle trajectories and evaluate competing motion models are lacking. An automated approach for robust evaluation of motion models that does not require manual intervention is highly desirable to enable analysis of datasets from high-throughput imaging technologies that contain hundreds or thousands of trajectories of biological particles, such as membrane receptors, vesicles, chromosomes or kinetochores, mRNA particles, or whole cells in developing embryos. Bayesian inference is a general theoretical framework for performing such model comparisons that has proven successful in handling noise and experimental limitations in other biological applications. The inherent Bayesian penalty on model complexity, which avoids overfitting, is particularly important for particle trajectory analysis given the highly stochastic nature of particle diffusion. This thesis presents two complementary approaches for analyzing particle motion using Bayesian inference. The first method, MSD-Bayes, discriminates a wide range of motion models--including diffusion, directed motion, anomalous and confined diffusion--based on mean- square displacement analysis of a set of particle trajectories, while the second method, HMM-Bayes, identifies dynamic switching between diffusive and directed motion along individual trajectories using hidden Markov models. These approaches are validated on biological particle trajectory datasets from a wide range of experimental systems, demonstrating their broad applicability to research in cell biology.

Submitted by MÁRCIA CAMILO FIGUEIREDO null (marciacamilof@gmail.com) on 2016-04-28T13:27:25Z No. of bitstreams: 1 TESE_UNESP_SP_BAURU_MARCIA_CAMILO_FIGUEIREDO_DEFESA_04_03_2016.pdf: 8905822 bytes, checksum: 7ea8b928aabd49b34c0aefc4bdbe536f (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-05-02T12:40:38Z (GMT) No. of bitstreams: 1 figueiredo_mc_dr_bauru.pdf: 8905822 bytes, checksum: 7ea8b928aabd49b34c0aefc4bdbe536f (MD5) / Made available in DSpace on 2016-05-02T12:40:38Z (GMT). No. of bitstreams: 1 figueiredo_mc_dr_bauru.pdf: 8905822 bytes, checksum: 7ea8b928aabd49b34c0aefc4bdbe536f (MD5) Previous issue date: 2016-03-04 / Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná (FAADCT/PR) / Esta pesquisa objetivou investigar se licenciandos em química enunciam e compreendem os conceitos de aleatoriedade e irreversibilidade, presentes na Teoria Cinética dos Gases, por meio de etapas construídas para um jogo digital e da sua aplicação após finalizado. Participaram da pesquisa vinte e um acadêmicos do curso de licenciatura em química de uma universidade tecnológica federal no Paraná, separados em: grupo 01, 02 e 03. Para a coleta de dados, cada grupo, em determinados momentos, respondeu questionários, elaborou desenhos e participou de entrevistas semiestruturadas. O desenvolvimento da pesquisa foi orientado pela abordagem qualitativa e por alguns estudos realizados por Piaget. Para tratar e analisar os dados, optamos pelos princípios da análise de conteúdo. A partir do conteúdo dos desenhos construídos nas etapas do jogo digital, foi possível constatar que, os participantes do grupo 01 e 02 buscaram ilustrar em alguma etapa do jogo, uma aproximação de distribuição homogênea do sistema. Nos desenhos dos níveis, verificamos que a maioria (quatorze) dos participantes levou em consideração as experiências obtidas durante o jogo, porque mudaram a maneira de prever em algum nível, as trajetórias de partículas no sistema; dentre os vinte e um sujeitos, apenas oito ilustraram nos quatro níveis do jogo, as primeiras previsões de colisões do lado esquerdo, alcançando o padrão de análise estabelecido. No conteúdo obtido nos discursos dos participantes, referente ao conceito de irreversibilidade, foi possível verificar que este conhecimento não está bem construído nas estruturas cognitivas dos participantes do grupo 01 e 02, porque cinco apresentaram discurso não elucidativo nas quatro etapas do jogo e dois não souberam elucidar o conceito investigado em três etapas. Com relação ao conceito de aleatoriedade, verificamos que os participantes utilizaram palavras diferentes em cada contexto de aplicação das etapas e dos níveis do jogo digital, apresentando distintos discursos, como de gênero científico, próximo do gênero científico, de senso comum, não elucidativo e elucidativo ao jogo. Depreende-se que os recursos didáticos digitais utilizados podem proporcionar aos estudantes compreenderem e apreenderem conteúdos de caráter microscópico e submicroscópico. Portanto, as etapas e os níveis do jogo digital poderão contribuir para que os sujeitos apreendam cientificamente os conceitos da teoria cinética dos gases, como também em outras áreas do conhecimento. / This research aimed to investigate whether licentiate in chemistry enunciate and understand the concepts of randomness and irreversibility present in Kinetic Theory of Gases, through the construction of steps of a digital game and its application after finalized. The participants were twenty-one academics in chemistry degree course of a federal technological university in Paraná, separated into: Group 01, 02 and 03. For the collection of data, each group, at certain times, answered questionnaires, prepared drawings and participated in semi-structured interviews. The development of the research was guided by a qualitative approach and some studies conducted by trough the ideas of Piaget. To process and analyze the data, we chose the principles of content analysis. From the content of the drawings built on the steps of digital game, it was found that the participants of group 01 and 02 sought to illustrate in some stage of the game, a homogeneous distribution approach of the system. In the drawings levels, we found that the majority (fourteen) of the participants took into account the experiences gained during the game because it changed the way to predict to some degree, the particle trajectories in the system; among the twenty-one subjects, only eight illustrated in the four levels of the game, the first predictions of collisions on the left side, reaching the established pattern analysis. The content obtained in the speeches of the participants, referring to the concept of irreversibility, it was found that this knowledge is not well built in cognitive structures of group members 01 and 02, because five had not been elucidated speech in the four stages of the game and two did not know how to elucidate the concept investigated in the three steps. Regarding the concept of randomness, we found that participants used different words in each application context of the stages and the digital game levels, with different speeches, as scientific genre, close to the scientific genus, common sense, not enlightening and instructive the game. It appears that digital teaching resources used can provide students understand and grasp microscopic and submicroscopic character content. Therefore, the steps and levels of the digital game can contribute to the subject scientifically seize the concepts of kinetic theory of gases, as well as in other areas of knowledge.

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The studies of particles advected by tubulent flows is an active area of research across many streams of sciences and engineering, which include astrophysics, fluid mechanics, statistical physics, nonlinear dynamics, and also chemistry and biology. Advances in experimental techniques and high performance computing have made it possible to investigate the properties these particles advected by fluid flows at very high Reynolds numbers. The main focus of this thesis is to study the statistics of Lagrangian tracers and heavy inertial particles in hydrodynamic and magnetohydrodynamic (MHD) turbulent flows by using direct numerical simulations (DNSs). We also study the statistics of particles in model stochastic flows; and we compare our results for such models with those that we obtain from DNSs of hydrodynamic equations. We uncover some of aspects of the statistical properties of particle trajectories that have not been looked at so far. In the last part of the thesis we present some results that we have obtained by solving the three-dimensional Euler equation by using a new method based on the Cauchy-Lagrange formulation. This thesis is divided into 6 chapters. Chapter 1 contains an introduction to the background material that is required for this thesis; it also contains an outline of the problems we study in subsequent Chapters. Chapter 2 contains our study of “Persistence and first-passage time problems with particles in three-dimensional, homogeneous, and isotropic turbulence”. Chapter 3 is devoted to our study of “Universal Statistical Properties of Inertial-particle Trajectories in Three-dimensional, Homogeneous, Isotropic, Fluid Turbulence”. Chapter 4 deals with “Time irreversibility of Inertial-particle trajectories in Homogeneous, Isotropic, Fluid Turbulence”. Chapter 5 contains our study of the “Statistics of charged inertial particles in three-dimensional magnetohydrodynamic (MHD) turbulence”. Chapter 6 is devoted to our study of “The Cauchy-Lagrange method for the numerical integration of the threedimensional Euler equation”.