京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21350号 / 工博第4509号 / 新制||工||1702(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 後藤 仁志, 教授 KIM Chul-Woo, 准教授 KHAYYER,Abbas / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

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Two numerical particle models, the Smoothed Particle Hydrodynamics (SPH) and Moving Particle Semi-implicit (MPS) methods, coupled with a sub-particle scale (SPS) turbulence model, are presented to simulate free surface flows. Both SPH and MPS methods have the advantages in that the governing Navier¿Stokes equations are solved by Lagrangian approach and no grid is needed in the computation. Thus the free surface can be easily and accurately tracked by particles without numerical diffusion. In this paper different particle interaction models for SPH and MPS methods are summarized and compared. The robustness of two models is validated through experimental data of a dam-break flow. In addition, a series of numerical runs are carried out to investigate the order of convergence of the models with regard to the time step and particle spacing. Finally the efficiency of the incorporated SPS model is further demonstrated by the computed turbulence patterns from a breaking wave. It is shown that both SPH and MPS models provide a useful tool for simulating free surface flows.

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This thesis developed a linear shaped charge (LSC) separation mechanism capable of severing the interstage skin for first stage separation of the Ares I launch vehicle. The derived LSC design solution was found using available data on Explosive Technology’s Jetcord LSC and from National Aeronautics and Space Administration (NASA) Marshall Space Flight Center’s (MSFC) desired characteristics. Mechanism components are designed after Minuteman III’s separation mechanism for first stage separation and NASA MSFC’s desired characteristics. Mechanism severance is verified through the use of the numerical method capability smoothed particle hydrodynamics that the hydrocode Autodyn offers. Three simulations are conducted to determine feasibility: the first of only the LSC exploding, to numerically validate the explosion process; the second of the LSC penetrating the target, to numerically validate the penetration process and failure mechanisms; and the last of the entire mechanism, to obtain information about the explosion, penetration, failure, and debris generated.

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An important practical problem in the survival analysis is predicting the time to a future event such as the death or failure of a subject. It is of great importance for the medical decision making to investigate how the predictor variables including repeated measurements of the same subjects are affecting the future time-to-event. Such a prediction problem is particularly more challenging due to the fact that the future values of predictor variables are unknown, and they may vary dynamically over time. In this dissertation, we consider a predictive approach based on modeling the forward intensity function. To handle the practical difficulty due to missing data in longitudinal measurements, and to accommodate observations at irregularly spaced time points, we propose a smoothed composite likelihood approach for estimations. The forward intensity function approach intrinsically incorporates the future dynamics in the predictor variables that affect the stochastic occurrence of the future event. Thus the proposed framework is advantageous and parsimonious from requiring no separated modeling step for the stochastic mechanism of the predictor variables. Our theoretical analysis establishes the validity of the forward intensity modeling approach and the smoothed composite likelihood method. To model the parameters as continuous functions of time, we introduce the penalized B-spline method into the proposed approach. Extensive simulations and real-data analyses demonstrate the promising performance of the proposed predictive approach. / Statistics

The modernization of the National Air Traffic Control System is on the horizon, and with it, the possible introduction of autonomous air vehicles into the national airspace. Per the FAA Aerospace Forecast (FAA, 2013), U.S. carrier passenger traffic is expected to average 2.2 percent growth per year over the next 20 years with government statistics indicating that the average domestic load factor for airlines in 2014 was approximately 84.4 percent (US Department of Transportation, 2015). Adding to that demand, the potential introduction of unmanned and autonomous air vehicles motivates reconsideration of control schemes. One of the proposed solutions (Eby, 1994) would involve a decentralized control protocol. Equipping each aircraft with the information necessary to navigate safely through integrated airspace becomes an information sharing problem: how much information about other aircraft is required for a pilot to safely fly the gamut of a heavily populated airspace and what paradigm shifts may be necessary to safely and efficiently utilize available airspace? This thesis describes the development of a tool for testing alternative traffic management systems, centralized or decentralized, in the presence of uncertainty. Applying a computational fluid dynamics-inspired approach to the problem creates a simulation tool to model both the movement of traffic within the airspace and also allows study of the effects of interactions between vehicles. By incorporating a Smoothed Particle Hydrodynamics (SPH) based model, discrete particle aircraft each carry a set of unique deterministic and stochastic properties. With this model, aircraft interaction can be studied to better understand how variations in the nondeterministic properties of the system affect its overall efficiency and safety. The tool is structured to be sufficiently flexible as to allow incorporation of different collision detection and avoidance rules for aircraft traffic management. / Master of Science