985 resultados para Super-Real Fields
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657 p.
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研究了SUPER CE/SE的新算法及其在爆炸力学中的应用. 算法和模型方面, 主要包括改进CE/SE算法、快速杂交粒子水平集方法、常用化学反应模型和两流体模型. 使用上述算法和模型, 对激波楔面反射、爆炸焊接、爆轰波胞格结构和气液两相爆轰问题进行了数值模拟. 数值结果表明, 该文采用的算法具有计算精度高、应用范围广和兼容性强等优点, 可广泛应用于爆炸力学的数值研究.
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The new numerical algorithms in SUPER/CESE and their applications in explosion mechanics are studied. The researched algorithms and models include an improved CE/SE (space-time Conservation Element and Solution Element) method, a local hybrid particle level set method, three chemical reaction models and a two-fluid model. Problems of shock wave reflection over wedges, explosive welding, cellular structure of gaseous detonations and two-phase detonations in the gas-droplet system are simulated by using the above-mentioned algorithms and models. The numerical results reveal that the adopted algorithms have many advantages such as high numerical accuracy, wide application field and good compatibility. The numerical algorithms presented in this paper may be applied to the numerical research of explosion mechanics.
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The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.
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[ES] La parte práctica de esta tesis se centra en un proyecto ERASMUS realizado en el Monasterio de San Prudencio de Monte Laturce (Clavijo, La Rioja). Dicho proyecto aparece descrito en varios registros de este mismo repositorio a los que se puede acceder a través del siguiente:
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Acute toxicity tests on the effects of Gramoxone and detergent (both applied as a single dose) to nile tilapia, Oreochromis niloticus, fingerlings (mean weight 2.7~c1 g) were conducted using static bioassay. The 96-h LC sub(50) of Gramoxone and detergent applied were 0.08ml/l and 0.004 g/l, respectively. The fingerlings showed increased hyperactivities exemplified by erratic movement, loss of reflex, and hyperventilation during the period of exposure. These effects increased with increasing concentrations of Gramoxone or detergent throughout the duration of exposure. Tilapia fingerlings of the same size showed different levels of tolerance to the same concentration of both pollutants
