944 resultados para Helicity method, subtraction method, numerical methods, random polarizations


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The Kineticist's Workbench is a program that simulates chemical reaction mechanisms by predicting, generating, and interpreting numerical data. Prior to simulation, it analyzes a given mechanism to predict that mechanism's behavior; it then simulates the mechanism numerically; and afterward, it interprets and summarizes the data it has generated. In performing these tasks, the Workbench uses a variety of techniques: graph- theoretic algorithms (for analyzing mechanisms), traditional numerical simulation methods, and algorithms that examine simulation results and reinterpret them in qualitative terms. The Workbench thus serves as a prototype for a new class of scientific computational tools---tools that provide symbiotic collaborations between qualitative and quantitative methods.

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Course notes for the Numerical Methods course (joint MATH3018 and MATH6111). Originally by Giampaolo d'Alessandro, modified by Ian Hawke. These contain only minimal examples and are distributed as is; examples are given in the lectures.

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These are the slides used in the joint lectures for MATH3018/MATH6111. They focus on the examples that do not appear in the course notes (see related material). Each lecture comes with example Matlab files that generate the figures used in the lectures.

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These worksheets are formative assessment for the Numerical Methods modules MATH3018 and MATH6111 (some material is only covered in MATH3018). Intended to back up both the theory and the coding (in Matlab) side

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We consider the two-point boundary value problem for stiff systems of ordinary differential equations. For systems that can be transformed to essentially diagonally dominant form with appropriate smoothness conditions, a priori estimates are obtained. Problems with turning points can be treated with this theory, and we discuss this in detail. We give robust difference approximations and present error estimates for these schemes. In particular we give a detailed description of how to transform a general system to essentially diagonally dominant form and then stretch the independent variable so that the system will satisfy the correct smoothness conditions. Numerical examples are presented for both linear and nonlinear problems.

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The objective of this work was to study the effect of selective thinning on the genetic divergence in progenies of Pinus caribaea var. bahamensis, aiming to identify the most productive and divergent progenies for the use of improvement program. The test of progenies containing 119 progenies and two commercial controls were planted in March 1990, using 11 × 11 square lattice design, sextuple, partially balanced, disposed in lineal plots with six trees in the spacing of 3,0 × 3,0m. 13 years after planting thinning was realized (selection for DBH), with 50% selection intensity based on Multi-effect index, leaving three trees per plot in all the experiment. The evaluations were done at four situations: A (before the thinning); B (thinned trees); C (remaining trees after thinning) and D (one year after thinning). The analyzed traits were: height, diameter at breast height (DBH), volume, form of stem and wood density. The genetic divergence among the progenies was studied with aid of the canonical variables and of clustering of Tocher method, using the generalized distance matrix of Mahalanobis (D2) as estimate of the genetic similarity. The progenies were grouped in four groups in situation A, fourteen in the situation B, two in the situation C and three in the situation D. The selective thinning of the trees within of the progenies caused a change in the genetic divergence among the progenies, genetically homogenizing the progenies, as demonstrated by the generalized distances of Mahalanobis, clustering of Tocher' and canonical variables methods. The thinning made possible a high uniformity in respect to the relative contribution of the traits for the total genetic divergence. The techniques of clustering were efficient to identify groups of divergent progenies for the use hybridization and little divergent progenies for the use in backcross program.

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This paper uses artificial neural networks (ANN) to compute the resonance frequencies of rectangular microstrip antennas (MSA), used in mobile communications. Perceptron Multi-layers (PML) networks were used, with the Quasi-Newton method proposed by Broyden, Fletcher, Goldfarb and Shanno (BFGS). Due to the nature of the problem, two hundred and fifty networks were trained, and the resonance frequency for each test antenna was calculated by statistical methods. The estimate resonance frequencies for six test antennas were compared with others results obtained by deterministic and ANN based empirical models from the literature, and presented a better agreement with the experimental values.

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Questo documento descrive gran parte del lavoro svolto durante un periodo di studio di sei mesi all’International Centre for Geohazards (ICG) di Oslo. Seguendo la linea guida dettata nel titolo, sono stati affrontati diversi aspetti riguardanti la modellazione numerica dei pendii quali l’influenza delle condizioni al contorno e delle proporzioni del modello, la back-analysis di eventi di scivolamento e l’applicazione delle analisi di stabilità monodimensionali. La realizzazione di semplici modelli con il programma agli elementi finiti PLAXIS (Brinkgreve et al., 2008) ha consentito di analizzare le prestazioni dei modelli numerici riguardo all’influenza delle condizioni al contorno confrontandoli con un calcolo teorico del fattore di amplificazione. Questa serie di test ha consentito di stabilire alcune linee guida per la realizzazione di test con un buon livello di affidabilità. Alcuni case-history, in particolare quello di Las Colinas (El Salvador), sono stati modellati allo scopo di applicare e verificare i risultati ottenuti con i semplici modelli sopracitati. Inoltre sono state svolte analisi di sensitività alla dimensione della mesh e ai parametri di smorzamento e di elasticità. I risultati hanno evidenziato una forte dipendenza dei risultati dai parametri di smorzamento, rilevando l’importanza di una corretta valutazione di questa grandezza. In ultima battuta ci si è occupati dell’accuratezza e dell’applicabilità dei modelli monodimensionali. I risultati di alcuni modelli monodimensionali realizzati con il software Quiver (Kaynia, 2009) sono stati confrontati con quelli ottenuti da modelli bidimensionali. Dal confronto è risultato un buon grado di approssimazione accompagnato da un margine di sicurezza costante. Le analisi monodimensionali sono poi state utilizzate per la verifica di sensitività. I risultati di questo lavoro sono qui presentati e accompagnati da suggerimenti qualitativi e quantitativi per la realizzazione di modelli bidimensionali affidabili. Inoltre si descrive la possibilità di utilizzare modelli monodimensionali in caso d’incertezze sui parametri. Dai risultati osservati emerge la possibilità di ottenere un risparmio di tempo nella realizzazione di importanti indagini di sensitività.