1,404 research outputs found
A modified Galerkin/finite element method for the numerical solution of the Serre-Green-Naghdi system
A new modified Galerkin / Finite Element Method is proposed for the numerical
solution of the fully nonlinear shallow water wave equations. The new numerical
method allows the use of low-order Lagrange finite element spaces, despite the
fact that the system contains third order spatial partial derivatives for the
depth averaged velocity of the fluid. After studying the efficacy and the
conservation properties of the new numerical method, we proceed with the
validation of the new numerical model and boundary conditions by comparing the
numerical solutions with laboratory experiments and with available theoretical
asymptotic results
A generalized Fellner-Schall method for smoothing parameter estimation with application to Tweedie location, scale and shape models
We consider the estimation of smoothing parameters and variance components in
models with a regular log likelihood subject to quadratic penalization of the
model coefficients, via a generalization of the method of Fellner (1986) and
Schall (1991). In particular: (i) we generalize the original method to the case
of penalties that are linear in several smoothing parameters, thereby covering
the important cases of tensor product and adaptive smoothers; (ii) we show why
the method's steps increase the restricted marginal likelihood of the model,
that it tends to converge faster than the EM algorithm, or obvious
accelerations of this, and investigate its relation to Newton optimization;
(iii) we generalize the method to any Fisher regular likelihood. The method
represents a considerable simplification over existing methods of estimating
smoothing parameters in the context of regular likelihoods, without sacrificing
generality: for example, it is only necessary to compute with the same first
and second derivatives of the log-likelihood required for coefficient
estimation, and not with the third or fourth order derivatives required by
alternative approaches. Examples are provided which would have been impossible
or impractical with pre-existing Fellner-Schall methods, along with an example
of a Tweedie location, scale and shape model which would be a challenge for
alternative methods
Collision-free path planning for robots using B-splines and simulated annealing
This thesis describes a technique to obtain an optimal collision-free path for an automated guided vehicle (AGV) and/or robot in two and three dimensions by synthesizing a B-spline curve under geometric and intrinsic constraints. The problem is formulated as a combinatorial optimization problem and solved by using simulated annealing. A two-link planar manipulator is included to show that the B-spline curve can also be synthesized by adding kinematic characteristics of the robot. A cost function, which includes obstacle proximity, excessive arc length, uneven parametric distribution and, possibly, link proximity costs, is developed for the simulated annealing algorithm. Three possible cases for the orientation of the moving object are explored: (a) fixed orientation, (b) orientation as another independent variable, and (c) orientation given by the slope of the curve. To demonstrate the robustness of the technique, several examples are presented. Objects are modeled as ellipsoid type shapes. The procedure to obtain the describing parameters of the ellipsoid is also presented
An adaptive, hanging-node, discontinuous isogeometric analysis method for the first-order form of the neutron transport equation with discrete ordinate (SN) angular discretisation
In this paper a discontinuous, hanging-node, isogeometric analysis (IGA) method is developed and applied to the first-order form of the neutron transport equation with a discrete ordinate (SN) angular discretisation in two-dimensional space. The complexities involved in upwinding across curved element boundaries that contain hanging-nodes have been addressed to ensure that the scheme remains conservative. A robust algorithm for cycle-breaking has also been introduced in order to develop a unique sweep ordering of the elements for each discrete ordinates direction. The convergence rate of the scheme has been verified using the method of manufactured solutions (MMS) with a smooth solution. Heuristic error indicators have been used to drive an adaptive mesh refinement (AMR) algorithm to take advantage of the hanging-node discretisation. The effectiveness of this method is demonstrated for three test cases. The first is a homogeneous square in a vacuum with varying mean free path and a prescribed extraneous unit source. The second test case is a radiation shielding problem and the third is a 3×3 “supercell” featuring a burnable absorber. In the final test case, comparisons are made to the discontinuous Galerkin finite element method (DGFEM) using both straight-sided and curved quadratic finite elements
Trajectory planning for industrial robot using genetic algorithms
En las últimas décadas, debido la importancia de sus aplicaciones, se han propuesto muchas investigaciones sobre la planificación de caminos y trayectorias para los manipuladores, algunos de los ámbitos en los que pueden encontrarse ejemplos de aplicación son; la robótica industrial, sistemas autónomos, creación de prototipos virtuales y diseño de fármacos asistido por ordenador. Por otro lado, los algoritmos evolutivos se han aplicado en muchos campos, lo que motiva el interés del autor por investigar sobre su aplicación a la planificación de caminos y trayectorias en robots industriales.
En este trabajo se ha llevado a cabo una búsqueda exhaustiva de la literatura existente relacionada con la tesis, que ha servido para crear una completa base de datos utilizada para realizar un examen detallado de la evolución histórica desde sus orígenes al estado actual de la técnica y las últimas tendencias.
Esta tesis presenta una nueva metodología que utiliza algoritmos genéticos para desarrollar y evaluar técnicas para la planificación de caminos y trayectorias. El conocimiento de problemas específicos y el conocimiento heurístico se incorporan a la codificación, la evaluación y los operadores genéticos del algoritmo.
Esta metodología introduce nuevos enfoques con el objetivo de resolver el problema de la planificación de caminos y la planificación de trayectorias para sistemas robóticos industriales que operan en entornos 3D con obstáculos estáticos, y que ha llevado a la creación de dos algoritmos (de alguna manera similares, con algunas variaciones), que son capaces de resolver los problemas de planificación mencionados.
El modelado de los obstáculos se ha realizado mediante el uso de combinaciones de objetos geométricos simples (esferas, cilindros, y los planos), de modo que se obtiene un algoritmo eficiente para la prevención de colisiones.
El algoritmo de planificación de caminos se basa en técnicas de
optimización globales, usando algoritmos genéticos para minimizar una función
objetivo considerando restricciones para evitar las colisiones con los obstáculos. El
camino está compuesto de configuraciones adyacentes obtenidas mediante una
técnica de optimización construida con algoritmos genéticos, buscando minimizar
una función multiobjetivo donde intervienen la distancia entre los puntos
significativos de las dos configuraciones adyacentes, así como la distancia desde
los puntos de la configuración actual a la final. El planteamiento del problema
mediante algoritmos genéticos requiere de una modelización acorde al
procedimiento, definiendo los individuos y operadores capaces de proporcionar
soluciones eficientes para el problema.Abu-Dakka, FJM. (2011). Trajectory planning for industrial robot using genetic algorithms [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10294Palanci
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