Efficient solvers for power flow equations : parametric solutions with accuracy control assessment

The Power Flow model is extensively used to predict the behavior of electric grids and results in solving a nonlinear algebraic system of equations. Modeling the grid is essential for design optimization and control. Both applications require a fast response for multiple queries to a parametric family of power flow problems. Different solvers have been introduced especially designed for the algebraic nonlinear power flow equations, providing efficient solutions for single problems, even when the number of degrees of freedom is considerably large. However, there is no existing methodology providing an explicit solution of the Parametric Power Flow problem (viz. a computational vademecum, explicit in terms of the parameters). This work aims precisely at designing algorithms producing computational vademecums for the Parametric Power Flow problem. Once these solutions are available, solving for different values of the parameters is an extremely fast (real-time) post-process and therefore both the optimal design and the control problem can readily be addressed. In a first phase, a new family of iteratives solvers for the non-parametric version of the problem is devised. The method is based on a hybrid formulation of the problem combined with an alternated search directions scheme. These methods are designed such that it can be generalized to deal with the parametric version of the problem following a Proper Generalized Decomposition (PGD) strategy. The solver for the parametric problem is conceived by performing the operations involving the unknowns in a PGD fashion. The algorithm follows the basic steps of the algebraic solver, but some operations are carried out in a PGD framework, that is requiring a nested iterative algorithm. The PGD solver is accompanied with an error assessment technique that allows monitoring the convergence of the iterative procedures and deciding the number of terms required to meet the accuracy prescriptions. Different examples of realistic grids and standard benchmark tests are used to demonstrate the performance of the proposed methodologies.El modelo de flujo de potencias se usa para predecir el comportamiento de redes eléctricas y desemboca en la resolución de un sistema de ecuaciones algebraicas no lineales. Modelar una red es esencial para optimizar su diseño y control. Ambas aplicaciones requieren una respuesta rápida a las múltiples peticiones de una familia paramétrica de problemas de flujo de potencias. Diversos métodos de resolución se diseñaron especialmente para resolver la versión algebraica de las ecuaciones de flujo de potencias. Sin embargo, no existe ninguna metodología que proporcione una solución explícita al problema paramétrico de flujo de potencias (esto quiere decir, un vademecum computacional explícito en términos de los parámetros). Esta tesis tiene como objetivo diseñar algoritmos que produzcan vademecums para el problema paramétrico de flujo de potencias. Una vez que las soluciones están disponibles, resolver problemas para diferentes valores de los parámetros es un posproceso extremadamente rápido (en tiempo real) y por lo tanto los problemas de diseño óptimo y control se pueden resolver inmediatamente. En la primera fase, una nueva familia de métodos de resolución iterativos para la versión algebraica del problema se construye. El método se basa en una formulación híbrida del problema combinado con un esquema de direcciones alternadas. Estos métodos se han diseñado para generalizarlos de forma que puedan resolver la versión paramétrica del problema siguiendo una estrategia llamada Descomposición Propia Generalizada (PGD). El método de resolución para el problema paramétrico calcula las incógnitas paramétricas usando la técnica PGD. El algoritmo sigue los mismo pasos que el algoritmo algebraico, pero algunas operaciones se llevan a cabo en el ambiente PGD, esto requiere algoritmos iterativos anidados. El método de resolución PGD se acompaña con una evaluación del error cometido permitiendo monitorizar la convergencia de los procesos iterativos y decidir el número de términos que requiere la solución para alcanzar la precisión preescrita. Diferentes ejemplos de redes reales y tests estándar se usan para demostrar el funcionamiento de las metodologías propuestas

Symbolic and analytic techniques for resource analysis of Java bytecode

Recent work in resource analysis has translated the idea of amortised resource analysis to imperative languages using a program logic that allows mixing of assertions about heap shapes, in the tradition of separation logic, and assertions about consumable resources. Separately, polyhedral methods have been used to calculate bounds on numbers of iterations in loop-based programs. We are attempting to combine these ideas to deal with Java programs involving both data structures and loops, focusing on the bytecode level rather than on source code

On the capture and representation of fonts

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The commercial need to capture, process and represent the shape and form of an outline has lead to the development of a number of spline routines. These use a mathematical curve format that approximates the contours of a given shape. The modelled outline lends itself to be used on, and for, a variety of purposes. These include graphic screens, laser printers and numerically controlled machines. The latter can be employed for cutting foil, metal. plastic and stone. One of the most widely used software design packages has been the lKARUS system. This, developed by URW of Hamburg (Gennany), employs a number of mathematical descriptions that facilitate the process of both modelling and representation of font characters. It uses a variety of curve formats, including Bezier cubics, general conics and parabolics. The work reported in this dissertation focuses on developing improved techniques, primarily. for the lKARUS system. This includes two algorithms which allow a Bezier cubic description, two for a general conic representation and, yet another, two for the parabolic case. In addition, a number of algorithms are presented which promote conversions between these mathematical forms; for example, Bezier cubics to a general conic form. Furthennore, algorithms are developed to assist the process of rasterising both cubic and quadratic arcs.This study was partly funded by the Science and Education Research Council (SERC)

Static and dynamic global stiffness analysis for automotive pre-design

In order to be worldwide competitive, the automotive industry is constantly challenged to produce higher quality vehicles in the shortest time possible and with the minimum costs of production. Most of the problems with new products derive from poor quality design processes, which often leads to undesired issues in a stage where changes are extremely expensive. During the preliminary design phase, designers have to deal with complex parametric problems where material and geometric characteristics of the car components are unknown. Any change in these parameters might significantly affect the global behaviour of the car. A target which is very sensitive to small variations of the parameters is the noise and vibration response of the vehicle (NVH study), which strictly depends on its global static and dynamic stiffness. In order to find the optimal solution, a lot of configurations exploring all the possible parametric combinations need to be tested. The current state of the art in the automotive design context is still based on standard numerical simulations, which are computationally very expensive when applied to this kind of multidimensional problems. As a consequence, a limited number of configurations is usually analysed, leading to suboptimal products. An alternative is represented by reduced order method (ROM) techniques, which are based on the idea that the essential behaviour of complex systems can be accurately described by simplified low-order models.This thesis proposes a novel extension of the proper generalized decomposi-tion (PGD) method to optimize the design process of a car structure with respect to its global static and dynamic stiffness properties. In particular, the PGD method is coupled with the inertia relief (IR) technique and the inverse power method (IPM) to solve, respectively, the parametric static and dynamic stiffness analysis of an unconstrained car structure and extract its noise and vibrations properties. A main advantage is that, unlike many other ROM methods, the proposed approach does not require any pre-processing phase to collect prior knowledge of the solution. Moreover, the PGD solution is computed with only one offline computation and presents an explicit dependency on the introduced design variables. This allows to compute the solutions at a negligible computational cost and therefore opens the door to fast optimisation studies and real-time visualisations of the results in a pre-defined range of parameters. A novel algebraic approach is also proposed which allows to involve both material and com-plex geometric parameters, such that shape optimisation studies can be performed. In addition, the method is developed in a nonintrusive format, such that an interaction with commercial software is possible, which makes it particularly interesting for industrial applications. Finally, in order to support the designers in the decision-making process, a graphical interface app is developed which allows to visualise in real-time how changes in the design variables affect pre-defined quantities of interest