FREQUENCY OPTIMIZATION AND TRANSIENT ANALYSES OF STIFFENED FOLDED LAMINATE COMPOSITE PLATE USING GENETIC ALGORITHM

In  this  study,  frequency  optimization  of  stiffened  folded  laminate  composite  plate  is investigated with  respect  to  fiber orientations by using genetic algorithm  (GA). The first order shear deformation theory was used for direct frequencies calculations. The Matlab programming using rectangular isoparametric plate element with five degrees of freedom per node was built to solve  the  problems. The modulus  of  selection,  crossover  and mutation were  used  as  standard sub-modulus.  The  effects  of  obtained  optimal  fiber  orientation  on  transient  response  of  the folded plate have been investigated with difference boundary conditions. A good agreement was found between the results of this technique and other published results available in the literature

Application of DIC in Solid Mechanics

During service life, composite structures are susceptible to damage which reduces their structural integrity. For improved service life, the damage needs to be repaired. In case of low velocity impact damage adhesively bonded patch repair has shown to be cost effective and most efficient in extending service life of damaged parts. The repair performance is mainly influenced by patch stacking sequence, patch shape, patch thickness, overlap length and adhesive strength. In the first phase of work, a 3D finite element based study is carried out using mechanics based approach to optimize the patch dimensions and stacking sequence so that the performance of repaired structure can be improved. Also, a genetic algorithm based approach in-conjunction with finite element analysis is implemented for arriving at an optimized patch and adhesive dimensions. Experimental study is then carried out with optimized geometry using non-contact optical based technique namely digital image correlation (DIC). The mechanics of double and single sided repair are discussed in detail and strain field from DIC have been compared with finite element (FE) estimates

Integrating the finite element method and genetic algorithms to solve structural damage detection and design optimisation problems

This thesis documents fundamental new research in to a specific application of structural box-section beams, for which weight reduction is highly desirable. It is proposed and demonstrated that the weight of these beams can be significantly reduced by using advanced, laminated fibre-reinforced composites in place of steel. Of the many issues raised during this investigation two, of particular importance, are considered in detail; (a) the detection and quantification of damage in composite structures and (b) the optimisation of laminate design to maximise the performance of loaded composite structuress ubject to given constraints. It is demonstrated that both these issues can be formulated and solved as optimisation problems using the finite element method, in which an appropriate objective function is minimised (or maximised). In case (a) the difference in static response obtained from a loaded structure containing damage and an equivalent mathematical model of the structure is minimised by iteratively updating the model. This reveals the damage within the model and subsequently allows the residual properties of the damaged structure to be quantified. Within the scope of this work is the ability to resolve damage, that consists of either penny-shaped sub-surface flaws or tearing damage of box-section beams from surface experimental data. In case (b) an objective function is formulated in terms of a given structural response, or combination of responses that is optimised in order to return an optimal structure, rather than just a satisfactory structure. For the solution of these optimisation problems a novel software tool, based on the integration of genetic algorithms and a commercially available finite element (FE) package, has been developed. A particular advantage of the described method is its applicability to a wide range of engineering problems. The tool is described and its effectiveness demonstrated with reference to two inverse damage detection and quantification problems and one laminate design optimisation problem. The tool allows the full suite of functions within the FE software to be used to solve non-convex optimisation problems, formulated in terms of both discrete and continuous variables, without explicitly stating the form of the stiffness matrix. Furthermore, a priori knowledge about the problem may be readily incorporated in to the method

Experimental and Numerical Study of Composite Patch Repair on Open Hole Carbon Fiber Reinforced Polymer Panel under Tensile Loading

Composite materials are widely used in aerospace applications due to their excellent properties like high specic strength, high specic stiness, high damage tolerance, good corrosion and fatigue resistance, good formability etc. Despite having excellent properties the inherently brittle nature of composites makes them highly susceptible to lo

Shape and topology optimization by fixed grid and genetic algorithms

[SPA] El objetivo de la optimización de estructuras es obtener un diseño, es decir, un conjunto de valores para las variables de diseño que hacen mínima una función objetivo, y satisfacen un conjunto de restricciones que dependen de estas variables. Los problemas de optimización de estructuras se pueden dividir en tres categorías: propiedades, forma, y topología.El desarrollo de los métodos para la optimización de estructuras ha sido bastante desordenado como resultado de la división de ideas: programación matemática (MP), criterios de optimalidad (OC), optimización estructural evolucionaria (ESO), microestructuras sólidas isótropas con penalización (SIMP), optimización estructural basada en el crecimiento biológico (BGSO), método de la curva de nivel (LSM), computación evolutiva (EC), etc. Existen diferentes métodos evolucionarios: estrategias evolutivas (ESs), programación evolucionaria (EP), programación genética (GP), y algoritmos genéticos (GAs); éstos últimos disponen de una base teórica más robusta, y están biológicamente mejor adaptados. El método de la malla fija ha sido utilizado en problemas en donde la geometría del objeto, o las propiedades físicas del cuerpo cambian con el tiempo. En este trabajo se muestra la posibilidad de utilizar el método de la malla fija como alternativa al método de los elementos finitos convencional, para resolver problemas de elasticidad.El principal objetivo de esta tesis es introducir un nuevo procedimiento, denominado MFAG, para la optimización de forma y topología de estructuras continuas bidimensionales. La forma y la topología de la estructura dependen de un algoritmo genético, el cual, a través de las isolíneas del problema define el número, forma y distribución de las cavidades. El análisis de la estructura se realiza mediante una malla fija de elementos finitos. El procedimiento ha sido implementado en el lenguaje de programación FORTRAN 95. Los resultados han sido comparados con los obtenidos en la bibliografía más reciente (multi-GA, MMA, SIMP, PBO, ESO, etc.), demostrando la efectividad del procedimiento, siendo capaz de proporcionar soluciones de calidad con contornos perfectamente definidos, evitando la interpretación de la topología para proponer el diseño final.[ENG] The objective of the optimization of structures is to obtain a design, that is to say, a group of values for some design variables that minimizes a function, and satisfy a series of constraints that depend on these variables. The optimization problems of structures can be divided in three categories: size, shape, and topology. The development of methods to optimize structures has been quite lawless due to division of ideologies: mathematical programming (MP), optimality criteria (OC), evolutionary structural optimization (ESO), solid isotropic microstructure with penalization (SIMP), biological growth structural optimization (BGSO), level set method (LSM), evolutionary computation (EC), etc. Different evolutionary methods exist: evolution strategies (ESs), evolutionary programming (EP), genetic programming (GP), and genetic algorithms (GAs); the last ones have a strong theoretical basis and are the most biologically adapted method. Fixed grid method (FG) has been previously used in problems in which the geometry of the object or the physical properties of the body change with time. In this work is shown the feasibility of using FG as an alternative to conventional finite elements method (FEM) to solve elasticity problems. The main objective of this thesis is to introduce a new procedure, called MFAG, for the shape and topology optimization of bidimensional continuum structures. The topology and shape of the design depend on a genetic algorithm, which, through the problem isolines defines the number, shape and distribution of the contours. The analysis of the structure is carried out by a fixed grid of finite elements. The procedure has been implemented in the programming language FORTRAN 95. The versatility and flexibility of this procedure has been proven through several examples. The results have been compared with those obtained in the most recent bibliography (multi-GA, MMA, SIMP, PBO, ESO, etc.). The results demonstrate the effectiveness of the procedure, providing quality solutions with perfectly defined contours, without the need to interpretate the topology to obtain a final design.Universidad Politécnica de CartagenaPrograma de doctorado en Estructuras y Construcció

Optimización estructural y topológica de estructuras morfológicamente no definidas mediante algoritmos genéticos

La optimización de estructuras ha sido una disciplina muy estudiada por numerosos investigadores durante los últimos cuarenta años. A pesar de que durante los primeros veinte años las técnicas de Programación Matemática fueron la herramienta fundamental en este campo, estas han ido perdiendo fuelle frente a un nuevo conjunto de técnicas metaheurísticas basadas en la Computación Evolutiva. De entre destacan, de manera significativa, los Algoritmos Genéticos. La irrupción de estas nuevas técnicas en el campo de la optimización de estructuras es debida, en gran medida, a las dificultades de la programación matemática para realizar la optimización simultánea de las variables de diseño debido a la elevada alinealidad de estas y sus restricciones El objetivo fundamental del presente trabajo es ir un poco más allá en el proceso de la optimización simultánea de las variables de diseño, definiendo un algoritmo que no parte de una estructura predefinida y que incorpora los parámetros que determinan la geometría. A diferencia de los métodos actuales, el algoritmo desarrollado no requiere de ningún tipo de estructura inicial ni otro tipo de información adicional, aparte de la definición de los puntos de aplicación de las cargas, los puntos de apoyo y el tipo de apoyo. El nuevo algoritmo desarrollado se justifica según la siguiente hipótesis: La definición previa de la forma, geometría, regla o modelo preconcebido en una estructura suponen restricciones del diseño en sí mismas y por lo tanto aquel algoritmo que no se encuentre sujeto a estas deberá poder generar diseños necesariamente mejores, o al menos tan buenos como los existentes. A partir de esta hipótesis se desarrolla un nuevo algoritmo con una codificación mixta, adaptada a cada grupo de variables de diseño, donde los diferentes operadores se definen y actúan de forma independiente para grupo.Sánchez Caballero, S. (2012). Optimización estructural y topológica de estructuras morfológicamente no definidas mediante algoritmos genéticos [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/15409Palanci

Extracting information from manufacturing data using data mining methods

EThOS - Electronic Theses Online ServiceGBUnited Kingdo