CAVITY DETECTION USING GENETIC ALGORITHM AND BOUNDARY ELEMENT METHOD IN ELASTOSTATICS PROBLEMS
Abbreviated Journal Title
Rev. Int. Metod. Numer. Calc. Dise.
Boundary element method (BEM); cavity detection; genetic algorithm; elastostatic; OPTIMIZATION; BEM; Engineering, Multidisciplinary; Mathematics, Interdisciplinary; Applications
A method for the efficient solution of the inverse optimization problem of cavity detection using a point load superposition technique in elastostatics boundary element methods is presented in this paper. The superposition of point load clusters to simulate the presence of cavities offers a tremendous advantage in reducing the computational tine in the elastostatics field solution with the boundary element method as no boundary re-discretization is necessary throughout the optimization process. An objective function is formulated to minimize the difference between BEM-computed and measured deformations along some of the field boundaries. A Genetic Algorithm is employed as the optimization method to guarantee a global optimal solution within the design space of a highly non-linear and multi-parameter objective function. In addition, the Genetic Algorithm is parallelized and dynamically balanced to mitigate its commonly known efficiently issues. Results of cavity detection problems simulated using numerical experiments and added random measurement errors validate the approach in regular and irregular geometrical configurations with single and multiple cavities.
Revista Internacional De Metodos Numericos Para Calculo Y Diseno En Ingenieria
"CAVITY DETECTION USING GENETIC ALGORITHM AND BOUNDARY ELEMENT METHOD IN ELASTOSTATICS PROBLEMS" (2007). Faculty Bibliography 2000s. 7485.