Browsing by Author "Adams, David B."
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- Global/Local Iteration for Blended Composite Laminate Panel Structure Optimization SubproblemsAdams, David B.; Watson, Layne T.; Seresta, Omprakash; Gürdal, Zafer (Department of Computer Science, Virginia Polytechnic Institute & State University, 2005)Composite panel structure optimization is commonly decomposed into panel optimization subproblems. Previous work applied a guide based design approach to the problem for a structure where the local loads were assumed to be fixed for each panel throughout the design process. This paper examines the application of guide based design to a more realistic representation of the structure where the local loads for each panel are determined through a global level analysis that is coupled with the stacking sequence for every design panel. A small problem is selected for which an exhaustive search of the subproblem design space verifies the optimality of the solution found through the global/local iteration process introduced in this work. The efficient discovery of solutions to these guide based design subproblems creates an opportunity to incorporate the solutions into a global level optimization process. A parallel genetic algorithm is proposed to control global optimization in which evaluating the fitness of each member of the population requires the solution of a guide based design subproblem where parallelism is solely within fitness evaluations. Results are presented for a wingbox design problem and compared with known solutions for the same problem to demonstrate weight reductions in a problem thought to already be near optimally solved.
- Optimization and Blending of Composite Laminates Using Genetic Algorithms with MigrationAdams, David B.; Watson, Layne T.; Gürdal, Zafer (Department of Computer Science, Virginia Polytechnic Institute & State University, 2002)Optimization of aircraft stiffened composite panel structures often results in manufacturing incompatibilities between adjacent panels. Using genetic algorithms to optimize local panel stacking sequences allows panel populations of stacking sequences to evolve in parallel and send migrants to adjacent panels, so as to blend the local panel designs globally. The blending process is accomplished using the edit distance between individuals of a population and the set of migrants from adjacent panels. The objective function evaluating the fitness of designs is modified according to the severity of mismatches detected between neighboring populations. This lays the ground work for natural evolution to a blended global solution without leaving the paradigm of genetic algorithms.
- Optimization and Blending of Composite Laminates Using Guide based Genetic AlgorithmsAdams, David B.; Watson, Layne T.; Gürdal, Zafer; Anderson-Cook, Christine M. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2003)Composite panel structure optimization is commonly decomposed into panel optimization subproblems, with specified local loads, resulting in manufacturing incompatibilities between adjacent panel designs. A new method proposed here for constructing globally blended panel designs uses a parallel decomposition antithetical to that of earlier work. Rather than performing concurrent panel genetic optimizations, a single genetic optimization is conducted for the entire structure with the parallelism solely within the fitness evaluations. A guide based genetic algorithm approach is introduced to exclusively generate and evaluate valid globally blended designs, utilizing a simple master-slave parallel implementation, implicitly reducing the size of the problem design space and increasing the quality of discovered local optima.
- Pipeline Implementation of Cellular Automata for Structural Design on Message-Passing MultiprocessorsSetoodeh, Shahriar; Adams, David B.; Gürdal, Zafer; Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 2003)The inherent structure of cellular automata is trivially parallelizable and can directly benefit from massively parallel machines in computationally intensive problems. This paper presents both synchronous and pipeline parallel implementations of cellular automata on distributed memory (message-passing) architectures. A structural design problem is considered to study the performance of the various cellular automata implementations. The synchronous parallel implementation is a mixture of Jacobi and Gauss-Seidel style iteration, where it is more Jacobi like as the number of processors increase. Therefore, it exhibits divergence because of the mathematical characteristics of Jacobi matrix iteration for the structural problem as the number of processors increases. The proposed pipeline implementation preserves convergence by simulating a pure Gauss-Seidel iteration. Numerical results for analysis and design of a cantilever plate made of composite material show that the pipeline update scheme is convergent and successfully generates optimal designs.