81 
Aerostructural Shape and Topology Optimization of Aircraft WingsJames, Kai A. 22 August 2012 (has links)
A series of novel algorithms for performing aerostructural shape and topology optimization are introduced and applied to the design of aircraft wings. An isoparametric level set method is developed for performing topology optimization of wings and other nonrectangular structures that must be modeled using a nonuniform, bodyfitted mesh. The shape sensitivities are mapped to computational space using the transformation defined by the Jacobian of the isoparametric finite elements. The mapped sensitivities are then passed to the HamiltonJacobi equation, which is solved on a uniform Cartesian grid. The method is derived for several objective functions including mass, compliance, and global von Mises stress. The results are compared with SIMP results for several twodimensional benchmark problems. The method is also demonstrated on a threedimensional wingbox structure subject to fixed loading. It is shown that the isoparametric level set method is competitive with the SIMP method in terms of the final objective value as well as computation time.
In a separate problem, the SIMP formulation is used to optimize the structural topology
of a wingbox as part of a larger MDO framework. Here, topology optimization is combined with aerodynamic shape optimization, using a monolithic MDO architecture that includes aerostructural coupling. The aerodynamic loads are modeled using a threedimensional panel method, and the structural analysis makes use of linear, isoparametric, hexahedral elements. The aerodynamic shape is parameterized via a set of twist variables representing the jig twist angle at equally spaced locations along the span of the wing. The sensitivities are determined analytically using a coupled adjoint method. The wing is optimized for minimum drag subject to a compliance constraint taken from a 2g maneuver condition.
The results from the MDO algorithm are compared with those of a sequential optimization procedure in order to quantify the benefits of the MDO approach. While the sequentially optimized wing exhibits a nearlyelliptical lift distribution, the MDO design seeks to push a greater portion of the load toward the root, thus reducing the structural deflection, and allowing for a lighter structure. By exploiting this tradeoff, the MDO design achieves a 42% lower drag than the sequential result.

82 
Aerostructural Shape and Topology Optimization of Aircraft WingsJames, Kai A. 22 August 2012 (has links)
A series of novel algorithms for performing aerostructural shape and topology optimization are introduced and applied to the design of aircraft wings. An isoparametric level set method is developed for performing topology optimization of wings and other nonrectangular structures that must be modeled using a nonuniform, bodyfitted mesh. The shape sensitivities are mapped to computational space using the transformation defined by the Jacobian of the isoparametric finite elements. The mapped sensitivities are then passed to the HamiltonJacobi equation, which is solved on a uniform Cartesian grid. The method is derived for several objective functions including mass, compliance, and global von Mises stress. The results are compared with SIMP results for several twodimensional benchmark problems. The method is also demonstrated on a threedimensional wingbox structure subject to fixed loading. It is shown that the isoparametric level set method is competitive with the SIMP method in terms of the final objective value as well as computation time.
In a separate problem, the SIMP formulation is used to optimize the structural topology
of a wingbox as part of a larger MDO framework. Here, topology optimization is combined with aerodynamic shape optimization, using a monolithic MDO architecture that includes aerostructural coupling. The aerodynamic loads are modeled using a threedimensional panel method, and the structural analysis makes use of linear, isoparametric, hexahedral elements. The aerodynamic shape is parameterized via a set of twist variables representing the jig twist angle at equally spaced locations along the span of the wing. The sensitivities are determined analytically using a coupled adjoint method. The wing is optimized for minimum drag subject to a compliance constraint taken from a 2g maneuver condition.
The results from the MDO algorithm are compared with those of a sequential optimization procedure in order to quantify the benefits of the MDO approach. While the sequentially optimized wing exhibits a nearlyelliptical lift distribution, the MDO design seeks to push a greater portion of the load toward the root, thus reducing the structural deflection, and allowing for a lighter structure. By exploiting this tradeoff, the MDO design achieves a 42% lower drag than the sequential result.

83 
Single Commodity Flow Algorithms for Lifts of Graphic and Cographic MatroidsStuive, Leanne January 2013 (has links)
Consider a binary matroid M given by its matrix representation. We show that if M is a lift of a graphic or a cographic matroid, then in polynomial time we can either solve the single commodity flow problem for M or find an obstruction for which the MaxFlow MinCut relation does not hold. The key tool is an algorithmic version of Lehman's Theorem for the set covering polyhedron.

84 
Single Commodity Flow Algorithms for Lifts of Graphic and Cographic MatroidsStuive, Leanne January 2013 (has links)
Consider a binary matroid M given by its matrix representation. We show that if M is a lift of a graphic or a cographic matroid, then in polynomial time we can either solve the single commodity flow problem for M or find an obstruction for which the MaxFlow MinCut relation does not hold. The key tool is an algorithmic version of Lehman's Theorem for the set covering polyhedron.

85 
Finite element developments and applications in structural topology optimizationLong, Craig Stephen. January 2007 (has links)
Thesis (PhD.(Mechanical and Aeronautical Engineering))Universiteit van Pretoria, 2007. / Abstract in English. Includes bibliographical references.

86 
Niching strategies for particle swarm optimizationBrits, Riaan. January 2002 (has links)
Thesis (M. Sc.)(Computer Science)University of Pretoria, 2002. / Includes bibliographical references (p. 130136).

87 
Otimizacao do sistema de alvo interno do ciclotron CV28 do IPENCNEN/SPARAUJO, SUMAIR G. de 09 October 2014 (has links)
Made available in DSpace on 20141009T12:38:54Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 20141009T14:02:00Z (GMT). No. of bitstreams: 1
02814.pdf: 7065257 bytes, checksum: 9cc7b6eb072600e69bbfbb2de41c251e (MD5) / Dissertacao (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares  IPEN/CNENSP

88 
Otimizacao do sistema de alvo interno do ciclotron CV28 do IPENCNEN/SPARAUJO, SUMAIR G. de 09 October 2014 (has links)
Made available in DSpace on 20141009T12:38:54Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 20141009T14:02:00Z (GMT). No. of bitstreams: 1
02814.pdf: 7065257 bytes, checksum: 9cc7b6eb072600e69bbfbb2de41c251e (MD5) / Dissertacao (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares  IPEN/CNENSP

89 
Parametric Designs and Weight Optimization using Direct and Indirect Aerostructure Load Transfer MethodsGandhi, Viraj D. 08 1900 (has links)
Indiana UniversityPurdue University Indianapolis (IUPUI) / Within the aerospace design, analysis and optimization community, there is an increasing demand to finalize the preliminary design phase of the wing as quickly as possible without losing much on accuracy. This includes rapid generation of designs, an early adaption of higher fidelity models and automation in structural analysis of the internal structure of the wing. To perform the structural analysis, the aerodynamic load can be transferred to the wing using many different methods. Generally, for preliminary analysis, indirect load transfer method is used and for detailed analysis, direct load transfer method is used. For the indirect load transfer method, load is discretized using shearmomenttorque (SMT) curve and applied to ribs of the wing. For the direct load transfer method, the load is distributed using oneway FluidStructure Interaction (FSI) and applied to the skin of the wing. In this research, structural analysis is performed using both methods and the nodal displacement is compared. Further, to optimize the internal structure, iterative changes are made in the number of structural members. To accommodate these changes in geometry as quickly as possible, the parametric design method is used through Engineering SketchPad (ESP). ESP can also provide attributions the geometric feature and generate multifidelity models consistently. ESP can generate the Nastran mesh file (.bdf) with the nodes and the elements grouped according to their geometric attributes. In this research, utilizing the attributions and consistency in multifidelity models an API is created between ESP and Nastran to automatize the multifidelity structural optimization. This API generates the design with appropriate parameters and mesh file using ESP. Through the attribution in the mesh file, the API works as a preprocessor to apply material properties, boundary condition, and optimization parameters. The API sends the mesh file to Nastran and reads the results file to iterate the number of the structural member in design. The result file is also used to transfer the nodal deformation from lowerorder fidelity structural models onto the higherorder ones to have multifidelity optimization. Here, static structural optimization on the whole wing serves as lower fidelity model and buckling optimization on each stiffened panel serves as higher fidelity model. To further extend this idea, a parametric model of the whole aircraft is also created. / 20210817

90 
Dynamic Programming MultiObjective Combinatorial OptimizationMankowski, Michal 18 October 2020 (has links)
In this dissertation, we consider extensions of dynamic programming for combinatorial optimization. We introduce two exact multiobjective optimization algorithms: the multistage optimization algorithm that optimizes the problem relative to the ordered sequence of objectives (lexicographic optimization) and the bicriteria optimization algorithm that simultaneously optimizes the problem relative to two objectives (Pareto optimization). We also introduce a counting algorithm to count optimal solution before and after every optimization stage of multistage optimization. We propose a fairly universal approach based on socalled circuits without repetitions in which each element is generated exactly one time. Such circuits represent the sets of elements under consideration (the sets of feasible solutions) and are used by counting, multistage, and bicriteria optimization algorithms. For a given optimization problem, we should describe an appropriate circuit and cost functions. Then, we can use the designed algorithms for which we already have proofs of their correctness and ways to evaluate the required number of operations and the time. We construct conventional (which work directly with elements) circuits without repetitions for matrix chain multiplication, global sequence alignment, optimal paths in directed graphs, binary search trees, convex polygon triangulation, line breaking (text justification), onedimensional clustering, optimal bitonic tour, and segmented least squares. For these problems, we evaluate the number of operations and the time required by the optimization and counting algorithms, and consider the results of computational experiments. If we cannot find a conventional circuit without repetitions for a problem, we can either create custom algorithms for optimization and counting from scratch or can transform a circuit with repetitions into a socalled syntactical circuit, which is a circuit without repetitions that works not with elements but with formulas representing these elements. We apply both approaches to the optimization of matchings in trees and apply the second approach to the 0/1 knapsack problem. We also briefly introduce our work in operation research with applications to health care. This work extends our interest in the optimization field from developing new methods included in this dissertation towards the practical application.

Page generated in 0.1036 seconds