Structural topology optimization has been extensively studied in aeronautical, civil, and mechanical engineering applications in order to improve performance of systems. This thesis focuses on an optimal design of damping treatment using topology optimization, and the reduction of computational expense of the topology optimization procedure. This thesis presents mainly two works on topology optimization. In the first work, topology optimization is implemented to optimally design damping treatments in unconstrained-layer damping material. Since the damping effect relies on the placement of damping treatment, and the weight of damping material may be an important factor, the placement of damping material is optimally determined using topology optimization with an allowable maximum. Unconstrained-layer plate and shell structures are modeled. The damping layer on the unconstrained-layer structures is considered as the design domain. Using topology optimization, the damping layer is designed numerically, and then experimentally validated by comparing the damping effects. In the numerical example, the topological damping treatment usually provides much higher damping effects compared to other approaches such as strain energy distribution (SED) and an evolutionary structural optimization (ESO). In the second work, a numerical algorithm, named as reducible design variable method (RDVM) topology optimization, is proposed in order to efficiently reduce the computational expense. Since it usually requires thousands to millions of design variables and up to hundreds of iterations in topology optimization, the major difficulty is its computational expense. The RDVM topology optimization is implemented into static (minimization of compliance) and dynamic (maximization of the fundamental resonance frequency) problems. The RDVM significantly reduces computing time, as confirmed by numerical examples. / Thesis (Ph.D, Mechanical and Materials Engineering) -- Queen's University, 2011-07-08 10:10:20.606

Truely optimal solutions to system design can only be obtained if the entire system is considered. In this research we consider design of commercial aircraft, but we expand the system to include a family of planes. A multidisciplinary design optimization framework is developed in which multiple aircraft, each with different missions, can be optimized simultaneously. Results are presented for a two-member family whose individual missions differ significantly. We show that both missions can be satisfied with common designs, and that by optimizing both planes simultaneously rather than following the traditional baseline plus derivative approach, the common solution is vastly improved. The new framework is also used to gain insight to the effect of design variable scaling on the optimization algorithm. / Singapore-MIT Alliance (SMA)

During recent years more and more emphasis has been put on saving and ecological aspects of the civil engineering industry. As the total volume of concrete being produced on our planet is immense (ca 1010 tons per year), the possibility of decreasing it by even a small percentage can bring large savings in material costs, transport and other costs and reduction of CO2 production and other pollution. Therefore, optimal analysis of design variables of concrete structures appears to be of high importance. Optimization is finding the best solution to a given problem. Many disciplines define different optimization problems and it is typically the minimum or maximum value of the objective function that is searched. It is known that mathematical procedures and algorithms to find an optimal structural design are used in practice in mechanical engineering, but the use of these tools in civil engineering is rather exceptional. Generally, scientific works deal with the optimal design of structures only. Finding of an optimal shape and dimensions is usually a question of the engineer’s experience and good “guess”, which is then verified by calculation. There are many reasons explaining why optimization in common practise is used only occasionally. One of them is the absence of proper user friendly software tools which could help within relatively short time available for structural design. Another reason is the complexity of optimization tasks as well as a lot of constraints in civil engineering design codes. Last but not least, the change of design variables of buildings, bridges and structures of special types do not express regular response. This issue is discussed in the submitted work.

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