New technological developments in engineering present the opportunity for improved efficiency in structural design. Increased number and capacity of Central Processing Units (CPUs) reduce the time needed for computational calculations. Concurrently, optimization algorithms have been evolved for solving complicated problems including multi-objective goals, constraints, and boundaries. Effective optimization algorithms along with the availability of high-performance computers have been a central focus within contemporary engineering.
This thesis aims to develop the framework for optimal design of viscously damped moment frames (VDMFs) considering a set of seismic engineering demand parameters (EDPs) and the multi-objective particle swarm optimization (MOPSO) algorithm. The study provides recommendations on how to efficiently generate reliable solution set utilizing MOPSO. The provided recommendations include the following: 1) modification of original MOPSO to include constraint functions, 2) selection of cost functions, and 3) selection of MOPSO input parameters.
Furthermore, this research study develops efficient optimization strategy for finding optimal design solutions in the absence of prior engineering knowledge about suitable damper properties that would meet design requirements. The proposed optimization strategy allows utilization of broad ranges of damping coefficients, the primary damper property that governs the design and therefore the primary decision variable, to efficiently find the optimal solutions (i.e., Pareto front) under the set of design objectives and constraints. The proposed strategy is verified utilizing an engineered solution of a viscously-damped moment frame.
|Commitee:||Calabrese, Andrea, Rahmani, Mehran|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 81/4(E), Masters Abstracts International|
|Subjects:||Civil engineering, Engineering|
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