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- Structural System Reliability using Fast Fourier Transforms
In probabilistic analysis, the failure of a structural system is governed by multiple failure criteria. In the estimation of system reliability, all of these failure criteria are to be taken into consideration. The evaluation of these failure criteria or limit-state functions often requires computationally expensive simulations. Moreover, the accuracy of the estimated structural failure probability highly depends on the ability to model the joint failure surface comprising of all the limit-state functions. Therefore, the use of high quality function approximations for each of the limit-states and the joint failure surface are considered in this work. Once the joint failure surface is represented using surrogate model, the convolution integral can be solved efficiently using a Fast Fourier Transform technique. Due to the high non-linearity of the joint failure region, a methodology is developed to evaluate the convolution integral based on multiple approximations over several disjoint regions spanning the entire design space.
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- Multi-Level Design Process For 3-D Preform Shape Optimization
The current research focuses on developing novel hybrid shape sensitivity analysis techniques that economize the die design process. This methodology starts by differentiating the objective/constraint functionals using the material derivative definitions. The derivatives of the objectives/constraints include unknown terms, such as material derivatives of velocities, strain-rates, and strains. These unknowns are then eliminated by utilizing the deformation process mechanics and finite element analyses. The developed sensitivity analysis reduces the computational cost of design optimization and assists in industry trade-off designs, and can be easily concatenated with any commercial analysis packages, which results in flexible, economical, and reliable designs.
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- Evolutionary Optimization Method for Thermal Protection System Design
The Evolutionary Optimization Method (ESO) is the evolution of the structure to its best topology by the removal of inefficient elements.. In this work, a multi-objective structural optimization method for the three-dimensional acreage TPS design is developed using an Evolutionary Structural Optimization (ESO) algorithm. The static control parameter used to find the optimum in minimum thermal stress design is modified to address an irregular mode-switching phenomenon, as well as for improving the modal stiffness in dynamic analysis. Two objectives are optimized simultaneously; namely, the maximization of fundamental natural frequency and the minimization of maximum thermal stress.
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- Multidisciplinary Optimization and Reliability Analysis of Undersea Weapons
Optimization and uncertainty analysis considering multiple design criteria involves seamless integration of often conflicting disciplines. CDOC at Wright State University has been applying analysis tools to predict the behavior of critical disciplines to produce highly robust torpedo designs using robust multi-disciplinary design optimization. An optimal configuration of a supercavitating torpedo model that fits in a cavity generated by the cavitator was obtained. An evidence theory-based method to determine the reliability of the cavitator is presented. Structural optimization of the lightweight torpedo model was done for it to be safe from underwater explosions and to reduce the acoustic signature. Also, reliability-based optimization was performed for the lightweight torpedo model using system reliability constraints.
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