Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.

An approach is presented for determining which parameters defining the features in a CAD model need to be modified, and by what amount, to optimize component performance. It uses sensitivities computed for the parameters to determine the change required in each to optimize the component. Parametric sensitivity is computed by combining a measure of boundary movement due to a parameter perturbation, known as design velocity, and an adjoint sensitivity map over the boundary. The sensitivity map results from an adjoint analysis and approximates the change in objective function (performance) due to a movement of the boundary. Gradient based optimization is used based on the parametric sensitivities.This presented method is significantly less computationally expensive than alternative approaches, and has the advantage that optimization is based on the parameters defining the CAD model, allowing it to be integrated into design workflows. The efficiency of the approach allows all of the parameters in the CAD model to be used as optimization variables, potentially offering better optimization. The work is immune to many of the issues hampering existing approaches.

No abstract

No abstract

No abstract

Surrogate-based-optimization methods provide a means to minimize expensive highfidelity models at reduced computational cost. The methods are useful in problems for which two models of the same physical system exist: a high-fidelity model which is accurate and expensive, and a low-fidelity model which is less costly but less accurate. A number of model management techniques have been developed and shown to work well for the case in which both models are defined over the same design space. However, many systems exist with variable fidelity models for which the design variables are defined over different spaces, and a mapping is required between the spaces. Previous work showed that two mapping methods, corrected space mapping and POD mapping, used in conjunction with a trust-region model management method, provide improved performance over conventional non-surrogate-based optimization methods for unconstrained problems. This paper extends that work to constrained problems. Three constraint-management methods are demonstrated with each of the mapping methods: Lagrangian minimization, an sequential quadratic programming-like surrogate method, and MAESTRO. The methods are demonstrated on a fixed-complexity analytical test problem and a variable-complexity wing design problem. The SQP-like method consistently outperformed optimization in the high-fidelity space and the other variable complexity methods. Corrected space mapping performed slightly better on average than POD mapping. On the wing design problem, the combination of the SQP-like method and corrected space mapping achieved 58% savings in high-fidelity function calls over optimization directly in the high-fidelity space.

We investigated intraspecific and interspecific patterns of paternity in Tribolium castaneum, the flour beetle, by mating females either to pairs of conspecific males or to one conspecific and one heterospecific male of the closely related species, T freemani. Females of both species store sperm in the spermatheca after copulation and postcopulatory, prezygotic reproductive isolation has been reported between this pair of species. When conspecific males of contrasting genotype were mated simultaneously to T. castaneum females, we observed extremely high levels of variation among females in the pattern of sperm precedence as shown by the offspring genotypes. In contrast, T. castaneum females mated simultaneously to a conspecific and a heterospecific male produced over 99 per cent conspecific progeny. When conspecific males were mated sequentially to T castaneum females, within 3-7 days, all offspring were sired by the second male. In contrast, when a conspecific male was replaced with a T freemani male, most females continued to produce only first-male, conspecific offspring for the next 10 days. When a heterospecific male was replaced with a conspecific male, T castaneum females changed from producing hybrid to conspecific offspring within 3 days. We discuss the evolutionary implications of these findings.

No abstract