Reduced cost mission design using surrogate models

Design Optimization Using Hyper-Reduced Order Models

1. Abstract Partial Differential Equation (PDE)-constrained optimization requires the solution of large-scale systems of equations at each iteration of the design process. The size of such systems scales with the dimension of the discretized model associated with the PDE and incurs large CPU costs and memory requirements. In the present work, projection-based reduced-order models (ROMs) [1] are...

On Design Mining: Coevolution and Surrogate Models

Design mining is the use of computational intelligence techniques to iteratively search and model the attribute space of physical objects evaluated directly through rapid prototyping to meet given objectives. It enables the exploitation of novel materials and processes without formal models or complex simulation. In this article, we focus upon the coevolutionary nature of the design process whe...

Certified PDE-constrained parameter optimization using reduced basis surrogate models for evolution problems

We consider parameter optimization problems which are subject to constraints given by parametrized partial differential equations (PDE). Discretizing this problem may lead to a largescale optimization problem which can hardly be solved rapidly. In order to accelerate the process of parameter optimization we will use a reduced basis surrogate model for numerical optimization. For many optimizati...

Reduced - Parameter Modeling for Cost Estimation Models

Computational design of patterned interfaces using reduced order models

Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids. Many interfaces have non-uniform internal structures comprised of misfit dislocations, which in turn govern interface properties. We develop and validate a computational strategy for designing interfaces with controlled misfit disloc...