The computational cost of high-fidelity injection molding simulations has been growing in the past years making it more and challenging to use them for performing analyses such as optimizations or uncertainty quantification. Surrogate modeling offers a cheaper way realize studies gaining attention field simulation. In this work, we propose compare three surrogate techniques along with two desig...

We present a parallel evolutionary optimization algorithm that leverages surrogate models for solving computationally expensive design problems with general constraints, on a limited computational budget. The essential backbone of our framework is an evolutionary algorithm coupled with a feasible sequential quadratic programming solver in the spirit of Lamarckian learning.We employ a trust-regi...

In assembly process control and design optimization, it is critical to establish a mathematical model that describes the relationship between the dimensional quality of the final product and the various process parameters (e.g., the fixture layout and locator position deviation). This article presents a surrogate modeling methodology for multistage assembly processes to characterize the relatio...

This paper deals with developing an efficient Robust Design Optimization (RDO) framework. The goal is to obtain an aerodynamic shape that is less sensitive to small random geometry perturbations and to uncertain operational conditions. The initial shape is the RAE2822 airfoil which is parameterized with 10 design variables. The robust design formulation used is based on an expectation measure. ...

For many problems from science and engineering it is impractical to perform experiments on the physical world directly (e.g., airfoil design, earthquake propagation). Instead, complex, physics-based simulation codes are used to run experiments on computer hardware. While allowing scientists more flexibility to study phenomena under controlled conditions, computer experiments require a substanti...

Emission preprocessing, defined as the creation of a spatially and temporally resolved emissions inventory from raw data, is a crucial part of air quality modeling. We have focused on improving emission preprocessing using the SMOKE system. Because emissions are rarely distributed evenly with respect to location, gridding surrogates are used to apportion emissions to each grid within the modeli...

Designing and optimizing complex systems generally requires the use of numerical models. However, it is often too expensive to evaluate these models at each step of an optimization problem. Instead surrogate models can be used to explore the design space, as they are much cheaper to evaluate. Constructing a surrogate becomes challenging when different numerical models are used to compute the sa...

Computational modeling of the structural behavior of continuous fiber composite materials often takes into account the periodicity of the underlying micro-structure. A well established method dealing with the structural behavior of periodic micro-structures is the socalled Asymptotic Expansion Homogenization (AEH). By considering a periodic perturbation of the material displacement, scale bridg...