Session: 02-02-01: Aero-, Servo-, Thermo-Elastic Modeling and Optimization of Aerial Vehicles

Paper Number: 137604

137604 - Applications of Optimal Sensor Placement, Inverse Methods, and Classification for Decision-Making in Aerospace Structural Dynamics 

The design of aerospace structures that can function as expected in harsh vibration environments is a pervasive need across the aerospace community. In a typical design scenario, activities may include gathering field data to assess severity of the aerodynamic loads, using the data to solve inverse problems that inform models of the relevant physics, and then leveraging the data- informed models to make decisions on candidate designs. For realistic aerospace designs, there are still significant research advancements needed in all of these areas to increase predictability of the simulations and mitigate the high computational expense for 3D vehicle designs and typical flight paths.

In this presentation we will present an overview of recent research activities in the development of methods for optimal sensor placement and inverse methods to inform models of aerodynamic loads, and machine-learning classifiers that can use the data- informed models to rapidly achieve binary (e.g. go/no-go) decisions for design trade studies. These approaches allow for the fusion of flight data and predictive models that are informed from field measurements, as well as a design approach that can rapidly scan high-dimensional parameter spaces while minimizing the number of required high-fidelity simulations for making design decisions. This goal of mitigating the “curse of dimensionlity” for high-dimensional design parameter spaces is central to the design process and rapid decision-making, especially in aerospace applications where high-fidelity simulations can take days or weeks to perform.

SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.

Presenting Author: Timothy Walsh Sandia National Laboratories

Presenting Author Biography: Timothy Walsh is a Distinguished Member of Technical Staff at Sandia National Laboratories and has over 20 years of experience in modeling and simulation of structural dynamics, with a particular focus on optimization and inverse problems.