Optimizing the Placement of Strain Gauges on Propeller Blades to Minimize Error in Enverse Load Calculations

Abstract

Classical problems in structural mechanics solve for the strain field of a structure given a known loading. However, there are a variety of practical situations in which it would be more desirable to infer the loading on a structure given a set of corresponding strain measurements. This so-called “inverse problem" is challenging because it can result in systems of equations that are ill-conditioned. The extent to which a system matrix is ill-conditioned will vary significantly depending on the configuration (i.e., number and/or placement) of strain gauges on the structure. We propose the development of an inverse method that will enable the use of strain data as valuable experimental evidence of fluid loading on propellers during operation. The calculated loads can also be used as experimental validation of computational fluid dynamics (CFD) simulations. The key feature of the proposed approach is to optimize the configuration of strain gauges through the global minimization of the condition number of the system matrix. The condition number is a measure of how much the output of a function will change due to a given change in the input. The proposed effort will develop rules for the optimal placement of sensors and corresponding pressure patches. The result will be a robust physics-based method for configuring instrumentation for large- to full-scale experiments.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 09, 2016
Source ID
N000141612290

Entities

People

  • Robert F Davis

Organizations

  • Office of Naval Research
  • The University of Georgia
  • United States Navy

Tags

Fields of Study

  • Engineering

Readers

  • Computational Fluid Dynamics (CFD)
  • Fluid Dynamics.
  • Structural Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms