Low-Dimensional Modeling of Flow-Induced Vibration with Coupled Map Lattices

Abstract

The overall objective of this project was to use tools from nonlinear chaos theory to gain a better fundamental understanding of vibrating cable flows. To accomplish this objective, low-order models based on iterative maps were developed. These models (or coupled map lattices) are highly efficient, and should have future application for flow control of vibrating cables. Specific capabilities developed during the course of the project include; 1) incorporation of self-learning features (neural networks) that allow the models to learn directly from a cable flow, 2) addition of control strategies into the models, and 3) integration of a structural dynamics model with the coupled map lattice. Numerical simulations and experiments on vibrating cables were also conducted to validate the models. At their current state of development, the models can predict certain observed features of cable flows, including cable vibration amplitudes and flow patterns. In addition, we studied an experimental technique that uses ultrasonic acoustic pulses to measure lift forces on vibrating structures.

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Document Details

Document Type
Technical Report
Publication Date
Jan 27, 2002
Accession Number
ADA410638

Entities

People

  • David J. Olinger
  • Michael Demetriou

Organizations

  • Worcester Polytechnic Institute

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Dynamics
  • Engineering
  • Flow
  • Fluid Flow
  • Hypervelocity Flow
  • Learning
  • Measurement
  • Neural Networks
  • Nonlinear Dynamics
  • Physics
  • Physics Laboratories
  • Simulations
  • Turbulent Mixing
  • Vibration
  • Vortex Shedding
  • Waves

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Modeling and Simulation
  • Neural Network Machine Learning.

Technology Areas

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