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A Local Regression Approach to Computing the Cauchy Green Strain Tensor

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Date Issued:
2015
Summary:
The Cauchy Green strain tensor provides an effective tool for understanding unsteady flows. In particular, the dominant eigenvalue of this tensor has been seen to be a reliable estimator of the finite time Lyapunov exponent. We propose a new method for computing the CG strain tensor using a local quadratic regression LOESS technique. We compare this LOESS method with several classical methods using closed form flows, noisy flows, and simulated time series. In each case, the CG strain tensor produced by the LOESS method is remarkably accurate and robust compared to classical methods.
Title: A Local Regression Approach to Computing the Cauchy Green Strain Tensor.
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Name(s): Kepley, Shane
Kalies, William D.
Graduate College
Type of Resource: text
Genre: Poster
Date Created: 2015
Date Issued: 2015
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 1 p.
Language(s): English
Summary: The Cauchy Green strain tensor provides an effective tool for understanding unsteady flows. In particular, the dominant eigenvalue of this tensor has been seen to be a reliable estimator of the finite time Lyapunov exponent. We propose a new method for computing the CG strain tensor using a local quadratic regression LOESS technique. We compare this LOESS method with several classical methods using closed form flows, noisy flows, and simulated time series. In each case, the CG strain tensor produced by the LOESS method is remarkably accurate and robust compared to classical methods.
Identifier: FA00005890 (IID)
Collection: FAU Student Research Digital Collection
Note(s): The Sixth Annual Graduate Research Day was organized by Florida Atlantic University’s Graduate Student Association. Graduate students from FAU Colleges present abstracts of original research and posters in a competition for monetary prizes, awards, and recognition.
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00005890
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Owner Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.