An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions

M. Chiachio, J. Chiachio, A. Saxena, G. Rus, K. Goebel

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

This work presents an efficient computational framework for estimating the end of life (EOL) and remaining useful life (RUL) by combining the prognostics principles with the technique of Subset simulation. It has been named PFP-SubSim on behalf of the full denomination of the computational framework, namely, particle filter-based prognostics using Subset Simulation. It is shown that the resulting algorithm is especially useful when dealing with the prognostics of evolving processes with asymptotic behaviors where the length of the dataset is limited, as observed in practice for many fatigue degradation processes in composites. Its efficiency is demonstrated on data collected from run-to-failure tension-tension fatigue experiments measuring the evolution of fatigue damage in CRFP cross-ply laminates using PZT sensors for obtaining data of matrix micro-crack density.

LanguageEnglish
Title of host publication16th European Conference on Composite Materials, ECCM 2014
Pages1-8
Number of pages8
ISBN (Electronic)9780000000002
Publication statusPublished - 2014
Event16th European Conference on Composite Materials, ECCM 2014 - Seville, Spain
Duration: 22 Jun 201426 Jun 2014

Conference

Conference16th European Conference on Composite Materials, ECCM 2014
CountrySpain
CitySeville
Period22/06/1426/06/14

Fingerprint

Fatigue
Efficient Algorithms
Composite
Fatigue of materials
Predict
Fatigue Damage
Microcracks
Subset
Laminates
Composite materials
Particle Filter
Fatigue damage
Simulation
Degradation
Asymptotic Behavior
Cracks
Sensor
Sensors
Experiment
Experiments

Keywords

  • fatigue damage
  • model-based prognostics
  • particle filters
  • structural health management
  • algorithms
  • distributed computer systems
  • laminates
  • Monte Carlo methods
  • signal filtering and prediction
  • systems engineering

Cite this

Chiachio, M., Chiachio, J., Saxena, A., Rus, G., & Goebel, K. (2014). An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions. In 16th European Conference on Composite Materials, ECCM 2014 (pp. 1-8)
Chiachio, M. ; Chiachio, J. ; Saxena, A. ; Rus, G. ; Goebel, K. / An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions. 16th European Conference on Composite Materials, ECCM 2014. 2014. pp. 1-8
@inproceedings{609056ce37fb4dbaa14ed1e67a32281c,
title = "An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions",
abstract = "This work presents an efficient computational framework for estimating the end of life (EOL) and remaining useful life (RUL) by combining the prognostics principles with the technique of Subset simulation. It has been named PFP-SubSim on behalf of the full denomination of the computational framework, namely, particle filter-based prognostics using Subset Simulation. It is shown that the resulting algorithm is especially useful when dealing with the prognostics of evolving processes with asymptotic behaviors where the length of the dataset is limited, as observed in practice for many fatigue degradation processes in composites. Its efficiency is demonstrated on data collected from run-to-failure tension-tension fatigue experiments measuring the evolution of fatigue damage in CRFP cross-ply laminates using PZT sensors for obtaining data of matrix micro-crack density.",
keywords = "fatigue damage, model-based prognostics, particle filters, structural health management, algorithms, distributed computer systems, laminates, Monte Carlo methods, signal filtering and prediction, systems engineering",
author = "M. Chiachio and J. Chiachio and A. Saxena and G. Rus and K. Goebel",
year = "2014",
language = "English",
pages = "1--8",
booktitle = "16th European Conference on Composite Materials, ECCM 2014",

}

Chiachio, M, Chiachio, J, Saxena, A, Rus, G & Goebel, K 2014, An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions. in 16th European Conference on Composite Materials, ECCM 2014. pp. 1-8, 16th European Conference on Composite Materials, ECCM 2014, Seville, Spain, 22/06/14.

An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions. / Chiachio, M.; Chiachio, J.; Saxena, A.; Rus, G.; Goebel, K.

16th European Conference on Composite Materials, ECCM 2014. 2014. p. 1-8.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

TY - GEN

T1 - An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions

AU - Chiachio, M.

AU - Chiachio, J.

AU - Saxena, A.

AU - Rus, G.

AU - Goebel, K.

PY - 2014

Y1 - 2014

N2 - This work presents an efficient computational framework for estimating the end of life (EOL) and remaining useful life (RUL) by combining the prognostics principles with the technique of Subset simulation. It has been named PFP-SubSim on behalf of the full denomination of the computational framework, namely, particle filter-based prognostics using Subset Simulation. It is shown that the resulting algorithm is especially useful when dealing with the prognostics of evolving processes with asymptotic behaviors where the length of the dataset is limited, as observed in practice for many fatigue degradation processes in composites. Its efficiency is demonstrated on data collected from run-to-failure tension-tension fatigue experiments measuring the evolution of fatigue damage in CRFP cross-ply laminates using PZT sensors for obtaining data of matrix micro-crack density.

AB - This work presents an efficient computational framework for estimating the end of life (EOL) and remaining useful life (RUL) by combining the prognostics principles with the technique of Subset simulation. It has been named PFP-SubSim on behalf of the full denomination of the computational framework, namely, particle filter-based prognostics using Subset Simulation. It is shown that the resulting algorithm is especially useful when dealing with the prognostics of evolving processes with asymptotic behaviors where the length of the dataset is limited, as observed in practice for many fatigue degradation processes in composites. Its efficiency is demonstrated on data collected from run-to-failure tension-tension fatigue experiments measuring the evolution of fatigue damage in CRFP cross-ply laminates using PZT sensors for obtaining data of matrix micro-crack density.

KW - fatigue damage

KW - model-based prognostics

KW - particle filters

KW - structural health management

KW - algorithms

KW - distributed computer systems

KW - laminates

KW - Monte Carlo methods

KW - signal filtering and prediction

KW - systems engineering

UR - http://www.scopus.com/inward/record.url?scp=84915746876&partnerID=8YFLogxK

M3 - Conference contribution book

SP - 1

EP - 8

BT - 16th European Conference on Composite Materials, ECCM 2014

ER -

Chiachio M, Chiachio J, Saxena A, Rus G, Goebel K. An efficient algorithm to predict the expected end-of-life in composites under fatigue conditions. In 16th European Conference on Composite Materials, ECCM 2014. 2014. p. 1-8