Stochastic crack growth under variable loading for health monitoring and prognosis

Christina Willhauck, Subhasish Mohanty, Aditi Chattopadhyay, Pedro Peralta

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

2 Citations (Scopus)

Abstract

This paper formulates a stochastic model of fatigue crack growth in ductile alloys under variable loading of the center wing type. This center wing loading has three different load ratios to depict the most demanding operating conditions. The cumulative distribution function of the crack length estimate is generated by numerically solving a stochastic differential equation describing the physics of the crack growth. The model parameters are obtained by analyzing each load span, and the variable model parameter is used in the corresponding load period. Simulations are used to show that the analytical crack exceedance probability follows the experimental data fairly well.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume6926
DOIs
StatePublished - 2008
EventModeling, Signal Processing, and Control for Smart Structures 2008 - San Diego, CA, United States
Duration: Mar 10 2008Mar 12 2008

Other

OtherModeling, Signal Processing, and Control for Smart Structures 2008
CountryUnited States
CitySan Diego, CA
Period3/10/083/12/08

Fingerprint

prognosis
health
Crack propagation
cracks
Health
Cracks
Monitoring
Stochastic models
Fatigue crack propagation
Distribution functions
wing loading
Differential equations
Physics
wings
differential equations
distribution functions
physics
estimates
simulation

Keywords

  • Experimental data
  • Fatigue crack growth
  • Random process
  • Statistical analysis
  • Stochastic modeling
  • Variable loading

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Willhauck, C., Mohanty, S., Chattopadhyay, A., & Peralta, P. (2008). Stochastic crack growth under variable loading for health monitoring and prognosis. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 6926). [69260L] https://doi.org/10.1117/12.776476

Stochastic crack growth under variable loading for health monitoring and prognosis. / Willhauck, Christina; Mohanty, Subhasish; Chattopadhyay, Aditi; Peralta, Pedro.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6926 2008. 69260L.

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

Willhauck, C, Mohanty, S, Chattopadhyay, A & Peralta, P 2008, Stochastic crack growth under variable loading for health monitoring and prognosis. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 6926, 69260L, Modeling, Signal Processing, and Control for Smart Structures 2008, San Diego, CA, United States, 3/10/08. https://doi.org/10.1117/12.776476
Willhauck C, Mohanty S, Chattopadhyay A, Peralta P. Stochastic crack growth under variable loading for health monitoring and prognosis. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6926. 2008. 69260L https://doi.org/10.1117/12.776476
Willhauck, Christina ; Mohanty, Subhasish ; Chattopadhyay, Aditi ; Peralta, Pedro. / Stochastic crack growth under variable loading for health monitoring and prognosis. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6926 2008.
@inproceedings{8d65025772ce492fadc7cbe34cec7aa8,
title = "Stochastic crack growth under variable loading for health monitoring and prognosis",
abstract = "This paper formulates a stochastic model of fatigue crack growth in ductile alloys under variable loading of the center wing type. This center wing loading has three different load ratios to depict the most demanding operating conditions. The cumulative distribution function of the crack length estimate is generated by numerically solving a stochastic differential equation describing the physics of the crack growth. The model parameters are obtained by analyzing each load span, and the variable model parameter is used in the corresponding load period. Simulations are used to show that the analytical crack exceedance probability follows the experimental data fairly well.",
keywords = "Experimental data, Fatigue crack growth, Random process, Statistical analysis, Stochastic modeling, Variable loading",
author = "Christina Willhauck and Subhasish Mohanty and Aditi Chattopadhyay and Pedro Peralta",
year = "2008",
doi = "10.1117/12.776476",
language = "English (US)",
isbn = "9780819471123",
volume = "6926",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

}

TY - GEN

T1 - Stochastic crack growth under variable loading for health monitoring and prognosis

AU - Willhauck, Christina

AU - Mohanty, Subhasish

AU - Chattopadhyay, Aditi

AU - Peralta, Pedro

PY - 2008

Y1 - 2008

N2 - This paper formulates a stochastic model of fatigue crack growth in ductile alloys under variable loading of the center wing type. This center wing loading has three different load ratios to depict the most demanding operating conditions. The cumulative distribution function of the crack length estimate is generated by numerically solving a stochastic differential equation describing the physics of the crack growth. The model parameters are obtained by analyzing each load span, and the variable model parameter is used in the corresponding load period. Simulations are used to show that the analytical crack exceedance probability follows the experimental data fairly well.

AB - This paper formulates a stochastic model of fatigue crack growth in ductile alloys under variable loading of the center wing type. This center wing loading has three different load ratios to depict the most demanding operating conditions. The cumulative distribution function of the crack length estimate is generated by numerically solving a stochastic differential equation describing the physics of the crack growth. The model parameters are obtained by analyzing each load span, and the variable model parameter is used in the corresponding load period. Simulations are used to show that the analytical crack exceedance probability follows the experimental data fairly well.

KW - Experimental data

KW - Fatigue crack growth

KW - Random process

KW - Statistical analysis

KW - Stochastic modeling

KW - Variable loading

UR - http://www.scopus.com/inward/record.url?scp=44349188130&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=44349188130&partnerID=8YFLogxK

U2 - 10.1117/12.776476

DO - 10.1117/12.776476

M3 - Conference contribution

AN - SCOPUS:44349188130

SN - 9780819471123

VL - 6926

BT - Proceedings of SPIE - The International Society for Optical Engineering

ER -