Probabilistic prognosis of fatigue crack growth for asphalt concretes

Seung Jung Lee; Goangseup Zi; Sungho Mun; Jun g Sik Kong; Joo Ho Choi

doi:10.1016/j.engfracmech.2015.04.033

Probabilistic prognosis of fatigue crack growth for asphalt concretes

Seung Jung Lee, Goangseup Zi, Sungho Mun, Jun g Sik Kong, Joo Ho Choi

Research output: Contribution to journal › Article › peer-review

25 Citations (Scopus)

Abstract

A probabilistic approach is presented for the prognosis of fatigue crack growth for asphalt concretes using the particle filtering method based on Bayesian theory. The random response of fatigue behavior is successively updated with the accumulation of the measured data by the particle filtering method. During the updating, particles with high probability are reproduced more, while others are eliminated via resampling procedures. The J integral is adopted for the fatigue crack growth to take into account the viscoelastic characteristics of asphalt concretes. The prognosis of fatigue crack growth and remaining service life under different conditions is presented using this method.

Original language	English
Pages (from-to)	212-229
Number of pages	18
Journal	Engineering Fracture Mechanics
Volume	141
DOIs	https://doi.org/10.1016/j.engfracmech.2015.04.033
Publication status	Published - 2015 Jun 1

Keywords

Asphalt concrete
Bayesian theory
Crack growth
Fatigue
J integral
Particle filtering
Prognosis
Remaining service life

ASJC Scopus subject areas

Materials Science(all)
Mechanics of Materials
Mechanical Engineering

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10.1016/j.engfracmech.2015.04.033

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title = "Probabilistic prognosis of fatigue crack growth for asphalt concretes",

abstract = "A probabilistic approach is presented for the prognosis of fatigue crack growth for asphalt concretes using the particle filtering method based on Bayesian theory. The random response of fatigue behavior is successively updated with the accumulation of the measured data by the particle filtering method. During the updating, particles with high probability are reproduced more, while others are eliminated via resampling procedures. The J integral is adopted for the fatigue crack growth to take into account the viscoelastic characteristics of asphalt concretes. The prognosis of fatigue crack growth and remaining service life under different conditions is presented using this method.",

keywords = "Asphalt concrete, Bayesian theory, Crack growth, Fatigue, J integral, Particle filtering, Prognosis, Remaining service life",

author = "Lee, {Seung Jung} and Goangseup Zi and Sungho Mun and Kong, {Jun g Sik} and Choi, {Joo Ho}",

note = "Funding Information: This research was supported by a Grant (No. 20133010021770 ) from the New & Renewable Energy Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), funded by the Ministry of Trade, Industry and Energy, and a Grant ( 15RDRP-B066780 ) from the Regional Development Research Program, funded by the Ministry of Land, Infrastructure and Transport, Republic of Korea . The first author appreciates a partial support of a Grant( 14SCIP-B065985-02 ) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport. Publisher Copyright: {\textcopyright} 2015 Elsevier Ltd.",

year = "2015",

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doi = "10.1016/j.engfracmech.2015.04.033",

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AU - Lee, Seung Jung

AU - Zi, Goangseup

AU - Mun, Sungho

AU - Kong, Jun g Sik

AU - Choi, Joo Ho

N1 - Funding Information: This research was supported by a Grant (No. 20133010021770 ) from the New & Renewable Energy Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), funded by the Ministry of Trade, Industry and Energy, and a Grant ( 15RDRP-B066780 ) from the Regional Development Research Program, funded by the Ministry of Land, Infrastructure and Transport, Republic of Korea . The first author appreciates a partial support of a Grant( 14SCIP-B065985-02 ) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport. Publisher Copyright: © 2015 Elsevier Ltd.

PY - 2015/6/1

Y1 - 2015/6/1

N2 - A probabilistic approach is presented for the prognosis of fatigue crack growth for asphalt concretes using the particle filtering method based on Bayesian theory. The random response of fatigue behavior is successively updated with the accumulation of the measured data by the particle filtering method. During the updating, particles with high probability are reproduced more, while others are eliminated via resampling procedures. The J integral is adopted for the fatigue crack growth to take into account the viscoelastic characteristics of asphalt concretes. The prognosis of fatigue crack growth and remaining service life under different conditions is presented using this method.

AB - A probabilistic approach is presented for the prognosis of fatigue crack growth for asphalt concretes using the particle filtering method based on Bayesian theory. The random response of fatigue behavior is successively updated with the accumulation of the measured data by the particle filtering method. During the updating, particles with high probability are reproduced more, while others are eliminated via resampling procedures. The J integral is adopted for the fatigue crack growth to take into account the viscoelastic characteristics of asphalt concretes. The prognosis of fatigue crack growth and remaining service life under different conditions is presented using this method.

KW - Asphalt concrete

KW - Bayesian theory

KW - Crack growth

KW - Fatigue

KW - J integral

KW - Particle filtering

KW - Prognosis

KW - Remaining service life

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M3 - Article

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SN - 0013-7944

VL - 141

SP - 212

EP - 229

JO - Engineering Fracture Mechanics

JF - Engineering Fracture Mechanics

ER -

Probabilistic prognosis of fatigue crack growth for asphalt concretes

Abstract

Keywords

ASJC Scopus subject areas

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